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冬季高海拔复杂地形下GRAPES—Mes0要素预报的检验评估

陈超君 王东海 李国平 张中锋 冯涛 刘英 尹金方

气象2012,Vol.38Issue(6):657-668,12.
气象2012,Vol.38Issue(6):657-668,12.

冬季高海拔复杂地形下GRAPES—Mes0要素预报的检验评估

A Study of the GRAPES-Meso Prediction Verification for High Altitude and Complex Terrain During Winter Time

陈超君 1王东海 2李国平 3张中锋 4冯涛 2刘英 2尹金方2

作者信息

  • 1. 成都信息工程学院大气科学学院,成都610225 中国气象科学研究院灾害天气国家重点实验室,北京100081
  • 2. 中国气象科学研究院灾害天气国家重点实验室,北京100081
  • 3. 成都信息工程学院大气科学学院,成都610225
  • 4. 民航气象中心,北京100122
  • 折叠

摘要

Abstract

Using the output from the run of GRAPES-Meso for the six venues during the Vancouver 2010 Winter Olympic and Paralympie Games, its capability to forecast the 2-m temperature, relative humidity, 10-m wind speed and wind direction is evaluated in terms lute error and Alpha Index. And also statistics TS, EH, of the forecast accuracy, mean error, mean abso- PO, NH, B and ETS are used for the verification of precipitation. The results show that the forecast accuracy of relative humidity is the highest and the forecast performance tends to be steady with the increasing leading time. The model exhibits a cold bias for temperature forecast. As for relative humidity, the forecast experiences a gradual transition from dry bias to wet bias, while wind speed forecast is always larger than observation. Among all the classification for the precipitation, the forecasts of GRAPES-Meso for rain or shine have the highest mean TS. And with the increase of precipitation, ETS is gradually close to the TS. At last compared with the other models wefound that there are some deficiencies in GRAPES-Meso. Through a certain systematic error in the forecasts, and if the error can be weather prediction will have a greater improvement. the verification it is found that there is effectively reduced then the numerical

关键词

GRAPES-Meso/检验评估/预报准确率/复杂地形

Key words

GRAPES-Meso model/verification/forecast accuracy/complex terrain

分类

天文与地球科学

引用本文复制引用

陈超君,王东海,李国平,张中锋,冯涛,刘英,尹金方..冬季高海拔复杂地形下GRAPES—Mes0要素预报的检验评估[J].气象,2012,38(6):657-668,12.

基金项目

公益性行业(气象)科研专项(GYHY200806007,GYHY201006014),国家自然科学基金项目(41175064)和中国气象科学研究院和灾害天气国家重点实验室基本科研业务专项基金共同资助 ()

气象

OA北大核心CSCDCSTPCD

1000-0526

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