顾及气候差异的区域加权平均温度模型——以中国陕西为例

doi:10.11947/j.AGCS.2021.20200163

测绘学报 ›› 2021, Vol. 50 ›› Issue (3): 356-367.doi: 10.11947/j.AGCS.2021.20200163

顾及气候差异的区域加权平均温度模型——以中国陕西为例

朱海, 黄观文, 张菊清

长安大学地质工程与测绘学院, 陕西西安 710054

收稿日期:2020-04-27 修回日期:2020-07-16 发布日期:2021-03-31
通讯作者: 黄观文 E-mail:huang830928@163.com
作者简介:朱海(1996-),男,硕士生,研究方向为GNSS气象学。E-mail:2018126050@chd.edu.cn
基金资助:
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）

A regional weighted mean temperature model that takes into account climate differences: taking Shaanxi, China as an example

ZHU Hai, HUANG Guanwen, ZHANG Juqing

College of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, China

Received:2020-04-27 Revised:2020-07-16 Published:2021-03-31
Supported by:
The National Natural Science Foundation of China (Nos. 41731066;41774025);The National Key Research and Development Program of China (No. 2018YFC1505102);The Outstanding Youth Foundation of Shaanxi (No. 2019JC-20);The Grand Projects of the BeiDou-2 System (No. GFZX0301040308);The Special Fund for Basic Scientific Research of Central Colleges (Nos. CHD300102268305;CHD300102268305)

摘要/Abstract

摘要： 加权平均温度T_m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T_m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T_m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T_m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T_m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。

关键词: 加权平均温度, 陕西省, 模型区域化

Abstract: The weighted mean temperature T_m 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 T_m 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 T_m 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 T_m 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 T_m 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.

Key words: weighted mean temperature, Shaanxi region, model regionalization

中图分类号:

P228

朱海, 黄观文, 张菊清. 顾及气候差异的区域加权平均温度模型——以中国陕西为例[J]. 测绘学报, 2021, 50(3): 356-367.

ZHU Hai, HUANG Guanwen, ZHANG Juqing. A regional weighted mean temperature model that takes into account climate differences: taking Shaanxi, China as an example[J]. Acta Geodaetica et Cartographica Sinica, 2021, 50(3): 356-367.

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顾及气候差异的区域加权平均温度模型——以中国陕西为例

A regional weighted mean temperature model that takes into account climate differences: taking Shaanxi, China as an example

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