Title: Detecting change in extreme seasonal precipitation events using
results from climateprediction.net


Speaker: H.J. Fowler
S.R. Sain, D. Cooley, M. Allen

Abstract:

We produce probabilistic predictions of seasonal changes in extreme
precipitation for 8 UK grid cells using results from the
climateprediction.net experiment for the SRES A1B emissions scenario. In
this experiment, a coupled atmosphere-ocean global climate model,
HadCM3L, was run in grand ensemble mode for a transient integration
from 1920 to 2080, varying 20 parameter values and initial conditions.
Two integrations were produced: the control run provides a non-forced
transient simulation from 1920-2080 and in the scenario run forcing is
applied from 2000. We fit the Generalized Extreme Value distribution
with a with time-varying mu (location) parameter to yearly time series
of seasonal maxima for each of the control and scenario simulations
using maximum likelihood estimation and estimate change in the 10, 25
and 50 year return values. We then use delta confidence intervals on the
return value estimates to determine when change in seasonal extremes
will be detectable for the UK, examining when the confidence intervals
on return values for the scenario run lie outside those for the control
run. We apply the principle of equal weighting to produce probability
distributions of change for different decades and to determine the
probability of detection of change in extreme precipitation for
different regions of the UK in different seasons.