摘要
加权平均温度Tm是全球导航卫星系统(GNSS)反演可降水量的关键参数。本文以中国陕西为例,结合欧洲天气预报中心(ECMWF)的再分析数据与3个探空站数据,基于最小二乘原理建立了一种顾及周期性的Tm区域化回归模型。利用陕西省内3个探空站数据进行验证。结果表明,本文所建立的顾及周期的Tm区域模型比传统Bevis模型精度平均提升率为16.1%。另外,针对不同气候类型地区的差异问题,建立了随纬度变化分段线性形式的顾及气候差异的Tm模型,解决了回归模型在不同气候区的适应性问题。与探空数据比较,顾及气候差异的Tm模型其外符合精度(RMS)范围在1.47~2.06 K之间,与Bevis模型比较,精度平均提高率为44.9%,提升效果显著;利用ECMWF数据选取19个格网点对模型进行精度评估。结果表明:平均RMS为3.26 K,最大RMS为3.67 K;平均STD为2.69 K,最大STD为3.19 K。
The weighted mean temperature Tm is a key parameter of the global navigation satellite system(GNSS)inversion of precipitation.Taking the Shaanxi area in China as an example,this paper combines the reanalysis data of the European Weather Forecast Center(ECMWF)with the data of three sounding stations,and establishes a Tm regionalized regression model considering periodicity based on the principle of least squares.The data from three radiosonde stations in Shaanxi Province were used for verification.The results show that the Tm regional model established in this paper taking into account the cycle has an average improvement rate of 16.1%compared with the traditional Bevis model.In addition,in view of the differences in regions with different climate types,this paper establishes a sub-climatic zone Tm model with a piecewise linear form that changes with latitude,and solves the problem of adaptability of the regression model in different climate zones.Compared with sounding data,the Tm model that takes into account the climate difference has an external accuracy(RMS)range of 1.47~2.06 K.Compared with the Bevis model,the average accuracy improvement rate is 44.9%,and the improvement effect is significant;using ECMWF data to select 19 each grid point evaluates the accuracy of the model.The results show that the average RMS is 3.26 K and the maximum RMS is 3.67 K;the average STD is 2.69 K and the maximum STD is 3.19 K.
作者
朱海
黄观文
张菊清
ZHU Hai;HUANG Guanwen;ZHANG Juqing(College of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, China)
出处
《测绘学报》
EI
CSCD
北大核心
2021年第3期356-367,共12页
Acta Geodaetica et Cartographica Sinica
基金
国家自然科学基金(41731066,41774025)
国家重点研发计划(2018YFC1505102)
陕西省杰出青年基金(2019JC-20)
二代导航重大专项(GFZX0301040308)
中央高校科研业务费专项(CHD300102268305,CHD300102268305)。
关键词
加权平均温度
陕西省
模型区域化
weighted mean temperature
Shaanxi region
model regionalization
