顾及垂直递减率函数的中国区域大气加权平均温度模型

doi:10.11947/j.AGCS.2020.20190168

测绘学报 ›› 2020, Vol. 49 ›› Issue (4): 432-442.doi: 10.11947/j.AGCS.2020.20190168

顾及垂直递减率函数的中国区域大气加权平均温度模型

黄良珂^1,2,3, 彭华^1,2, 刘立龙^1,2, 李琛^1,2, 康传利^1,2, 谢劭峰^1,2

1. 桂林理工大学测绘地理信息学院, 广西桂林 541004;
2. 广西空间信息与测绘重点实验室, 广西桂林 541004;
3. 武汉大学卫星导航定位技术研究中心, 湖北武汉 430079

收稿日期:2019-05-10 修回日期:2019-11-27 发布日期:2020-04-17
通讯作者: 刘立龙 E-mail:hn_liulilong@163.com
作者简介:黄良珂(1986-),男,博士生,副教授,研究方向为GNSS气象学。E-mail:lkhuang666@163.com
基金资助:
国家自然科学基金（41704027；41664002；41864002）；广西自然科学基金（2017GXNSFBA198139；2018GXNSFAA281182；2017GXNSFDA198016）；广西“八桂学者”岗位专项

An empirical atmospheric weighted mean temperature model considering the lapse rate function for China

HUANG Liangke^1,2,3, PENG Hua^1,2, LIU Lilong^1,2, LI Chen^1,2, KANG Chuanli^1,2, XIE Shaofeng^1,2

1. College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China;
2. Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin 541004, China;
3. GNSS Research Center, Wuhan University, Wuhan 430079, China

Received:2019-05-10 Revised:2019-11-27 Published:2020-04-17
Supported by:
The National Natural Foundation of China (Nos. 41704027;41664002;41864002);The Guangxi Natural Science Foundation of China (Nos. 2017GXNSFBA198139;2018GXNSFAA281182;2017GXNSFDA198016);The “Ba Gui Scholars” Program of the Provincial Government of Guangxi

摘要/Abstract

摘要： 大气加权平均温度（T_m）是全球导航卫星系统（GNSS）水汽监测的关键参数。针对中国区域地形起伏较大的特点，本文构建了顾及精细季节变化的T_m垂直递减率函数模型，在此基础上，利用2007—2014年的Global Geodetic Observing System （GGOS） atmosphere格网数据建立了中国区域的T_m格网新模型（简称为CT_m模型）。以2015年GGOS格网数据和无线电探空资料为参考值，对CT_m模型进行精度检验，并与常用的Bevis公式和GPT2w模型进行比较分析。结果表明：①以GGOS格网数据为参考值，CT_m模型的年均偏差和均方根误差（RMS）分别为-0.52 K和3.28 K，相比于GPT2w-5和GPT2w-1模型，精度（RMS值）分别提高了27%和13%；②以探空数据为参考值，CT_m模型的年均偏差和RMS误差分别为0.26 K和3.75 K，相对于GPT2w-5和GPT2w-1模型，精度分别提高了21%和16%，尤其在中国西部地区，CT_m模型表现出更为显著的优势。此外，将CT_m模型用于GNSS水汽计算，其引起的水汽计算RMS误差和相对误差分别为0.29 mm和1.36%。CT_m模型不需要实测气象参数，因此，在中国区域的GNSS实时高精度水汽探测中具有重要的应用。

关键词: CT_m模型, 垂直递减率函数, GNSS大气水汽, 中国区域

Abstract: The atmospheric weighted mean temperature, T_m, plays an important role in the process of retrieving precipitable water vapor from Global Navigation Satellite System (GNSS) signals. Aiming at the characteristics of complex terrain in China,we develop a T_m lapse rate function that considering sophisticated seasonal variations, and then a new grid T_m model for China, named as CT_m, is established using gridded T_m data over an 8-year period from 2007 to 2014 provided by the global geodetic observing system (GGOS) atmosphere.Both gridded T_m data and radiosonde profiles from 2015 are treated as reference values to assess the performance of CT_m. The results are compared with the Bevis formula and the GPT2w model. The results show that the CT_m with the annual bias and RMS error of -0.52 K and 3.28 K when compared with gridded T_m data, respectively. In terms of RMS,the CT_m has improved by approximately 27% and 13% against GPT2w-5 and GPT2w-1, respectively. While the CT_m has the annual bias and RMS error of 0.26 K and 3.75 K against radiosonde data, and which has improved by approximately 21% and 16% against GPT2w-5 and GPT2w-1, respectively,especially in Western China, where the significant performance was observed for CT_m. Besides, the CT_m has RMS_PWV and RMS_PWV/PWV values of 0.29 mm and 1.36% when used to estimate GNSS-PWV. The CT_m model does not require any in situ meteorological parameters, thus, which has potential application for high-precision real-time GNSS-PWV retrieving in China.

Key words: CT_m model, lapse rate function, GNSS precipitable water vapor, China area

中图分类号:

P227

黄良珂, 彭华, 刘立龙, 李琛, 康传利, 谢劭峰. 顾及垂直递减率函数的中国区域大气加权平均温度模型[J]. 测绘学报, 2020, 49(4): 432-442.

HUANG Liangke, PENG Hua, LIU Lilong, LI Chen, KANG Chuanli, XIE Shaofeng. An empirical atmospheric weighted mean temperature model considering the lapse rate function for China[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(4): 432-442.

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顾及垂直递减率函数的中国区域大气加权平均温度模型

An empirical atmospheric weighted mean temperature model considering the lapse rate function for China

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