Agne Burauskaite-Harju, Division of Statistics,
Department of Computer and Information Science
Linköpings Universitet

Trends in Precipitation Extremes

Abstract It is generally believed that global warming is accompanied
by extreme weather events. Assessments of trends in intensity and
frequency of extreme rainfall events are of considerable practical
importance and have been presented in numerous
publications. Nevertheless, we believe there are aspects that have not
previously received enough of attention.

In the seminar I will present a procedure for trend testing in
precipitation extremes for entire network of meteorological
stations. In our developed procedure we first make separate estimates
of tail probabilities of precipitation amounts for each combination of
station and year by fitting a Generalized Pareto Distribution (GPD) to
data above a user-defined threshold. Then, the resulting time series
of annual percentile estimates are fed into a multivariate
Mann-Kendall (MK) test for monotonic trends. Extensive simulations
involving artificially generated precipitation data showed that the
power of tests for temporal trends was substantially enhanced when
ordinary percentiles were substituted for
GPD-percentiles. Furthermore, we found that: the trend detection was
robust to misspecification of the extreme-value distribution. The MK
test has the advantage that it can accommodate nonlinear trends and
takes into account the dependencies between stations in a network.

Further in the seminar I will highlight the importance of data
resolution choice.  We demonstrate that trends in rainfall intensity
can differ in direction and significance for choice of resolution
(duration) and quantile. We also show that sub-daily rainfall data can
contain important information about climate change that cannot be
detected in daily data. We suggest that trend tests be performed for
different resolutions and quantiles, and that the results be presented
as  tables that allow further interpretation (analogous to
intensity-duration-frequency tables used in hydrology).

To illustrate methods simulated, observational and regional climate
model output data will be used. A short overview of meteorological
variables, of global and regional climate modeling, climate change and
future greenhouse gas emission scenarios will be given to help
understanding properties of data sets and potential difficulties.

For more information on methodology and software please visit
http://www.ida.liu.se/~agbur/index.htm