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SCF Folio
A compilation of information and research materials
on seasonal climate forecast (SCF)
Start of project
SCF project launch
The Government of the Philippines, through the Philippine Council for Agriculture, Forestry and Natural
Resources Research and Development (PCARRD), and the Australian Government, through the
Australian Centre for International Agricultural Research (ACIAR), signed a Memorandum of Subsidiary
Arrangement in October 2004 for the undertaking of a four-year project titled Bridging the gap between seasonal
climate forecasts and decisionmakers in agriculture. The project will aim to look into and close the gap between
the potential value of seasonal climate forecasts (SCFs), particularly those looking at the El Niño Southern Oscillation
(ENSO) phenomenon, and their actual use and application in the risk-management decisions of farmers at the
farm level and policymakers at the macro level. Implementing institutions for the Philippines are the Philippine
Atmospheric, Geophysical and Astronomical Services Administration (PAGASA), the Philippine Institute for
Development Studies (PIDS) and the Leyte State University (LSU) while for Australia, the key institutions involved
are the South Australian Research and Development Institute (SARDI), New South Wales Department of Primary
Industries (NSW/DPI), and University of Sydney.
In order to raise awareness of the project, a project launch will be held on July 27, 2005 at the Dusit Hotel
Nikko, Makati City. The launch primarily aims to introduce to the public—especially to the major stakeholders of
the results of the project—the thrusts and direction of the project, its objectives, the various research and case
studies to be undertaken, the various activities and expected outputs, and the institutions/individuals involved.
The launch will also include presentations of the issues (both in the Philippines and in Australia) that the project
intends to effectively address. This activity will be attended by the project team members, members of the Philippine
Project Steering Committee, various government and private agencies/institutions affected or concerned with
the results, members of media, Australian embassy and ACIAR representatives, members of the academe,
representatives from nongovernment organizations and farmers groups, and regular participants of PAGASA’s
Quarterly Climate Outlook Forum.
A question-and-answer portion for both members of the media and other stakeholders will follow the various
presentations regarding the project in order to entertain further questions about the project and elicit comments
and possible feedback on some of its aspects. (SCF Project Updates June 2005)
The project Bridging the gap between seasonal climate forecasts (SCFs) and
decisionmakers in agriculture funded by the Australian Centre for International Agricultural
Research (ACIAR) is a four-year collaborative undertaking that started in March 2005. Its
key objective is to identify and close the gap between the potential and practical application
of SCFs to agricultural systems and policies in the Philippines and Australia. The project
involves research staff from the Philippine Atmospheric, Geophysical and Astronomical
Services Administration (PAGASA), Philippine Institute for Development Studies (PIDS),
Leyte State University (LSU), South Australian Research and Development Institute
(SARDI), Charles Sturt University (CSU), and New South Wales Department of Primary
Industries (NSW-DPI).
Contents
1 Start of project
5 Learning the basics
13 Reaching out and increasing awareness
31 Analysis and research/survey results

2 SCF Folio
About the project...
Background
Agriculture in the Philippines and eastern Australia is
greatly affected by the El Niño Southern Oscillation
(ENSO). Climate in these two countries has higher
season-to-season variability relative to other regions at
the same latitude and level of annual rainfall. Such
variability has significant effects on farm incomes. In
Australia, it accounts for around 40 percent of the
variation in its agricultural income. Similar
consequences are also seen in the Philippines. Climate
variability leaves rainfed agricultural producers exposed
to high levels of risk when making decisions about the
choice of outputs and inputs. It can also lead to
conservative practices that, while reducing the negative
effects of climatic extremes, may however come at the
expense of reduced agricultural incomes and higher
resource degradation. Because of all these, a strategic
mitigation of climatic risk that is so endemic to rainfed
agriculture would clearly be of significant value to
farmers.
Areas affected by ENSO suffer from increased
variability, but one compensation is that improvements
El Niño is a phenomenon that occurs in a specific point in the eastern
equatorial Pacific Ocean—which is quite a distance away from the
Philippines and Australia—but its effects and impact are nonetheless felt
because of the interactions between the ocean surface temperature effect
and the overlying atmosphere in the tropical Pacific region. This
interaction is better known as the El Niño Southern Oscillation (ENSO).
Effect of ENSO in the tropical Pacific
in the understanding of ENSO now provide a degree
of predictability about climate fluctuations. Climate
forecasts offer information on climatic conditions in the
coming season and are sometimes presented in the
form of a probability of receiving ‘above median’ or
‘below median’ rainfall. They offer skillful albeit
uncertain information about climatic conditions in
periods of 3–12 months ahead.
In Australia, the Bureau of Meteorology provides
three monthly seasonal climate outlooks based on the
Southern Oscillation Index (SOI) and sea surface
temperature (SST) anomalies. Although about 45
percent of Australian farmers claim to take seasonal
climate forecasts into account when making decisions,
focus groups show that many still have reservations on
the accuracy, lead time and economic benefits of their
application to a specific decision. The El Niño-related
drought of 2002 that affected eastern Australia,
however, has led to a heightened media and farmer
interest in climate science.
In the Philippines, PAGASA issues seasonal climate
forecasts based on the state of the equatorial Pacific
Ocean. The Philippines is a country greatly affected by
ENSO. In this regard, PAGASA releases ENSO bulletins
as part of the National ENSO Early Warning Monitoring
System (NEEWMS).
It is important to ensure the accuracy and
timeliness of climate forecasts to reduce the difficulty
of using probabilistic climate forecasts in decisionmaking.
Forecasts that shift the odds but do not remove
all the uncertainty are difficult for decisionmakers to
use. Specifically, there is a widespread belief that the
adoption of SCFs is hampered in both the Philippines
and Australia by the lack of robust means of showing
the economic value of SCF for specific decisions.
Source: Australian Rainman
Australia and the Philippines promote SCFs
In an attempt to address the above shortcoming, a
Memorandum of Subsidiary Arrangement was inked
between the Philippine Council for Agriculture, Forestry
and Natural Resources Research and Development
(PCARRD) and the Australian Centre for International
Agricultural Research (ACIAR) in October 2004 for the
undertaking of a four-year project titled Bridging the
gap between seasonal climate forecasts and
decisionmakers in agriculture. Implementing
institutions for the Philippines are the Philippine
Atmospheric, Geophysical and Astronomical Services

3
Administration (PAGASA), the Philippine Institute for
Development Studies (PIDS) and the Leyte State
University (LSU) while for Australia, the key institutions
involved are South Australian Research and Development
Institute (SARDI), New South Wales Department of Primary
Industries (NSW-DPI), and University of Sydney.
The SCF project between Australian and Philippine
institutions will draw on economics and other disciplines
to develop robust ways to use SCFs in risk management.
This project will work with decisionmakers in the
Philippines and Australia to see where, when, and why
skillful but uncertain SCFs can be valuable, and the
circumstances when they are best ignored. The end result
will be increased incomes of rural communities in the
Philippines and Australia.
The project is expected to bring about improved
economic, social, and environmental outcomes in the
collaborating countries given that better management of
climate variability has the potential to improve resource
use efficiency by providing economic benefits through
improved crop planting, management and grazing
strategies.
Case studies in the Philippines and Australia will be
used to assess where economic, environmental and social
benefits may arise. The Philippine studies will focus on
poor Filipino farmers who are vulnerable to climate
variability while Australian studies will consider the impact
of droughts on farming families and rural communities.
Two key methods are to be employed in this project.
The first is to value the potential contribution of SCF to
decisionmaking under climate uncertainty based on
insights from economics and psychology. The second
method is the use of farm and policy-level case studies in
the Philippines and Australia to gain a practical appreciation
of how decisionmakers actually use SCF and how to
bridge the gap between potential and actual use of SCF.
Case studies will use representative farm models to
estimate the potential value of SCFs and will provide
information on how farmers and other decisionmakers
use SCFs to make real decisions. An important component
of the project is the development of extension strategies
based on the case study experiences to promote the value
of SCFs. To help implement this, the project will tap into
extension networks in Australia and the Philippines and
provide tools for agricultural advisers to confidently
promote SCFs to decision problems with the greatest
payoff.
Objectives
• To improve the capacity of PAGASA to develop and
deliver SCF for the case study regions of the
Philippines;
• To distill key practical and methodological features of
economic and psychological approaches to valuing SCF;
• To estimate the potential economic value of SCF for
farm and policy or industry level case studies in the
Philippines and Australia;
• To identify those factors leading to a gap between
actual and potential values of SCF; and
• To develop and implement strategies to better match
forecasts with decisionmaker’s needs. (SCF Project
Updates June 2005)
People and organizations involved...
Philippine Atmospheric, Geophysical and
Astronomical Services Administration (PAGASA)
PAGASA is the Philippines’ meteorological service
organization and is a member of the World Meteorological
Organization. Its mandate is “to mitigate or reduce the
losses to life, property and the economy of the nation
occasioned by typhoons, floods, droughts and other
destructive weather disturbances.” Its website is http://
www.pagasa. dost.gov.ph/.
Dr. Flaviana D. Hilario is the chief of the Climatology
and Agrometeorology Branch (CAB). She will supervise
the preparation of the SCF and will coordinate with
concerned agencies like the PIDS and LSU in the smooth
implementation of the project.
Ms. Edna L. Juanillo is the head of the Climate
Information Monitoring and Prediction Center (CLIMPC)
of the PAGASA (Weather Bureau). She is involved in the
interpretation and analysis of the different climate
parameters needed in the preparation of SCF. She will
assist in the coordination of the Philippine activities with
PIDS and LSU in the conduct of the study in the first two
years of the project.
Ms. Rosalina de Guzman is the assistant head of
CLIMPC. She is involved in the preparation and issuance

4 SCF Folio
of El Niño/La Niña advisories, weather outlook, and
seasonal forecast. She will participate in the translation
of global climate forecasts into local climate predictions
which is one of the information needed in the
preparation of SCF.
Mr. Ernesto R. Verceles is a weather specialist
assigned at the CLIMPC. He is involved in the
preparation and issuance of El Niño/La Niña updates,
climate information and forecasts. He will participate
in the translation of global climate forecasts into local
climate predictions.
Dr. Aida M. Jose is the former chief of the CAB. As a
local consultant of the project, she is involved in the
overall analysis and interpretation of the data and
information which will be vital in the preparation of the SCF.
Leyte State University (LSU)
Leyte State University is situated in Eastern Visayas,
Philippines and is recognized as the center of excellence
for instruction, research and development in agriculture
and related fields, including forestry in the Visayas. It
provides its students with the highest quality of
scientific knowledge to serve the needs of the region.
Its web address is http://www.lsu-visca. edu.ph/.
Dr. Canesio Predo is an assistant professor
(Resource and Environmental Economics) with the
National Abaca Research Center. He is reviewing
methods of valuing SCF and applying these methods
to case studies in the Philippines.
Ms. Eva Monte is an agricultural economics
researcher at LSU. She will be working with Dr. Predo on
the case studies and the development of tools and
information packages on valuing SCFs.
Philippine Institute for Development Studies
(PIDS)
The Institute is a government research institution
engaged in long-term, policy-oriented research.
Through the Institute’s activities, it is hoped that policyoriented
research on social and economic development
can be expanded to assist the government in planning
and policymaking. An important goal of PIDS is to
provide analysis of socioeconomic problems and issues
to support the formulation of plans and policies for
sustained socioeconomic development in the
Philippines. Its website is http://www.pids.gov.ph/.
Dr. Celia M. Reyes is a senior research fellow at PIDS.
Her expertise lies in econometric modelling and
poverty analysis. She is applying this expertise to both
farm and policy-level case studies in the Philippines.
Ms. Jennifer P.T. Liguton is the director for Research
Information at PIDS. She is involved in coming up with
strategies to communicate the results of the Project’s
studies to farmers and policymakers as well as to other
stakeholders.
Mr. Mario C. Feranil is the concurrent OIC vicepresident
of PIDS and director for Project Services. He
will be responsible, in partnership with Dr. Kevin Parton,
for the monitoring and evaluation aspects of the project.
Mr. Christian D. Mina is an information systems
researcher at PIDS under the supervision of Dr. Celia M.
Reyes. He will be working with Dr. Reyes on the case
studies and the development of tools and information
packages on valuing seasonal climate forecasts.
South Australian Research and Development
Institute (SARDI)
SARDI is a leading research and development institute
that conducts innovative applied research and
development to enhance the efficiency and economic
contribution to South Australia’s industries on field crop,
horticulture, livestock, and fishing and aquaculture as
well as on pastures and sustainable resources, and
natural resource management. Its website is
www.sardi.sa.gov.au/index.html.
Dr. Peter Hayman is principal scientist for Climate
Applications at the SARDI in Adelaide. As project leader
for both the Australian and Philippine groups, he will
draw together the inputs from economists, applied
climatologists and farm advisers and will actively be
engaged in developing learning packages for
intermediaries promoting SCFs. He will particularly
be responsible for developing the information
packages for endusers and will assist in the case
studies in Australia.
New South Wales Department of Primary
Industries (NSW/DPI)
NSW/DPI is the largest provider of research and extension
services to agriculture in New South Wales. It is a partner
in the development of profitable, sustainable primary
industries for New South Wales to ensure that primary
industries have appropriate access to natural resources;
communities benefit from the wise use of natural
resources; and regional economies are enhanced. Its
website is http://www.dpi.nsw.gov.au/reader/dpi.

5
Learning the basics
Dr. John Mullen is research leader for Economics
Coordination and Evaluation at the NSW/DPI and adjunct
professor at the Faculty of Rural Management at the
University of Sydney. He is involved in the review of
methods for valuing SCF and in the proposed case study
in the rangelands of NSW.
University of Sydney
The Faculty of Rural Management has research strengths
in agribusiness, farming systems and natural resource
management. Improvements in the availability and use
of seasonal climate forecasts clearly impact on all three of
these areas. Its web address is http://www.csu.edu.au/.
Professor Kevin Parton is dean of the Faculty of Rural
Management. He will concentrate on the relationships
between the economics and psychology approaches to
decisionmaking and valuation of SCF. Professor Parton will
be involved in policy case studies in both Australia and
the Philippines.
Jason Crean is a postgraduate student at the
University of Sydney and is currently undertaking a PhD
on the value of climate forecasting in selected farming
systems in eastern Australia. He has expertise in the
economic modelling of farming systems and will be
involved in the policy and farm level case studies in
Australia. (SCF Project Updates June 2005)
Philippine weather and climate 101
In a forum on Basic Climatology Concepts and
Information organized by the Philippine Institute
for Development Studies (PIDS), in collaboration
with the Philippine Atmospheric, Geophysical and
Astronomical Services Administration (PAGASA) and Leyte
State University (LSU), on April 21 under the project on
seasonal climate forecasts (SCFs) funded by the Australian
Centre for International Agricultural Research (ACIAR), a
team of climate experts and researchers from PAGASA
briefed an audience of technical and policy-level
representatives from various government agencies and
members of the academe on certain basic concepts and
information about Philippine weather and climate. The
briefings included a compehensive lecture on the El Niño
phenomenon—its definition, characteristics, evolution,
and tools of prediction, among others.
The forum is only the first of a series of fora to be
conducted by the abovementioned institutions under the
four-year ACIAR-funded project and is part of the
information, education, and communication component
of the project to help people have a better understanding
of the effects of certain climatic events and conditions
like the El Niño phenomenon and how to respond to them.
In his lecture on the El Niño event, for instance, Mr.
Ernesto Verceles, a weather specialist from PAGASA,
explained that while the El Niño is a phenomenon that
occurs in a specific point in the eastern equatorial Pacific
Ocean—which is quite a distance away from the
Philippines—its effects and impact are nonetheless felt
in the country because of the interactions between the
ocean surface temperature effect and the overlying
atmosphere in the tropical Pacific region. This interaction
is better known as the El Niño Southern Oscillation (ENSO).
While there is no way that an El Niño and its effects
may be stopped, efforts in research and prediction
modelling may, however, help improve the capacity to
understand the phenomenon and the reliability of
forecasts about the onset of the El Niño, thereby helping
to prepare for it. In the Philippines, PAGASA will play a big
role in providing more reliable SCFs to guide various
stakeholders, more specifically the farm sector. It is
expected that from case studies to be done in different
regions in the country, PAGASA will be in a position to
better match forecasts with decisionmakers’ needs,
thereby closing the gap between actual and potential
values of SCF.
Finally, during the forum, the difference between
weather and climate was explained. Weather is a specific
condition of the atmosphere at a particular time and
space while climate is the average weather for a longer
period of time. The various elements or factors affecting
the weather and/or climate as well as the different climate
types in the various regions of the Philippines were also
presented and discussed. As a supplement, the PAGASA
also gave an outlook of the climate in the Philippines for
the next three months. (SCF Project Updates June 2005)

6 SCF Folio
Basics on Philippine climatology
In our daily lives, the weather plays a particular
role. Whether we commute to our work stations
or work in the farm or do our daily chores as
homebodies, knowing what the weather outlook will
be is useful for our respective purposes.
Beyond the knowledge of having the sun shining
brightly or having rains for the day, however, the average
citizen does not know much about the weather or
climate.
And for a country like the Philippines where
certain weather/climate conditions affect lives,
properties and sources of livelihood on an almost
regular basis, understanding more about the nature,
causes and manifestations of these conditions may, in
a way, help be better prepared for them when they
come. This writeup is thus a starting point for learning
a little more about them.
Weather is the specific condition of the atmosphere
at a particular place and time. It can change from hour
to hour and from one season to another. Climate, on
the other hand, is the average weather of a particular
area that prevails over a particular period of, for instance,
over a month, one season, a year, or even several years.
Figure 1. Climate map of the Philippines based
on the modified Coronas classification
Weather/climate is measured and characterized by
a number of elements but the three most important
are temperature, humidity and rainfall. Temperature
refers to the degree of hotness and coldness of the
atmosphere. Humidity is the moisture content of the
atmosphere while rainfall is the amount of precipitation
in liquid form falling over a specific area. Its distribution
varies across regions in the country depending on the
direction of moisture-bearing winds and the presence
of mountain systems.
The climate of the Philipines is influenced by the
complex interaction of various factors such as the
country’s geography and topography; principal air
streams; ocean currents; linear systems such as the
intertropical convergence zone; and tropical cyclones
which are classified as tropical depression, tropical
storm or typhoon, depending on their intensities (to
be presented in a separate issue of the Economic Issue
of the Day).
Among these factors, it is perhaps useful to
understand the movements of air streams. Rainfall is
generally a result of the movement and interaction of
cold and warm air masses in a particular period. The
Southwest Monsoon or locally known as Habagat, for
instance, affects the country from May to September
and occurs when warm moist air flows over the country
from the southwest direction. This brings in rains to the
western portion of the country. The Northeast Monsoon
or Amihan, meanwhile, affects the eastern portions of
the country from October to late March. Cold and dry
air mass from Siberia gathers moisture as it travels over
the Pacific and brings widespread cloudiness with rains
and showers upon reaching the eastern parts of the
Philippines. In addition, a cold front affects the country
from November to February and brings increased
cloudiness and heavy rains. This occurs when a mass of
moving cold air overtakes a mass of moving warm air
resulting in towering cloud formations that bring heavy
rains and thunderstorms.
On the whole, the climate of the Philippines (using
temperature and rainfall as the gauge) can be divided
into two major seasons: the rainy season, which sets in
by June and ends around November, and the dry
season, which sets in by December and ends in May.

7
The dry season is also subdivided into the cool dry season
from December to February and the hot dry season from
March to May.
The entire country, however, may be characterized
by four types or classifications (Figure 1) of climate based
on the distribution of rainfall.
Type I—has two pronounced seasons: dry from
November to April and wet throughout the rest of the
year. The western parts of Luzon, Mindoro, Negros, and
Palawan experience this climate. These areas are shielded
by mountain ranges but are open to rains brought in by
Habagat and tropical cyclones.
Type II—characterized by the absence of a dry
season but with a very pronounced maximum rain period
from November to January. Regions with this climate are
along or very near the eastern coast (Catanduanes,
Sorsogon, eastern part of Albay, eastern and northern
parts of Camarines Norte and Sur, eastern part of Samar,
and large portions of Eastern Mindanao).
Type III—seasons are not very pronounced but are
relatively dry from November to April and wet during the
rest of the year. Areas under this type include the western
part of Cagayan, Isabela, parts of Northern Mindanao, and
most of Eastern Palawan. These areas are partly sheltered
from tradewinds but are open to Habagat and are
frequented by tropical cyclones.
Type IV—characterized by a more or less even
distribution of rainfall throughout the year. Areas with this
climate include Batanes, Northeastern Luzon, Southwest
Camarines Norte, west of Camarines Sur, Albay, Northern
Cebu, Bohol, and most of Central, Eastern, and Southern
Mindanao. (Economic Issue of the Day Vol. V, No. 2-July 2005)
Tropical cyclone signals: bracing
for the wind
Typhoons, tropical storms, tropical depressions, and
other weather disturbances are usual occurrences
in the Philippines. According to the Philippine
Atmospheric, Geophysical and Astronomical Services
Administration (PAGASA), an average of 19–20 tropical
cyclones visit the country every year, some of which may
cause deaths to many people and millions of pesos in
damaged property.
But how strong can tropical cyclones be and how
much damage can they cause What is their pattern of
occurrence
These questions are important to consider especially
for a typhoon-frequented country like the Philippines so
In meteorology, a tropical cyclone is a low-pressure system
wherein the central region is warmer than the surrounding
atmosphere. Its strongest winds are concentrated close to its
center. From pictures taken above the earth, a tropical cyclone
resembles a huge whirlpool of white clouds.
Tropical cyclone is the general term for all storm circulations
that originate over tropical waters. It is called hurricane over
the Atlantic Ocean, cyclone over the Indian Ocean, and typhoon
over the Pacific Ocean.
that one can be better prepared to deal with them and
thereupon prevent possible damages and loss of lives.
In a nutshell, the various terms listed herein are
actually interchangeable, depending on the intensity of
the weather disturbance and location. By international
agreement, tropical cyclone is the general term for all
storm circulations that originate over tropical waters. It is
called hurricane over the Atlantic Ocean, cyclone over the
Indian Ocean and typhoon over the Pacific Ocean.
In meteorology, a tropical cyclone is a low-pressure
system wherein the central region is warmer than the
surrounding atmosphere. Its strongest winds are
concentrated close to its center. From pictures taken
above the earth, a tropical cyclone resembles a huge
whirlpool of white clouds. It has a disc-like shape with a
vertical scale of tens of kilometers against horizontal
dimensions of hundreds of kilometers.
Types of tropical cyclones
Tropical cyclones are categorized into three types:
• Tropical depression – a tropical cyclone with
maximum surface winds ranging from 37 to 62
kilometers per hour (kph) (20 to 33 knots).
• Tropical storm – a tropical cyclone with maximum

8 SCF Folio
Signal No. Wind Speed and Time Impact of Winds
of Occurrence
1 30–60 kph within the next Twigs and branches may be broken; some banana plants may be tilted;
36 hours houses of very light material may be unroofed; flowering rice crop may be
damaged; in general, very little or no damage may be experienced by the
community.
2 60–100 kph within the next Some coconut trees may be tilted and broken; few big trees may be
24 hours uprooted and many banana plants may be downed; rice and corn may be
adversely damaged; many nipa and cogon houses may be partially or totally
unroofed and old galvanized iron roofings may be peeled off; in general,
winds may bring light to moderate damage to the community.
3 100–185 kph within the next Many coconut trees may be broken or destroyed; almost all banana plants
18 hours may be downed while many trees may be uprooted; rice and corn crops
may suffer heavy losses; majority of nipa and cogon houses may be unroofed
or destroyed and there may be considerable damage to structures of light to
medium construction; widespread disruption of electrical power and
communication services may also occur; in general, moderate to heavy
damage may be expected, practically in the agricultural and industrial
sectors.
4 Greater than 185 kph within Coconut, rice, and corn plantations may suffer extensive damage and many
the next 12 hours
large trees may be uprooted; most residential and institutional buildings of
mixed construction may also be severely damaged; electrical power
distribution and communication services may be disrupted; in general,
damage to affected communities can be very heavy.
surface winds in the range of 63 to 117 kph (34 to
63 knots).
• Typhoon/hurricane – a tropical cyclone with
maximum surface winds of 119 to 239 kph (64 to 129
knots).
A super typhoon is a term used by the U.S. Joint
Typhoon Warning Center in Guam for typhoons that
reach maximum surface winds of at least 242 kph (130
knots).
The areas affected by these tropical cyclones, as
indicated by their respective term, are those in the
tropics, the region of the earth centered on the equator
and sandwiched between the Tropic of Cancer in the
northern hemisphere and the Tropic of Capricorn in the
southern hemisphere. Countries that are situated in
these areas are found in Africa, Asia, South and Central
America, the Caribbean, and those in the Indian and
Pacific Oceans. Most of these are developing countries
such as Kenya, Mozambique, the Philippines, Indonesia,
Malaysia, Egypt, Mexico, Ecuador, Brazil, Saudi Arabia,
and the Bahamas, among others. It also includes
southern China, Australia, and Chile.
Philippine storm warning signals
For the Philippines, PAGASA devised four warning
signals that describe the meteorological conditions and
impact of the winds of an approaching tropical cyclone
as shown above.
Seasons and path of potential destruction
An average of 100 tropical cyclones are formed every
year around the world. Of this total, the bulk is formed
in one region or area—the western north Pacific Ocean.
An average of 30 cyclones every year are formed here.
They usually move westward approaching the
Philippines.
Once in the Philippine area of responsibility (PAR),
these tropical cyclones, now called typhoons, usually
move northwest; in the process, leaving destruction to
the provinces in northern Luzon. The typhoons then
exit the PAR and head toward Taiwan, southern China
or Japan.
What has been the pattern of frequency that
tropical cyclones or typhoons enter the Philippines
When and where can they bring potential destruction
PAGASA estimates that the monthly average
frequencies of tropical cyclones that enter the PAR from

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Tropical cyclone average tracks
Jan to Mar
Apr to Jun
Jul to Sep
January to April are 0.4, 0.3, 0.3, and 0.5, respectively. This
suggests that these months have the slimmest chance of
tropical cyclone activities in the Philippines throughout
the year. Starting May and June, however, an average of
one tropical cyclone for each month occurs and then
jumps to about three each for the months of July, August,
and September. By October and November, an estimate
of about two per month occurs, signaling the start of
descent of the cyclone activities in the Philippines, with
just about one occurrence for the month of December.
Although there is a recession in the number of
tropical cyclone occurrences in the months of October
to December, it is to be noted nevertheless that most of
the destructive cyclones/typhoons that have taken place
were recorded during this period. This is due to the fact
that the paths of these disturbances have, as seen in the
illustrations, a much wider range of possible tracks over
Luzon and Visayas during this period. At the same time,
there is also a high probability that these cyclones tend
to cross the archipelago, creating much damage to the
populace.
Is there any change in the cyclones/typhoons' path
when seasonal phenomena like El Niño and La Niña take
place At the moment, the weather bureau is in the
process of further tracking the average paths of tropical
cyclones and determining if there is a difference in their
usual path during the periods of El Niño and La Niña.
(Economic Issue of the Day Vol. V, Nos. 3&4-December 2005)
References
http://hurricanewaves.org
http://www.hko.gov.hk/informtc/nature.htm
http://www.ndcc.gov.ph
http://www.pagasa.dost.gov.ph
http://www.typhoon2000.ph/info.htm
http://www.wikipedia.org
Lucero, A. Warning system for tropical cyclones in the Philippines.
Powerpoint presentation. PAGASA.
Verceles, E. Climate concepts, climate of the Philippines, and
ENSO. Powerpoint presentation. PAGASA.

