摘要
通过对1961—2010年中国540个气象站逐日降水观测数据和高精度区域气候模式CCLM(COSMO model in climatemode)3839个格点模拟值的对比,检验CCLM模式对中国日降水的模拟能力,揭示了1961—2010年日降水分布格局的变化特征;同时利用CCLM模式对中国地区2011—2050年的日降水预估值(SRES-A1B情景),运用概率统计和极值理论方法,分析了2011—2050年日降水序列及其极值的可能变化趋势。结果表明:除华南和青藏高原西部存在着较大的偏差以外,模式和观测日降水序列的峰度和偏度的分布格局较一致,空间相关系数达到0.75以上,CCLM能够很好地模拟中国日降水的分布特征。2011—2050年,峰度和偏度在江淮部分地区、东北与内蒙中东部等地区呈显著增加趋势,降水极端事件将会增多;最大日降水量和汛期最多无降水日数在上述地区的增加,进一步反映干旱和洪涝出现概率将升高。
Based on the observed daily precipitation records from 540 stations and the 3839 gridded data from a high-resolution regional climate model （CCLM） in 1961- 2010, the simulation ability of the CCLM on the daily precipitation in China was examined, and the variation of daily precipitation distribution pattern was revealed as well. By applying the probability method and extreme value theory to the projected data of daily precipitation under the A1B scenario in 2011 2050 by the CCLM, possible trends of daily precipitation series and its extremes were analyzed. Results show that except the western of the Qinghai-Tibet Plateau and South China, distributive patterns of the kurtosis and skewness calculated from the simulated and observed series are consistent with each other, and their spatial con＇elation coefficients are up to 0.75 or more. The CCLM model can well capture the distribution characteristics of daily precipitation over China. It was projected that in some parts of the Jianghuai region, the mid-eastern part of Northeast China and Inner Mongolia, the kurtosis and skewness will rise significantly, and precipitation extremes will also increase simultaneously in 2011 2050. The increases in projected maximum daily rainfall and largest non- precipitation days in the flood season in the above mentioned regions, also prove the intensified trends of droughts and floods in the next 40 years afar 2010.
出处
《气候变化研究进展》
CSCD
北大核心
2013年第2期89-95,共7页
Climate Change Research
基金
国家重点基础研究发展计划项目(973计划)(2010CB428401)
海河和鄱阳湖流域气候极端值变化趋势评价和比较(40911130506)
气候变化背景下海河流域土地利用和管理模式对水资源的影响研究(GZ601)
关键词
CCLM模式
日降水格局
峰度
偏度
CCLM model
daily precipitation pattern
kurtosis
skewness
