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Convection-resolving regional climate modeling and extreme event statistics
for recent and future summer climate
Christoph Knote 1 , Günther Heinemann 2 and Burkhardt Rockel 3
1)
christoph.knote@empa.ch, Empa Materials Science and Technology, Überlandstr. 129, 8600 Dübendorf, Switzerland
2)
Environmental meteorology, University of Trier, Behringstr. 21, 54286 Trier, Germany
3)
GKSS research centre, Max-Planck-Str. 1, 21502 Geesthacht, Germany
1. Introduction
Global and regional climate models are currently employed
on horizontal resolutions up to 5 km. State-of-the-art
numerical weather prediction (NWP) models though have
arrived at the kilometer-scale. At this resolution explicit
calculation of convection becomes feasible and effects of
small-scale topographic features (e.g. valleys) can be
accounted for. It is assumed that consequently extremes like
wind gusts, thunderstorms or heavy rain will be modelled
more realistic.
Extreme events exert the most imminent effect on people’s
lifes, which reasons a detailed treatment of possible changes
within future climate scenarios. Changes in extreme events
do not necessarily origin in changes of the mean. An
increase in variability is another possible source of change,
as has recently been shown for the summer heat wave over
Europe in 2003 by Schär et. al (2004). Extreme value
development is therefore not equivalent to mean
development and requires special analysis.
The combination of convection resolving regional climate
simulations with a state-of-the-art extreme value analysis is
believed to result in more accurate and more detailed
information about the changes in extremes in a future
climate.
2. Modeling
The COSMO-CLM version 4.2 has been employed in
simulations at 1.3 km resolution over the region of
Rhineland-Palatine in Germany. The simulations are nested
in simulations at 5 km which are based on the COSMO-
CLM consortial runs as reported in Hollweg et al. (2008).
Two time slices of 10 years (1960-69 and 2015-24) show
changes in extremes for the IPCC A1B scenario. Due to
computational demand only the summer months June, July
and August of each year have been modelled.
3. Extreme value analysis
A "peaks over threshold" (POT) extreme value analysis
gives information about changes in extremes of near-surface
wind speed, screen level temperature and precipitation. This
method is commonly used for the analysis of extreme values
of meteorological data, e. g. in Brabson and Palutikof
(2000). The modelled extreme values are fitted to a GPD
function to achieve comparable return value statistics for the
selected variables. Return values are widely used in urban
planning, disaster management and insurance. This
methodology is applied to regional means as well as to
single grid points to derive information about mean changes
as well as the regional differences.
4. Accuracy assessment
To assess the accuracy of the statistical procedure a nonparametric
method called “moving-block bootstrapping”
after Wilks (1997) is used. Therein the simulation data itself
forms the basis of a synthetic sample from which statistical
error properties of the POT procedure can be inferred,
without an a priori assumption about its distribution.
5. Results
It can be shown that the simulations result in added
variability when compared to simulations on a coarser
grid. Comparison of the two time slices results in positive
changes of daily extremes of temperature variables,
including an increasing variability between daily minima,
mean and maxima values. Wind speed and gust extremes
show no significant changes. These results are in
accordance with findings in the PRUDENCE project
(Kjellström et al. (2007), Beniston et al. (2007)).
Bootstrapping shows that the extreme value analysis itself
is stable.
References
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Ferro, C. A. T., Frei, C., Goyette, S., Halsnaes, K.,
Holt, T., Jylhä, K., Koffi, B., Palutikof, J., Schöll, R.,
Semmler, T., and Woth, K., Future extreme events in
european climate: an exploration of regional climate
model projections, Climatic Change, 81, pp. 71–95,
2007
Brabson, B. B. and Palutikof, J. P., Tests of the
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