10 SCF Folio
Understanding the ENSO phenomenon
and its implications
Ask anyone about what he/she thinks El Niño place and something must be done to address its
is and the usual answers would be—a possible consequences.
severe drought or a long hot summer or a
dry spell followed by heavy rains. While all of these are
indeed associated with El Niño, they are, however,
merely the effects or impacts of this phenomenon. What
it really is lies somewhere in the Pacific.
Feeling the heat
Although the physical occurrence of El Niño (and La
Niña) takes place in the Pacific, its effects are felt in other
parts of the world, similar to a ripple effect in a big pond.
This is due to the so-called southern oscillation (SO)
What it basically is…
El Niño is a condition that takes place in the Central and
Eastern Equatorial Pacific (CEEP) Ocean, when the sea
surface temperature (SST) becomes unusually warmer
than the normal temperature. This condition can prevail
for more than a year, thus adversely affecting the
economy in both local and global scale.
The sea or ocean surface usually registers a certain
normal temperature. Any departure from this normal
level is considered an anomaly. If the temperature rises
from normal, it is called a positive anomaly. This
condition is associated with El Niño. Conversely, if the
temperature drops from normal, it is called a negative
anomaly and is more popularly related to La Niña. Either
way, any change in the temperature, just like in the
human body, indicates that something unusual is taking
which refers to a “see-saw” in atmospheric pressure
between the western (represented by Darwin in
Australia) and eastern Pacific (represented by the island
of Tahiti).
These variations in the atmosphere in the Pacific,
combined with changes in the SST as discussed earlier,
are responsible for bringing about abnormal climatic
events. The interaction between sea and atmosphere
variations refers to the El Niño Southern Oscillation
(ENSO) and potentially influences extreme climate
events in the world (El Niño refers to the ocean or sea
component of ENSO while the SO refers to the
atmospheric component).
El Niño and La Niña are basically flip sides (warm
and cold phases, respectively) of the ENSO and as such,
do not take place simultaneously in one area/region.
However, in terms of
teleconnection or the links of
El Niño
El Niño (EN) is Spanish for “The Christ Child,” a name given by Peruvian fishermen to the
phenomenon that they usually observed during the period near Christmas time when the water in
climate over great distances, if
the eastern part of the Pacific
experiences an unusual ocean
the Pacific Ocean off the coast of Peru would become unusually warm. Every two to nine years, for
warming and low atmospheric
unexplained reason, trade winds in the Pacific region, which drive the surface warm waters of the
pressure (characteristics of the
tropics to the west Pacific, weaken. As a result, these warm waters of the western Pacific drift
eastward, resulting in the occurrence of El Niño in the eastern part of the Pacific.
warm phase or El Niño), then the
western part of the Pacific will
Southern oscillation
Southern oscilllation (SO) is an east-west balancing movement of air masses between the eastern
likely experience the opposite
effect, characterized by cooler
Pacific and the Indo-Australian areas. It is measured as the difference between the overlying
ocean and high atmospheric
atmospheric pressures at Darwin (northern Australia) and Tahiti (south-central Pacific). This term
pressure.
was coined by the British scientist named Sir Gilbert Walker during the 1920s when he observed
that when the atmospheric pressure rises in the east, the waters of the eastern Pacific are unusually
cold, and when the atmospheric pressure drops in the eastern Pacific, the waters in this part of the
Pacific are unusually warm. The opposite effects are observed in the western Pacific.
The implications
The effects of ENSO on climate
variability all over the globe

11
inevitably have impacts on the various ecological and
agricultural production systems around the world.
In the Philippines, for instance, an ENSO event can
trigger extreme climatic effects such as droughts, strong
winds, floods and flashfloods, increasing or decreasing
temperatures and many more. The impacts on Philippine
climate are initially felt three or five months after the
development of an ENSO phenomenon in the tropical
Pacific. If the ocean-atmosphere interaction or ENSO is
stronger than the usual, however, the Philippines may feel
the weather abnormalities much earlier.
One of the abnormalities brought about by El Niño,
the warm phase of ENSO, is a generally drier weather
condition, the effect of which is greatly felt during the
dry season. From May to September or during the
country’s rainy season due to the southwest monsoon,
though, rains may still be expected or felt even with an El
Niño occurring in the Pacific.
Once the southwest monsoon rainy season ends by
late September or early October, rains may be much lesser
than normal during an El Niño event. This is critical
especially for rice farmers in Central Luzon who
traditionally prepare for their second cropping season
before the end of the year. If there is indeed an El Niño
event, this implies, among others, that enough water
should have been stored in the water reservoirs so as to
provide irrigation for the crop upon the onset of the dry
season (January to April) when hardly any or no rain might
be expected.
Finally, once the El Niño/La Niña signs start to brew,
there is nothing that can stop them from occurring. It is
nonetheless useful to understand the processes on how
they evolve to be able to be better prepared for them.
(Economic Issue of the Day Vol. V, No. 1-July 2005)
Knowing when El Niño/La Niña is here
In a previous Economic Issue of the Day (Vol. V, No. 1,
July 2005), a basic understanding was presented on
what the El Niño Southern Oscillation (ENSO)
phenomenon is all about, its characteristics and two
phases, and its implications.
ENSO is a phenomenon that takes place in the
central and eastern equatorial Pacific largely
characterized by an interaction between the ocean and
the atmosphere and their combined effect on climate. The
mutual interaction between the ocean and the
atmosphere is a critical aspect of the ENSO phenomenon.
Major ENSO indicators are the sea surface
temperature anomaly (SSTA) and the Southern Oscillation
Index (SOI).
SSTA refers to the departure or difference from the
normal value in the sea or ocean surface temperature. El
Niño events are characterized by positive values (greater
than zero) within a defined warm temperature threshold
while La Niña events are characterized by negative values
(less than zero) within a defined cold temperature
threshold.
The SOI, on the other hand, measures the differences
or fluctuations in air or atmospheric pressure that occur
between the western and eastern tropical Pacific during
El Niño and La Niña episodes. It is calculated on the basis
of the differences in air pressure anomaly between Darwin
in Australia (western Pacific) and Tahiti in French Polynesia
(eastern Pacific). These two locations/stations are used in
view of their having long data records.
Albeit the seeming straightforward description of
these ENSO-related events as noted in the above, it is to
be emphasized that through the years, it has not been
easy to come up with a commonly agreed definition and
identification of these ENSO-related events, i.e., El Niño or
La Niña. The reason is due to the use of more than one
standard index as basis in monitoring ENSO phenomena
and the employ of different methods in determining the
magnitude or value of such index and threshold as well
as the length of time that such magnitude persists. In line
with this, the Philippines adopted the World
Meteorological Organization (WMO) Regional Association
IV Consensus Index and Definitions of El Niño and La Niña.
Region IV includes the North and Central America
member nations of the WMO, whose operational
definitions in use of the two ENSO phases are the
following:
El Niño: A phenomenon in the equatorial Pacific
Ocean characterized by a positive SST departure from

12 SCF Folio
normal (for the 1971–2000 base period) in the Niño 3.4
region, greater than or equal in magnitude to 0.5
degrees C, and averaged over three consecutive
months. Defined when the threshold or value is met
for a minimum of five consecutive overlapping seasons.
La Niña: A phenomenon in the equatorial Pacific
Ocean characterized by a negative SST departure from
normal (for the 1971–2000 base period) in the Niño 3.4
region greater than or equal in magnitude to 0.5
degrees C, and averaged over three consecutive
months. Defined when the threshold or value is met
for a minimum of five consecutive overlapping seasons.
PAGASA: monitoring El Niño/La Niña events
in the Philippines
In the Philippines, how is El Niño/La Niña identified/
monitored The country’s national meteorological
agency, the Philippine Atmospheric, Geophysical and
Astronomical Services Administration (PAGASA), defines
and identifies these phenomena on the basis of the
abovementioned indicators which are also being used
by the National Oceanic and Atmospheric
Administration-National Centers for Environmental
Prediction (NOAA-NCEP) of the United States.
Through the years and based on this definition
and data from the NOAA, PAGASA has monitored the
occurrence of El Niño/La Niña by category, as follows:
a) weak El Niño/La Niña – magnitude of +0.5 to +1.0
°C (or -0.5 to -1.0 °C)
b) moderate El Niño/La Niña – magnitude of +1.0 to
+1.5 °C (or -1.0 to -1.5 °C)
c) strong El Niño/La Niña – magnitude of more than
+1.5 °C (or less than -1.5 °C)
When is El Niño/La Niña occurring
Because ENSO-related phenomena have been a major
source of interannual climate variability around the
globe, especially in recent years, it is important to be
able to determine or identify when an El Niño/La Niña
is occurring or will take place.
As noted earlier, monitoring the occurrence of an
El Niño/La Niña involves the use of two most common
indicators, the SSTA and the SOI, with the SSTA based Table 1 shows the years when these events and
on the magnitude of departures/anomalies in the sea their categories have taken place in the last decade. It
surface temperature in the Niño regions (see box), and is to be noted that no two ENSO events are alike in terms
the SOI based on the difference in air pressure between of climate impacts. Accordingly, PAGASA gives out the
Tahiti and Darwin.
appropriate advisories to the various sectors and
decisionmakers concerned on the occurrence/presence
of El Niño/La Niña for their
corresponding action.
Box. NIÑO regions
(Economic Issue of the Day Vol.
VII, No. 1-January 2007)
El Niño regions: Although El Niño is a generalized event in the equatorial Pacific, there are different
regions which show different characteristics and different moments in the process. Past studies
References
show that the Philippine climate responds more significantly to temperature changes in the NIÑO
3.4 region.
Columbia University. 2006. When
can we say El Niño will occur
[online]. Available from the
World Wide Web:(http://
www.columbia.edu/~za2121/
Peru-ENSO/Peru-ENSO/Webpages/El%20Nino/
When%20will%20it%20
occur.html).
International Research Institute
for Climate and Society. 2006.
Defining ENSO [online]. Available
from the World Wide Web:(http:/
/iri.columbia.edu/climate/ENSO/
Source: International Research Institute for Climate and Society
background/pastevent.html).

13
Reaching out and increasing awareness
Table 1. El Niño and La Niña episodes during the past decade
Period Event Category
May 1994 – April 1995 El Niño weak to moderate
October 1995 – April 1996 La Niña weak
June 1997 – May 1998 El Niño strong
August 1998 – July 2000 La Niña moderate to strong
November 2000 – March 2001 La Niña moderate
June 2002 – April 2003 El Niño weak to moderate
August 2004 – March 2005 El Niño weak
Source of data: Climate Prediction Center – National Oceanic and Atmospheric
Administration (CPC-NOAA), 2006
Reaching out to local population
on seasonal climate information
Part of the information dissemination activity of
the project funded by the Australian Centre for
International Agricultural Research (ACIAR) on
seasonal climate forecasts (SCFs) was a seminar-workshop
held on June 30, 2005 at the Leyte State University (LSU)
in Baybay, Leyte. In coordination with the Philippine
Atmospheric, Geophysical and Astronomical Services
Administration (PAGASA) and the Philippine Institute for
Development Studies (PIDS), the LSU hosted the seminarworkshop
to inform the local people, particularly
members of the academe in the region, agricultural
officers, and other local officials, about the project and the
value of SCFs in their decisionmaking processes in relation
to crop production, especially in addressing the impact
of El Niño and other extreme climate events. The seminar
also aimed to strengthen the coordination and
cooperation between PAGASA and the agricultural sector
The seminar aimed to inform the local people, particularly
members of the academe in the region, agricultural officers,
and other local officials, about the project and the value of SCFs
in their decisionmaking processes in relation to crop
production, especially in addressing the impact of El Niño and
other extreme climate events.
National Oceanic and Atmospheric Administration (NOAA). 2006.
ENSO cycle: recent evolution, current status, and predictions
[online]. Climate Prediction Center, National Centers for
Environmental Prediction. Available from the World Wide
Web:(http://www.cpc.ncep.noaa.gov/products/
analysis_monitoring/lanina/.
Philippine Institute for Development Studies/Australian Centre
for International Agricultural Research. 2006. SCF Project
Updates Vol. II Nos. 1&2, 2006. Makati City: PIDS.
Trenberth, K.E. 1997. The definition of El Niño. Bulletin of the
American Meteorological Society 78:2771-2777.
in order for the latter to be better served through proper
application of weather and climate information.
Similar to what had been presented in the first
Pulong Saliksikan held at the PIDS last April, resource
persons from PAGASA presented basic climatology
concepts and information such as Philippine climatology,
basic El Niño Southern Oscillation (ENSO) concepts,
tropical cyclone warning system as well as a climate
outlook for the province of Leyte. After the PAGASA
lectures, responses from the local government unit (LGU)
representatives regarding their agriculture response
strategies to extreme climate events such as El Niño and
La Niña were presented. The LGU representatives
discussed the various measures they adopt under these
circumstances, as divided into the (a) predisaster phase,
(b) disaster phase, and (c) postdisaster phase.
A lecture on PAGASA’s climate information products
and services offered then followed, after which the
participants were divided into two groups and were asked
their assessment of such products and services in terms
of usefulness, timeliness, ease of understanding, and
comprehensiveness. Suggestions on how said products
may be further improved were likewise solicited from the
participants. During this portion, exercises such as the
plotting of a tropical cyclone track and interpretation of
certain/selected PAGASA climate information products were
also given to the participants. (SCF Project Updates, June 2005)

14 SCF Folio
Making the most out of seasonal climate
forecasts (SCFs)
No one can tell for sure what the next season
will be like. Even when a climate in a
particular place or region is generally
predictable, there is a varying difference in the yearly
duration, intensity and timing of rainy and dry periods.
Thus, it is important to know and understand SCF and
how it may benefit the population.
Global changes in weather and climate are largely
brought about by the cycle of atmospheric and pattern
changes in the Pacific Ocean called the El Niño Southern
Oscillation (ENSO). This usually occurs in December;
hence, the term “El Niño” for the “Christ Child,” and
usually has a cycle duration of four years. The ENSO is a
complex process but basically it involves the unusual
warming and cooling of the ocean’s surface sea
temperature. The El Niño is the warm phase of the ENSO
while La Niña is the cool phase. The changes in
temperature that these phases bring affect weather and
climate in many parts of the world, even those that are
far from the Pacific Ocean.
With advances in science and technology, people’s
knowledge on seasonal climate changes such as ENSO
has grown considerably. A seasonal climate forecast is
an estimate of how rainfall or temperature in a coming
season is likely to be different from the prevailing
average climate. SCFs use dynamical (based on laws of
physics) or statistical (based on historical patterns)
methods to predict the climate. They usually forecast
“above median” or “below median” rainfall. Seasonal
climate forecasting is usually done three months to a
year in advance or longer.
Why it is important to understand SCFs
Weather and climate are significant forces in people’s
lives. Important and not-so-important decisions are
made depending on the weather or ensuing climate.
Planning for social and economic benefits would be
greatly enhanced by being able to forecast seasonal
conditions in the months ahead. Conversely, it can mean
human lives and incomes lost when changes in climate
are not anticipated. Thus, knowing and understanding
SCFs can save lives, lessen the costs and present
opportunities to various sectors for better planning and
decisionmaking.
The agriculture sector would naturally be the
major beneficiary of SCF. For the Philippines, it is one of
the country’s top industries which accounted for about
18 percent of the total gross domestic product (GDP)
and whose labor force reached 11.38 million in 2004.
Since agriculture is vulnerable to climate variability,
farmers may benefit from SCFs by being able to choose
what crops to plant and when to plant them. While the
risks may not be completely eliminated, information
from SCFs can lessen the costs that would have been
incurred and may even enable farmers to make
substantial yields and higher incomes.
Other end users of SCFs include the energy
sector—suppliers of electricity and natural gas which
benefit from forecasts to help them plan energy usage
and make operations run efficiently. The tourism
industry is likewise a logical beneficiary as travel agents
and event organizers are able to put together vacation
packages and schedule occasions at appropriate times.
Retailers and other businesses can also benefit from
valuable climate forecasts as they will be able to time
their procurement of stocks that may be in demand
once the weather changes. National and local
governments can strengthen their civil defense
programs by being able to stock up on supplies and
train for emergency disaster operations and drought
relief activities.
Limitations of SCFs: bridging the gap
Certainly, SCF is still an imperfect science even with the
advancement of technology and research. The accuracy
of the forecasts is the primary concern which may
fluctuate over a period of time and with successive
forecasts. It is not known what percentage of farmers
in the Philippines rely on SCFs in their decisionmaking.
It is said that the use of SCFs in the country and in
Australia is “hampered by the lack of robust means of
showing the economic value of SCF-specific decisions.”
Some of the major concerns regarding SCFs are
their accuracy and timeliness, the difficulties

15
To ensure that the SCFs are rendered useful to their
beneficiaries, it is important that they reach them in a timely
fashion and that they contain the needed information for the
decisionmakers. Thus, information like when the rains will
come, how frequently they will occur, and how much rainfall
is to be expected must be delivered in the clearest, simplest,
and most accurate manner.
encountered in applying them to farm management
decisions, and the apparent lack of evidence of their
economic value to reduce the risks associated with their
adoption. In view of this, the application of SCFs in
decisionmaking has been more difficult than initially
thought.
blitzes to the farmers on the basics of weather, climate
and seasonal forecasts, issuing frequent weather and
climate analyses in popular mass media, and making
information readily available and accessible to the farmers
and other end users.
A study on the usage of SCFs in Zimbabwe found
that farmers complained of receiving climate forecasts
after they have made planting decisions. They also did
not understand nor trusted the forecasts. Thus, any
seasonal climate forecast communications system that
will be developed by any country should involve the
active participation of farmers and other stakeholders. In
so doing, SCFs would have greater relevance, credibility
and legitimacy. (SCF Project Updates, December 2005)
Ground level: reaching out to end users for SCF
information
To ensure that the SCFs are rendered useful to their
beneficiaries, it is important that they reach them in a
timely fashion and that they contain the needed
information for the decisionmakers. Thus, information like
when the rains will come, how frequently they will occur,
and how much rainfall is to be expected must be delivered
in the clearest, simplest, and most accurate manner. This
may be achieved by conducting frequent information
Sources
SCF Project Updates Vol. 1, June 2005.
“Valuing seasonal climate forecasts” by Dr. John Mullen.
www.nscb.gov.ph.
www.ksg.harvard.edu/sed/docs/k4dev/
lemos_k4dev_031002.pp.
www.census.gov.ph/data.
http://iri.columbia.edu/outreach/meeting/MediaWS2001/
Glossary.html.
http://www.bas.gov.ph/agri_dev.php.
Tale of two surveys: feedback to PAGASA’s
climate information products and services
On June 30 and December 1, 2005, seminarworkshops
on “Toward bridging the gap between
seasonal climate forecasts and decisionmakers in
agriculture” were held in Baybay, Leyte and Malaybalay,
Bukidnon, respectively. These seminars were part of the
dissemination program of the four-year project with the
above title sponsored by the Australian Centre for
International Agricultural Research (ACIAR) and were
jointly conducted by the Philippine project implementing
institutions, namely, the Philippine Atmospheric,
Geophysical and Astronomical Services Administration
(PAGASA), the Philippine Institute for Development
Studies (PIDS), and the Leyte State University (LSU). The
purpose of these seminar-workshops was to introduce the
project to various local government units, members of
academe, and farmer groups in terms of its objectives,
plan of activities, expected outputs, and possible utility in
the decisionmaking and risk management of
stakeholders/decisionmakers in agriculture. Some basic
concepts relating to the project like the El Niño Southern
Oscillation phenomenon, tropical cyclones, climate
outlook and local forecasts, and other useful
meteorological terms and information were also
explained. Participants in these two seminars were from
LGUs (mostly municipal agriculturists), the academe, and
a few groups representing farmers.
To help PAGASA in its goal of improving its service
delivery, especially in terms of its climate information
products and services, to the agriculture sector and other
related stakeholders, the participants were asked to

16 SCF Folio
answer a survey questionnaire during the seminars. The
questionnaire had two parts. The first referred to the
participants’ profile which identified the respondents’
designations and sector/category representation. The
second referred to the participants’ feedback which had
11 questions on what the respondents thought about
PAGASA’s products and services. Aside from directly
offering information to PAGASA, the responses to the
questionnaire may also provide some insights to the
project team members on how decisionmakers in
agriculture source and make use of information
regarding climate, including seasonal forecasts.
Findings
Majority of the respondents were municipal
agriculturists and members of the academe with a few
members of farmers’ groups. All of them considered
weather/climate as a factor in planning and
decisionmaking in their work/source of livelihood, with
the majority claiming it is a critical factor.
Radio/tv were cited as the sources of information
about weather/climate used by the majority of the
respondents, with PAGASA stations coming in second
and the rest a split among local practices/beliefs,
broadsheets/tabloids, advisories from head offices and
associates and extension workers.
In terms of awareness of PAGASA’s products and
services, majority of the respondents in Leyte were
aware while less than half of the respondents in
Bukidnon were. Those who were aware and went on to
rate these products and services gave generally good
assessments.
Suggestions given by the respondents on how to
improve PAGASA’s products and services were basically
the same as gleaned from the two surveys. Essentially,
what the respondents want is for PAGASA to have a
stronger presence in their municipalities and establish
a stronger linkage with them. There was also a clamor
for publications that are easier to understand, preferably
PAGASA needs to do more to reach the people who use its products
and services to make decisions that affect their work, especially
since these people are in the rural areas and far from informationrich
metropolises...More effort must also be made in making the
information more understandable and more accessible to the
clients.
in the vernacular, and more information and education
campaign (IEC) activities, trainings and seminars from
PAGASA. Establishment of agromet and weather
stations in their local government units (LGUs) was also
shared by many of the respondents as well as the
improvement of PAGASA’s facilities. Perhaps owing to
the difference in the sector they belong to, the
members of the academe in Leyte have access to the
internet and thus wanted weather/climate data
available online.
The respondents in Leyte recommended a closer
link between PAGASA and LGUs in order that the LGUs
themselves could request the kind of information that
are more suited to their constituents and localities. They
also cited the need for more site-specific data that the
local weather stations could regularly disseminate to
the community. Those in Bukidnon, on the other hand,
basically wanted to have agromet stations and rain
collector systems facilities in addition to more related
publications and trainings from PAGASA.
Implications and recommendations
It is clear that PAGASA needs to do more to reach the
people who use its products and services to make
decisions that affect their work, especially since these
people are in the rural areas and far from informationrich
metropolises.
In order to achieve this, the weather bureau needs
to have more partners in nongovernment organizations
(NGOs), LGUs, the academic research community and
individual experts who can help disseminate and
explain weather/climate information. The more
vigorous partnership with these groups and individuals
would help establish better communication among the
stakeholders and help make the receivers of
information inform PAGASA of the data they need in
their localities.
More effort must also be made in making the
information more understandable and more accessible
to the clients. This would indeed be challenging since
scientific data are difficult to translate to local dialects
and so it is necessary to have more seminars and
lectures by PAGASA particularly in the regions.
Lastly, the mass media should be tapped not just
to report weather forecasts that are usually steeped in
weather jargon but also to explain basic concepts in
order to reach more people. (SCF Project Updates,
December 2005)

Communicating through climate indicator
signs
17
Bronya Alexander
and Peter Hayman
Motorists are often
exposed to
informative road
signs such as bushfire risk or
number of road accidents. So why
not have a sign to convey seasonal
climate information Based on an
idea from the Birchip cropping
group in Victoria, along with
funding from the South Australian
Grains Industry Trust Fund and
other organizations, the South
Australia Research and
Development Institute (SARDI) has developed the Climate
Indicator signs. These large signs are used to convey a
range of different types of seasonal climate information
through the use of colored dials. They are placed in
paddocks on the road side so that farmers and
agriculturists can see the latest information and outlooks.
The signs have also been shown and discussed at
agricultural field days like the one shown in the photo
above.
There are six dials on the signs as seen in Figure 1
and described below.
1) Current growing season rainfall (GSR) decile –
this is calculated by comparing the amount of current
season rainfall with the long-term rainfall at the closest
meteorology station.
2) Forecast GSR deciles – the Department of
Agriculture and Food Western Australia (DAFWA) has
designed an experimental system for producing seasonal
climate forecasts. This system draws from indices based
on the El Niño Southern Oscillation (ENSO), and produces
five years that are considered to have performed similarly
to this year. The GSR from these five analogue years are
indicated via the five arrows on the dial.
3) Probability of exceeding median rainfall using
SOI – this shows two arrows. One represents the current
Melissa Rebbeck from SARDI presents the Climate Indicator Signs at a Yorke Peninsula
field day in South Australia in September 2006.
outlook from the Australian Government Bureau of
Meteorology for the chance of exceeding the median
rainfall over the following three months. The other arrow
is the outlook based on the SOI, provided by the
Queensland Department of Primary Industries.
4) Yield Prophet – this indicates the expected crop
yield from the Yield Prophet model developed by the
Birchip Cropping Group. Yield Prophet is the interface to
the crop simulation model called APSIM (Agricultural
Production Systems Simulator), which simulates crop
growth on a daily time step.
5) Nitrogen Calculator – this model, developed by
CSIRO (Australian Commonwealth Scientific and Research
Organisation), estimates the expected crop yield and the
corresponding nitrogen amounts recommended for the
soil. The expected yield from Nitrogen Calculator is
indicated on the dial.
6) Soil moisture guide – this shows the Yield
Prophet estimate for current stored soil moisture.
The SARDI Climate Applications Unit is updating the
signs in Morchard (upper north), Paskeville (Yorke
____________
The authors are Project Officer and Principal Scientist on Climate
Applications, respectively, both from the South Australia Research
and Development Institute (SARDI).

