摘要
为了提高湖南极端降水的模拟能力,利用转移累计概率分布(CDF-t)统计降尺度方法及基于第5次国际耦合模式比较计划(CMIP5)中的24个耦合模式数据,结合3个极端降水指数,从空间特征和年际变率两方面评估降尺度前后CMIP5模式对湖南极端降水的模拟能力。结果表明,较低空间分辨率的CM IP5气候模式无法细致反映区域极端降水变化特征,且由于各模式结果差异较大,多模式集合的模拟效果差。CDF-t统计降尺度通过建立大尺度变量的CDF与区域尺度相同变量的CDF之间的函数关系,对CMIP5模拟湖南极端降水变化特征有一定的改善能力。就空间结构而言,该方法对于模式模拟大雨日数(R10)和连续5天最大降水量(R5d)的空间结构能力都有很大改善,且模式之间表现出较高的一致性,尤其是R10改善效果最显著,与观测相比,湖南地区空间平均绝对误差达到2.18天,较降尺度前绝对误差降低了45.46%。就时间变率而言,该方法对于模式模拟R90P和R5d的时间变率能力都有很大改善,降尺度后IVS值分别由降尺度前的2.2和1.5降低至0.3和0.6。
Intensify,frequency and duration of Extreme Precipitation would increase in the future under a warming climate.Especially for Hunan where is sensitive to the climate change.Based on the CMIP5 historical simulations datasets,the ability of the CMIP5 models in simulating the spatial pattern andinterannual variability of extreme precipitation over Hunan province are evaluated using the statistical downscaling method of transform cumulative distribution function(CDF-t)combined with four extreme precipitation indices.The results show that due to the low resolution of GCM models,characteristics of extreme precipitation related to the terrain and atmospheric circulation over Hunan were not exactly reproduced.There are great differences between patterns,and the model sets have relatively poor simulation results.CDF-t statistical downscaling can improve CMIP5 simulation of extreme precipitation in Hunan by establishing the functional relationship between large-scale variable CDF and the same regional variable CDF.As far as the spatial structure is concerned,this method can greatly improve the spatial structure ability of the model to simulate the heavy rain days(R10)and the continuous five-day maximum precipitation(R5 d),and shows a high consistency between the models,especially the effect of R10 improvement is the most remarkable.Compared with the observation,the spatial average absolute error in Hunan area reaches 2.18 d,which is lower.The absolute error before scale is reduced by 45.46%.As far as time variability is concerned,this method can greatly improve the time variability ability of model simulation R90 P and R5 d.After scaling down,the IVS value decreases from 2.2 and 1.5 to 0.3 and 0.6 respectively.
作者
周莉
兰明才
蔡荣辉
黄娟
江志红
ZHOU Li;LAN Mingcai;CAI Ronghui;HUANG Juan;JIANG Zhihong(Hunan Meteotological Observatory,Changsha 410118,Hunan,China;Nanjing University of Information Science and Technology,Nanjing 210044,Jiangsu,China)
出处
《高原气象》
CSCD
北大核心
2019年第4期734-743,共10页
Plateau Meteorology
基金
中国气象局预报员专项(CMAYBY2019-078)
湖南省气象局预报员专项(XQKJ18C011)
湖南省气象局重点项目(XQKJ18A001)
关键词
湖南
转移累计概率分布
统计降尺度
极端降水
模式评估
Hunan
transfer cumulative probability distribution
statistical downscaling
extreme precipitation
model assessment
