An optimal tropospheric tomography approach with the support of an auxiliary area

TLDR: In this article, the authors proposed an optimized tropospheric tomography method using an auxiliary area to estimate the top height of the tomography body based on the average water vapour distribution derived from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) radio occultation (RO) products.

Abstract: . Among most current tropospheric tomography studies, only the signals crossing out from the top boundary of the tomographic area are used for reconstructing the three-dimensional water vapour field, while signals penetrating from the side faces of the tomographic body are ignored as invalid information. Such a method wastes the valuable Global Navigation Satellite System (GNSS) observations and decreases the utilisation efficiency of GNSS rays. This is the focus of this paper, which tries to effectively use signals penetrating from the side faces of the tomographic body for water vapour reconstruction. An optimised tropospheric tomography method is proposed using an auxiliary area. The top height of the tomography body is determined based on the average water vapour distribution derived from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) radio occultation (RO) products. In addition, the coefficients of a negative exponential function between the adjacent layers for vertical constraints are fitted using the COSMIC RO profiles. Thirteen GPS stations are selected in the CORS Network of Texas to perform the tomographic experiment and validate the performance of the proposed method at 00:00 and 12:00 UTC daily using the radiosonde data for a period of 15 days. Compared to the conventional method, the accuracy of the reconstructed water vapour information derived from the proposed method is increased by 14.37 % and 16.13 %, respectively, in terms of mean root mean square (rms) and mean absolute error (MAE). The tomographic results obtained from the proposed method are further validated with the slant water vapour (SWV) data derived using the GAMIT (GNSS processing software package). Results show that the rms and MAE accuracy of SWV values has been improved by 18.18 % and 27.62 %, respectively, when compared to the conventional method. Keywords. History of geophysics (atmospheric sciences)