18 SCF Folio
Figure 1. Electronic version of the Climate Indicator signs created to allow for easy distribution
to farmers and consultants via email
Peninsula), and Tarlee (mid-north) in South Australia this
season. An electronic version of the signs has also been
created to help with communicating and distributing
the outputs via email. Some focus group sessions will
be held for farmers in these areas to discuss how to use
the information in the signs in decisionmaking. The
ACIAR project Bridging the gap between seasonal
climate forecasts and decisionmakers in agriculture has
been assessing how the information on the signs has
been used in decisionmaking and analyzing the relative
weight that should be given to measurements such as
the level of water stored in the soil or rainfall to date
versus predictions of the coming season based on
seasonal climate forecast. (SCF Project Updates, June 2007)
Giving better seasonal climate forecasts
and climate-related information
The Philippine Atmospheric, Geophysical and
Astronomical Service Administration (PAGASA),
the country’s national meteorological agency,
offers a range of climate information products on a
regular basis. It has around 10 advisories/information
products designed to inform and warn the populace
on upcoming climatic/weather conditions.
More significant to seasonal climate variability are
PAGASA’s seasonal climate forecasts (SCFs). SCF is one
of the tools which could help farmers and
decisionmakers better prepare for seasonal variability.
SCF applies probabilistic principles in projecting climatic
deviations. PAGASA uses seasonal predictions from both
national and international climate centers in coming up
with its own forecasts for a certain period. International
agencies tapped for the purpose are the National
Center for Environmental Prediction/Climate Prediction
Center (NCEP/CPC), International Research Institute for

19
Table 1. Awareness, usefulness, and reliabilty of PAGASA climate information products
Product Awareness Usefulness * (%) Reliability ** (%)
(%) 1 2 3 4 5 1 2 3 4
Monthly weather situation and outlook 19 1 4 4 8 4 2 6 6 6
Annual seasonal climate forecast 19 1 5 7 2 2 1 4 8 5
El Niño/La Niña advisory 94 11 16 38 16 13 9 26 24 18
Tropical cyclone warning 85 5 14 32 16 14 6 22 27 18
10-day advisory 7 - 1 5 - 1 - 2 2 1
Farm weather forecast 5 - 1 1 - 2 - 1 - 2
Philippine Agroclimatic Review and Outlook 2 - - - - 2 - - - 2
Press release on significant events 2 - - 1 - 1 - 1 - 1
Phil agri-weather forecast 4 - - 2 - 1 - 1 1 1
Climate impact assessment bulletin for agriculture 4 - - 2 - 1 - 1 1 1
*
Usefulness rating: 1 - not useful, 2 - somewhat useful, 3 - useful, 4 - highly useful, 5 - vital
**
Reliability rating: 1 - unreliable, 2 - somewhat reliable, 3 - reliable, 4 - excellent
Source: Reyes et al. 2006
Climate and Society (IRI), and the Australian Bureau of
Meteorology (ADPC and IRI 2005).
PAGASA’s Climate Monitoring and Prediction Center
(CLIMPC) comes up with monthly and seasonal rainfall
forecasts, and an annual seasonal climate forecast or
outlook. It uses the average values of five different
statistical techniques in forecasting rainfall. These include
the analogue method, Fourier analysis, Rainman, Principal
Component Analysis using sea surface temperature as
predictor, and climate predictability tool (CPT). Fourier
analysis uses long time data series; Rainman is a software
developed by the Australian Center for International
Agricultural Research (ACIAR) that uses ENSO indicators;
and CPT is a forecasting tool from the IRI.
Though the list of climate information products from
PAGASA is long, only El Niño/La Niña Advisory and Tropical
Cyclone Warning effectively reach majority of the farming
populace. From the study of Reyes et al. (2006), 94 percent
of farmers in Isabela were aware of ENSO forecasts while
85 percent received tropical cyclone warnings. The rest
of the information products got a low awareness rating
ranging from 2 percent to 19 percent. Usefulness and
reliability ratings were acceptable with only a few
expressing extreme discontent on the products (Table 1).
However, the figures still indicate that much has to be
done to properly disseminate climatic information,
improve its accuracy, and package the products in more
useful ways.
PAGASA has a wide range of meteorological
products, which could address a variety of climate-related
queries and informational needs among farmers. The
usefulness of these products would be in question if
access to them by target clienteles is impaired. An
advocacy to use wider communication channels would
address this concern. Television and radio programs have
proven to be effective means of bringing information to
farmers in the countryside. Print materials in layman form
and preferably written in the local dialect would also help
a lot in informing farmers and other agricultural
stakeholders.
Another related challenge is the updating and
review of national meteorological archives. Data from all
meteorological stations should be cleaned and
completed for ease in analysis and data processing. This
would also open up a lot of windows for the application
of new technologies and methodologies like the
application of simulation modeling in assessing the
impact of climatic variability.
A more complex issue to tackle is the upgrading of
PAGASA’a capacity to come up with localized seasonal
climate forecasts, aside from the national and/or regional
forecasts it currently gives. Many farmers had aired the
need for more area-specific advisories/information given
the archipelagic nature of the country and the diversity
of local climate/weather conditions. This is a more longterm
goal, which would require huge investments in
establishing local facilities and training necessary
manpower. A possible mechanism to make this more
attainable is to link with local governments and
communities for manpower and resources support.
PAGASA has been doing much to provide the best
meteorological service to the country’s population but
the challenge to do better is ever pressing. The bottom
line is that forecasts and other climate-related information
should reach the most number of users at the earliest
possible time. (SCF Project Updates, December 2007)

20 SCF Folio
Bringing SCFs into the realm
of agricultural decisionmaking in Isabela
For the ACIAR-funded project titled “Bridging
the gap between seasonal climate forecasts
(SCFs) and decisionmakers in agriculture,”
one of the ultimate challenges is on how to be able to
introduce the concept of SCFs and make information
relating to them understood by, available to, and used
by the key stakeholders in the agriculture sector in their
decisions and options for decisionmaking. The end
objective is to help improve productivity and overall
welfare in said sector.
Certainly, this was a challenge posed to the
Philippine project team composed of members from
the Philippine Atmospheric, Geophysical, and
Astronomical Services Administration (PAGASA), the
Philippine Institute for Development Studies (PIDS), and
the Philippine Rice Research Institute (PhilRice), during
the seminar-workshop that it conducted at the Cagayan
Valley Integrated Agricultural Research Center (CVIARC)
of the Department of Agriculture in Ilagan, province of
Isabela on 14 February 2008 to present some of the
highlights of the project and key findings of its study
surveys in the province.
A good start: full provincial leadership support
The province of Isabela is one of the five study sites in
the Philippines chosen for the project to see where,
when, and why SCFs can be valuable—under what
circumstances—and how they may be incorporated as
a major factor in the process of decisionmaking among
the stakeholders in said areas. The other Philippine
study sites are in the key corn-producing areas of
Bukidnon, Cebu, and Leyte, and in major rice-growing
areas of Nueva Ecija. Counterpart case studies are also
being conducted in certain areas in New South Wales
(NSW) and Southern Australia in Australia, the other
country site of the project.
Isabela was selected not only because it is—and
has always been—one of the top producers of both rice
and corn in the country but also because it is a place
that has often been adversely affected by extreme
climate events in varying degree. This was stressed upon
by PAGASA Director Dr. Prisco Nilo, as he pointed out
that the SCF project is basically about the application
of SCFs by various decisionmakers in agriculture, both
at the national and local levels, as a potential means of
mitigating the adverse impacts of climate variability.
To which Isabela’s governor, the Honorable Maria
Gracia Cielo Padaca, in her keynote address during the
seminar-workshop, expressed elation because she
believes that making the various stakeholders in
agriculture in the province acquainted with the
concepts of SCFs and their possible application in their
decisions would provide them with more knowledge
and understanding on how they can turn the climate
adversities into opportunities for them to adopt better
farming systems through, say, crop diversification.
Governor Padaca acknowledged the importance
of the project’s objectives and activities in the province
of Isabela and urged the participants to lend
attentiveness to the presentations so that they may fully
understand the implications of the information and be
able to share them with their fellow Isabelinos who are
also challenged by seasonal climate variability. At the
same time, the governor expressed her wish that the
information to be conveyed by the project in general
are transmitted in a form that could easily be
understood, especially by the farmers.
Basic climatology concepts and their implications
Serving as a springboard for the presentation of the
SCFs for Region 2 which includes Isabela, the PAGASA
team of Ms. Daisy Ortega and Ms. Rosalina de Guzman
first explained some basic climatology concepts and
specifics affecting Region 2.
Region 2 is among the areas in the Philippines
classified as having Climate Type III, one of the four
climate typologies in the Philippines that are based on
the distribution of rainfall. Type III is characterized by
seasons that are not very pronounced but are relatively
dry from November to April and wet during the rest of
the year. For this climate type, while the area (Region 2,
in this case) is partly sheltered from tradewinds, it is
open to the southwest monsoon (habagat) which
brings in rains to the western portion of the country.

21
Very often, this leads to extreme climate occurrences
and subsequent calamities. As Governor Padaca earlier
noted, it is unfortunate that while their province has a
significant contribution to the food supply of the
Philippines, it is a frequent victim of climate calamities that
eventually result in damages in products and properties
worth billions of pesos. It is in this light that SCFs have to
be continuously improved as well as disseminated and
properly explained in terms of their impact, degree of
uncertainties, value, and applications.
Understanding SCFs
Simply put, SCFs are predictions of the likelihood of the
total amount of rainfall to be above, near, or below the
normal range of rainfall received for a particular area in
the coming three to six months. SCFs differ from weather
forecasts in that they provide a longer lead time, say, three
months or sometimes even six months. The question,
however, is: since weather forecasts beyond seven days
tend to decrease in accuracy, how can SCFs provide useful
forecasts if they have a longer lead time period
The reason is because over the years, certain skills in
predicting “anomalies” or “departures from the normal” in
the seasonal average of the weather have been
developed. These anomalies are usually associated with
the earth’s surface conditions that affect the climate like
the sea surface temperature. These are best manifested
in the phenomenon of the El Niño Southern Oscillation
(ENSO)—both in its warm (El Niño) and cold (La Niña)
phases—which causes much of the climate variability in
the world.
SCFs as probabilistic type of forecasts
In presenting the SCFs for Region 2, Ms. de Guzman
introduced the example of the “spinning wheel” which is
divided into three terciles representing three ranges of
values of rainfall. One tercile represents the values in the
lower range; another, the values in the middle range; and
the other, in the upper range. In short, each of the terciles
refers to values that are either: (a) lower than the normal
amount of rainfall; (b) near (or middle range) the normal
amount of rainfall; or (c) above the normal amount of
rainfall. Without any forecasting, the probability of any one
of these three terciles occurring will always be the same—
one out of three—every time one spins the wheel.
With forecasting (SCFs), however, based on
measuring and calculating the climate “anomalies”
mentioned earlier, one is able to predict the higher (or
lower) probability of either one of the terciles occurring
than when no forecasts were made.
Responding to El Niño/La Niña: Isabela’s strategies for calamity mitigation
The province of Isabela is no stranger to natural calamities. In view of its geographical location and topographic characteristics, it is
regularly frequented by occurrences brought about by climate variability. In the past two or three decades, for instance, the province has
seen the onslaught of El Niño/La Niña occurrences.
Because of this, the provincial government, in particular, the Office of the Provincial Agriculturist (OPA), has learned not only to
cope with the adverse effects of such extreme climate events after their occurrence but also to adopt agricultural preparation strategies
before and during the onset of the phenomena.
During the seminar-workshop sponsored by the project on “Bridging the gap between seasonal climate forecasts (SCFs) and
decisionmakers in agriculture” in Ilagan, Isabela on February 14, 2008, the province’s provincial corn and rice coordinators, Mr. Florencio
Viesca Jr. and Mr. Romeo Cadauan, respectively, presented some of these strategies adopted by the OPA in response to El Niño/La Niña
events before, during, and after said events’ onset.
Before the occurrence of said climate phenomena, the OPA conducts a series of information dissemination activities on their possible
and expected effects as well as the alternative crops that can be recommended for planting during this time. The dissemination activities
take the form of meetings, briefings, radio, television and print features, and leaflets, among others. During the onslaught of the calamity,
the OPA, together with all the local government units (LGUs) of the province, the Department of Agriculture’s Cagayan Valley Integrated
Agricultural Research Center and Bureau of Agricultural Statistics, and other partners monitor the extent of damage caused among the
rice and corn farms within the province and, if and where necessary, position available irrigation pumps in required locations.
After the calamity, meanwhile, a team of concerned agencies first validate the areas affected by computing for the amount of damages
and losses caused by the calamity. Thereafter, the Department of Agriculture and sometimes the LGUs, under counterpart agreements,
implement the seed rehabilitation program by giving out free corn, vegetable, and legume seeds to farmers. In addition, the provincial
government has also recently advocated the idea of crop diversification by encouraging the affected farmers to plant legume and vegetable
seeds, apart from corn, on at least a small portion of their farm areas.

22 SCF Folio
For instance, given the observed “anomalies” in the
surface conditions like the sea surface temperatures
associated with an El Niño, the probability of having the
“above normal” rainfall is 15 percent; the “near normal”
is 35 percent; and the “lower than normal” is 50 percent.
This means that the chance or probability for
experiencing “lower than normal” rainfall or a drier
episode is higher at 50 percent. However, precisely
because the probability is only 50 percent, there is also
equally a 50 percent likelihood that this condition of
getting “lower than normal” rainfall may not happen.
As such, there is still a degree of uncertainty attached
to the forecasts. Moreover, it should be noted that the
forecasts for a particular period may vary across
different locations depending on various other factors
like topography.
The ACIAR-sponsored SCF project: what it
hopes to do
Following the presentations on the concepts related to
SCFs, project team member from PAGASA, Dr. Flaviana
Hilario, presented the rationale and objectives of the
“Bridging the gap...” project as well as the activities that
it will undertake in order to address the project’s
objectives. Among the objectives are: (a) to improve the
capacity of PAGASA to develop and deliver SCFs for the
case study regions of the Philippines, including the
province of Isabela; (b) to estimate the potential
economic value of SCFs for farm and policy case studies
in the Philippines and Australia; (c) to identify the factors
that may lead to gaps, if any, in the actual utilization by
the stakeholders of the SCFs vis-à-vis the SCFs’ potential
economic value; and (d) to develop and implement
strategies to better match the forecasts (SCFs) with the
stakeholders’ needs.
Situation in the field: possible interventions to
help
How useful are SCFs and climate-related information
to farmers and other agriculture decisionmakers in the
field In order to have a better understanding of this,
the SCF project conducted a number of case studies in
selected sites. As mentioned earlier, certain locations in
Isabela were selected as sites for the conduct of surveys
and focus group discussions (FGDs) with farmers to get
their knowledge, perception, and attitude on climate
information and SCFs as well as to have more
information about their farm production systems,
points of decisionmaking, and coping mechanisms
during extreme climate events.
Dr. Celia Reyes, project team member from PIDS,
presented the highlights of the results of the surveys
and FGDs conducted among farmers in various sites in
Isabela as well as their policy implications. The results
indicate that despite of the many assistance programs
extended by the national and local governments in
Isabela, there is still much that need to be done. For one,
while the respondents all agree on the importance and
need for climate information and forecasts to help in
their preparations against possible adverse climate
effects, their actual adoption of risk management and
mitigation measures falls short of the potential benefits
that could be had because other related or
complementary mitigation measures were either not
present or inadequate. As gathered, the types and kinds
of assistance needed and preferred by the farmers are:
(a) better, and preferably localized, climate information;
(b) accessible credit; (c) crop insurance; and (d) special
assistance programs like irrigation and seeds provision.
(Details of these preferred mitigation tools by farmers
are discussed in the December 2007 issue of this SCF
Project Updates newsletter.)
A similar presentation that provides a comparative
look at the farmers’ perception, knowledge, and
attitudes on SCFs in the province of Nueva Ecija was
then given by Ms. Rowena Manalili of the PhilRice team
based on their farm and household surveys conducted
in rainfed rice farming communities in said province.
Disseminating SCFs: aiming for their better use
Based on the field surveys, interviews, and the
questions/comments raised during the open forum in
this Isabela seminar-workshop, it became apparent that
getting farmers and other stakeholders in agriculture
to make good use of climate information and SCFs is
premised on how well the information is understood
and appreciated by them.
The process therefore basically entails that said
information are properly disseminated to them and
thereupon explained thoroughly through information
and education-sharing type of activities and methods.
This, according to Ms. Jennifer Liguton of the PIDS
project component team, is how the process of
disseminating the SCFs should begin. Ms. Liguton then
traced the present manner of disseminating SCFs as
originating from the country’s national meteorological

23
agency, PAGASA, and sent out to the various national
agencies and media, with the hope that such information
are brought by these entities across and down to the
various loci of potential users and decisionmakers in
agriculture.
Unfortunately, as gathered during the discussions,
not all the targeted users—basically the farmers—are able
to get the information in the manner that will be most
useful to them based on this present dissemination
scheme. In most cases, it becomes clear that not all
national agencies pass on the information immediately
and appropriately down to their regional, provincial, and
municipal offices and not all information channeled over
radio, television, and print media feature the implications
that are relevant for the intended users to know.
Thereupon, the implication is for PAGASA to adopt a
deliberate strategy for dissemination that makes use of
conduits and various partners that may provide useful
interpretations and sector-specific advice regarding the
climate information and forecasts. Ms. Liguton
enumerated some of these conduits/partners that may
be tapped, namely:
• local government units. Partnerships with them
through Memoranda of Agreement (MOA) may be
initiated by PAGASA, with the provincial level as the locus
which will thereupon course the SCFs to the next lower
levels;
• extension workers. Agricultural field workers,
being natural links with farmers, will play a major role in
disseminating, explaining, and interpreting the SCFs to
farmers as well as giving them appropriate advice on how
to make the best use of the SCFs;
• traders/suppliers. Being the major source of
financing for farmers, they have a direct link with farmers
and given the proper information and knowledge about
SCFs, they may also provide appropriate advice to farmers
on the type and quantity of inputs to acquire and use;
• media. Focused programs at certain given times
most practical for farmers may be co-developed with
PAGASA;
• community leaders/farm leaders. Being looked
up by farmers, they can serve as good disseminators of
climate news, forecasts, and advice;
• research and academic-based institutions. Those
engaged in agriculture- and climate-related research
projects and have regular contacts with farmers and
farmer groups are also logical partners; and
• NGOs, including faith/church-based groups. In
recent years, a number of these groups have involved
themselves in environmental concerns and thus may be
tapped to help in the dissemination and interpretation
of SCFs during their regular congregation meetings.
There are, however, requirements called for to ensure
the successful use of the abovementioned potential
conduits/partners in dissemination. Among them are: (a)
formalized partnerships through the forging of
agreements such as in PAGASA with LGUs, PAGASA with
media, LGUs with traders/financiers, and PAGASA with
research and academic institutions; (b) appropriate
training for the partners/conduits on the interpretation
of SCFs and on the meaning of their probabilistic nature
of forecasting; (c) regular briefings; (d) seminar-workshops;
and (e) development and distribution of appropriate
printed informational materials about SCFs like manuals,
brochures, posters, calendars, comics, and newsletters with
the help of research and academic institutions. See Figure
1 for a proposed dissemination chart for Isabela using
such conduits.
Having their say: feedback from the participants
The stimulating open discussions where the participants
fielded questions, gave comments, and raised points of
clarifications are a gauge of how receptive the participants
were to understanding and making use of SCFs in their
respective realm of decisionmaking in agriculture in
Isabela. The following are the points taken up.
Dissemination of climate information
and forecasts
Forging of a MOA between PAGASA and the
provincial government of Isabela where the Office of the
Provincial Agriculturist (OPA) will be the center of all
climate information received as well as the one
responsible for relaying the information to all the Offices
of Municipal Agriculturist (OMAs) and units below.
In response to the Isabela Provincial Agriculturist’s
(Mr. Danilo Tumamao) request that PAGASA sends its
forecasts directly to the OPA as well as to the OMAs so
that these offices will be the ones to share the information
with their local executives, Dr. Nilo suggested that all
information, i.e., forecasts, advisories, etc., related to
agriculture that PAGASA produces be sent directly to the
OPA which will thereupon be responsible for relaying the
information to all the OMAs and other units below.
After some discussions, it was agreed that a MOA
between PAGASA and the provincial government of

24 SCF Folio
Figure 1. Proposed dissemination chart for Isabela
weather/climate
updates and broadcast
these in their programs
for the farmers’
information.
Isabela will be prepared and forged regarding this
particular arrangement. Relatedly, Mr. Tumamao
suggested that all the technical information released
by PAGASA as well as the outputs of the SCF project be
translated into a form easily understood by the endusers,
especially the farmers, so that the OPA can easily
disseminate them to the OMAs and all other types of
clients according to location and capacity.
This proposed tie-up/arrangement was welcomed
by the participants, especially by Mr. Arcadio Garcillan
who also expressed the desire to have an opportunity
to gather together the provincial and municipal
agriculturists as well as farmer-leaders and have a closer
access to the SCFs.
Use of broadcast media to disseminate climate
information.
In relation to the proposed more focused
dissemination of climate information by the media,
especially radio stations, a farmer-leader from Barangay
Jones suggested that climate forecasts being delivered
to the OPA also be furnished radio stations for inclusion
in their newscasts for 7:00 a.m., 12:00 noon, and 6:00
p.m. Director Nilo promised that PAGASA will arrange
with local radio stations for them to call up PAGASA–
Echague office regularly before 6:00 a.m. for the latest
R e g u l a r
interaction between
PAGASA and LGUs on
climate information.
Some participants
also raised the
possibility of having a
representative from
PAGASA attend the
regular meetings of the
municipal agriculture
officers (MAOs) so that
he/she may update the
MAOs on the latest
forecasts/advisories and
explain to them the
meaning/interpretations of the forecasts as well as their
implications.
Dr. Hilario of PAGASA agreed to this arrangement
and requested the representative of the MAOs to
provide PAGASA–Echague office with advanced notices
of the schedule of the MAOs’ meetings. Dr. Hilario also
expressed her hope that the local PAGASA office can
be more visible in all relevant activities of the local
agricultural offices in the same vein that PAGASA central
office is actively participating in all relevant activities of
various national government offices.
Request for more localized or site-specific
climate forecasts and rain gauges
Regarding the requests for more localized and sitespecific
forecasts, PAGASA pointed out that it is currently
downscaling the climate forecasts for specific areas in
Isabela, the province being one of the SCF project’s case
study sites. However, it stressed that it is not easy to
develop forecasts for each area since PAGASA does not
have a station nor rain gauges in all of these localities.
Moreover, PAGASA has to have a longer period (more
years) of weather data to be able to develop more
skillful and accurate forecasts.
As a starter, PAGASA said that it is exploring certain
schemes where it can install rain gauges in every

25
municipality. LGUs may send in their formal requests for
the installation of the instrument and likewise indicate if
they will be willing to enter into counterpart
arrangements with PAGASA on the operation and
maintenance of the rain gauges.
Relatedly, Isabela’s Assistant Provincial Planning and
Development Coordinator noted that since the rainfall
data of Echague do not give the true picture of the whole
province of Isabela, PAGASA previously distributed 11 rain
gauges to the following municipalities in Isabela: San
Mariano, San Guillermo, Roxas, San Isidro, Palanan, and
Reina Mercedes. Farmers from these areas are therefore
advised to get their climate data from the municipalities
where they come from and adjust their cropping patterns
accordingly.
Information on the probability and level
of accuracy of the SCFs
On the request for PAGASA to disseminate to the LGUs
and farmers, through radio broadcasts, also the probability
On the side: additional feedback
Supplementing the information/feedback gathered from the participants during the seminar-workshop and focus group discussions are
the insights gathered from the results of the evaluation and dissemination questionnaires given to the participants.
Below are some of the key points gathered.
On PAGASA’s products and services
A majority of the 71 participants who attended the seminar-workshop came from the LGU sector (48%), followed by the farmer sector
(32%), and government (20%) sector. Ninety-seven percent of the participants claimed that weather/climate is a factor in their
decisionmaking process while 62 percent of them said that the role of weather/climate in their decisionmaking is of critical value. Radio/
television ranked the highest—at 97 percent—as their main source of information on climate, followed by PAGASA station (52%) and
broadsheet/tabloids (38%). Ninety-three percent of the participants are familiar with PAGASA’s products and services, with the top three
products they are aware of being tropical cyclone warning, El Niño/La Niña advisories, and the annual seasonal climate forecast. Participants
rated PAGASA’s products in terms of accessibility, content, ease of understanding, timeliness, and delivery/medium of dissemination.
For accessibility, 48 percent said PAGASA’s products are very good; for content, 63 percent said they are very good; for ease of understanding,
45 percent said they are very easy to understand; for timeliness, 50 percent said they are timely; and for delivery/medium of dissemination,
53 percent said they are very effective.
As to the ways that PAGASA may improve their products, the suggestions include: improve accuracy of the weather forecast;
information must reach far-flung barangays; and more pamphlets be distributed for guide and localized forecasting. Essentially, the
participants wanted the PAGASA to exert greater effort in the dissemination of their products. They also said that they need climate
information so that the timing of planting and harvesting can be scheduled to minimize losses and increase their production.
On dissemination of climate information/SCFs
More seminar-workshops and better training of farmers are needed since they are the keys to better diffuse SCF knowledge. Participants
suggested some specific types of climate information that will benefit them. These are: when it’s going to rain; more accurate weather
updates; and length of dry spells. Seventy-eight percent of the participants wanted this kind of information every 2–3 months; 22 percent
said every quarter, and 13 percent, during the critical months. A majority of farmers prefer to receive this information through television
(19%), radio (16%), extension workers (12%), and print (11%). When asked about their role regarding the dissemination of SCF, 77
percent of the participants said that they are both users and disseminators of the information.
On the seminar-workshop
The top three recommendations given by the participants are:
• daily releases of news on SCFs through local TV and radio stations,
• increase in the percent assurance/accuracy or probability of the weather forecast, and
• designation of a PAGASA representative to be present during the local agriculturists’ regular meetings.
The participants found the seminar-workshop to be highly successful. They learned from the informative sessions on the basics of
Philippine climatology, climate outlook for Isabela, farmers’ perception on SCF, overview and the status of the project, and the dissemination
program of the project. They also found the seminar-workshop materials and handouts as well as posters on display, which are brief and
very informative, to be very useful. On the whole, the participants were extremely satisfied about the seminar-workshop because in
addition to the knowledge that they have gained, they were also able to have informal exchanges with other participants on various projects.

26 SCF Folio
of occurrence of the particular forecasts so that farmers
may have a wider outlook or range for the planning of
their farming activities, PAGASA responded that SCFs
are really based on the principle of probability. In
disseminating the forecasts, therefore, the degree of
probability is always included. Because of this, the
meaning of the probability principle needs to be clearly
explained to the farmers and other end-users, especially
on the implications.
Director Nilo further emphasized that in climate
science, there are datasets on which forecasts are based
and certain methodologies are followed. Per the
datasets and methodology available at the PAGASA, the
level of a 100 percent—or even just 90 percent—
accuracy in terms of the probability or likelihood of the
occurrence of the forecasts cannot yet be delivered. In
Isabela, he said that the highest probability that they
can give, for instance, for rainfall to be above normal
during a La Niña period is only 50 percent. Nonetheless,
PAGASA is continuously trying to improve its skills in
this particular aspect so that they can respond better to
the needs of farmers.
Relatedly, PAGASA noted, in response to another
query, that the standard coverage of a weather station,
according to the World Meteorological Organization, is
50-km radius. Forecasts for a site made on the basis of
such radius are hence quite effective or skillful.
Possible strategic alliance with tradersfinanciers
on provision of input selection advice
to farmers based on climate forecasts received
In order to have a better matching of seed varieties
with the cropping season, there were suggestions and
likewise an agreement in principle to have a better
understanding by both the farmers and traders/
suppliers of the various seed varieties suitable to certain
months of the year. In response to the points raised by
some farmers on the quality of seeds, in particular,
hybrid corn seeds, being sold to them by certain seed
companies and traders, the research director of the
Isabela State University (ISU) suggested the setting up
of an independent body that would assess the
performance of seeds being sold by seed companies
vis-à-vis their suitability to the farms as well as cropping
season.
In this regard, it was noted that a strategic alliance
between traders-suppliers and farmers could possibly
be established through the help of the MAOs and
PAGASA. By regularly supplying traders-suppliers with
information and explanations of the meaning and
interpretations of SCFs and what possible implications
these might have on the characteristics and
performance of various input varieties, traders-suppliers
may be influenced to keep in stock the appropriate
inputs and varieties as well as be enjoined to provide
the corresponding appropriate advice to farmers on the
varieties that will prove to do well under such
circumstances. Conversely, farmers may likewise
indicate their preferences of the varieties they need
given their farms’ circumstances to which traderssuppliers
may correspondingly adjust their supplies.
A final note
Dr. Celia Reyes concluded the seminar-workshop by
providing a summary of the following major
agreements reached as well as the next steps
considered:
• A MOA between the PAGASA and the province
of Isabela, through the Office of the Provincial
Agriculturist (OPA), will be forged to ensure that all SCFs
and other PAGASA climate information/products reach
the stakeholders/decisionmakers in agriculture in the
province.
• PAGASA will now provide modified forecasts
on the basis of probabilities as explained earlier. These
modified forecasts therefore call for a clearer
explanation of the meaning and implication of the
probabilities.
• The PAGASA central and local offices, with the
help and collaboration of the OPA and MAOs, will forge
agreements/arrangements with the local media,
especially radio stations, on the regular dissemination
and explanation of SCFs and their meanings/
implications to farmers and farmer-groups through
special programs focusing on agriculture-related
climate information and forecasts.
• Finally, strategic alliances with traderssuppliers
may be explored where, through regular
information and briefings supplied/given to them by
PAGASA and the OPA, they may be used as conduits in
passing on such information and giving appropriate
advice to farmers on the corresponding farm inputs
selection that the latter should make. (SCF Project
Updates, March 2008)

27
SCF is popular in Bukidnon but...
Gian Carlo Borines, Rotacio Gravoso,
Jude Nonie Sales, and Ulderico Alviola
Yes, seasonal climate forecast (SCF) is popular
among corn farmers in Bukidnon. This is
according to a recent study on “Corn farmers’
decisionmaking based on probabilistic climate
forecast” conducted by a team of researchers from the
Visayas State University (VSU) based on the results of focus
group discussions among farmers from selected sites in
the province of Bukidnon in Mindanao. The study found
that farmers are aware of SCF, their sources of which
included television, radio, and the PAGASA station in
Malaybalay City. At the same time, it was learned that
PAGASA and the City Agriculture Office often hold
seminars and workshops on the SCF.
Notwithstanding this, however, “farmers depend
more on their indigenous climate forecasting than on
SCF,” the study reported. For one, the study found that
farmers think of climate forecasts as deterministic rather
than probabilistic [please see explanation of probabilistic
nature of SCFs in SCF Project Updates March 2008, page
2]. Thereupon, if the forecasts given do not jibe with what
climatic condition actually takes place, then farmers tend
to lose confidence in the forecasts. They also said that
climate forecasts are hard to understand. Thus, they
suggested that said forecasts use simple words and be
downscaled to their locality.
The decisionmaking exercises utilizing hypothetical
forecasts showed that under unfavorable climate
forecasts, farmers would apply coping mechanisms like
growing short-season crops, backyard gardening, raising
animals, and finding a job in sugarcane plantations and
industries in Malaybalay City. Generally, farmers’ decisions
were aimed to maximize profits and minimize cost. (SCF
Project Updates, June 2008)
Cebu workshop stresses need
to disseminate SCF
The need to disseminate seasonal climate forecasts
(SCFs) has been repeatedly underscored by
researchers and farmers alike in the seminarworkshop
on the “Role of seasonal climate forecast” held
on September 29, 2008 at the Cebu Business Hotel, Cebu City.
Participated in by about 40 farmers, representatives
from the agricultural offices in Cebu, researchers from the
Philippine Atmospheric, Geophysical and Astronomical
Services Administration (PAGASA), Philippine Institute for
Development Studies (PIDS), Visayas State University
(VSU), the academe, and Cebu’s media, the workshop was
part of the dissemination effort of the project, “Bridging
the gap between seasonal climate forecast and
decisionmakers in agriculture,” a collaborative project
between Philippine implementing agencies—PAGASA,
PIDS, and the VSU—and their Australian counterparts.
During the workshop, Dr. Flaviana Hilario, Weather
Services Chief of the Climatology and Agrometeorology
Branch (CAB) of PAGASA, noted that SCF is among
PAGASA’s climate products and services that have been
introduced to the public, particularly farmers and
fisherfolks, in recent years and whose benefits to farmers
and fisherfolks, especially during occurrences of climatic
anomalies, have been cited by several studies. She
acknowledged, however, that its dissemination to its
intended end-users has been wanting.
In his presentation, meanwhile, Dr. Canesio Predo of
the VSU, said that the use of SCF allows farmers to improve

28 SCF Folio
Climate information needs assessment for Cebu
The specific types of climate-related information that the respondents during the Cebu workshop want to receive are predicted rainfall
(12.5%), rainfall and temperature pattern (12.5%), onset and termination of wet and dry spells (12.5%), and seasonal climate forecast
(25.0%) as shown in Table 1.
The reasons of the participants on why they need the specific types
of climate-related information include: for instruction and extension
Table 1. Specific types of climate-related information
that the participants want to receive
services (12.5%), for decisionmaking (12.5%), for maintaining crops on
large scale (12.5%), for recommending possible crops to be planted
Item
Predicted rainfall
Rainfall and temperature pattern in Argao
Onset and termination of wet and dry spells
n
1
1
1
%
12.5
12.5
12.5
(12.5%), and for disseminating information and assisting clients in
decisionmaking (12.5%).
Table 2 presents the participants’ responses on the time and
frequency of receipt of the information. Participants said that they want
to receive the information during critical periods (12.5%), more than half
No answer 3 37.5 said that they want to get them on quarterly (62.5%) basis, and some
Seasonal climate forecast (SCF) 2 25.0
(25%) answered that it should be within 2–3 months before the usual
Total 8 100.0
planting season.
The channel through which the participants want to receive the
Table 2. When and how often would the respondents
want to receive the information
information are through bulletins from weather station (25%), radio
(20.8%), television (16.7%), extension workers (8.3%), print (8.3%), fax
Item n %
(8.3%), internet (e-mail) (8.3%), and pamphlets, manuals, etc. (4.2%).
The results also show (Table 3) that it is with community leaders
and community associations that the participants interact more regarding
2–3 months before usual planting season 2 25.0
During critical periods 1 12.5
community welfare issues (at 33.3% and 26.7%, respectively). Local
Quarterly
Total
5
8
62.5
100.0
government officials/representatives are next (20%), followed equally
afterwards by the media and nongovernment organizations.
Finally, more than half (62.5%) of the respondents said
that they are both user and disseminator concerning the
Table 3. Sector/group that the respondents normally interact/ dissemination of seasonal climate forecast (Table 4).
discuss on issues affecting community welfare
Item n %
Local government officials/representatives 3 20.0
Community leaders 5 33.3
Media 1 6.7
NGOs/faith-based groups 1 6.7
Community associations 4 26.7
No answer 1 6.7
Total 15 100.0
Table 4. Role of respondents regarding
dissemination of seasonal climate forecast
Item n %
User 3 37.5
Both user and disseminator 5 62.5
Total 8 100.0
profits resulting from better farm management
decisions as they take advantage of the opportunity
during good seasons and minimize losses during bad
seasons. He also discussed the various tactical farm
management applications of SCF to address climate
variability such as crop choice, timing of cropping period
or planting time, and levels of input use, among others.
He likewise presented research findings that show how
farmers found SCF to be valuable in better managing
cropping systems. In particular, SCF was found to be
valuable in deciding what crop/variety to plant during
the growing season. The findings also indicated that
farmers using SCF have realized higher incomes than
those who are not. However, Predo stressed that farmers
need to be conscious of when to apply and when to
disregard the information provided by the SCF.
In underscoring the need to disseminate SCF, Mr.
Renelio J. Mabao, City Agricultural Officer of Toledo City,
reported that to date, they only get weather forecasts
through the radio and television, especially during bad
weather. It is only when “there are forecasts on the
occurrence of El Niño or El Niña from PAGASA that either

29
the Provincial Agriculture Office (PAO) or the Department
of Agriculture Regional Field Office (DA-RFO) calls for a
meeting for precautionary measures,” Mr. Mabao said.
Mr. Mabao said that they disseminate these forecasts
that they get during their meetings with the farmers.
Fisherfolks, meanwhile, depend on the daily weather
forecasts from PAGASA on whether or not they will go
fishing. “Thus, it would be better if there could be a way
by which PAGASA could send us a copy of their SCFs in
advance so as to improve the system of forecasting,”
Magbao added.
In a related focus group discussion (FGD) that the
representatives from PAGASA, PIDS, and VSU had with
corn farmers and their spouses at Brgy. Sangi, Toledo City
(see photo below), Julieta Daclan, one of the farmerleaders
of said barangay, explained that “there is no such
thing as proper time for planting corn” in Barangay Sangi.
The reason for this, she said, is that most of the farmers
are totally dependent on their corn produce as their
source of living. Thus, immediately after harvesting, land
preparation follows and then, after 3–5 days, the planting
starts, ensuring that the farmers will not all be harvesting
at the same time.
The farmer-leader explained that they harvest their
corn after 72–73 days after planting during the dry season
and after 75 days during the wet season. They harvest
corn as young corn and seldom allow the corn to mature
and be milled into grain.
She also admitted that the climate change has
affected their produce, thereby affecting their livelihood
too. “If PAGASA can inform us ahead that there will be a
drought for the coming three months, then we will plant
the native variety of corn that could withstand drought,”
she stressed.
Responding to the call for a more proactive
dissemination of the SCF, Ms. Jennifer Liguton, Director
for Research Information at PIDS, discussed the need for a
strategic dissemination of SCF involving PAGASA local
offices, community organizations, the media, extension
workers, and the academe. She emphasized that the SCFs
will be more assured of reaching the various stakeholders,
especially the farmers, if the dissemination of said
information is devolved. For instance, forecasts from
PAGASA’s central office will be sent to PAGASA’s local
offices or to the Department of
Agriculture, then passed on to
the provincial and municipal
agricultural offices. Extension
workers will play a key role in
the process as they pass on the
information to farmers. The
SCF dissemination will likewise
be more effective if the
information is presented and
explained in simple and easyto-understand
terms, and if
the forecast is suitable to local
application, specific to sites,
and issued on timely basis.
(SCF Project Updates, September
2008)

30 SCF Folio
PAGASA hosts seminar-workshop
on seasonal climate forecasts
The last of the series of seminar-workshops on
“The Role of Seasonal Climate Forecasts in the
Agriculture Sector” was held at the Pine Hills
Hotel in Malaybalay, Bukidnon on 27 November 2008.
It was well attended and featured speakers coming from
PAGASA, Visayas State University (VSU), and the
Philippine Institute for Development Studies (PIDS) who
discussed current issues affecting the climate and corn
industry in Bukidnon. The workshop also featured Engr.
Alson G. Quimba, Acting Provincial Agricultural Officer
of Bukidnon, who talked about how climate change is
becoming to be a reality in the province, what with new
climate pattern occurrences like strong typhoons and
flooding taking place in the province, and discussed
how the province is dealing with these. Meanwhile, the
keynote speaker, the Hon. Jose Ma. R. Zubiri, governor
of Bukidnon, in a message read on his behalf, recognized
the importance of the seminar-workshop, particularly
in the applicability of the research results for use by
decisionmakers in agriculture, and said that the local
government welcomes projects like these because they
allow them to look at their strengths and limitations for
the good of the people.
A total of 85 participants representing the different
municipalities of Bukidnon, municipal and city
agriculturists, officials from the Governor’s office, and
members of the academe attended the seminarworkshop.
Members of the project team lectured on
climate concepts to acquaint key decisionmakers in
agriculture in Bukidnon on the possible role of seasonal
climate forecasts in improving productivity and overall
welfare of the agriculture sector in the province.
Also presented were studies relating to riskefficient
planting schedule for corn in Bukidnon, and
climate variability and corn farming in Bukidnon as well
as the Decisionmaking Game based on SCF using a
spinning wheel. Dr. Canesio D. Predo, Assistant Professor
of VSU, led the game where the participants were able
to apply the knowledge they gained from the
workshop. Ms. Jennifer P.T. Liguton, Director for Research
Information of PIDS, then presented the different
communication pathways to be employed by the
project in disseminating its various outputs to
agricultural stakeholders.
Finally, Dr. Flaviana D. Hilario of PAGASA, in her
closing remarks, assured the participants that regular
SCF updates will be provided to the province since
Bukidnon is one of the pilot areas of the project. (SCF
Project Updates, September 2008)

31
Analysis and research/survey results
Assessing rainfall variability in Philippine
study sites: the Rainman application
Because of its geographical location, the ranging from one season to over a year in advance. This
Philippines is prone to extreme weather and improvement means that impending extreme climate
climate events. Floods and droughts have, for events can be predicted with greater accuracy.
instance, been common occurrences in the country
especially in the recent past resulting in massive
destruction of property, loss of life, diseases, and food
shortages. Sectors of the economy, including agriculture
and water resources, have likewise been severely affected
by these weather/climate events.
The Philippine Atmospheric, Geophysical and
Astronomical Services Administration (PAGASA) monitors
weather and climate conditions from both local and global
perspectives. It has a network of weather stations
strategically located all over the country that monitor
meteorological and weather elements. These parameters
are then analyzed using various statistical techniques and
procedures to come up with weather or climate forecasts.
Provision of these forecasts and early warnings of
potential crop failure due to drought, with a lead time of
30-60 days before harvest, is important because it enables
policy/decisionmakers to implement alternative courses
of action to mitigate potential damages to the agricultural
Predictability of the climate from season-to-season
and year-to-year arises from the interaction of the ocean
and the atmosphere. The best-known example is the
ENSO phenomenon. The combination of the slowly
changing temperature of the oceans and their
interactions with the atmosphere provides a degree of
predictability for seasonal climate in many regions of the
world. Based on global studies, ENSO and other sea
surface temperature anomalies are known to influence
global climate, altering rainfall and other climate variables
throughout much of the tropics and subtropics and in a
few locations in mid-latitudes. Seasonal climate prediction
is based on the expectation of the effects of these
influences in the coming season. In this regard, climate
forecasters normally ask two basic questions: (1) what will
the sea surface temperature anomalies be in the coming
season and (2) how will they impact on global climate
There are models available which can evaluate the
effects of ENSO on seasonal climatic patterns and on the
sector. Seasonal forecasting is an
attempt to provide information on Statistical test results on forecasts of rainfall in Southeast Asia
(Analysis of historical data—1903 to 1995—using SST Phase forecast in September for rainfall
the likely conditions of the weather
period: Oct to Dec, leadtime of 0 months)
several months in advance.
The Climate Information,
Monitoring and Prediction Center
(CLIMPC), one of the sections of the
Climatology and Agrometeorology
Branch (CAB) of PAGASA, is
responsible for the issuance and
dissemination of seasonal climate
forecasts and advisories. With the
recent advancement in the
understanding of the El Niño
Southern Oscillation (ENSO)
phenomenon and climate
prediction, seasonal to interannual
prediction has made it possible to
predict climate with improved
accuracy and with lead times

32 SCF Folio
The Philippine study sites
variability of rainfall in the Philippines. One of these is
Rainman. This brief writeup focuses on the use of this
program in evaluating the effects of the ENSO
phenomenon on seasonal climatic patterns and
variability of rainfall in three selected study sites of the
Philippines—Isabela in the island of Luzon; Baybay
(Leyte) in the Visayas; and Malaybalay (Bukidnon) in
Mindanao.
The Rainman Program: providing an enhanced
method of forecasting ENSO effects on rainfall
Rainman is an integrated package about rainfall and
streamflow information developed by the Queensland
Department of Primary Industry, Australia in a previous
ACIAR-funded project. A unique feature of Rainman is
the seasonal rainfall analysis which may be done with
monthly data and also daily data where they are
available. Here, one can see what influence either the
Southern Oscillation index (SOI) or the sea surface
temperature (SST) may have on rainfall, using any
length of season (1–12 months), up to the coming year.
This prediction or forecast is helpful for those making
management decisions in a highly variable climate.
The initial results of the seasonal climate forecasts
for 12 overlapping seasons (i.e., December-January-
February; January-February-March; February-March-
April; and so on) at zero lead time (meaning that for
forecasts for, say, February-March-April, the data used
are those for January) in the three study sites earlier
mentioned are presented here. The statistical skills of
these forecasts were evaluated
using the SST forecast phase system
(the Pacific effects) of Rainman to
indicate whether changes in rainfall
pattern as predicted or forecasted
are real or are due to chance.
*Data substituted for Isabela
The Philippine study sites
and the test applications
The Philippine component of the
ACIAR project on seasonal climate
forecasts selected four sites for its
case studies, namely: Isabela in the
island of Luzon; Baybay (Leyte) and
Cebu in the Visayas; and Malaybalay
(Bukidnon) in Mindanao. For this
particular study, however, certain
considerations were taken into
account and some changes/
substitutes were made.
In particular, the significance of
the test results is sensitive to the
number of years of data; the more
years (minimum is 30 years), the
better. In this light, the absence of
longer climate record for the stations
in Baybay, Leyte and in Isabela
influenced this study’s use instead
of the climate data in nearby areas
(Tacloban for Baybay and
Tuguegarao in Cagayan Valley for
Isabela) that have the same climate
types as the original study sites.

