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1998年夏季我国异常洪涝区域气候的物理集合模拟
引用本文:钟科,王汉杰,蔡其发,余清平.1998年夏季我国异常洪涝区域气候的物理集合模拟[J].高原气象,2007,26(5):992-1003.
作者姓名:钟科  王汉杰  蔡其发  余清平
作者单位:1. 中国科学院,大气物理研究所,LASG,北京,100029
2. 中国科学院东亚区域气候-环境重点实验室,北京,100029
3. 解放军理工大学,气象学院,江苏,南京,211101
4. 兰州军区空军气象中心,甘肃,兰州,730020
基金项目:国家自然科学基金项目(40675040),国家重点基础研究发展计划项目(973计划)(2006CB400505)共同资助
摘    要:通过对MM5有限区域模式中的5种物理过程加以扰动、组合得到一个有19个成员的物理集合,并用其对1998年夏季发生在我国东部地区的异常洪涝天气气候特征进行了模拟研究。结果表明:相对于集合平均、高分辨率试验,集合概率预报有着最高的分辨力,这从一个方面验证了集合预报方法认为在数值天气预报中应该以概率的形式来认识大气状态的观点的合理性。另外,对不同的集合模拟质量检验方法,有较好表现的具体物理实现方案不尽相同,同时,模拟结果对扰动物理过程的敏感性分布有一些差异,但从统计意义来看:某些物理过程的扰动对模拟结果产生强扰动效应的频率更高一些及某些具体物理实现方案表现好的频率更高一些。

关 键 词:物理集合  区域气候模拟  概率预报  分辨力
文章编号:1000-0534(2007)05-0992-12
修稿时间:2006-09-302007-03-30

The Physical Ensemble Simulation of the Chinese Anomaly Flood Regional Climate in Summer of 1998
ZHONG Ke,WANG Han-jie,CAI Qi-fa,YU Qing-ping.The Physical Ensemble Simulation of the Chinese Anomaly Flood Regional Climate in Summer of 1998[J].Plateau Meteorology,2007,26(5):992-1003.
Authors:ZHONG Ke  WANG Han-jie  CAI Qi-fa  YU Qing-ping
Institution:1.State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics(LASG
Abstract:Through disturbing five kinds of physical processes of the regional model MM5,a physical ensemble with 19 members is formed in this paper.With this ensemble system the simulation research is applied to the Chinese anomaly flood regional climate in summer of 1998.The ensemble probability forecast has higher accuracy and discrimination ability than the ensemble mean and the higher resolution experiment do,which verifies to certain extent that describing atmospheric state in probability form is more accurate in numerical weather prediction.The physical scheme performing better and the sensitivity distribution among the disturbed physical processes change with the validated aspects of simulation quality;nevertheless,according to the statistical results of all the validated aspects of simulation quality,some physical processes produce strong disturbance more frequently,and some physical schemes perform better than others more frequently.
Keywords:Physical ensemble  Regional climate simulation  Probability forecast  Resolving power
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