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我国近年来短期气候预测研究的若干进展
引用本文:王会军,周广庆,林朝晖.我国近年来短期气候预测研究的若干进展[J].气候与环境研究,2002,7(2):220-226.
作者姓名:王会军  周广庆  林朝晖
作者单位:中国科学院大气物理研究所大气科学和地球流体力学数值模拟实验室,北京,100029
基金项目:国家杰出青年基金项目40125014及中国科学院知识创新工程重要方向性项目KZCX2-203
摘    要:回顾了近年来我国短期气候预测研究的若干进展,主要是在中国科学院大气物理研究所完成的以气候模式为基础的短期气候预测方面工作.第一个基于气候数值模式开展短期气候预测试验的是曾庆存等人,他们所采用的是IAP AGCM耦合一个热带太平洋环流模式(OGCM);1997年,基于耦合气候模式基础上的ENSO预测系统建立起来;同时开展了东亚区气候可预测性研究;利用气候变动的准两年信号提出了对模式预测结果进行有效修正的方案;为了考虑初始土壤湿度异常对夏季气候的影响,建立了气象变量和土壤湿度的经验关系;还系统地研究了1998年海面温度异常和大气春季异常对夏季气候(特别是发生于中国的大水)预测的影响.

关 键 词:短期气候预测  气候模式  进展
修稿时间:2002年4月28日

Reviews on Study of the Short-term Climate Prediction in China
Wang Huijun,Zhou Guangqing and Lin Zhaohui.Reviews on Study of the Short-term Climate Prediction in China[J].Climatic and Environmental Research,2002,7(2):220-226.
Authors:Wang Huijun  Zhou Guangqing and Lin Zhaohui
Abstract:This is an overview paper on the short-term climate prediction studies made in the Insti tute of Atmospheric Physics (IAP) Chinese Academy of Sciences (CAS) in China over the past 10 years. The first attempt of climate prediction was experimented by Zeng's group in 1989 by using the AGCM coupled with a tropical Pacific OGCM designed in IAP. In 1997, IAP established the first version of the ENSO prediction system by using the Tropical Pacific and Global Atmosphere CGCM. The predictability has been studied in IAP since 1996. Based on the model's ability on reproducing the bian nual oscillation existed in the climate, Wang et al. designed an effective correction method for the sea sonal climate prediction system. A system for empirical relationship between the atmospheric variables and the soil moisture was established, in order to take account the impact on the springtime soil mois ture anomalies in the summer rainfall anomalies. IAP also studied the role of the global SST anomalies and the springtime anomalous atmospheric circulation on the summer flood over the Yangtze River Valley in 1998 by use of the AGCMs developed in IAP and the Center for Climate System Research at the University of Tokyo.
Keywords:short-term climate prediction  climate model  review
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