33
As the results in this initial study suggest, more specific
climate information provided in advance of a particular
planting or harvest season will be of great help to those who
make specific decisions in the agriculture sector...What is
important is to be able to determine which forecasting system
will be able to yield better results depending on various
variables like season, location, time of year, lead time, and
the status of ENSO.
decreases from 40 to 20 percent from September to March.
• The seasonal forecast skill in Malaybalay and
Tacloban is statistically significant starting the month of
October up to March.
• Meanwhile, like in Tacloban, the percent chance of
exceeding the median rainfall in Tuguegarao is increased
from 60–80 percent during a cooler Pacific Ocean while
the chance of getting this level is reduced during a hotter
Pacific Ocean.
For the Malaybalay site, meanwhile, since the
available climate record is about 79 years, the same site
was used. On the other hand, no evaluation was done as
yet for the Cebu site.
As mentioned, the SST phase system using the Pacific
Ocean effects was the one applied in evaluating the
impact on the study sites. In particular, the following main
effects of the Pacific Ocean were tested: (1) cooler Pacific
Ocean pattern where phases 1, 4, and 7 (which are
associated with wetter than normal rainfall condition in
the Philippines) were combined; (2) neutral Pacific Ocean
pattern where phases 2, 5, and 8 (wherein neutral
conditions indicate that there is an equal chance of
getting above normal or below normal rainfall in the
Philippines) were combined; and (3) hotter Pacific Ocean
pattern where phases 3, 6, and 9 (which are associated
with drier than normal rainfall condition in the Philippines)
were combined.
Results of analysis
The following are the key results of the analysis/
evaluation:
• An analysis of the historical data (from 1919–2004)
in Malaybalay found that there is a 70 percent chance or
probability of having the rains exceed the median rainfall
during a cooler Pacific Ocean from September to February
while there is a lower chance—at 20 to 30 percent—of
getting a median rainfall during a hotter Pacific Ocean
from September to March.
• For the study site in Tacloban, analysis of historical
data showed that for a constant lead time (0 month)
before a three-month rainfall period, there is a 60–80
percent chance of exceeding the median rainfall starting
the month of November up to March during a cooler
Pacific Ocean. During Phases 3, 6, 9 of the hotter Pacific
Ocean pattern, the chance of getting above median rainfall
What do the above results mean
Simply told, the impact of ENSO on the Philippines varies
with season and location. Generally, the forecast skill is
higher for October to March.
With regard to the status of the ENSO, the results
indicate that during the onset of El Niño and La Niña
(hotter Pacific Ocean and cooler Pacific Ocean
occurrences, respectively), the trends established in the
chances of getting lesser (for the El Niño period) or more
(for La Niña period) amounts of rain than the median
rainfall are more distinct.
Unfortunately, however, there are also neutral
conditions when there is an equal chance of getting
above or below normal rainfall in the country. During this
period, the forecast skill is not statistically significant and
decisionmakers need to use the long-term climate
record.
Conclusion
As the results in this initial study suggest, more specific
climate information provided in advance of a particular
planting or harvest season will be of great help to those
who make specific decisions in the agriculture sector.
For this study, focus was on the use of the SST phase
system as an ENSO indicator at zero lead time. There are,
however, other features in Rainman that can look, for
instance, at the seasonal forecast skill using various lead
times like, say, 30–60 days before a harvest season.
In this regard, Rainman will be used and tested in
the coming months to provide better answers to the
specific needs of the users.
What is important is to be able to determine which
forecasting system will be able to yield better results
depending on various variables like season, location, time
of year, lead time, and the status of ENSO. (SCF Project
Updates, December 2005)

34 SCF Folio
A decade of destruction from seasonal
climatic aberrations
Much had happened in the Philippines’ 2004 alone, climatic aberrations had damaged a total
agricultural sector over the past decade. of 4.1 million hectares of prime rice and corn farmlands.
Great technological milestones were Cumulative losses incurred amounted to P16 billion for
made but setbacks were also ever present. Productivity
in the crop sector has generally been increasing over
the last 10 years but production losses, especially those
from seasonal climatic aberrations, have also been huge.
Data from the Department of Agriculture prove
the vulnerability of the farming sector to the
unpredictability of nature. Droughts, floods, and
typhoons have been wreaking havoc on crops and
causing untold miseries among farmers. From 1995–
rice farmers and P7.2 billion for corn growers (Table 1).
A major cause of the climatic catastrophes being
experienced in the country, and in other parts of the
world, is the El Niño Southern Oscillation (ENSO)
phenomenon. ENSO has two major phases: the El Niño
or warm event and the La Niña or cold event. El Niño
conditions lead to drier seasons due to suppressed
tropical cyclone activity and weak monsoon
characterized by delayed onset and early termination
of the rainy season and by prolonged dry
Palay and corn damages
5,000,000
periods. La Niña, on the other hand, is
characterized by above normal rainfall and
longer rainy seasons. The impact of ENSO
4,500,000
was clearly documented during the 1997–
4,000,000
3,500,000
1998 El Niño/La Niña episode when a total
3,000,000
of P7.6 billion in rice and corn production
2,500,000
2,000,000
losses were incurred.
1,500,000
1,000,000
More alarming is the seemingly
500,000
frequent occurrence of the ENSO
-
phenomenon in recent years. There has not
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Palay Area(ha) Palay Volume(MT) Palay Value (P'000)
been a single year from 1994 up to the
YEAR
Corn Area(ha) Corn Volume (MT) Corn Value (P'000)
present when either the cold or warm phase
of ENSO was not present (Table 2).
This fact is distressing given the
Table 1. Damages to rice and corn production due to droughts, floods, and typhoons
trend that the event only occurred
from 1995–2004
on average by intervals of 2–7 years
Year Palay Damages Corn Damages
during the last 300 years. This
1995
Area (ha)
581,511
Volume(MT)
953,436
Value (P’000)
3,977,341
Area (ha)
126,863
Volume (MT)
192,979
Value (P’000)
476,412
apparent increase in climatic
variability equates to elevated risks
1996 95,326 114,979 234,706 13,196 418,481 704,416
in agricultural production and
1997 201,021 204,186 433,284 30,675 27,697 82,439
1998 1,281,838 1,863,848 4,679,394 350,357 497,075 1,846,004 postproduction operations.
1999 278,956 258,487 809,088 9,883 5,714 32,873
Risks are easily converted to
2000 375,029 510,553 1,594,869 19,394 10,535 57,598
2001 214,593 296,040 805,059 140,882 162,808 546,143
losses when not properly
2002 121,199 220,760 548,347 53,271 87,046 330,354 addressed. ENSO impacts all
2003 287,199 413,155 1,320,091 255,565 663,901 1,696,124
segments of society but among
2004 362,086 649,531 1,696,584 148,578 492,183 1,436,241
the most affected are resourceconstrained
Total 3,798,758 5,484,975 16,098,763 1,148,664 2,558,419 7,208,604
farmers whose
Mean 379,876 548,498 1,609,876 114,866 255,842 720,860
livelihoods are greatly dependent
Source: Department of Agriculture, 2006
on the changing seasons. This is
AMOUNT

35
Table 2. El Niño and La Niña episodes
during the past decade
Period
May 1994 – April 1995
October 1995 – April 1996
June 1997 – May 1998
August 1998 – July 2000
November 2000 – March 2001
June 2002 – April 2003
August 2004 – March 2005
Source:
Event
El Niño
La Niña
El Niño
La Niña
La Niña
El Niño
El Niño
Climate Prediction Center-National
Oceanic and Atmospheric Administration
(CPC-NOAA), 2006
most evident among rainfed farmers who rely exclusively
on rainfall to irrigate their crops.
Other agricultural businesses that operate with
better resources and more modern technology on better
farmlands are also not spared from the same risks.
Prolonged dry spells, excessive rains, and flooding are
critical events that could easily destroy a season’s crop.
The coming of rains signals the start of a new planting
season but the same gift from nature—or lack of it—could
easily wipe out a standing crop. The need to safeguard
the interests and investments of local farmers and
industry players is therefore of great importance.
To address these concerns, the Philippine
government has been implementing a range of risk
management programs for farmers and other agricultural
stakeholders. These include price stabilization measures,
typhoon and/or drought relief, livestock and feed
subsidies, fertilizer, and other input subsidies as well as
subsidized crop insurance schemes. Specialized projects
are also being implemented in collaboration with local
and international partners to aid in the effort.
An example of this workable partnership is the
ACIAR-funded Bridging the gap between SCF and
decisionmakers in agriculture. The project is a
collaborative undertaking between the governments of
Australia and the Philippines, through the Philippine
Atmospheric, Geophysical and Astronomical Services
Administration (PAGASA), the Philippine Institute for
Development Studies (PIDS), and the Leyte State
University, for the Philippines. It essentially deals with
managing climate variability through better forecast
information and better utilization and appreciation of
these forecasts by agricultural decisionmakers.
Though not much could be done when a “prolonged
drought” or a “super typhoon” strikes, there is still a wide
array of applicable tools that could help agricultural
workers mitigate environmental challenges and decide
intelligently in the face of seasonal uncertainties. A crop
farmer will have a healthier chance of going through
seasonal abnormalities and coming out unscathed if he
is well informed. The decision to push through with the
cropping season should ideally be the product of an
enlightened process.
A decade of destruction and challenges from
seasonal climate variability should have provided ample
insights and learning to everyone concerned. The coming
years should now serve as testament to this added
wisdom, ushering in a more secured, productive, and
profitable era for rice and corn farmers in the country. (SCF
Project Updates, December 2006)
El Niño is here again!
El Niño is back and here to stay, at least until the first
half of year 2007.
Climate monitoring bodies from all over the
world, including the local meteorological agency PAGASA,
have confirmed that the warm phase of the El Niño
Southern Oscillation (ENSO) is continuing to progress. As
of October this year, sea surface temperatures (SSTs) in
the central equatorial Pacific have been rising and the
Southern Oscillation Index (SOI) has been decreasing.
Over the past six months, most of the statistical and
coupled model forecasts employed by climate monitoring
agencies like the Climate Prediction Center (CPC) in the
United States have projected warmer conditions in the
tropical Pacific. Weaker-than-average low-level equatorial
easterly winds have also been observed across most of
the region. CPC stated that collectively, current oceanic
and atmospheric anomalies are consistent with the early
stages of El Niño.

36 SCF Folio
In the Philippines, PAGASA had already come up
with local advisories related to the progressive evolution
of the current El Niño episode. The meteorological agency
reported that the event is likely to intensify during the
next three months and persist through April to June 2007.
Below normal rainfall conditions were already
observed by PAGASA over the past months in parts of
northern and western Luzon, most of northern Panay
Island including Iloilo, southern Cebu, the western parts
of Bohol and Zamboanga provinces, most parts of the
CARAGA provinces, Davao Oriental, eastern part of
Davao del Norte and the southern tip of Davao del Sur,
and South Cotabato. Only the intertropical convergence
zone (ITCZ) and the occurrence of destructive typhoons
had brought above normal rainfall in affected areas, as
witnessed in the recent typhoons Milenyo, Neneng,
Ompong, and Paeng.
Rainfall forecasts for November included below
normal projections in most parts of the country, except
in Isabela, Quirino, Aurora, South Cotabato, and Surigao,
and Regions IVB, V, and VIII where rainfall is forecast to
be normal.
This early, the threat to the country’s water reserves
is already being felt by some sectors. Possible shortage
of water supply in Metro Manila is a cause of alarm
because the low rainfall volume might lead to a lower
water level in Angat Dam. Dependent on rainfall to
replenish its water reserve, the dam supplies water to
Metro Manila’s 12 million residents and irrigates the vast
agricultural lands of Central Luzon. The same problem
is expected to be experienced in other parts of the
country as El Niño intensifies.
The government has already advised everybody
to continue implementing appropriate measures to
mitigate the potential adverse impacts of the episode
on agriculture, water resources, hydropower generation,
health and sanitation, and other affected sectors. (SCF
Project Updates, December 2006)
Researcher presents findings on SCF
impact simulation
Dr. Felino Lansigan, Professor of Statistics at the
University of the Philippines Los Baños
(UPLB), presented the results of his study
titled “Analysis of the effects of climate variability on
corn productivity in the Philippines” on September 22,
2006 at the NEDA sa Makati Building, Makati City.
Working with the ACIAR-funded project Bridging
the gap between SCF and decisionmakers in agriculture,
Dr. Lansigan discussed the initial results of his research
during the “Pulong Saliksikan at PIDS” before an
appreciative crowd of government and NGO
representatives. He presented the effects of climatic
variability on corn yield under different El Niño southern
oscillation (ENSO) phases in three different locations,
Dr. Lansigan succeeded in showing the effect of climate variability
on corn productivity through yield variability and yield
differences within and between locations...As a positive note, he
ended by stressing that the vulnerability of corn-growing areas
may be reduced given appropriate coping strategies.
namely: (a) Los Baños, Laguna, (b) Ilagan, Isabela, and
(c) Malaybalay, Bukidnon.
In assessing the impact of SCF, Dr. Lansigan
classified historical weather data into three categories:
“dry (El Niño) year,” “wet (La Niña) year,” and “average
(neutral) year.” He also generated synthetic weather
data for the crop yield—climate variability analysis
using applicable software to complete a 50-year
weather data series.
The CERES-maize model, an ecophysiologicalbased
crop simulation model for corn, was used to
simulate yields given varying climatic and cultural
conditions. Results showed that mean crop yields in the
three locations were significantly different during wet
and dry years. Simulated corn yields in Ilagan gave the
highest coefficient of variation (CV) of 35.2 percent
during average years, and 27.7 percent and 27.0 percent
during wet and dry years, respectively. Los Baños gave
the lowest CV at 17.7 percent during wet years, and 28.9
percent and 26.4 percent during dry and average years,
respectively. In Malaybalay, respective CVs for dry,

37
average, and wet years were calculated at 22.4, 23.3, and
31.6 percent. Resulting figures also showed negligible
yield differences during wet season cropping and
appreciable changes during dry season cropping.
Dr. Lansigan succeeded in showing the effect of
climate variability on corn productivity through yield
variability and yield differences within and between
locations. Among the study sites, Ilagan, Isabela was found
to be the most vulnerable to climatic variability especially
during dry years, while Los Baños, Laguna proved to be
the least vulnerable. As a positive note, Dr. Lansigan ended
by stressing that the vulnerability of corn-growing areas
may be reduced given appropriate coping strategies. (SCF
Project Updates, December 2006)
SCF use and indigenous knowledge
among corn farmers in Isabela
Corn farmers in Isabela,
Philippines hold both seasonal
climate forecast (SCF) and
indigenous forecasting means in high
regard. A survey done among corn
growers in the province showed that
seasonal climate information from both
traditional and scientific sources greatly
influenced farming decisions on
working capital, type of crop to plant,
and time of planting.
When asked on why SCF is
important, 96 percent of the
respondents answered that it aids in onfarm
decisionmaking as it allows
Members of the PIDS-SCF Project Team meet with municipal agriculturists in Isabela.
farmers to prepare for climatic events.
Many also recognized the role of climatic information in
deciding when to plant or commence the cropping
season.
At the same time, a long list of traditional forecasting
methods was also gathered from many of the interviewed
farmers. To predict the coming of rains, local folks looked
for a variety of signs ranging from the appearance of
heavenly bodies like the moon, stars, sun, and clouds;
behavior of local fauna like insects, birds, and farm animals;
and the performance of local flora like the flowering of
orchids and grasses, and fruiting of trees.
One third of the farmers also believed in
superstitions when commencing farm activities. Good
luck and bad luck beliefs influenced decisions on the
timing of and cultural approaches to certain farm
operations. Though not with scientific basis, these beliefs
and practices are part of the indigenous make-up of local
farmers and should be regarded when pushing for the
adoption of applicable technological interventions.
Interestingly, majority of farmers believed in the
reliability of indigenous weather forecasting means.
Among the respondents, only 25 percent voiced out that
such methods were unreliable.
The figures look good as the overall responses of
farmers reinforced the claim on the significance of
seasonal variability and climate forecast. However, enough
caution should be exercised when interpreting things.
Though many claimed to appreciate SCF, actual
application seemed to be not enough. The start of each
cropping season was still principally based on the coming
of rains and the traditional seasonal schedule. Among
those who acknowledged the influence of SCF on the
general timing of planting in farm operations, only 1
percent claimed actual application on the planting

38 SCF Folio
schedule for corn. This shortcoming made farmers
vulnerable to climatic variability as proven in 2005 when
many corn growers had to replant three times due to
El Niño/La Niña-induced drought and floodings.
The indigenous means of forecasting also focused
more on seasonal onset and day-to-day weather.
Reliable projections on seasonal variability like the
possible occurrence of drought and excessive rains
were few. Indigenous mitigating measures as well as
modern interventions against droughts and floodings
were also found wanting.
With scarce reliable indigenous knowledge on
climate forecasting, the task becomes the sole
responsibility of the country’s meteorological bureau.
Other support institutions should also do their part in
helping farmers cope up with seasonal challenges. Corn
farmers should not only be recipients of information
but should also be target clienteles for the transfer of
appropriate agricultural technologies.
What is truly promising in all these is the
continuous validation that climate and climate-related
information are of prime consideration to farmers. The
positive figures and responses mentioned above are
close to what researchers and development workers
have been advocating. This seeming match between
the ideals of farmers and change agents could help
offset the technology application gap and possibly
make the campaign on SCF use much easier.
Without putting down the importance of
indigenous practices and know-how, reliable seasonal
climate forecast remains the key to answering the riddle
of seasonal variability. A dependable seasonal advisory
would allow farmers to securely harness the goodness
of the changing seasons. (SCF Project Updates, March 2007)
Indigenous forecasting means in Matalom
and Mahaplag, Leyte
When clouds in the east turn red at sunrise and narra
trees start to bud; when gangis (dragonflies) and
tukbahaw (birds) call and nights turn cold, then rainfall
will not be so bold…
This is neither an excerpt from a poetic piece nor an
introduction to a religious prophecy. Rather, it is an
enumeration of local indigenous indicators among corn
growers in Leyte province signifying that rainfall would
be scarce in the coming planting season.
In a farm and household survey conducted by Dr.
Canesio Predo and the Seasonal Climate Forecasts (SCF)
project team from Leyte State University, 125 corn
farmers from the municipalities of Matalom and
Mahaplag, Leyte were asked about their perception,
awareness, attitude, and indigenous knowledge on
forecasting and mitigating the effects of seasonal
climatic variability.
Farmers enumerated a list of traditional indicators
that are being used to project the overall theme of the
coming planting season. To predict the coming of rains,
many corn growers looked for a variety of signs such as
the behavior of plants and animals, appearance of stars,
color of the sky, and direction of the wind.
Among those identified as indigenous means of
forecasting a wetter season were: the falling of leaves
and flowering of narra trees, appearance of red sky
during sunset, presence of winds coming from the
northeast, and sighting of the Big Dipper constellation.
Some also believed in the impakta 1 phenomenon,
which suggests that the conditions of the first 12 days
of the year represent the general conditions of their
corresponding month in the 12-month calendar year.
Farmers generally perceived such indigenous
means as dependable, with around 60 percent of them
believing that traditional forecasting methods were
reliable. Only 39 percent of the farmers claimed
otherwise.
The results of the study are interesting as they
give a glimpse of the psychology and rich culture of
____________
1
Impakta phenomenon occurs, i.e., if the first day of the year is
raining, the whole month of January will be rainy; if the second
day of the year is raining, then the month of February will be rainy;
and so on until 12 days to complete the 12 months of the year.

39
local corn growers. In guiding farmers and infusing science
in their operations and on-farm decisionmaking, therefore,
awareness and enough vigilance of such beliefs should
be exercised. Indeed, much could be done to promote
productivity and minimize damages from climatic happenings
when knowledge of these local means is on hand.
Damages from climatic variability during the past
years were indeed immense, with 92 percent of the
respondents claiming that they had experienced losing
crops due to droughts, floods, and typhoons. The situation
is made worse as most of the farmers were pessimistic
about mitigating the adverse effects of these events. Still,
some corn growers claimed to have implemented
indigenous solutions like hilling-up, planting less, and
abandoning/fallowing the field.
A positive light is that more than 90 percent of the
farmers considered weather/climate as a major factor in
planning and crop production decisionmaking. Majority
claimed that advanced seasonal climate information
could aid in their production activities. This openness to
intervention, complemented with a rich blend of
experience and culture, could help jumpstart a wave of
development and increased productivity among the
country’s corn growers. (SCF Project Updates, March 2007)
Lunar-based agriculture: logic or folly
For centuries, the mysterious magnificence of the
moon has inspired the human mind to wander
in search of tributes and tales. From the rising
and falling of the tides to countless folklores of charms
and night creatures, the moon has been a staple in many
scientific and literary discourses. The same level of interest
applies to the field of agriculture where many farmers
have designated the various phases and faces of the moon
as indicators for a successful cropping or an impending
disaster.
Present-day lunar enthusiasts have tried to put a
semblance of logic to the value of the moon in agriculture.
It is claimed that all water on earth, from seas and rivers
to underground sources, are affected by the moon’s
gravitational pull. As the moon gets bigger during its
waxing phase (1st to 2nd quarter), water is said to rise
and become more available for plant growth. During its
waning or decreasing phase (3rd to 4th quarter), the water
table is said to recede. Practitioners of the art therefore
recommend that crops that need more water should be
planted during the waxing phase while crops that thrive
in dry conditions should be planted during the waning
phase.
Some sense could be gleaned from the above
premise but prudence is best to be exercised. One should
realize that the lunar cycle is completed every 27.3 days,
with each of the waxing and waning phases lasting for
only a couple of weeks. A simple review of the physiology
of major economic crops like corn and rice would show
that a typical cropping season extends from 90–120 days.
Both the increasing and decreasing phases of the moon
are therefore repeated 3–4 times during the whole
cropping season. The problem of attribution then
becomes a concern.
An article published in the web quoted John
Teasdale, the director of the United States Department of
Agriculture’s (USDA) Agricultural Systems Laboratory in
Maryland, saying, “he is not aware of any research on lunar
influences in agriculture, but a simple hypothesis is that
lunar cycles could influence meteorological cycles which
in turn could influence crops.” Again, it seems reasonable
that if the moon is strong enough to influence ocean tides,
then it must in some way also affect the atmosphere.
Earth and Sky Communications, an internet-based
organization, explained the problem with this hypothesis
by focusing on science. They say that the combined gravity
of the sun and moon does pull both air and water as the
planet rotates, creating tides in both the earth’s oceans
and atmosphere. However, recorded levels of air tides are
very insignificant near the earth’s equator where tidal
effects are supposedly at their strongest. The tidal effect
increases air pressure by only a fraction of one percent,
too insignificant to impact local weather.
Though claims of significance are easily validated
through science, the moon’s romance with the farmers’
psyche has been ongoing for hundreds of generations.
Most ancient civilizations had their own versions of lunar
calendars where they based their cropping and

40 SCF Folio
agricultural cycles. In Asia alone, the Chinese, Japanese,
and Korean people have their respective traditional
moon-based calendars. The sociocultural connection
between the moon and the Asian people is indeed very
evident.
In the Philippines where traditional beliefs and
values are very much alive, the moon serves as
foundation for many indigenous agricultural practices.
A simple survey in the country’s corn-growing provinces
proved that farmers still give high regard to the stages
and characteristics of the moon when commencing
farm operations and interpreting climatic happenings.
Indeed, it is hard to put sense and exact value to
the relevance of the moon in agricultural operations.
But it is easy to see that the influence of this radiant
heavenly body on the psychology of agricultural
workers rivals its impact on the changing tides. This
knowledge is worth a lot when dealing with farmers
and pushing for agricultural reforms. (SCF Project
Updates, March 2007)
Lessons from the Lopez calendar
If the Chinese, Japanese, Thais, and Koreans have their traditional lunar-based agricultural calendars, the Filipinos have the Kalendaryong
Tagalog or the Don Honorio Lopez calendar.
Written more than a century ago by Don Honorio Lopez, a native of Manila, Kalendaryong Tagalog chronicles the lunar cycle and
movements of the tides. It gives advice on a wide range of topics—from the most mundane like mannerisms and good conduct to the most
profound like economic and political concerns. The publication is also a good record of religious events and other significant happenings
in the country and enumerates notable names within religious and social circles. Up until now, Filipino babies are being named after the
saints and personalities enumerated in the pamphlet.
Kalendaryong Tagalog was never just an ordinary calendar depicting the days and events of the year. Since its publication in 1898,
the 40-page pamphlet instantly gained popularity and a lot of loyal following. For most part of the past century, Kalendaryong Tagalog
served as a bible for many rural farmers and fisherfolks. Not a few Filipino families allowed the publication to dictate their lives and
activities. There was a time when most rural farmers consulted the calendar on the best time to work the land and plant crops.
Perhaps the most notable accomplishment of Kalendaryong Tagalog is its longevity and impact on the local farming community. At
present, many farmers from Luzon to Mindanao still base their cropping decisions on the calendar. Regardless of climate forecasts, many
crop growers still religiously follow the recommended plowing and planting dates indicated in the publication.
The situation is remarkable yet alarming at the same time. It seems unsound that farmers would prefer traditional ways over science,
especially in an age where advancements in technology give man the ability to look at the inner workings of the atmosphere and forecast
climatic anomalies. The Filipino farmer needs to have a more reliable and systematic guide in his farm activities.
Through Kalendaryong Tagalog, Don Honorio Lopez addressed a legitimate societal need and succeeded in immortalizing his
name and ideas in the process. The challenge for present-day scientists and extension workers is to do the same and effectively imbed the
culture of science among local farmers. A reliable science-based option would bring farmers to a more enlightened plane and boost their
productivity to greater heights.
Are seasonal climate forecasts valuable
to farmers in Central West NSW
Jason Crean, Kevin Parton,
and Randall Jones *
Climate variability is a major source of
uncertainty to farmers in Australia. Recent
advances in the understanding and
predictability of interannual climatic variations have led
to renewed interest in the value of seasonal climate
forecasts (SCFs).
Past studies of the value of SCFs in Australia have
focused on the management of single crops rather than
farms and have tended to concentrate on the cropping-
____________
*
Postgraduate research student, University of Sydney; Professor,
Charles Sturt University; and Senior Research Scientist, NSW
Department of Primary Industries, respectively.

41
dominated regions of northern New South Wales (NSW)
and southern Queensland.
One of our Australian case studies attempts to shed
light on whether SCFs are of practical value to mixed
farming systems typical of central and southern NSW. We
use a whole farm analysis to assess the value of SCFs to
improve decisions about crop and livestock mix as well
as the choice of crop fertilizer inputs at sowing.
Approach
In order to have value, SCFs must lead to a different crop
and livestock mix or a different level of crop fertilizer
inputs. Value arises from decisions which either reduce
losses associated with expected adverse climatic
conditions or take advantage of expected good climatic
conditions.
A representative farm model for the Central West
region was used to assess the outcomes of decisions taken
with and without SCFs. The model captures some of the
whole farm interactions, resource limitations, and other
influences that may affect the value of SCFs. It uses
biological outputs from a crop simulation model to
determine the optimal area of crops and pasture to grow
and the optimal level of fertilizer to apply.
The Agricultural Production Systems Simulator
(APSIM) simulated crop yields for a period of 92 years,
under three starting levels of soil moisture and four
nitrogen application rates.
The climate forecast system assessed in this study is
referred to as the ‘SOI Phase’ system. The phases give
credence to both the absolute value of the SOI and its
rate of change. Seasons in the historical record are
categorized into one of five phases based on two
consecutive monthly values of the SOI. The five phases
are as follows:
Phase 1 - SOI consistently negative (SOI negative)
Phase 2 - SOI consistently positive (SOI positive)
Phase 3 - SOI rapidly falling (SOI falling)
Phase 4 - SOI rapidly rising (SOI rising)
Phase 5 - SOI neutral (SOI neutral)
Phases 1 and 3 identified in late autumn are
associated with below average rainfall in the following
winter and early spring period in eastern Australia while
Phases 2 and 4 are associated with above average rainfall.
Phase 5 is the neutral phase and is associated with
generally average rainfall conditions over the same period.
To estimate the value of an SCF, we rely only on the
observed influence of the SCF on rainfall probabilities and
its correlation with crop yields.
The ‘without SCF’ case (fixed management) is based
on a single farm strategy that performs best in an average
year over all climatic years. In contrast, the ‘with SCF’ case
(flexible management) implements the best farm strategy
for a given forecast type (phase) based on the subset of
years of that phase type. The overall value of SCF is found
by comparing farm profits between fixed and flexible
management over the 92-year simulation period.
Figure 1. Average farm profit with and without seasonal climate forecasts (SOI Phase)
Findings
Average returns
Farm profits with and without the SCF
under different levels of soil moisture are
shown in Figure 1. Farm profits improve as
the starting level of soil moisture increases.
The difference between the bars indicates
the gain in farm profit from forecast use.
Using the SCF at the lowest, moderate, and
maximum level of soil moisture improves
farm returns by 11.6 percent, 7.9 percent,
and 0.2 percent, respectively.
The SCF is found to be of most value
under low levels of starting soil moisture.
Low levels of starting soil moisture mean
that crop yields are more dependent on
in-season rainfall and, hence, better

42 SCF Folio
correlated to growing season
rainfall. Forecasts of lower
rainfall lead to decisions to
plant smaller crop areas and
lower fertilizer rates whereas
forecasts of higher rainfall
lead to larger cropping areas
and higher fertilizer rates.
At the highest level of
soil moisture, we find
practically no value from
SCFs. The reason is that only
one of the forecast categories
(SOI negative) leads to a
different decision and the
outcomes of that decision are
only a minor improvement
over not using the forecast.
Variability of returns
As well as considering the average value of using SCFs,
farmers might also be concerned with the variability in
farm returns. Farm returns over the 92 years with and
without the forecast are ranked from lowest to highest
in the form of cumulative distribution functions (Figure
2). The curves indicate the maximum level of profit
obtained at a given level of probability.
The use of the SCF reduces the probability of
incurring a farm loss from around 20 percent to almost
zero. Losses are avoided because a more conservative
crop and livestock mix is adopted when dry conditions
are forecast (SOI negative and SOI falling). The benefit
of reducing farm losses in dry years does, however, come
at some cost of lower farm profits when better than
predicted seasonal conditions arise. At 2/3 soil moisture,
farm returns become more stable under the SCF as both
gains and losses are limited.
While farm returns can be less variable when
following a SCF, this will not always be the case. Under
the 1/3 soil moisture case, returns were sometimes
found to be more variable as the representative farm
reacted to forecasts of higher seasonal rainfall (SOI
positive and SOI rising). This led to an increase in crop
area in those years when forecasts of higher season
rainfall were issued. This lifted returns when the
favorable seasons predicted occurred but also resulted
in losses when the season was dry despite the forecast.
Figure 2.Distribution of farm profit – with and without SCF (2/3 soil moisture)
On average, however, farmers were much better off with
the SCF as the gains exceeded the losses.
Conclusions
Climate forecasts are valuable to farmers in Central West
NSW with the extent of value dependent on the level
of soil moisture at planting. When starting soil moisture
is low, both the level of crop production and the level
of economic returns are more reliant on in-season
rainfall conditions. Consequently, an accurate forecast
of in-season rainfall is more valuable when these
conditions exist.
There is a complex interaction between SCFs and
farm decisionmaking. At different levels of soil moisture,
forecast categories vary in their influence over farm
decisions and change the distribution of returns. In the
2/3 soil moisture case, the SCF led to more stable returns
whereas returns in the 1/3 soil moisture case were
slightly more variable.
SCFs have the potential to either enhance or
moderate income variability. Individual farmers will
have different attitudes toward these outcomes
depending on their level of risk aversion.
The overall economic value of SCFs can be
dominated by the value associated with following just
one or two forecast categories within that system. A
message from this is that farmers need to be conscious
of when to apply and when best to disregard the
information provided by SCFs. (SCF Project Updates, June 2007)

43
The influence of ENSO on frost risk
in eastern and southeastern Australia
Bronya Alexander and Peter Hayman *
Frost can cause large losses in the yield of
agricultural crops in many areas of the world,
including much of Australia’s agricultural
regions. Frosts usually occur from late autumn (May) to
spring (October) in the Southern Hemisphere. In Australia,
frosts typically occur when a region is under the influence
of a high pressure system. This creates clear skies and a
dry atmosphere, and often very little wind—conditions
that are conducive to frost formation. A drier atmosphere
at night allows more heat to escape from the ground,
causing the air near the ground to be cooler. Whereas, if
there is moisture in the atmosphere, it helps to absorb
the escaping heat, keeping it close to the ground and
reducing the chance of frost.
Southeastern Australia has a winter dominant rainfall
pattern, so crops such as wheat and barley are sown midlate
autumn or early winter, and generally flower around
spring. A plant is very susceptible to frost at the time of
flowering, so in frost-prone areas, you want your crop to
flower after the frost-risky season. Later flowering can be
achieved by sowing the crop later. However, the later you
sow, the less yield you are likely to get. Therefore,
managing frost risk is a balancing act between the crop
flowering too early and suffering frost damage and the
yield penalty from moisture and heat stress of the crop
flowering too late in spring. Ideally, grain farmers would
aim for their wheat crop to flower immediately after the
last frost in spring, but this date is highly variable. Figure 1
shows typical sowing and flowering periods with respect
to rainfall and minimum temperature for a cropping town
in South Australia.
Impacts from the El Niño Southern Oscillation (ENSO)
are most commonly associated with rainfall. However,
ENSO is also associated with temperatures and therefore
may influence the frost risk in Australia. The increased
frequency of clear skies and high surface pressures often
associated with El Niño conditions in Australia generally
mean less clouds, less wind, colder nights, and therefore
potentially more frosts. The following study was done to
investigate the effect of ENSO on the frequency of frosts,
and also on the date of the last frost for a number of
stations in eastern and southeastern Australia.
Data
The minimum temperature data used in this analysis were
patched point data from the Bureau of Meteorology’s SILO
website. These daily data consist of original measurements
from a particular meteorological station along with
interpolated data used to fill any gaps in the record. Data
from 1900–2005 were analyzed for the following eight
stations across eastern and southeastern Australia:
____________
*
Project Officer and Principal Scientist on Climate Applications,
respectively, both from the South Australia Research and
Development Institute (SARDI).
Figure 1. Mean monthly rainfall and minimum temperature for Snowtown in South Australia, 1900–2006
Note: Average rainfall and minimum temperatures across a year at Snowtown, South Australia are shown above. Also shown are
periods of time when sowing, flowering, and frost risk are common.

44 SCF Folio
Emerald and Goondiwindi (Queensland); Gunnedah,
Wagga Wagga, and Deniliquin (New South Wales);
Mildura and Nhill (Victoria); and Snowtown (South
Australia).
To classify years as El Niño or La Niña, we have used
a list provided by the Bureau of Meteorology (Table 1).
Any year that does not appear as El Niño or La Niña
between 1900 and 2005 in this list was classified as a
neutral year by the Bureau.
Graphs
Three types of graphs were analyzed. Figure 2 shows
the probability of there being a particular number of
days of frost [minimum temperature less than 2 degrees
Celsius (C)] per year at Snowtown, South Australia,
throughout the historical record from 1900 to 2005. Also
shown are the probability curves for El Niño, La Niña or
neutral years, as well as the curve created from the last
20 years of data.
Figure 3 presents the latest date of a frost each
year at Snowtown, i.e., the probability that the last frost
each year has occurred by the given date. Again, the
probability curves for the three ENSO classifications are
shown as well as the last 20 years. The final set of graphs
analyzed were again looking at the latest date of frost,
except that this time, a frost was defined as getting a
minimum temperature less than 0 degrees C.
Discussion
From Figure 2, it can be seen that there are generally
more frost days in El Niño years at Snowtown compared
to La Niña years. For example, in a La Niña year, 50
percent of the time, there are over 14 frost days, whereas
in an El Niño year, 50 percent of the time, there are over
18 frost days. This distinction between the frequency
of frost in El Niño and La Niña years was apparent in all
the locations looked at in this study. It is interesting to
also note from Figure 2 that the number of frosts in the
last 20 years was less than the historical average.
However, this observation was not consistent across the
other sites analyzed, with many showing average frost
frequencies over the last 20 years and two sites showing
an increase in frequency.
Figure 3 displays the latest date of a frost each year
at Snowtown, revealing little distinction between El
Niño and La Niña years, particularly in the latest 30
Table 1. El Niño and La Niña
years as defined by the
Australian Government Bureau
of Meteorology
Figure 2.Probability distribution of the number of frost days (less than 2 degrees
Celsius measured at Stevenson Screen height) at Snowtown, South Australia
El Niño
La Niña
1902 1903
1905 1906
1911 1909
1913 1910
1914 1916
1919 1917
1925 1924
1940 1928
1941 1938
1946 1950
1952 1955
1953 1956
1959 1964
1965 1970
1969 1971
1972 1973
1977 1974
1982 1975
1987 1988
1991 1996
1993 1998
1994
1997
2002
Figure 3.Probability distribution of the latest date of frost (less than 2 degrees
Celsius measured at Stevenson screen height) at Snowtown, South Australia

45
It is the timing of the latest frosts that are useful to know
because they often hit unexpectedly, but it seems that ENSO
does not influence this enough to be of much use in terms of
forecasting potential.
percent of frosts. Similarly, most of the other sites analyzed
did not show much distinction between El Niño and La
Niña in terms of the latest date of frost, particularly for
the last 20–30 percent of the years. Graphs showing the
latest date of frost, where a frost was defined as less than
zero degrees Celsius were also analyzed. Many locations
showed some distinction with the last frosts more likely
to occur in El Niño years, but most still showed little
distinction for the latest 20 percent of frosts. Figure 3 also
demonstrates the wide range in the last date of a frost
from year to year. For example, the last frost (

46 SCF Folio
and most of the irrigation Figure 2.Areas affected by dry spell
requirements of farms in
Bulacan and some areas in
Pampanga, with a belowcritical
level of water supply.
Consequently, this led to a
scarcity in the domestic
water supply, especially in
Metro Manila, and crop
failures in many areas in
Central Luzon due to the
reduced irrigated areas.
Figure 2 shows the areas
badly hit by the dry spell. In
addition, the incidence of
fires and certain health
problems rose.
For the agricultural
sector, the prolonged dry
condition slowed down
productivity due to delays in planting and harvesting, instituted; repair of dikes and other impounding
setting the farmers’ production outputs back by one to infrastructures was ordered; small water impounding
two months. As a result, for the first half of 2007, projects were adopted; and cloud seeding operations
agricultural growth slowed down to 3.5 percent as in some areas in Metro Manila, Cagayan Valley, and
compared to the 5.4 percent growth recorded over the Central Luzon were undertaken, among others. On the
same period in 2006. Corn shortages of about 1 million demand side, meanwhile, water conservation was
metric tons were also recorded while rice production encouraged among the public; use of resistant crops
losses of about 400,000 metric tons were estimated. In requiring less water and of early maturing varieties was
sum, about PhP1.14 billion worth of agricultural adopted; and energy conservation was observed in
damages were estimated as a consequence of the dry various public offices.
spell.
In addition, other government bodies led by the
country’s national meteorological agency, the PAGASA,
What were some of the responses
and the Department of Science and Technology (DOST)
A number of mitigating measures were instituted by conducted an intensive information, education, and
various government agencies to help address the communication (IEC) campaign for Dry Spell Vulnerable
adverse consequences of the dry spell.
Areas. The objective was to raise public awareness on
On the supply side, directives on optimum water the effects of the dry spell and to build the capacity of
allocation and utilization were issued by national water the local chief executives, the constituents, and the
resources agencies; water supply distribution was media in communities under or vulnerable to said dry
spell condition to assess their current situation.
The objective of the IEC campaign for Dry Spell Vulnerable Areas Hopefully, they will have a better understanding of the
was to raise public awareness on the effects of the dry spell and to weather and climate advisories issued by PAGASA, and
build the capacity of the local chief executives, the constituents, and will be able to recommend and set up necessary
the media in communities under or vulnerable to said dry spell mitigation measures to address the impact of the dry
condition to assess their current situation. Hopefully, they will have spell. The target areas of this IEC drive include 22
a better understanding of the weather and climate advisories issued provinces in five regions of Luzon (Regions 1, 2, 3, 4, and
by PAGASA, and will be able to recommend and set up necessary the Cordillera Administrative Region). (SCF Project
mitigation measures to address the impact of the dry spell.
Updates, September 2007)

A model for valuing seasonal climate forecast
47
The losses and setbacks in agricultural production
experienced recently by many farms in Luzon due
to the dry spell that hit the country last June and
July raise the question on whether such losses could have
been reduced, if not totally prevented, had farmers
adjusted their production activities accordingly with
advanced information given them on the possible onset,
timing, and duration of the dry spell.
In the first place, too, do farmers and other
agricultural decisionmakers get advanced information or
climate forecasts regarding the coming of seasonal
climate phenomena like El Niño, La Niña, dry spell or wet
spell
And how much is it worth to a farmer in terms of
“saved” or increased incomes/revenues if he indeed has
The losses and setbacks in agricultural production experienced
recently by many farms in Luzon due to the dry spell that hit
the country last June and July raise the question on whether
such losses could have been reduced, if not totally prevented,
had farmers adjusted their production activities accordingly
with advanced information given them on the possible onset,
timing, and duration of the dry spell.
Figure 1. Economic valuation framework used in the study
these seasonal climate forecasts (SCFs) and makes good
use of them
In the joint Australian-Philippine project titled
“Bridging the gap between seasonal climate forecasts and
decisionmakers in agriculture” sponsored by the
Australian Centre for International Agricultural Research
(ACIAR), one of the objectives is to determine, through
case studies and surveys, if a farmer gets the right
information about the onset of seasonal climate
phenomena like the El Niño Southern Oscillation (ENSO)
phases (El Niño and La Niña) at the appropriate time and
if he does, whether or not he makes use of them and
incorporates them in his decisions affecting crop
production and choices.
Assuming that the farmer incorporates the
information in his decisionmaking, what economic value
does he gain, if any With the additional information, does
he have more options to choose from Does it give him
additional income Does it reduce his potential losses visà-vis
a situation where he has no such information about
the onset of these climate occurrences
In order to answer these questions, Dr. Canesio Predo
and Ms. Zyra May Holmes of the Visayas State University
(formerly Leyte State University) adopted
an economic valuation framework that
builds on the expected utility theory and
decision tree analysis but employs an
alternative approach in measuring and
estimating the value and utility of SCFs in
the context of farm level cropping
decisions. Predo and Holmes applied the
framework in their Philippine case study
areas for the seasonal climate forecasts
project in Bohol and Leyte.
The model, as seen in Figure 1, looks
at farming decisions under two scenarios,
namely: (a) without SCFs, and (b) with SCFs.
For both scenarios, crop simulation
models are required to be calibrated with
corn farming systems’ input parameters,
e.g., biophysical data, input requirements,
prices, etc. Simulation outputs are also
generated to come up with the crop
yields under various ENSO phases such as

48 SCF Folio
Peso value of SCF use in Bohol Province
In an economic assessment of seasonal climate forecast (SCF) use in corn production decisions of farmers in Bohol
Province as conducted by Ms. Zyra May Holmes and Dr. Canesio Predo of the Visayas State University (VSU), the authors
calculated the economic value of using SCF for corn cropping system to be around PhP51.22/ha/season. This is based on
the summary statistics of simulated results showing that the stochastic net returns of cropping choice without SCF ranged
from PhP2,084.47 to PhP2,837.63/ha/season with a mean of PhP2,439.31/ha/season. With SCF forecast, the stochastic
net returns ranged from PhP2,119.24 to PhP2,934.21/ha/season with a mean of PhP2,490.53/ha/season.
While the amount may be considered too minimal for individual smallholder corn farmers to change their cropping
decision, the figure, however, is significant enough if the total corn-producing area of Bohol Province is to be considered.
The authors made the calculations using the economic valuation model that they adopted (see feature on the Model).
Valuing SCF use for corn farmers in Leyte
Using the same model as the one they used in their case study in Bohol Province, Ms. Zyra May Holmes and Dr. Canesio
Predo of the Visayas State University (VSU) estimated the economic value of using SCFs in corn farming areas in Mahaplag
and Matalom municipalities in Leyte Province to be PhP119/ha/season. A forecast was found to be valuable in deciding
when to plant corn. A forecast has value if the “with forecast “ scenario leads to different decisions and improved outcomes
over those in the “without forecast” scenario. In the Leyte case study sites, the authors found that there was indeed value
as shown in their resulting estimates.
El Niño, La Niña, and neutral years as noted in Figure 1.
However, to generate crop yields under different ENSO
years, complete historical daily climate data such as
rainfall, solar radiation, minimum and maximum
temperatures, among others, are required.
Because these data are not, however, available (or
incomplete during the time of analysis) in the Philippine
case study areas, Predo and Holmes decided to employ
an alternative approach through the use of experts’
opinions/observations and farmers’ practices regarding
corn yields during dry years (El Niño), wet years (La Niña),
and normal years (neutral years). For each category of
ENSO years, farmers were asked to provide corn yield
estimates during good, average, and poor seasons.
To see what the additional value of the information to be provided
by the forecasts or the SCFs would be or what value any revision
in a farmer’s prior decision would be, the RAINMAN international
software package, developed under a previous ACIAR project,
was used to provide the probability of a good, average, and poor
season based on the Southern Oscillation Index (SOI) system of
forecasts...With this model/framework, it would thus be possible
to calculate the value in peso terms for the farmers regarding the
use of climate forecasts in making production decisions.
Using these data, the stochastic decision tree
analysis within the framework of expected monetary
value or expected payoffs of the crop choice was
estimated and valued.
To see what the additional value of the information
to be provided by the forecasts or the SCFs (amount of
rainfall, timing of rainfall events, frequency of rainfall)
would be or what value any revision in a farmer’s prior
decision (when he had no forecasts) would be, the
RAINMAN international software package, developed
under a previous ACIAR project, was used to provide
the probability of a good, average, and poor season
based on the Southern Oscillation Index (SOI) system
of forecasts. The stochastic gross margin for the
outcome of each season was calculated using the
SIMETAR software to generate the cumulative
distribution function of the expected value of crop
choice for both “with SCF” and “without SCF” scenarios.
The value of the SCF is derived as the difference
between the expected value of choice with forecast and
the expected value of action without forecast.
With this model/framework, it would thus be
possible to calculate the value in peso terms for the
farmers regarding the use of climate forecasts in making
production decisions. (SCF Project Updates, September 2007)

49
And on rice crop...
Nueva Ecija farmers favor SCF over traditional
forecasting methods
Although they were aware of some indigenous
forecasting methods, most of the rice farmers
in two municipalities of Nueva Ecija have faith
only in the seasonal climate forecasts (SCFs) provided by
PAGASA.
This was the result of a survey conducted by PhilRice
researchers among 120 farmers in Talugtug and Lupao,
Nueva Ecija. The farmers served as participants in the
study that aims to assess the potential farm-level value of
SCF for rice-based farming systems in Central Luzon,
Philippines.
Both of the study sites are rainfed, flood plain
belonging to the upper vega. Rice farmers plant only
during the wet season and some farmers use
supplementary irrigation sourced from deep well, small
farm reservoir, and shallow tube wells.
Random sampling was used to identify respondents
based on the list of samples taken from the municipalities’
Agriculture Offices. Of the 120 respondents, 60 were taken
from each of the two municipalities.
Most of the respondents were male (83%), married
(89%), and with an average age of 50 years. Their average
number of years in rice farming was 25.
Ninety-six percent of the farmers considered climate
in their farm planning and decisionmaking. They also
opined that early climate forecasts would help in their
decisionmaking. However, the result of the survey also
shows that most of the farmers do not have mitigation
measures and risk-coping mechanisms in times of calamity.
More than half of the respondents (74%) said that
they were satisfied with the climate-related information
that they have been receiving. As to the sufficiency and
correctness of the information they received, 66 percent
claimed that they received sufficient information while
47 percent said that the climate-related information that
they received was correct.
Farmers also said that most of the climate advisories
that they received were on typhoons and El Niño, with
their main sources of information coming from radio and
television. (SCF Project Updates, September 2007)
Looking for options amidst seasonal
climate variability
The vulnerability of agriculture to the
unpredictability of nature is an age-old riddle,
which has left even the wisest of men without
answers. In most cases, people are given no other recourse
but to adapt to environmental happenings and make do
with what they have. In the Philippines where agricultural
production represents a major source of livelihood for
many rural people, the pressure to do better amidst
seasonal climatic variability is immense.
Scholars claim that climatic variability has great
socioeconomic consequences and would worsen the
disparity between the rich and poor. With more than 90
percent of local agricultural workers classified as
smallholders, many could not afford a failed season of
cropping. Measures to address this concern should
therefore be multidimensional—tackling both physical
and welfare issues. Safeguarding the livelihood and
interests of local farmers entails concrete action in the
social, economic, and political fronts.
A major cause of the climatic variability and
catastrophes being experienced in the country is the El
Niño Southern Oscillation (ENSO) phenomenon. ENSO
shows its destructive face through two major phases: the
El Niño or warm event and the La Niña or cold event. El

50 SCF Folio
Niño conditions generally lead to drier seasons due to
suppressed tropical cyclone activity and weak monsoon
characterized by delayed onset, dry periods, and short
monsoon season. In contrast, La Niña is characterized
by above normal rainfall and longer rainy seasons.
The destructive power of ENSO was clearly
documented during the 1997–1998 El Niño/La Niña
episode when a total of PhP7.6 billion in rice and corn
production losses were incurred. Greenpeace (2007)
also estimated that from 1975 to 2002 alone,
intensifying tropical cyclones in the Philippines have
caused an average yearly damage to property of PhP4.5
billion with agricultural damages reaching as high as
PhP3 billion. The organization further claimed that the
Philippines, like the rest of the region, would likely
continue to experience extreme climatic variability as
manifestation of the impact of climate change.
Nature’s challenges are daunting for everyone
concerned. Farmers with their meager resources and
traditional ways have been trying to adapt and survive.
National and local governments, nongovernment
organizations (NGOs), and other institutional bodies/
stakeholders are doing their part but further
consolidation of efforts is needed. Among the measures
that the Philippine government has come up with to
assist farmers in the face of seasonal climate variability
are price stabilization measures, typhoon and/or
drought relief, livestock and feed subsidies, farm input
subsidies, agricultural credit, and subsidized crop
insurance schemes.
Indeed, the identified problems and issues due to
climatic variability also present opportunities for
interventions. But most important to consider
in any development effort is the suitability of the
intervention to the needs and situation of the
target population. Not a few development
initiatives have failed because of mismatch
between the help offered and what was
required in the field. The best way to proceed
then is to do situational analysis and extract from
the target clientele the types and kinds of
assistance that are needed and preferred.
Decades of agricultural support, risk
mitigation, and relief efforts have resulted to
some degree of success, but a more lasting and
sustainable solution is yet to come. Studies done
under the ACIAR-funded project “Bridging the
gap between seasonal climate forecasts (SCFs)
and decisionmakers in agriculture” characterized the
target farmer populace and put value to SCFs and other
possible interventions. Surveys among rice and corn
farmers in key producing municipalities made it
apparent that the sector still needs much assistance.
General farm productivity needs to be improved, farms
are still very vulnerable to damages brought about by
floods, drought, and typhoons, and many farmers are
up to their necks in debt. There are a number of possible
entry points for development interventions that the
surveys identified. Among the most preferred by
farmers are provision of better climate information,
accessible credit, crop insurance, and special assistance
programs.
Individually, farmers could decide to work with a
number of on-farm mitigating measures like proper
timing of planting, use of appropriate crops and crop
varieties, and establishment of on-farm supplementary
irrigation systems, among others. The range of
applicable tools, however, is usually subject to the
availability of information and resources and their
openness to interventions.
A lot could be done to alleviate the plight of
smallholder farmers and help increase their capacity to
cope with shocks and environmental stresses. The
specific interventions, though administered individually,
should complement, justify, and strengthen each other.
Ultimately, the smallholder farmer should end up with
appropriate tools and increased capacity to better deal
with the challenges offered by seasonal climate
variability. (SCF Project Updates, December 2007)

51
Security against climate variability
through agricultural insurance
Experts agree that agricultural insurance is one of
the best ways to address the adverse impacts of
seasonal climatic variability and secure the welfare
of smallholder farmers. Designed to protect agricultural
producers against loss due to natural calamities, pests, and
other risks, agricultural insurance has a lot of potential
benefits especially in the Philippines where climatic and
other environmental uncertainties are of great concern.
Agricultural insurance in the country is implemented
and managed by the Philippine Crop Insurance
Corporation (PCIC). Although the government subsidizes
insurance for rice and corn, the PCIC operates as a business
corporation and does not receive any budget from the
government for its administrative operations.
Rice and corn insurance constitute about 84 percent
of PCIC’s total business. From 1981 to 2007, the program
was able to serve a total of 3,468,155 farmers, insuring a
total sum of PhP31 billion. Total gross premiums received
during the period exceeded indemnities paid at a ratio
of 1.27:1. Earlier, however, the PCIC had a rough time
during its first decade of operation when damage claims
consistently surpassed premium collections from 1983 to
1989. The program had its highest accomplishment
during the early part of the 1990s when it reached its peak
coverage at 336,000 farmers.
Seasonal climate variability proved to be the top
source of uncertainty for rice and corn farmers. Overall,
typhoons and floods were the major causes of production
damage for rice while drought was the number one cause
of loss for corn. Claims on rice insurance from typhoon
and flooding totaled PhP1.050 billion from 1981 to 2007.
Table 1. Cumulative insurance coverage and claims paid for rice
and corn from 1981 to 2007
Insurance Insurance Coverage Claims Paid
Lines No. of Farmers/ Sum Insured No. of Farmers/ Claims Paid
Policies Written (PM) Policies Paid (PM)
Rice 3,010,929 26,437.23 845,812 1,960.54
Corn 457,226 5,011.11 189,548 611.22
TOTAL 3,468,155 31,448 1,035,360 2,572
Source: PCIC 2007
Claims on corn insurance caused by drought amounted
to PhP258 million from 1982 to 2007.
The PCIC attributes an aggregate amount of PhP1.7
billion in rice and corn crop insurance claims to damages
from typhoons/floods and droughts. This figure
represents 66 percent of the total indemnity paid by PCIC
for all insured commodities covering all causes since the
start of its operation. This effectively describes the impact
of seasonal climate variability on crop insurance
operations and agricultural productivity as a whole.
Bridging SCF with agricultural insurance use could
possibly soften the damage figures.
While agricultural insurance has earned its place in
the government’s risk management portfolio, program
implementation is greatly hampered by a number of
concerns. In the Philippines and in many parts of the
developing world, harnessing the potential benefits from
the scheme is constrained by operational and
sustainability issues.
In a recent PIDS-led survey conducted in Isabela,
Philippines, for instance, it was found that formal lending
institutions and crop insurance were virtually nonexistent
in select farming communities. Insurance service is also
inadequate in many other key agricultural production
areas. Data from the PCIC showed that program coverage
drastically declined after reaching its peak in 1991. By year
2001, the number of covered farmers leveled off just
below the 50,000 mark. PCIC closed the year 2006 with
barely 36,000 farmers covered.
Estacio and Mordeno (2001) attributed the decline
in insured farmers to the contraction of the self-financed
market program and the shrinking of directed credit
programs which automatically availed of insurance
coverage. PCIC also claimed that with the borrowing
farmers dominating the traditional lines, the
decreasing trend on crop insurance coverage greatly
reflected the lending performance of formal lenders,
particularly the Land Bank of the Philippines (LBP)
which accounted for 77 percent of its clients.
As it is right now, agricultural credit and
agricultural insurance are intertwined. If the
insurance program is not allowed by law to impose

