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基于转移累计概率分布统计降尺度方法的未来降水预估研究:以湖南省为例
引用本文:周莉,江志红.基于转移累计概率分布统计降尺度方法的未来降水预估研究:以湖南省为例[J].气象学报,2017,75(2):223-235.
作者姓名:周莉  江志红
作者单位:1.湖南省气象台, 长沙, 410118
基金项目:湖南省气象台短平快项目“基于统计降尺度的湖南极端降水时空分布特征及未来风险预估研究”、湖南省局重点项目(XQKJ15A002)、国家自然科学基金重点项目(41230528)。
摘    要:基于最新一代CMIP5(Coupled Model Intercomparison Project Phase 5)模式历史情景和未来RCP4.5情景下的模式逐日降水数据,使用转移累计概率分布(CDF-t)统计降尺度方法,从空间变化和时间变率两个方面评估该降尺度方法对湖南日降水量模拟能力的改善效果,并在此基础上对未来降水量变化进行预估。结果表明, CMIP5气候模式由于分辨率较低,无法细致反映湖南地形变化和大气环流影响导致的区域降水变化特征。经过CDF-t统计降尺度处理之后,模式对湖南降水的时、空分布模拟与实况更为接近,绝大部分模式对降水空间结构的模拟能力都有显著提高。基于CDF-t统计降尺度的多模式集合预估结果表明,21世纪湖南省日降水量呈弱的增多趋势(0.95%/(10 a))。21世纪初、中和末期相对于1986—2005年的气候平均态,湖南省日降水量分别增加了4.6%、5%和5.2%。3个时期湖南省日平均降水变化的空间分布存在较强的一致性,皆表现为湖南西北、东北和东南3个地区降水增幅最为显著,且随着辐射强迫的增大,3个地区降水增幅也呈递增趋势。需要指出的是,预估结果在模式之间存在一定差异,并且这种差异随着辐射强迫的增大而增大。 

关 键 词:统计降尺度    转移累计概率分布    湖南省    未来降水预估
收稿时间:2016/3/17 0:00:00
修稿时间:2016/11/11 0:00:00

Future changes in precipitation over Hunan Province based on CMIP5 simulations using the statistical downscaling method of transform cumulative distribution function
ZHOU Li and JIANG Zhihong.Future changes in precipitation over Hunan Province based on CMIP5 simulations using the statistical downscaling method of transform cumulative distribution function[J].Acta Meteorologica Sinica,2017,75(2):223-235.
Authors:ZHOU Li and JIANG Zhihong
Institution:1.Hunan Meteotological Observatory, Changsha 410118, China2.Key Laboratory of Meteorological Disaster of Ministry of Education, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China
Abstract:Based on the CMIP5 historical simulations and RCP4.5 datasets, the ability of the CMIP5 models in simulating the spatial pattern and interannual variability of precipitation over Hunan Province are evaluated using the statistical downscaling method of transform cumulative distribution function (CDF-t). The future precipitation change is then projected. The results show that due to the low resolution of GCM models, characteristics of precipitation related to the terrain and atmospheric circulation over Hunan Province were not exactly reproduced. The downscaled precipitation agrees well with observations, and the capacity of CMIP5 models for simulating the spatial pattern and interannual variability of precipitation can be effectively improved by the downscaling approach. The multi-model ensemble projection of future changes in precipitation shows that in the 21 century, precipitation over Hunan Province will slightly increase by a rate of 0.95% perdecade. Precipitation was projected to increase by 4.6%, 5% and 5.2% with respect to that during 1986-2005 for Hunan Province in 2016-2035, 2046-2065 and 2081-2100 respectively. The spatial pattern of the future change in the three periods displays a good consistency, with the most obvious change occurring in the northeast, northwest and southeast of Hunan Province. It should be noted that there exist differences among models. With increases in radiative forcing, the differences among various model situations tend to become larger.
Keywords:Statistical downscaling  Cumulative distribution function-transform (CDF-t)  Hunan Province  Projection
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