An empirical zenith wet delay correction model using piecewise height functions

被引:15
|
作者
Yao, YiBin [1 ,2 ,3 ]
Hu, YuFeng [1 ,4 ]
机构
[1] Wuhan Univ, Sch Geodesy & Geomat, 129 Luoyu Rd, Wuhan 430079, Hubei, Peoples R China
[2] Wuhan Univ, Key Lab Geospace Environm & Geodesy, Minist Educ, 129 Luoyu Rd, Wuhan 430079, Hubei, Peoples R China
[3] Collaborat Innovat Ctr Geospatial Technol, 129 Luoyu Rd, Wuhan 430079, Hubei, Peoples R China
[4] Changan Univ, Coll Geol Engn & Geomat, Xian 710054, Shanxi, Peoples R China
基金
中国国家自然科学基金;
关键词
TROPOSPHERIC CORRECTION; GPS METEOROLOGY; CRYOSAT-2;
D O I
10.5194/angeo-36-1507-2018
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
Tropospheric delay is an important error source in space geodetic techniques. The temporal and spatial variations of the zenith wet delay (ZWD) are very large and thus limit the accuracy of tropospheric delay modelling. Thus, it is worthwhile undertaking research aimed at constructing a precise ZWD model. Based on the analysis of vertical variations of ZWD, we divided the troposphere into three height intervals (below 2 km, 2 to 5 km, and 5 to 10 km) and determined the fitting functions for the ZWD within these height intervals. The global empirical ZWD model HZWD, which considers the periodic variations of ZWD with a spatial resolution of 5 degrees x 5 degrees, is established using the ECMWF ZWD profiles from 2001 to 2010. Validated by the ECMWF ZWD data in 2015, the precision of the ZWD estimation in the HZWD model over the three height intervals are improved by 1.4, 0.9, and 1.2 mm, respectively, compared to that of the currently best GPT2w model (23.8, 13.1, and 2.6 mm). The test results from ZWD data from 318 radiosonde stations show that the root mean square error (RMSE) in the HZWD model over the three height intervals was reduced by 2% (0.6 mm), 5% (0.9 mm), and 33% (1.7 mm), respectively, compared to the GPT2w model (30.1, 15.8, and 3.5 mm) over the three height intervals. In addition, the spatial and temporal stabilities of the HZWD model are higher than those of GPT2w and UNB3m.
引用
收藏
页码:1507 / 1519
页数:13
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