52 SCF Folio
commercially competitive rates and profit from
smallholder farmers, then the program has no choice
but to stick close to formal lenders and avail of subsidies.
But still, the market for borrowing farmers is big enough
for PCIC to create waves and generate significant
impact. The program just has to find creative ways to
expand its share of the market.
International development organizations have
been claiming that traditional crop insurance schemes
like the one in the Philippines are plagued with inherent
problems. The common ones are problems in
information asymmetry, adverse selection, moral hazard,
and high administrative and
transaction costs. Information
asymmetry refers to the unequal
information available to insurers and
clients; adverse selection refers to
the noninclination of low-risk
farmers to buy insurance; moral
hazard relates to a farmer’s
inclination not to do enough to
avoid or minimize loss; and high
administrative and transaction costs
refer to the huge expense in
marketing, calculating, and
collecting individual premiums and paying claims.
If the agricultural insurance program is to survive
and become operationally sustainable, it will have to
operate as an economically viable unit. Efforts must be
made to streamline the program’s operation and install
a more aggressive marketing component. It may be
wise to explore emerging innovative insurance
schemes like index-based and market-based insurance
products. Ultimately, the PCIC and the Philippine
agricultural insurance program must go after its
mandated target market with more efficiency and
determination. (SCF Project Updates, December 2007)
Augmenting resources of smallholder
farmers through agricultural credit
Lack of capital limits most smallholder farmers
from achieving greater farm productivity. The
presence of formal and informal lenders in the
rural financial scene serves a critical purpose and
ensures that farmers are able to meet their operational
and household needs.
Formal lenders include commercial banks, thrift
and development banks, rural banks, and credit
guarantee institutions. Informal lenders, on the other
hand, include traditional moneylenders and credit
organizations/groupings.
On the part of the government, the Agricultural
Credit Policy Council (ACPC) oversees agricultural credit
and helps develop and implement strategies and
policies designed to increase and sustain the flow of
credit to agriculture and fisheries, improve the viability
of farmers and fisherfolk, and support agriculture
modernization, food security, and poverty alleviation.
Government banks like the Land Bank of the Philippines
(LBP) and the Development Bank of the Philippines
(DBP) are also key players in rural credit. LBP is the most
active bank in agricultural credit while DBP also
provides credit to agriculture and small and mediumscale
industries. QUEDANCOR or the Quedan and Rural
Credit Guarantee Corporation, a semigovernment
entity, also supports farmers and rural enterprises and
is tasked to accelerate the flow of investments and
credit resources into the countryside.
While government and private banks have been
providing agricultural credit, informal lenders have

53
been dominating the Table 1. Borrowing by major source of loans, 1996–2002 setting. If formal
rural lending scene for
Source 1996–1997 1999–2000 2001–2002
institutions are to
decades. Data from the
regain a substantial
Bangko Sentral ng All borrowers 100.0 100.0 100.0
portion of the credit
Formal institutions 24.0 28.6 34.4
Pilipinas (BSP) prove Informal lenders 76.0 61.3 60.3 market, they will have to
that majority of farmers Formal and informal lenders 5.3 adopt some flexibility.
go to informal lenders
Source: ACPC 2002
One way of doing
for their credit needs
this is to accept
and although informal
lending decreased by 16 percent from 1996 to 2002, its
hold on the credit market is still formidable at 60 percent.
The risk averseness of formal banks when it comes to
targeting clients makes it hard for them to fully venture
into the rural financial market.
Seasonal climate variability, aside from increasing
risks in agricultural operations, further decreases the
attractiveness of farmers to formal lenders. Extreme
climate/weather events like floods, droughts, and
typhoons could easily destroy a season’s crop and erode
whatever financial capacity farmers have. Available figures
on damages to agriculture from extreme climatic events
substitute collaterals.
Informal lenders have long been exploiting this
alternative by accepting pawning of cultivation rights,
required sale of output to trader-lenders, joint liability or
having a guarantor to back up the loan, mutual guarantee
by group members, interlinked contracts, and
government guarantee (Llanto 2004). In short, formal
institutions need to evolve if they are to fare well in the
rural credit market.
Another possible workable arrangement is shown
in the government’s attempts to partner with informal
lenders in rural credit delivery. QUEDANCOR, for instance,
has tapped traders and millers with access to traditional
are staggering. With local and international banking as credit intermediaries. Guarantees were given
meteorological organizations predicting that the
occurrence of ENSO and other extreme climatic events
would be more frequent and intense, the future does not
seem to be more attractive to formal bank ventures. In
contrast, informal lenders are able to capitalize on these
events since they are still able to earn through collateral
substitution even when farmers’ crops fail.
The small presence of formal banks/creditors in the
rural scene has opened up opportunities for informal
entities to grow and fill in this void. The ability of informal
lenders to adapt to local requirements sets them apart
from their formal counterparts. High transaction costs as
well as high loan risk impair the ability of formal banks to
operate cost-effectively under a rural set-up. Their rigid
credit requirements also do not go well with the rural
to these traders and millers who, after obtaining bank
loans, provided credit to their small farmer clients in turn.
The LBP was also motivated to use NGOs and cooperatives
as credit intermediaries to deliver credit to numerous
small borrowers. Practical arrangements like these should
be considered more seriously to take advantage of the
strengths of the informal lending sector.
A promising development is the present popularity
of alternative lending schemes like microcredit.
Microfinance institutions (MFIs) may charge marketoriented
interest rates, enabling them to recover costs and
allowing their operations to get a semblance of
sustainability. NGOs have also pioneered the use of
lending techniques that draw inspiration from the
informal moneylenders like the use of third party
guarantees, timely processing and quick release of loans,
Seasonal climate variability, aside from increasing risks in
agricultural operations, further decreases the attractiveness of
farmers to formal lenders. Extreme climate/weather events like
floods, droughts, and typhoons could easily destroy a season’s
crop and erode whatever financial capacity farmers have...In
contrast, informal lenders are able to capitalize on these events
since they are still able to earn through collateral substitution
even when farmers’ crops fail.
and lending without requiring traditional collateral,
among others (Llanto 2004).
In sum, more efforts must be exerted by concerned
parties to make the operation of formal institutions in the
countryside more attractive and viable. Alternative
modalities like microfinancing present great potential in
bringing better credit service to the countryside. (SCF
Project Updates, December 2007)

54 SCF Folio
Addressing farmers’ needs through
other special development programs
The importance of rice and corn to the economy
and welfare of many Filipinos as well as the
immense challenge in improving productivity
justifies government intervention through special
programs.
A snapshot of the rice and corn industries shows
both promise and despair. With an average annual
national production of 11.20 million tons (MT) for rice
and 5.25 MT for corn, the Philippines incurs yearly
production deficits of 1.5 MT and 1.33 MT for rice and
corn, respectively (PCARRD 2005, Lantican 2004, BAS
2006). The country fills this supply gap through
appropriate importation from neighboring countries.
Farmers and industry people could cash in on the
unmet demand through greater productivity and more
efficient trade.
A little over 4 million hectares are planted to rice
while another 2.5 million hectares are planted to corn.
Lantican (2004) estimated that for the Philippines to be
self-sufficient in its grain requirements, productivity for
both crops should be raised to at least 3.80T/ha. Salazar
(2003), on the other hand, deduced that given an annual
population growth rate of 2.2 percent and an estimated
rice consumption of 105 kg per person per year, the
country will need to produce 21 MT of rice in 2025 and
34 MT in 2050 to feed about 123 million and 203 million
people, respectively.
Adequate farm inputs and irrigation water are
necessary if greater productivity and higher areas
planted to crops, especially rice, are to be targeted. This
is very much true for rice where increased yield would
entail proper irrigation support. Corn, on the other hand,
could survive in less developed agricultural lands and
thrive exclusively on rainfall. Better corn productivity,
however, could be had if water during the crop’s critical
growth stages could be assured.
Various types of assistance are being offered by
the government to rice and corn farmers. For example,
subsidies on seeds and other inputs, irrigation
development, credit facilitation, crop insurance, farmto-market
roads, capacity building through technical
assistance, training and extension, postharvest
development, and price support, among others, are
being made available by government to farmers.
Among these interventions, seed subsidy during
calamities and irrigation development were mentioned
by interviewed farmers as most needed and relevant
in coping with seasonal climate variability.
To help small farmers meet the high cost of inputs,
the government, through the Department of
Agriculture (DA), implements programs that subsidize
the price of hybrid and inbred seeds for rice; and hybrid
and open pollinated varieties for corn. The seeds are
provided during regular season to increase farm
productivity, and at times during postcalamity relief to
aid in the rehabilitation and replanting of damaged
farms. Two umbrella programs within the DA, the
Ginintuang Masaganang Ani (GMA) Rice Program and
the GMA Corn Program cover the implementation of
the seed subsidy programs.
Input subsidies such as provision of seeds for rice
and corn farmers are of big help to many. However, the
cost-effectiveness of this intervention must be studied
more carefully. Billions have already been incurred by
the government in providing highly subsidized hybrid
and inbred seeds, without the benefit of seeing
dramatic productivity improvements and social
benefits. Provision of seeds as part of relief assistance
to areas damaged by drought/flood/typhoon, though,
is commendable and necessary especially for
subsistence farmers.
For irrigation support, the National Irrigation
Administration (NIA) operated and maintained national
irrigation systems (NIS) servicing around 972,692 ha in
the year 2005. This consisted of 496,242 ha for wet crops
and 476,450 ha for dry crops. The total irrigated area by
Communal Irrigation Systems (CIS) totaled 558,598 ha
comprising of 291,891 ha during wet season and
266,707 ha during the dry season. All in all, NIA (2006)
estimated that the total irrigated area in both wet and
dry seasons for NIS and CIS is 1,531,290 ha.
As of 2007, the Bureau of Soils and Water
Management (BSWM) also reported the construction
of a total of 1,399 small water impounding projects

55
The need to help rice and corn farmers is ever pressing,
especially given problems on seasonal climate variability.
Government programs on input subsidy and irrigation
support serve a very good purpose but prudence should also
be exercised in ensuring the cost-effectiveness and
sustainability of any development intervention.
(SWIPs), 22,282 small farm reservoirs (SFRs) and 30,728
shallow tubewells (STWs). These are classified as smallscale
irrigation systems, with each structure servicing only
limited farm areas. Average service areas for the systems
are 55 ha for SWIP, 1–2 ha for SFR, and 3–5 ha for STW.
Though relatively limited in coverage, small scale irrigation
systems have lower investment cost per hectare, and most
could be developed by private persons or entities.
As mitigating measure against climatic aberration
like droughts and floods, irrigation facilities serve both as
water reservoir and drainage. There are, however,
limitations. During times of drought, for instance, the
service areas of NIA-administered systems are drastically
cut. The tail-end portion of serviced farms often
experience water shortages during prolonged dry spells
or sometimes even during regular dry season. The
situation entails the use of supplementary water sources
such as on-farm reservoirs or other small-scale irrigation
systems.
Agronomists agree that irrigation support for rice is
necessary if greater productivity is to be desired. However,
the cost involved in establishing, rehabilitiating, and
managing irrigation systems is staggering. PCARRD (2005)
estimated that the cost of just rehabilitating existing
irrigation facilities is about P100,000 to P150,000 per
hectare with an operation cost of P2,000–3,000 per
hectare per year. As most irrigation facilities in the country
service only rice, it may be wise to look into diversification,
specifically into the possibility of providing irrigation to
more high-value crops/commodities. Another option is
the establishment of small-scale irrigation systems, which
cost much less per hectare as compared to national and
communal irrigation systems.
The need to help rice and corn farmers is ever
pressing, especially given problems on seasonal climate
variability. Government programs on input subsidy and
irrigation support serve a very good purpose but
prudence should also be exercised in ensuring the costeffectiveness
and sustainability of any development
intervention. (SCF Project Updates, December 2007)
Evolution of the 2007–2008 La Niña
episode and the climate scenario
In July 2007, signs of an evolving La Niña episode
were already confirmed which later developed into
a full-blown La Niña, albeit a weak one, in September
2007. This then reached its maximum strength in February
2008. By May 2008, though, transition from this cold event
to a neutral condition began to be observed and this
month—June—the La Niña episode is expected to end.
Developments that unfolded
The onset of La Niña toward the last quarter of last year
brought to an end the June–July 2007 dry spell condition
experienced in Regions 1, 2, Cordillera Administrative
Region (CAR), National Capital Region (NCR), and Central
Luzon (see story on the 2007 dry spell in Luzon in the SCF
Project Updates issue of September 2007). With it came a
significant increase in rainfall volume as three tropical
cyclones immediately entered the Philippines’ area of
responsibility (PAR) in August 2007, followed by another
rainy month in September with the coming of another
three cyclones, namely, Falcon, Goring, and Hanna. These
disturbances, especially Hanna which crossed the country,
brought heavy rains, widespread flooding, and landslides
over Western Visayas and some areas of Luzon. This was
the time when the southwest monsoon was active.
As the transition period from the southwest to the
northeast monsoon season took place in October, the
presence of the ridge of high pressure area persisted over
Luzon, signifying generally good weather with below
normal rainfall condition for the area. Unfortunately, for
the other parts of the country like the Visayas and some

56 SCF Folio
areas in southern Mindanao, this was not the case as
they experienced above normal rainfall, bringing in
floods and landslides in certain places. The La Niña
gathered moderate strength and from November to
December 2007, affected the country’s climate through
the enhanced northeast monsoon by bringing in three
tropical cyclones that crossed the country and
thereupon causing widespread rains and landslides in
most areas of Luzon, some areas of the Bicol region, and
southern Mindanao.
La Niña conditions intensified in January 2008 and
as earlier mentioned, reached maximum strength last
February. The cold event enhanced the northeast
monsoon activity which in turn brought massive
flooding and landslides over most areas of the Visayas,
Bicol region, and Mindanao due to the week-long rains.
In Borongan, Eastern Samar, the historical record of
“highest 24-hour rainfall” of 298.5 mm registered on
February 10, 1939 was surpassed, setting a new record
for the country on February 14, 2008 at 371.4 mm. No
tropical cyclones, however, developed or entered the
PAR during the period.
Signs of a weakening of the cold event were
observed by March, after La Niña reached its peak in
February, as manifested by the warming in the eastern
equatorial Pacific Ocean.
In the meantime, the period from mid-March to
June normally represents the warmest months of the
year. The hot condition is usually seen as a precursor to
Table 1. Summary of tropical cyclones in the Philippines,
January–June 2008
Month Tropical Tropical Typhoon Crossed
Depression Storm the Country
January
February
March
April 1 1
May 2 2 1
June 1 1
Total 3 3 3
Source: PAGASA
thunderstorm activity. The northeast monsoon season
came to an end in late March and the transition to the
southwest monsoon season took place in April. By mid-
April, the first tropical storm for 2008—Ambo—entered
the country.
The “official” onset of the rainy season associated
with the southwest monsoon, though, began in the
middle of May 2008, with the passage of tropical storm
Cosme which developed in the South China Sea. Cosme
was not supposed to touch land in the country but its
movement toward an exit to the northwest was blocked
by the presence of the ridge of high pressure area
whose axis extended north of the Philippines toward
Southern China and Thailand. And with the
simultaneous development of typhoon Dindo in the
northeastern section of Luzon, Cosme’s movement was
pulled and propelled by Dindo toward the northeastern
direction. The interaction of these two tropical cyclones
thereupon caused Cosme to make a landfall in western
Pangasinan and to cross the country as it raced toward
northeastern Luzon, causing massive destruction to
properties, agriculture, fisheries, and infrastructures
along the path that it crossed due to its torrential rains
and strong winds. As reported by the National Disaster
Coordinating Council (NDCC), overall damages reached
more than PhP180 million, particularly in Regions 1, 3,
and the Cordillera Administrative Region (CAR).
Two more tropical cyclones entered the country
in May, making a total of four and setting the highest
record of typhoons for the month since 1948. Above
normal rainfall in most parts of the country, especially
over the Visayas and parts of Northern Luzon, was
experienced.
Just recently this month (June), typhoon Frank
wrought havoc to lives, properties, infrastructures,
agriculture, fisheries, and the maritime industry in the
Philippines worth billions of pesos as massive flooding,
flashfloods, landslides, and storm surges took place in
several provinces, especially in Western Visayas, where
they have been declared to be under a state of calamity
even several weeks after the onslaught of the typhoon.
Table 1 summarizes the number of tropical
cyclones that entered the PAR in the first half of 2008
and indicates how many crossed the country.
The La Niña event is seen to come to an end this
June. On the whole, its impact was particularly felt in
the Visayas area and some areas in Mindanao as
manifested by the rainfall conditions during the event.

57
Figure 1. Rainfall outlook, July–August 2008
What to expect in the next two months
For July 2008, the western part of Luzon, except the Ilocos
region, will likely experience below normal rainfall
condition. Ditto with the southern part of Bicol, provinces
of Leyte, Masbate, and northern Cebu. Meanwhile, above
normal rainfall is expected
over Cagayan Valley, as the
rest of the country will
likely receive near normal
rainfall.
The August forecast
seems to veer toward near
normal to below normal
rainfall conditions over
Luzon, including most
parts of Eastern Visayas. For
Central and Western
Visayas as well as most
parts of Mindanao, the
likely scenario will be near
normal rainfall condition.
Western Mindanao,
however, is expected to
have the opposite
condition as above normal
rainfall condition is forecast to prevail there in August.
Figure 1 shows the rainfall outlook for the country
for the months of July and August 2008. (SCF Project
Updates, June 2008)
SCFs in monetary terms: How much
is their worth to farmers
In Isabela: marginal, individually but significant, on the whole
As part of the ACIAR-funded project “Bridging
the gap between seasonal climate forecasts
(SCFs) and decisionmakers in agriculture,” a
simulation study was carried out in selected sites in the
province of Isabela, with the aim of developing an
approach to valuing the contribution of SCFs in
decisionmaking under conditions of climate uncertainty.
The study was conducted in Angadanan and
Echague, the top two corn-producing municipalities of
Isabela province. From the two municipalities, three
barangays were chosen based on their land types—river/
flood plain, broad plain, and hilly/rolling. The agroclimatic
condition, which mainly determines the timing and
number of cropping a rainfed farmer can have in a year, is
dry to moist for Echague and moist for Angadangan. The
traditional corn planting seasons in Echague and
Angadangan are April to June for the wet season cropping
and October to December for the dry season cropping.
Each cropping season lasts approximately 120 days or 4
months.
Historic climatic data (1951–2006) of Tuguegarao, 1
which include daily values of solar radiation (MJ/m2-day),
____________
1
Unfortunately, solar radiation data from Isabela are unavailable.
The nearest weather station, with similar climatic conditions as
Isabela, is in Tuguegarao.

58 SCF Folio
daily maximum and minimum air temperature (C), and
daily rainfall (mm), were collected from PAGASA while
crop management practices of farmers were gathered
using the Decision Support System for Agrotechnology
Transfer (DSSAT) program. The DSSAT program is an
approach developed for the purpose of helping provide
a more precise SCF and simulates outcomes of corn
yield.
Said program allows the simulation of different
corn varieties and cropping systems, targeting issues
such as climate variability, crop rotations, and
management alternatives in generating corn yields. In
terms of corn varieties, the only local hybrid variety
available in the DSSAT program is the Pioneer corn
variety. Thus, even if the survey conducted by the
project team did not actually use such variety, corn
yields for the areas using the DSSAT were simulated
based on this variety for both the wet and dry seasons.
Yields were also simulated under different climate
variability conditions, viz, for El Niño (poor year), La Niña
(good year), and Neutral (neutral year) scenarios. The
amount of rainfall is an important variable that greatly
influences corn production. In view of this, having an
accurate forecast is potentially of value to the farmers
inasmuch as it could help them decide whether to grow
their corn now or to delay it for the next cropping
opportunity. Meanwhile, the simulated long-term corn
yields generated from the DSSAT were then used to
calculate farmers’ income. Income was calculated by
multiplying the simulated corn yield by the price of corn,
a variable gathered from the responses during the
interview process.
For the study, with the use of weather data from
Tuguegarao, corn yield was simulated using DSSAT for
the period 1950 to 2006. The crop parameters used
were within the observed values reported in the survey,
Table 1. Expected gross margin (PhP/ha/season)
of Pioneer corn variety at various climatic
variabilities during wet and dry season
Season/Climate Good Neutral Poor
Wet 31,378 26,903 26,704
Dry 29,067 29,626 28,958
implying that crop growth and development were
simulated realistically. Hence, the simulation provides
confidence that the DSSAT is able to capture the
sensitivity of corn productivity to climate over a long
time series.
To be able to evaluate the monetary value of SCF
information, the expected gross margin of each Pioneer
corn variety was calculated at various climatic
conditions (Table 1). Corn is very susceptible to climate
variations due to the plant’s requirement for water for
cell elongation and its inability to delay vegetative
growth. Therefore, there is always the danger of yield
loss regardless of the timing of planting. The amount of
yield loss that occurs during climate variations depends
on what growth stage the corn is in and how severe
the climate conditions may become. Highest yields will
be obtained only where environmental conditions are
favorable at all stages of growth.
Based on the results, it was found that during the
wet season, the good years (La Niña) yielded
PhP31,378/ha on average; more than the yield for
neutral years at PhP26,903/ha. On the other hand, the
neutral years yielded more (PhP29,626/ha) than the
good years (PhP29,067/ha) during the dry season.
Hence, the Pioneer variety is estimated to have higher
gross margin during the dry season across different
climatic variabilities.
The value of SCF information can be computed as
the difference between the gross margins of those with
and without SCF scenarios. Chances of farmers who
were not using SCF to attain higher gross margin might
be lower than those who were using the forecast. Such
value difference calculated was found to be PhP221/
ha/season. While this figure could be considered very
marginal for the individual subsistence farmers whose
landholdings average only about 3.56 hectares,
translating this amount to the total land area planted
to corn in the Philippines (2.6 million hectares as of
2007) would, however, redound to a substantial amount
and thereupon be of great significance for Philippine
agriculture. Because of this, it would be of critical
importance for decisionmakers/policymakers in
agriculture to greatly improve the access of farmers to
SCF information as well as to make such information
affordable and efficiently available to corn farmers.

