Publications

Zhang, WY; Zhang, SB; Zheng, NS; Zhang, QZ; Ding, N (2022). Study on the retrieval of 3D atmospheric water vapor distribution using GNSS and RS multi-source data. CHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITION, 65(6), 1951-1964.

Abstract
Atmospheric water vapor, one of the most important greenhouse gas, plays a crucial role in understanding the global climate change and forecasting the extreme weather events. Global Navigation Satellite System (GNSS) tomography technique has become one of the significant techniques for retrieving the three-dimensional distribution of water vapor, and this technique has developed rapidly and has made some applications come true. However, due to the limitation of GNSS acquisition geometry, traditional tomography model is faced with the problems of uneven distribution of observations and many blank voxels. We propose a new water vapor tomography method using GNSS and Remote Sensing (RS) multi-source data to retrieve high-precision three-dimensional distribution of atmospheric water vapor for the first time. GNSS data and PWV observations from MODIS and MERSI over Xuzhou region are used to validate the GNSS/RS tomography method. The experimental results show that the average number of effective observations is improved by 38. 41% and the mean number of the crossed voxels is increased by 55. 56%. Taking the high-precision radiosonde water vapor profile and 3D water vapor density field from ERAS as reference values, it can be observed that the proposed method is superior to the traditional method in all kinds of precision indexes, with the mean root-mean-square error improved by 29. 68% and 20. 31%, respectively. Additionally, GNSS/RS model can retrieve the more accurate water vapor products than GNSS model in the different altitude layers. This indicates that the GNSS combining RS tomography method is able to improve the quality of tomographic results, retrieving the accurate and reliable 3D atmospheric water vapor distribution.

DOI:
10.6038/cjg2022P0078

ISSN: