Performance of climate models on simulation of extreme precipitation in China
Abstract
By comparing the gridded extreme precipitation indices from two approaches, from station indices or from gridded precipitation, influence of grid box area on gridded extreme index has been studied. The percentile of dry (wet) days will decrease (increase) with the increase of grid box area, except for the dry region in west China. And the percentile of extreme precipitation will decrease. Due to the influence of grid box area on the distribution of daily precipitation, most of the extreme indices from gridded precipitation will decrease with the increase of grid box area, except for wet days. The mean condition of maximum number of consecutive dry days is less influenced by the increase of grid box area. The inter-annual variation of extreme index is also influenced by the increase of grid box area. The gridded extreme index from gridded precipitation is suggested to be used to evaluate the model simulated extreme precipitation. The simulated extremes of 15 IPCC AR4 model have been evaluated, based on the extreme index from gridded precipitation, during 1961-2000. Most of the models simulated too wet in western China, especially around the Tibet Plateau (high mountain region), and too dry in southern China where the summer rainfall is largely underestimated. This will lead to overestimate extreme precipitation around mountain region and underestimate extreme precipitation in southern China. All the models intent to overestimate the precipitation in northern China and this will underestimate the dry days and overestimate the extreme precipitation there. Not all the models can well simulate the trend of extreme precipitation during 1961-2000 compare to the instrument observation. Further study is needed to evaluate how to project the future change of extreme precipitation in China based on the state-of-the-art climate models.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2011
- Bibcode:
- 2011AGUFMNH51B1697O
- Keywords:
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- 4313 NATURAL HAZARDS / Extreme events;
- 4318 NATURAL HAZARDS / Statistical analysis