59
In Cebu: use of SCF gives higher income to corn farmers
Recently, a survey conducted by the Visayas State
University in connection with the ACIAR-funded
project “Bridging the gap between seasonal
climate forecasts (SCFs) and decisionmakers in agriculture”
shows that almost all of the SCF-user respondents
considered climate in their production decisions. In fact,
they considered SCF as having a medium to high
significance in terms of value or contribution to their
farming enterprise. The main reason cited by farmers is
that climate plays a major role in corn production.
The study also indicates that both users and
nonusers of SCF received adequate information about
weather/climate. However, a higher proportion of SCFuser
respondents reported receiving more accurate
information about climate.
Using SCF innovation in corn production has indeed
provided monetary benefits to corn farmers in Cebu. The
study shows that the mean gross margin during the first
season for SCF users was about PhP4,290/ha. This is
comparatively higher than the mean gross margin of
nonusers of SCF (PhP3,080/ha). Computed as the
difference of gross margin between users and nonusers
of SCF, the economic value of using SCF was found to be
PhP1,210/ha. For the second cropping, the mean gross
margin obtained by SCF users was about PhP7,867/ha
while nonusers of SCF realized only PhP3,080/ha, which
indicates that the economic value of using SCF in corn
production decision is about PhP4,787/ha. Findings of this
study imply that there is economic incentive for farmers
to use farming innovation such as SCF in corn production.
(SCF Project Updates, June 2008)
The challenge of using seasonal climate
forecasts for decisionmaking:
proposed frameworks
Seasonal climate forecasting based on the
interaction of the ocean and atmosphere has
been regarded by experts as one of the premier
advances in the field of atmospheric sciences in the 20 th
century; yet its use in decisionmaking is greatly hampered
by communication and application issues.
In their paper titled “Frameworks for using seasonal
climate forecasts for decisionmaking,” Peter Hayman,
Kevin Parton, Bronya Alexander, and Canesio Predo 1
explored some ideas on how information on probabilistic
forecasts can be used in agricultural decisionmaking.
____________
1
Principal Scientist, South Australian Research and Development
Institute (SARDI); Professor of Economics, Charles Sturt University;
Project Officer, SARDI; and Assistant Professor, Visayas State
University, respectively.
The authors recognized that majority of users find it
difficult to comprehend and use forecasts when they are
presented as probabilities. Many people, when faced with
uncertainty, rely on mental shortcuts which sometimes
lead to biases that impair the decisionmaking process.
An accurate categorical forecast that fits the logic of
IF, THEN, ELSE has been the more appreciated format by
decisionmakers. An example of this reasoning is, ‘IF the
season ahead is going to be a drought, THEN reduce
inputs, ELSE continue as normal.’
It is common for intermediaries such as agronomists
to state that farmers need a categorical forecast because
in the end, they need to make a decision. The media is
also more inclined to sending out categorical statements.
Forecasts for El Niño or La Niña episodes, for instance, are
respectively simplified to forecasts for drought or

60 SCF Folio
...The notion that probabilistic forecasts cannot be used in
decisionmaking is not true. Notwithstanding difficulties in
communication, a forecast should be presented as a
probability because it is the honest way of doing it...The
challenge is how to communicate and use in decisionmaking
skillful but uncertain forecasts that are best represented as
shifts in climatological probability distributions.
excessive rains rather than to a more qualified
statement of increased chances of the events occurring.
Implied in these inclinations is the notion that
probabilistic forecasts cannot be used in
decisionmaking. This notion, however, needs to be
corrected because it is not true. Notwithstanding
difficulties in communication, a forecast should be
presented as a probability because it is the honest way
of doing it. As an expert puts it, the atmosphere is a
complex chaotic fluid, and although patterns of ocean
temperatures ‘nudge’ this chaos in certain directions,
there will always be a significant proportion of
unexplained variation. Hence, the challenge is how to
communicate and use in decisionmaking skillful but
uncertain forecasts that are best represented as shifts
in climatological probability distributions.
Probabilistic forecasts also ensure that risk
management is not hindered. A farmer who
misunderstands SCF as a categorical forecast may be
led to devise poorer risk management strategies
compared to a situation where he did not hear of the
Figure 1. Decision tree analysis showing gross margins for different fertilizer rates and season
types, and probability weighted value for each of the three fertilizer rates
forecast at all. A crop grower may plan for a wide range
of outcomes in the absence of a forecast. But if only
one outcome is in his mind, then the planning exercise
will definitely be narrower.
An imposing challenge therefore is how to use
uncertain information for decisionmaking. The use of
decision analysis was mentioned as an approach that
provides a logical framework for a decisionmaker to
formulate preferences, assess uncertainty, and make
judgments. There has been a tradition in agricultural
science to talk the language of choice-consequence.
For example, if you put on x units of nitrogen, you will
get a yield of y. A more forward-looking language is that
of choice-chance-consequences. This means that if
you put on x units of nitrogen, depending on the season
type, you will get a yield of either y 1
, y 2
, or y 3
.
A good example (Figure 1) is the use of decision
tree analysis in determining the level of fertilizer inputs
given uncertain forecasts. Decision tree analysis is a
technique to aid decisionmakers in identifying the
outcomes for each decision alternative. It involves
assessing the probabilities associated with each
outcome, assigning payoffs, and keeping the sequence
of outcomes and decisions in the proper chronological
order. Because the decision tree reflects choices,
probabilities, and consequences, it thereupon
effectively illustrates how uncertain forecasts might be
used to change fertilizer decisions.
The figure shows how forecasts can influence the
decision of N fertilizer rates application. For instance,
during the season with a
poor, average, and good
outcome, about 20, 60, and
100 units, respectively, of N
fertilizer will be applied.
Given this information and
knowing the expected
season from the seasonal
climate forecast, the farmer
can therefore decide on the
level of fertilizer application.
Results from the figure
show that if the forecast is
neutral, the farmer is better
off when he will apply 100
units than 20 units and even
60 units of N fertilizer.
However, if he will apply 100

61
units of N fertilizer based on good outcome season but
the actual season turns out to be poor, the farmer will
incur a loss or negative gross margin. Similarly, if he is
expecting a poor season outcome by applying 20 units
of N fertilizer but a good season has actually occurred,
then he has missed the opportunity for a bigger gross margin.
In the paper, the authors also present a fresher and
more fun way of looking at decision analysis through
‘Wonder Bean,’ an innovative game about choosing the
right crop to plant given SCF and seasonal climate
variability. The game features spinning probability disks
in a simple Excel®-based spreadsheet where participants
decide on the area of a farm to plant to a higher-return
but higher-risk crop vis-à-vis the area to leave to a lowerreturn
but lower-risk crop.
Although the enumerated applications with
spinning probability disks, decision trees and crop choice
games are not intended for regular decision support
systems, they are nonetheless useful in organizing ideas
and engaging decisionmakers. A step toward bridging the
gap between climate science and decisionmaking, no
matter how small, is after all a step toward better
managing the risks from seasonal climate variability. (SCF
Project Updates, September 2008)
Choosing risk-efficient planting schedules
for corn: the Matalom, Leyte case
One of the most important decisions affecting crop
production in rainfed areas is the timing of
planting. A farmer may select a planting schedule
in such a way that the cropping period would be less risky,
avoiding or minimizing the impact of projected
destructive seasonal climatic events within the growing
season. This is now made more possible with recent
developments in atmospheric science, particularly on
seasonal climate forecasting (SCF).
Remberto Patindol, Canesio Predo, and Rosalina de
Guzman 1 explored this possibility of shifting cropping
schedules from traditional dates to fit forecast seasonal
climatic events in a rainfed area in Matalom, Leyte,
Philippines. In a study titled “Risk-efficient planting
schedules for corn in Matalom, Leyte,” they looked into
historical weather data and information about past
occurrences of the different El Niño Southern Oscillation
(ENSO) phases to see if these can be used in selecting the
best cropping schedules.
Local farmers usually follow traditional planting
schedules under the assumption that the conditions
____________
1
Associate Professor and Assistant Professor at the Visayas State
University, and Assistant Head, Climate Information, Monitoring, and
Prediction Services Center of the Philippine Atmospheric,
Geophysical, and Astronomical Services Administration (PAGASA),
respectively.
during a particular planting period are repeated over the
years. Thus, it would not be uncommon to observe farmers
in a given locality, for example, to plant corn in the first
week of May and repeat this schedule over the years. This
practice, however, makes local farming prone to damages
because farmers usually do not use SCF and account for
seasonal climate variability especially during El Niño and
La Niña events.
The authors thus identified risk-efficient planting
schedules for corn using stochastic dominance analysis
of simulated yields given ENSO forecasts for different
cropping periods. The method requires the use of
probability distributions of corn yields for different
planting schedules. Given the absence of historical data
and lack of time for conducting multiyear experiments,
corn yields for the different planting scenarios were
generated through the use of a simulation modelling
software. The model utilized actual and synthetic data to
reflect the variability associated with the different ENSO
phases.
Inputs in the yield simulation modelling included
actual and generated weather data from the nearest

62 SCF Folio
Table 1. Summary of the simulated yields (kg/ha)
for the most preferred planting schedules
during the first season
Schedule Rank Mean Standard Minimum
Deviation
La Niña
June, week 3 1 2,591.29 133.27 2,419.00
June, week 1 2 2,510.14 113.07 2,377.00
April, week 4 3 2,476.67 78.56 2,371.00
June, week 4 4 2,500.00 143.18 2,347.00
June, week 2 5 2,528.57 135.76 2,286.00
El Niño
June, week 1 1 2,510.22 109.44 2,372.00
June, week 2 2 2,490.78 151.16 2,052.00
May, week 3 3 2,404.60 95.09 2,264.00
June, week 4 4 2,411.00 113.70 2,221.00
July, week 3 5 2,416.45 158.50 2,084.00
Neutral
July, week 1 1 2,418.73 145.71 2,141.00
July, week 2 2 2,468.87 159.31 2,087.00
July, week 3 3 2,417.80 152.50 2,081.00
May, week 3 4 2,378.94 147.06 2,152.00
June, week 3 5 2,397.11 184.20 2,093.00
All Years
May, week 3 1 2,412.88 135.53 2,152.00
July, week 3 2 2,416.68 141.33 2,081.00
June, week 3 3 2,455.71 191.45 2,066.00
June, week 4 4 2,414.85 163.40 2,050.00
May, week 4 5 2,403.53 158.53 2,066.00
Table 2. Summary of the simulated yields (kg/ha)
for the most preferred planting schedules
during the second season
Schedule Rank Mean Standard Minimum
Deviation
La Niña
December, week 4 1 2,540.11 198.21 2,290.00
December, week 1 2 2,527.78 173.09 2,204.00
December, week 2 3 2,466.11 151.57 2,244.00
December, week 3 4 2,443.33 167.73 2,246.00
August, week 1 5 2,400.90 125.48 2,179.00
El Niño
December, week 1 1 2,602.82 178.54 2,351.00
September, week 2 2 2,413.30 74.83 2,308.00
September, week 3 3 2,452.80 125.61 2,229.00
December, week 2 4 2,547.55 228.52 2,192.00
December, week 4 5 2,451.82 169.58 2,171.00
Neutral
December, week 1 1 2,518.14 153.80 2,253.00
September, week 1 2 2,370.71 90.14 2,237.00
December, week 2 3 2,502.36 208.62 2,133.00
August, week 4 4 2,374.23 134.37 2,211.00
October, week 3 5 2,377.54 153.52 2,141.00
All Years
December, week 1 1 2,548.09 166.53 2,204.00
December, week 2 2 2,507.38 198.87 2,133.00
December, week 4 3 2,500.85 223.84 2,099.00
December, week 3 4 2,449.21 185.02 2,056.00
August, week 3 5 2,339.91 152.89 2,102.00
weather station, soil characteristics of the site, cropspecific
parameters, and common cultural practices in
corn production. The method of stochastic dominance
analysis was then applied on the probability
distributions of the simulated yields using two criteria:
first-degree stochastic dominance and stochastic
dominance with respect to a function, with three levels
of risk aversion.
The process led to the identification of riskefficient
strategies for each stochastic dominance
criterion and the most preferred schedule within each
season, given the ENSO episode during the cropping
period. These schedules could be used as guide by
farmers in the site if PAGASA could provide a forecast
about the ENSO episode in the next cropping period.
Likewise, the study was able to identify the risk-efficient
and most preferred schedules within every season
without considering the ENSO episode during the
cropping period. The schedules identified in this
manner can be used by the farmers in the site if no
forecast is available (represented as All Years in Tables 1
and 2).
The study successfully demonstrated in principle
that stochastic dominance analysis can be applied to
identify risk-efficient schedules under the different
ENSO episodes using probability distributions of
simulated yields. It also showed that stochastic
dominance analysis is sensitive in the sense that it can
still provide a ranking of the strategies even with
relatively small differences in the mean values. This
implies that the method could be a good alternative
when comparing outcomes of different strategies.
The ultimate question would be on how to make
the outputs of the study relevant to local farmers.
Considering that the actual schedules followed by
farmers in the site differed from the risk-efficient
schedules identified in the study, the authors expressed
the need for a more detailed enquiry. For one, the
research did not incorporate all factors that may have
some influence in a farmer’s choice of planting
schedule. In the absence of relevant explanations for
farmers’ actual choices, dissemination of information
pertaining to risk-efficient planting schedules was
thereupon advised. (SCF Project Updates, September 2008)

63
Determining corn farmers’ decisions
based on SCFs
Gian Carlo M. Borines, Rotacio S. Gravoso,
Canesio D. Predo *
The advent of the anomalous weather and climate
conditions aggravated by global warming has
underscored the need to disseminate climate
information to guide farmers in their farm decisions.
Advance climate information, like the seasonal climate
forecast (SCF), helps farmers decide which land to use for
a particular crop, chart out production schedules, and
devise commercialization strategies—decisions that are
normally made by farmers long before the sowing season
starts. Experiences from other countries show that the risk
of production losses due to anomalous climatic conditions
can be mitigated if farmers are aware of and use SCF.
In the Philippines, the project, “Bridging the gap
between seasonal climate forecasts and decisionmakers
in agriculture,” funded by the Australian Centre for
International Agricultural Research (ACIAR), has shown the
possibility for farmers to improve their income if they use
SCF. Thus, the project intends to actively disseminate and
encourage farmers to incorporate SCF into their farming
practices.
Central to the use and application of climate
information is the decisionmaking by farmers. Based on
existing literature, in dealing with uncertain climate
information, farmers engage themselves in descriptionand
experience-based modes of decisionmaking,
thereupon increasing the risks of possible losses. This
study was therefore conducted to find out how farmers
will decide if they are presented with probabilistic climate
forecasts.
Methods
This study was conducted in Brgy. Miglamin, Brgy. Laguitas,
and Brgy. Magsaysay in Malaybalay City, Bukidnon
Province in consultation with the Department of
Agriculture in Malaybalay City.
____________
*
Staff and faculty, Visayas State University.
A focus group discussion (FGD) was conducted to
gather the background on the farmers’ exposure, access
and use of SCF. To find out about the farmers’
decisionmaking based on uncertain information, two
decisionmaking workshops were conducted. In each
workshop, farmer participants were made to assume five
varying hypothetic assumptions wherein they have
experienced unfavorable cropping seasons in the past
three consecutive years (March–June, 2005–2007). The
participants were then presented with a climate forecast
(in video) developed specifically for this study (Table 1).
Subsequently, farmers were asked to make decisions or
courses of action for the next cropping season based on
the forecast (Table 2). A total of 30 farmers participated in
the two workshops.
Highlights of results
Exposure and access to SCF information
Data showed that farmers in this study were aware of SCFs
and climate information. Farmers, especially those who
are planting in big areas of land or are producing crops
on a large scale, pay visits to the PAGASA station in
Malaybalay or the Department of Agriculture (DA) office
to consult on what the climate would be like before they
begin to plant and what crops would be best to plant.
Information obtained from these consultations is used to
schedule the time of planting and to decide on which
crop to plant.
Not all farmers in Malaybalay, however, are able to
go to the city proper to inquire about the climatic
conditions. Thus, PAGASA and the DA hold seminars and
fora about the climate in areas surrounding the province.
Likewise, staff from the PAGASA station are invited
occasionally to air climate forecasts and issues over the
local radio station.
Evaluation of SCF information
Farmers reported that they get climate forecasts from the
radio or television through the national stations. In
general, they felt that climate forecasts are helpful.
However, to be more useful, they suggested some
changes. These suggestions include: 1) avoid the use of

64 SCF Folio
Table 1. Forecasts given to farmers
Hypothetic Assumption and Forecast
Wet season for March–June, 2005–07;
forecast with dry season for March-June 2008
Dry season for March–June, 2005–07;
forecast with dry season for March–June 2008
Wet season for March–June, 2005–07;
forecast with wet season for March–June 2008
Average season for March–June, 2005–07;
forecast with dry season for March–June 2008
Average season for March–June 2005–07;
forecast with La Niña for March–June 2008
Detailed Description of Event
Farmers were told to assume that hypothetically, they experienced a
rainy season for the last cropping season for three consecutive years.
They were then given a dry season forecast for the incoming cropping
season. Farmers were then allowed to make decisions for their farms,
bearing the knowledge that forecasts are not always 100 percent
accurate.
Farmers were told to assume that hypothetically, they experienced
drought for the last cropping season for three consecutive years. They
were then given a dry season forecast for the incoming cropping
season. Farmers are then allowed to make decisions for their farms,
bearing the knowledge that forecasts are not always 100 percent
accurate.
Farmers were told to assume that hypothetically, they experienced a
rainy season for the last cropping season for three consecutive years.
They were then given another wet season forecast for the incoming
cropping season. Farmers are then allowed to make decisions for their
farms, bearing the knowledge that forecasts are not always 100
percent accurate.
Farmers were told to assume that hypothetically, they experienced
normal amount of rainfall for the last cropping season for three
consecutive years. They were then given a dry season forecast for the
incoming cropping season. Farmers are then allowed to make
decisions for their farms, bearing the knowledge that forecasts are not
always 100 percent accurate.
Farmers were told to assume that hypothetically, they experienced
normal amount of rainfall for the last cropping season for three
consecutive years. They were then given a La Niña forecast for the
incoming cropping season. Farmers are then allowed to make
decisions for their farms, bearing the knowledge that forecasts are not
always 100 percent accurate.
scientific terms, 2) downscale the forecast to their
locality, and 3) forecasters should “tell the truth.” The
third suggestion emanated from their experience of a
forecast of an unsuitable cropping season that did not
come true. This resulted in an opportunity missed for
the farmers to plant their crops. For farmers like them
who rely on their ability to produce crops for sustenance
of their households, missing an opportunity to plant
crops may result in their inability to feed their respective
families.
The farmers also said that they use SCF in deciding
farm activities. However, some of them likewise said that
they just predict the climate by themselves and do not
rely on SCFs provided by PAGASA. “Mo tan-aw tan-aw
na lang ko og sakto ba kaha ipamugas ang panahon,
ug sakto unya mo pugas pud ako mga silingan, aw mo
pugas pud ko” (I just observe the climate, if my
neighbors sow, I also sow), a farmer reported. Farmers
also said that if they feel that a forecast will not
materialize, they just ignore it, “Mo sugal na lang mi”
(To some extent, we just gamble). By this statement,
farmers mean that they are prepared to face the
possibility of a cropping failure due to planting in an
unfavorable climate condition.
Farmers in Malaybalay had a hard time trying to
understand the complex terms used in climate forecasts
such as monsoons, intertropical convergence zone
(ITCZ) and low- pressure areas. Because of this, farmers
are unable to completely comprehend the information.
Farmers’ decisions based on probabilistic
climate forecasts
For the various forecasts given them during the
decisionmaking workshops, the following decisions
came out (refer also to Table 2):
Wet cropping season experience and dry forecast.
For this situation, farmers said that they would cultivate
only a small portion of their land to minimize cost for
the labor of land preparation. They also said that if the
dry season comes, they would plant crops resistant to
drought (i.e., sugarcane, cassava, banana, and other
similar crops) or short-season crops like sweet potato,

65
Table 2. Farmers’ responses to SCFs
Experiential Data Analytical Data Farmers’ Decisions
(Hypothetic Assumption) (Climate Forecast)
Wet cropping season for Dry season Prepare a small portion of their land to minimize spending. If the dry
three years
season comes, plant crops which are resistant to drought or shortseason
crops. Plant in small quantities to avoid too much input for an
expected below-average output.
Dry cropping season Dry season Find other means of earning income. Practise backyard gardening to
for three years
have an immediate source of food for their family. Raise farm
animals such as chickens, goats, cows, and pigs to have alternative
sources of income. Look for work in Malaybalay. Switch from corn to
more drought-tolerant crops (high risk option).
Wet cropping season Wet season Still plant corn, and plant other crops in the periphery to earn
for three years
additional income. There would be very little (or no) changes in their
farming practices because of the rainy climate for the cropping
season.
Average cropping season Dry season Prepare a small portion of their land. Farmers and their families will
for three years
cultivate their land to minimize cost in land preparation. If the dry
season comes, plant crops which are resistant to drought. Plant in
small quantities.
Average cropping season La Niña Plant crops that grow even with too much water or use corn varieties
for three years
that thrive under a wet climate condition.
mongo, soybeans, cowpeas, and other leguminous plants
so that before the dry season comes, they would have
had finished harvesting. They added that they would leave
the silage of their crops to fertilize the land. They
maintained that they would plant in small quantities to
minimize production cost for what they expect to be a
low yield due to the dry climate.
Dry cropping season experience and dry forecast.
Under this situation, the decisions made by the
respondents were more for sustaining their households
and not for income. They reasoned that by the fourth year
of a drought, they would have run out of savings for their
families. Participants said that they would find alternative
livelihood or other means of earning an income. One of
the alternative sources of income they mentioned was to
work as hired laborers in sugarcane plantations. They
claimed that sugarcane is a drought-resistant crop; hence,
sugarcane plantations will continue to operate even
during drought.
Some farmers said that they would find other work
in Malaybalay. Other farmers said that they would practice
handicraft making as an alternative source of income. As
an immediate source of food, participants said that they
would venture into backyard gardening. They claimed
that it is easier to maintain crops when grown in small
numbers. For these backyard gardens, they would use
their used water at home to water their crops. Farmers
said that they would also raise farm animals like chicken,
goats, pigs, and cows for additional income.
Wet cropping season experience and wet forecast.
For this situation, participants said that they would still
plant corn but will use the native or the “bisaya” variety.
They claimed that the native variety is cheaper and grows
well both in wet and dry seasons compared to the hybrid
varieties. Other than corn, they would also plant other
crops in the sides of their farm as a source of additional
income.
Average cropping season experience and dry
forecast. Farmers’ decisions in this situation are similar to
the decisions they have made in the wet forecast. Farmers
said that they would cultivate corn in a small portion of
their land. According to them, they will not hire laborers
to cultivate their land. Instead, their family members will
help, from land preparation to planting until harvesting.
If the dry season comes, a small number of farmers said
that they would plant crops that are resistant to drought
such as banana, sugarcane, rubber, and cassava. They
maintained that they would be planting in smaller
quantities.
Average season experience and La Niña forecast. For
this situation, farmers were asked to assume that they
have experienced an average climate for the cropping
season for three consecutive years in the past and were
then given a La Niña forecast for the present cropping

66 SCF Folio
season. In response,
farmers said that they
would plant crops that are
water-tolerant or use corn
varieties that thrive even
under wet conditions.
However, farmers in
Bukidnon rarely cultivate
rice because according to
them, the area is not
suitable for rice
production. Farmers stated
that even with a La Niña
forecast, they need to plant
crops or else they will have
nothing to spend for the
education of their children
and for their day-to-day
sustenance.
Implications
Despite the popularity of
SCFs among farmers in Malaybalay, the value of this
information is not maximized because farmers just
ignore them. According to them, they have several
experiences where forecasts did not materialize. There
is, therefore, a need to implement an intensive
educational campaign to explain to farmers about the
probabilistic nature of the SCF and to teach them on
how to make use of these forecasts wisely.
This study found that farmers apply indigenous
climate forecasting in their farming practices. For
example, to decide when to sow, they observe what
they call “planting by the moon,” that is, they sow during
full moon. According to them, a full moon ensures them
of a good harvest. While, according to farmers, there is
no scientific explanation for this practice that they know
of as yet, they have nonetheless observed that “planting
by the moon” has been bringing them good harvests
and profits. Considering this finding, it is suggested that
agencies mandated to provide climate advisory to
farmers should look for ways to integrate farmers’
indigenous forecasting system in their efforts to
encourage farmers to use seasonal climate forecasts.
Despite the popularity of SCF in Malaybalay, farmers often ignore these information because
according to them, the forecast did not come true. In this photo, farmers watch an SCF in
video during a decisionmaking workshop. They will plan their farming activities for the next
season based on the forecasts.
Judging from the outputs generated during the
decisionmaking workshops, farmers’ coping
mechanisms for extreme climate will enable them to
earn income that will sustain their respective families’
needs. The problem, however, is that in extremely
unfavorable cropping conditions, their only choice is to
work as menial laborers in factories, department stores,
and other industries in Malaybalay City. Since climate
change is inevitable, research and development
agencies are called on to start technology development
works that will help farmers mitigate the impacts of or
make farmers adapt to the climate change.
Finally, findings in this study showing that farmers
find it hard to appreciate and understand climate
forecasts suggest the need for academic institutions to
integrate climate reporting in their curricular programs.
To date, contents of communication programs usually
relegate this topic to the background. Hence, this is one
area that may be seriously considered to help in the
communication and understanding of seasonal climate
forecasts and their probabilistic nature. (SCF Project
Updates, December 2008)

67
Project Team
Australia
Dr. Peter Hayman
South Australian Research and Development Institute
Prof. Kevin Parton
Charles Sturt University
Dr. John Mullen
New South Wales Department of Primary Industries
Mr. Jason Crean
New South Wales Department of Primary Industries
Ms. Bronya Alexander
South Australian Research and Development Institute
Philippines
Philippine Institute for Development Studies
Dr. Celia M. Reyes
Ms. Jennifer P. T. Liguton
Mr. Sonny N. Domingo
Mr. Christian D. Mina
Ms. Kathrina G. Gonzales
Visayas State University
Dr. Canesio D. Predo
National Abaca Research Center /
Department of Economics
Dr. Rotacio S. Gravoso
Department of Development Communication
Dr. Remberto A. Patindol
College of Arts and Sciences
Ms. Eva L. Monte
National Abaca Research Center
Philippine Atmospheric, Geophysical and Astronomical
Services Administration
Dr. Flaviana D. Hilario
Climatology and Agrometeorology Division
Ms. Edna L. Juanillo
Climatology and Agrometeorology Division
Ms. Rosalina G. De Guzman
Climatology and Agrometeorology Division
Ms. Daisy F. Ortega
Climate Information Monitoring and Prediction Services Center
Philippine Rice Research Institute
Dr. Eduardo Jimmy P. Quilang
Agronomy and Soils Division
Dr. Constancio Asis, Jr.
Agronomy and Soils Division
Ms. Rowena G. Manalili
Socioeconomic Division
Mr. Jovino De Dios
Agronomy and Soils Division
Ms. Guadalupe Redondo
Socioeconomic Division
Mr. Roy F. Tabalno
Socioeconomic Division
Sources
SCF Project Updates (various issues beginning June 2005 up to
December 2008). This is the official newsletter of the SCF
project. It started as a newsletter published on a semestral
basis but beginning 2007, it appeared on a quarterly basis.
Economic Issue of the Day (various issues). This explains
concepts related to economic matters and relates the concepts
to everyday activities and how they may apply to daily lives.
Design and layout by
Jane C. Alcantara

68 SCF Folio
Bridging the gap between seasonal
climate forecasts and decisionmakers
in agriculture
Implementing
Agencies
A project funded by
Australian Government
Australian Centre for International
Agricultural Research