A Method to Improve the Distribution of Observations in GNSS Water Vapor Tomography

Sensors

Junbo Shi¹  Fei Yang¹  Yi Xu¹  Lv Zhou¹  Ming Chen¹  Jiming Guo¹ 

[1] School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China;

关键词: GNSS remote sensing;    atmospheric sounding;    water vapor tomography;    meteorology;   

DOI  :  10.3390/s18082526

来源: DOAJ

【 摘 要 】

Water vapor is an important driving factor in the related weather processes in the troposphere, and its temporal-spatial distribution and change are crucial to the formation of cloud and rainfall. Global Navigation Satellite System (GNSS) water vapor tomography, which can reconstruct the water vapor distribution using GNSS observation data, plays an increasingly important role in GNSS meteorology. In this paper, a method to improve the distribution of observations in GNSS water vapor tomography is proposed to overcome the problem of the relatively concentrated distribution of observations, enable satellite signal rays to penetrate more tomographic voxels, and improve the issue of overabundance of zero elements in a tomographic matrix. Numerical results indicate that the accuracy of the water vapor tomography is improved by the proposed method when the slant water vapor calculated by GAMIT is used as a reference. Comparative results of precipitable water vapor (PWV) and water vapor density (WVD) profiles from radiosonde station data indicate that the proposed method is superior to the conventional method in terms of the mean absolute error (MAE), standard deviations (STD), and root-mean-square error (RMS). Further discussion shows that the ill-condition of tomographic equation and the richness of data in the tomographic model need to be discussed separately.

【 授权许可】

Unknown