The tenth IMSC, Beijing, China, 2007 - International Meetings on ...

homogeneity principle is used to remove the unknown climate change signal since we have no
information about the shape of this signal. This means that the climate data series are
compared mutually in order to detect the inhomogeneities and to correct the series. <strong>The</strong>
possible errors are type one error i.e. detection of false inhomogeneity and type two error i.e.
neglecting real inhomogeneity. <strong>The</strong> significance and the power of the procedures can be
defined according to the probabilities of these errors.
<strong>The</strong> methodology of comparison of series is related to the questions as reference series
creation, difference series constitution, multiple comparison of series etc. This topic is very
important for detection as well as for correction, because the efficient comparison of series can
increase both the significance and the power. <strong>The</strong> development of efficient methods can be
based on the examination of the spatial covariance structure of climate data series.
<strong>The</strong> next question is the methodology for multiple break points (changepoint) detection.
One of the possibilities is to use penalized likelihood methods based on the Bayesien model
selection. Different criteria, penalty terms (e.g. AIC, BIC) may be applied according to the
assumed a priori probabilities. However the significance level of these methods is
questionable. Another possibility is to use hypothesis test methods for this purpose. At the
MASH a hypothesis test procedure has been developed, as we want to avoid the type one
error that is the damage of data series.
<strong>The</strong> third question is the methodology for correction of series. Almost all the methods use
the maximum likelihood estimation for the correction factors at the detected break points. <strong>The</strong>
MASH procedure is an exception because the correction factors are estimated on the basis of
confidence intervals.
Summarily, the philosophy of MASH is as follows: cautious break points detection and
correction in order to decrease the probability of type one error, but using optimal series
comparison for decreasing the probability of type two error that is increasing the power.
References
Szentimrey, T., 1999: Multiple Analysis of Series for Homogenization (MASH)
Trend Analysis of Extreme Climatic Indices in Iran using Extreme Climate Index Software
(ECIS)
Speaker: Farahnaz Taghavi
Farahnaz Taghavi
Institute of Geophysics, University of Tehran , Tehran, IRAN
ftaghavi@ut.ac.ir
In recent years, extreme events (droughts, floods, heat waves) and climate –related
hazards take the heaviest toll on human life and exert high damage costs in Iran. In this study,
the behavior and the frequency of extreme events are investigated using extreme climate
index software (ECIS).<strong>The</strong> ECIS is a code under MATLAB includes several subroutines, such
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