中国南部地区大气加权平均温度模型精化研究  

Refinement of Atmospheric Weighted Mean Temperature Model for Southern China

作　　者：廖发圣 黄良珂 刘立龙 黄玲 郭希 刘喆栋 LIAO Fasheng;HUANG Liangke;LIU Lilong;HUANG Ling;GUO Xi;LIU Zhedong(College of Geomatics and Geoinformation,Guilin University of Technology,319 Yanshan Street,Guilin 541006,China)

机构地区：[1]桂林理工大学测绘地理信息学院,桂林市541006

出　　处：《大地测量与地球动力学》2022年第1期41-47,共7页Journal of Geodesy and Geodynamics

基　　金：国家自然科学基金(41864002,41704027,41664002);广西自然科学基金(2017GXNSFBA198139,2017GXNSFDA198016,2018GXNSFAA281182);湖南省自然资源调查与监测工程技术研究中心开放课题(2020-9);广西“八桂学者”岗位专项。

摘　　要：针对中国南部地区地势西高东低、沿海与内陆存在差异等情况,分析中国南部地区T_(m)与地面温度、测站高度、季节变化以及纬度的关系,利用中国南部地区19个探空站2015~2017年的探空数据,在Bevis公式的基础上建立只考虑地面温度的线性模型(T_(m)-SC1模型)和与地面温度、高程、季节变化以及纬度有关的新T_(m)模型(T_(m)-SC2模型)。以2018年的探空数据为参考值,对T_(m)-SC1模型和T_(m)-SC2模型进行精度验证,并与广泛使用的Bevis公式和GPT3模型进行精度比较。结果表明,T_(m)-SC1模型的年均偏差和均方根误差(RMS)分别为0.76 K和2.57 K,相比Bevis模型和GPT3模型,其精度(RMS值)分别提高13.8%和2.2%;T_(m)-SC2模型的年均偏差和均方根误差(RMS)分别为-0.10 K和1.64 K,相比Bevis模型和GPT3模型其精度(RMS值)分别提高44.9%和37.6%。T_(m)-SC2模型用于GNSS水汽计算导致的理论RMS误差和相对误差分别为0.16 mm和0.43%。因此,T_(m)-SC2模型更适用于中国南部地区的GNSS水汽探测以及气象研究。In southern China the terrain is high in the west and low in the east, and there are differences between the coast and the inland. Using 19 sounding stations in southern China from 2015-2017, we analyze the relationship between T_(m)and station height, ground temperature, seasonal variation and latitude. For the annual sounding data, we establish a linear model(T_(m)-SC1) that only considers ground temperature and a new T_(m)model(T_(m)-SC2) related to ground temperature, elevation, seasonal changes, and latitude on the basis of the Bevis formula. Using the sounding data in 2018 as a reference, we analyze the accuracy of the models. We compare the accuracy with the widely used Bevis formula and GPT3 model. The results show that the average annual deviation and root mean square error(RMS) of the T_(m)-SC1 model are 0.76 K and 2.57 K, respectively. Compared with the Bevis model and the GPT3 model, the accuracy(RMS value) is increased by 13.8% and 2.2%, respectively. The annual average deviation and root mean square error(RMS) of the T_(m)-SC2 model are-0.10 K and 1.64 K, respectively. Compared with the Bevis model and the GPT3 model, the accuracy(RMS value) is increased by 44.9% and 37.6%, respectively. The theoretical RMS error and relative error of water vapor calculation caused by the T_(m)-SC2 model used in GNSS water vapor calculation are 0.16 mm and 0.43%, respectively. Therefore, the T_(m)-SC2 model is more suitable for GNSS water vapor detection and meteorological research in southern China.

关 键 词：大气加权平均温度 中国南部地区 T_(m)-SC模型 GNSS大气水汽 

分 类 号：P228[天文地球—大地测量学与测量工程]