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11 IMSC Session Program interesting example exists in eastern Australia, where the probability of extended heatwaves is significantly higher in El Niño years in New South Wales and Queensland (which matches the ENSO signal in mean seasonal temperatures), but significantly lower in Tasmania and the south of Victoria and South Australia (which does not). This may indicate a greater mobility of synoptic-scale systems in El Niño summers. Abstracts 343
11 IMSC Session Program Sources of uncertainty in the extreme value statistics of climate data Friday - Parallel Session 7 Michael Wehner Lawrence Berkeley National Laboratory, Bekeley, USA We investigate three sources of uncertainty in the calculation of extreme value statistics for observed and modelled climate data. Inter-model differentces in formulation, unforced interval variability and choice of statistical model all contribute to uncertainty. Using fits to the GEV distribution to obtain twenty year reutrm values, we quantify these uncertainties for the annual maximum daily mean surface air temperatures of pre-industrial control rtuns from fifteen climate model in the CMIP3 dataset. We find that uncertainty resulting from differing model formulations is much larger than that due to both unforced internal climate variability and the fit of the statistical model. A consistent spatial pattern of higher uncertainty over land than over ocean is true for all three types of uncertainties. The uncertrainties due to unforced internal climate variability and the fit of the statistic model are similar in both magnitude and spatial pattern with both exhibiting a strong poleward gradiant over land, especaily in the northern hemisphere. Figure: Measures of uncertainty of calculated 20 years return values of annual maximum daily mean surface ait temperature from the CMIP3 archieve. A) from intermodal differences b) from unforced internal variability c) from the fit of the statistical model. (Expressed as a standard deviation in kelvins) Abstracts 344
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