4.7 Article

A new method for tropospheric tomography using GNSS and Fengyun-4A data

Journal

ATMOSPHERIC RESEARCH
Volume 280, Issue -, Pages -

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.atmosres.2022.106460

Keywords

GNSS data; Fengyun-4A data; Tropospheric tomography

Funding

  1. National Natural Science Foundation of China [42274021, 41874040]
  2. State Key Program of National Natural Science Foundation of China [41730109]
  3. Independent Innovation Project of Double-First Class Construction [2022ZZCX06]
  4. Programme of Introducing Talents of Discipline to Universities [B20046]
  5. 2022 Jiangsu Provincial Science and Technology Initiative-Special Fund for International Science and Technology Cooperation [BZ2022018]

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A new tropospheric tomographic method using both GNSS and FY-4A data is proposed in this study to reflect the three-dimensional distribution of water vapor. Test results show that the new method improves upon traditional methods by effectively addressing the ill-posed problem and increasing the accuracy of water vapor density measurements.
Global Navigation Satellite Systems (GNSS) tropospheric tomography can reflect a three-dimensional distribu-tion of water vapour. However, the common ill-posed problem for GNSS tropospheric tomography needs to be addressed. The relatively newly launched Chinese Fengyun-4A (FY-4A) satellite water vapour data have a high spatiotemporal resolution and may be used to assist in resolving the ill-posed problem. In this study, a new tropospheric tomographic method using both GNSS and FY-4A data was proposed. Tomographic schemes for the new method with the coverage rate of GNSS sites (CRGS, which is defined as the ratio of the number of GNSS sites to the number of horizontal grids in the tropospheric tomography) of 0.2, 0.28, 0.36 and 0.44 were compared with traditional tomographic schemes using the same CRGS. Test results showed that adding FY-4A data, in addition to GNSS data, to the tomographic system could effectively increase the number of voxels crossed by signals, which benefits the ill-posed problem. When CRGS equated 0.28, the new method had the largest improvement compared with the traditional method, in which the mean of the root mean squared error (RMSE) of the water vapour density (WVD) was reduced from 2.44 and 1.38 g/m3 to 2.05 and 1.22 g/m3 using radiosonde and ERA5 data as the references, respectively. Statistical results showed that the new method that used both GNSS and FY-4A data outperformed the traditional method that only used GNSS data.

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