###
气象:2020,46(3):346-356
本文二维码信息
码上扫一扫!
西北四省(区)GRAPES模式降水预报的定量评估
吴晶,李照荣,颜鹏程,杨艳芬,白磊,杨建才,彭筱
(兰州中心气象台,兰州 730020; 中国气象局兰州干旱气象研究所,甘肃省干旱气候变化与减灾重点实验室,中国气象局干旱气候变化与减灾重点实验室,兰州 730020; 西北农林科技大学水土保持研究所黄土高原土壤侵蚀与旱地农业国家重点实验室,陕西杨凌 712100; 武汉理工大学,智能交通系统研究中心,武汉 430070)
Quantitative Assessment of GRAPES Rainfall Forecast for Four Provinces of Northwest China
WU Jing,LI Zhaorong,YAN Pengcheng,YANG Yanfen,BAI Lei,YANG Jiancai,PENG Xiao
(Lanzhou Central Meteorological Observatory, Lanzhou 730020; Key Laboratory of Arid Climatic Change and Reducing Disaster of Gansu Province/Key Open Laboratory of Arid Climatic Change and Reducing Disaster of China Meteorological Administration, Institute of Arid Meteorology, CMA, Lanzhou 730020; State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest Agriculture and Forestory University, Shaanxi, Yangling 712100; Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430070)
摘要
图/表
参考文献
相似文献
本文已被:浏览 751次   下载 545
投稿时间:2018-11-09    修订日期:2019-09-18
中文摘要: 基于中国西北四省(区)2016—2017年的站点观测降水数据和GRAPES区域数值模式24 h和48 h预报结果,采用平均误差、均方根误差、相关系数、分等级TS评分等指标,对GRAPES区域数值模式在西北四省(区)降水预报进行定量评估。结果表明:时间上,模式对西北四省的晴雨预报准确率能达到0.7以上,逐日空间相关系数为0.2~0.4。夏季降水的偏差最大,24 h和48 h预报平均误差分别为4、6 mm·d-1,均方根误差分别为6、8 mm·d-1。不同等级降水的24 h和48 h预报TS评分显示,各个月份小雨TS评分为0.2~0.5,中雨为0.1~0.2,大雨以上不到0.1。空间上,24 h和48 h预报晴雨准确率在大部分地区达到0.6以上,相关系数在甘肃东部、陕西中部和南部超过0.6。24 h预报平均误差在青海、甘肃、陕西三省南部最大(达到2~4 mm·d-1), 48 h预报的平均误差比相同区域的24 h预报高出1~2 mm·d-1,在陕西南部平均误差最大(达到5~8 mm·d-1)。各个量级的24 h预报TS评分明显好于48 h,24 h预报对大雨、暴雨有所预报,48 h预报对中雨以上量级降水预报较差。
Abstract:Combining the gauged precipitation and the predicted precipitation in 24 h and 48 h of regional numerical model named GRAPES during 2016 to 2017, GRAPES was quantitatively evaluated in the four provinces (regions) of Northwest China, using the indices including mean error, root mean square error, correlation coefficient and TS score. The results showed that the forecast accuracy of rain probability was higher than 0.7, daily spatial correlation coefficient was 0.2-0.4. The highest bias appeared in summer, the mean errors of 24 h and 48 h forecast were 4 mm·d-1 and 6 mm·d-1, the root mean square errorr were 6 mm·d-1 and 8 mm·d-1, respectively. The TS of heavy rain and above was less than 0.1, TSs of light rain and moderate rain were 0.2-0.5 and 0.1-0.2, respectively. Spatially, the 24 h and 48 h forecast accuracies of rain probability were higher than 0.6 in most regions, the correlation coefficients in eastern Gansu, middle and southern Shaanxi were higher than 0.6. The highest mean error of 24 h forecast appeared in the southern part of Qinghai, Gansu and Shaanxi, which reached to 2-4 mm·d-1. The highest mean error of 48 h forecast reached to 5~8 mm·d-1 and appeared in the southern Shaanxi. The mean error of 48 h forecast was 1~2 mm·d-1 higher than 24 h forecast in other regions, The TS score of 24 h forecast for each precipitation level was obviously better than that of 48 h, 24 h forecast could predict heavy rain and rainstorm, while 48 h forecast showed poor ability for moderate rain and above.
文章编号:     中图分类号:    文献标志码:
基金项目:兰州中心气象台创新基金项目(LCMO 201805)和国家自然科学基金项目(41501301)共同资助
引用文本:
吴晶,李照荣,颜鹏程,杨艳芬,白磊,杨建才,彭筱,2020.西北四省(区)GRAPES模式降水预报的定量评估[J].气象,46(3):346-356.
WU Jing,LI Zhaorong,YAN Pengcheng,YANG Yanfen,BAI Lei,YANG Jiancai,PENG Xiao,2020.Quantitative Assessment of GRAPES Rainfall Forecast for Four Provinces of Northwest China[J].Meteor Mon,46(3):346-356.