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精细化MOS相对湿度预报方法研究
引用本文:陈豫英,陈晓光,马筛艳,马金仁,丁建军.精细化MOS相对湿度预报方法研究[J].气象科技,2006,34(2):143-146.
作者姓名:陈豫英  陈晓光  马筛艳  马金仁  丁建军
作者单位:宁夏气象局防灾减灾重点实验室,银川,750002
摘    要:利用2003年5~9月MM5模式每隔1 h的站点基本要素预报场和物理量诊断场资料,以及相应时段内宁夏25个测站的相对湿度自记观测资料,同时采用多元线性和逐步回归2种MOS统计方法,预报宁夏25个测站5~9月48 h逐时相对湿度。对2004年夏季6~8月预报效果检验表明:MOS方法制作宁夏48 h逐时相对湿度预报结果是可用的或是可参考的;2种MOS统计方法预报结果相近,逐步回归方法比多元线性方法预报效果稍好,08:00预报误差明显低于20:00;当天气形势变化较平稳时,MOS预报结果稳定,平均绝对误差控制在10%左右;当有明显的变温等特殊天气时,误差变率起伏波动大,预报结果不稳定。

关 键 词:MM5模式  相对湿度  精细化预报  MOS方法
收稿时间:2004-11-23
修稿时间:2005-03-04

Fine MOS Forecasting Method of Relative Humidity
Chen Yuying,Chen Xiaoguang,Ma Shaiyan,Ma Jinren,Ding Jianjun.Fine MOS Forecasting Method of Relative Humidity[J].Meteorological Science and Technology,2006,34(2):143-146.
Authors:Chen Yuying  Chen Xiaoguang  Ma Shaiyan  Ma Jinren  Ding Jianjun
Institution:Key Laboratory of Disaster Prevention and Reduction, Ningxia Autonomous Regional Meteorological Bureau, Yinchuan 750002
Abstract:By means of the hour-to-hour MM5-predicted basic element fields and physical-quantity diagnostic fields,as well as the recording humidity data of 25 stations over Ningxia Autonomous Region from May to September 2003,predictions are made of the 48-hour hour-to-hour relative humidity of 25 stations in Ningxia from May to September using the multiple linear and successive regression MOS methods.Verification of the forecasts is conducted for summer(June to August) 2004.The results indicate that to make the 48-hour hour-to-hour relative humidity forecast by means of the two MOS methods is feasible,and the results are of reference significance.The forecasts resulted from the two methods are very close;the one from successive regression is slightly better than that from multiple linear.The forecast error is obviously lower at 08:00 than that at 20:00.The MOS-predicted results are stable while the weather situation is stable with a mean absolute error of about 10%;the forecast error fluctuates greatly while there are obvious weather changes such as temperature change.
Keywords:MM5  relative humidity  fine forecasting  MOS(Model Output Statistics) method
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