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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/amt-2019-95
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2019-95
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 04 Apr 2019

Research article | 04 Apr 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).

A GPS water vapor tomography method based on a genetic algorithm

Fei Yang1,2,3,4, Jiming Guo1,3,4, Junbo Shi1,3, Xiaolin Meng2, Yinzhi Zhao1, Lv Zhou5, and Di Zhang1 Fei Yang et al.
  • 1School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
  • 2Nottingham Geospatial Institute, University of Nottingham, Nottingham NG7 2TU, United Kingdom
  • 3Key Laboratory of Precise Engineering and Industry Surveying of National Administration of Surveying, Mapping and Geoinformation, Wuhan University, Wuhan 430079, China
  • 4Research Center for High Accuracy Location Awareness, Wuhan University, China
  • 5Guilin University of Technology, Guilin 541004, China

Abstract. Water vapor is an important part in the atmosphere, but its spatial and temporal distribution is difficult to detect. Global Positioning System (GPS) water vapor tomography, which can sense three-dimensional water vapor distribution, has been developed as a research point in the fields of GPS meteorology. In this paper, a new water vapor tomography method based on a genetic algorithm (GA) is proposed to overcome the ill-conditioned problem. By using the proposed approach, it is not necessary to perform the matrix inversion process, and the water vapor tomography is no longer dependent on excessive constraints, priori information and external data, which give rise to many limitations and difficulties. Experiments in Hong Kong under rainy and rainless conditions show a serious ill-conditioned problem in the tomographic matrix by grayscale and condition numbers. Numerical results indicate that the proposed method achieves high levels of agreement and internal/external accuracy with the GAMIT-estimated slant water vapor (SWV) as a reference. Comparative results of water vapor density (WVD) derived from radiosonde data reveal that the tomographic results based on the GA are in good agreement with that of radiosonde measurements. In comparison to the traditional Least squares method, a reliable tomographic result with high accuracy can be achieved by the GA without the restrictions mentioned-above. Furthermore, the tomographic results in a rainless scenario are better than those of a rainy scenario, and the reasons are discussed in detail.

Fei Yang et al.
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Short summary
The development of GPS station networks that provide rich data sources containing atmospheric information will enable more GPS applications in the field of meteorology. This study describes a genetic algorithm for the water vapor tomography, overcomes the ill-conditioned problem and eliminates the reliance on excessive constraints, priori information and external data. It is proven in the paper that accurate 3-D water vapor distribution can be provided by this study for atmospheric research.
The development of GPS station networks that provide rich data sources containing atmospheric...
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