World Meteorological Organization Symposium on Nowcasting - WMO

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2.8
A Proposed Strategy for the Environment Canada Nowcasting Program
Stewart G. Cober
Cloud Physics and Severe Weather Research Section, Environment Canada
In March 2003, the <strong>Meteorological</strong> Service of Canada initiated a five-year restructuring
program in order to modernize the observation networks and to establish a sustainable
organization. The transition program included the consolidation of forecasting operations into
five major centres in order to produce a more efficient and effective forecasting program. It
was also supposed to allow greater emphasis on the provision of specialized weather
information to weather-sensitive communities, including the agriculture, aviation, forestry,
marine, transportation and tourism communities. The role of the human operational forecaster
was expected to be increasingly focused on short-term forecasts of high impact and severe
weather while longer term weather forecasting was expected to be largely automated through
the application of numerical weather prediction forecast models. A white paper developed in
2008 for the <strong>Meteorological</strong> Service of Canada reiterated these goals, while also advocating
the evolution of the forecaster role towards greater emphasis on contributing to the decision
making processes for clients. The Environment Canada research program was tasked with
developing a comprehensive research and development strategy for nowcasting that would
support the achievement of the goals listed above.
During the development of a research and development strategy for nowcasting, numerous
implicit definitions, assumptions and questions were identified that needed to be defined,
challenged and answered respectively. For example, what is the definition of nowcasting?
What does automated mean with respect to human oversight? What can and cannot be
automated? Are NWP models capable of providing fully automated output products at 12
hours, day 1, day 3, etc.? Can forecasters provide decision support for clients without having
undertaken analysis, diagnosis and prognosis? Is the role of the operational forecaster
changing with respect to the provision of watches and warnings and short term forecasts of
high impact weather? What is the difference between severe weather and high impact
weather? Can consensus within the department be achieved with respect to the resolution of
these ideas?
A nowcasting strategy is much broader than the research and development program alone
because it will impact on the entire prediction program. Consequently a nowcasting research
strategy includes the requirement for significant coordination, cooperation and collaboration
between monitoring, research, development, implementation, prediction-operations,
performance measurement, informatics technology, client services and the clients. The
nowcasting component must be seamlessly integrated into the overall prediction program.
There must be an effective and rapid technology transfer system that allows advances in
monitoring, research or development to impact on the prediction program and the clients.
The preliminary results of this exercise include recommendations on the following:
parameterized physical processes suggests that the subtle balance between the various
processes is achieved. This study also shows that the fog evolution depends on the turbulent
exchange coefficients, the single scatter albedo of cloud droplets, the condition of cloud
droplet activation, and the sedimentation velocity.
P1.10
Fine-Scale Road Stretch Forecasting
Alexander Mahura, Claus Petersen, Bent Sass, Kai Sattler
Danish <strong>Meteorological</strong> Institute (DMI), Research Department
The DMI has in collaboration with the Danish Road Directorate (DRD) for almost two decades
used a Road Condition Model (RCM) system (based on a dense road observations network
and the numerical weather prediction model - HIgh Resolution Limited Area Model, HIRLAM)
to provide operational forecasts of main road conditions at selected road stations of the
Danish road network. Presently there are about 350 road stations (equipped in total with
more than 400 sensors), where measurements and forecasts of road surface temperature, air
and dew point temperatures are provided for the end users. Forecasts of other important
meteorological parameters such as cloud cover and precipitations as well as radar and
satellite images are also distributed to the users through the web-based interface vejvejr.dk
and through DMI and DRD web-pages. For icing conditions, new technology has made it
easy to vary the dose of spreaded salt, making it possible to use salt only on the parts of the
road network where it is really needed. Measurements of road surface temperature from road
stations and salt spreaders have additionally been used to examine both road stations and
road stretches (among 17000 points along the Danish road network) forecasts. These results
have underlined critical importance of detailed characteristics of road stretches themselves as
well as their surroundings. In other words: if you want to make local forecasts in a specific
point you need all possible local information. Until now the description of the physiographic
conditions in the used RCM system is at a relatively low resolution. Since the high resolution
models running at faster supercomputers as well as detailed physiographic datasets now are
available, it provides possibility to improve the modelling and parameterization of significant
physical processes influencing the formation of the slippery road conditions and their
operational forecasting. First of all, it is based on a new dataset available from Kort og
Matrikel styrelsen, the so-called Danish Height Model (Danmarks Højdemodel) which now
allows access to details of the topography with a precision and high resolution much better
than in previous datasets, and to take into account the shadowing effects when forecasting
the road surface temperature. The main aim of this study is to research, develop, and
improve the quality of the road condition forecasts by refining, setting up, and running the
fine-scale resolution numerical weather prediction model with integration (from high resolution
databases) of characteristics and derived parameters of land-use, terrain, positioning and
road properties at road stations/ stretches. The main objectives include: (1) Research and
development of the existing RCM based on input from a fine-scale numerical weather
prediction modelling; (2) Analysis and integration of detailed data and derived parameters at
road stations/stretches into the RCM based on available detailed Danish datasets on terrain,
GPS positioning, land-use, and road properties; and (3) Elaboration, testing, evaluation, and
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