应用数值模型提高GPS可降水量反演精度的研究  

The application of mesoscale NWP on improving the accuracy of GPS precipitable vapor

作　　者：袁招洪[1] 

机构地区：[1]上海市气象局,上海200030

出　　处：《测绘科学》2007年第6期39-41,共3页Science of Surveying and Mapping

基　　金：科技部世博专项(2005BA908B15);上海市科委世博专项(05dz05815);中科院知识创新工程重要方向项目(KJCX2-SW-T1-3)

摘　　要：利用建立在长江三角洲地区GPS观测网的资料,以上海宝山探空观测为例,进行了应用数值模式提高GPS可降水量反演精度的试验。研究结果表明:大气平均温度的估计误差直接影响大气可降水量的反演精度,用MM5中尺度数值预报模式预报估计的大气平均温度可减小大气平均温度的估计误差,从而提高大气可降水量的反演精度。Based on the GPS data from GPS networks in Yangtze delta,the radio sounding data of Baoshan station is explored to investigate that output of mesoscale NWP can be used for calculating average atmospheric temperature and improvement of GPS precipitable water(PW) accuracy.The results show that the accuracy of PW is closely related to the error of average atmospheric temperature,and the accuracy of PW will be improved resulting from the average error of atmospheric temperature decreasing by using outputs of MM5 mesoscale numerical prediction model.

关 键 词：GPS可降水量 中尺度数值预报模式 大气平均温度 

分 类 号：P228[天文地球—大地测量学与测量工程]