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An improved GNSS tropospheric tomography method with the GPT2w model

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Abstract

The GNSS tropospheric tomography technique has been proven to be a powerful tool for three-dimensional water vapor reconstruction. In most previous studies, the signals leaving the side face of the tomography area are ignored as having invalid information, which wastes valuable observations and decreases signal coverage of the research area. To include the contribution of such signals to the final tomographic result, an improved tropospheric tomography approach, which makes the most use of GNSS observations by combining the data derived from the empirical Global Pressure and Temperature 2 wet model, is proposed. Compared to the conventional method, the proposed method can adaptively use the signals penetrating from the model’s side face to the tomographic model, which increases the number of voxels crossed by rays and improves the stability of the tomography model. Numerical results in Hong Kong over the period of day of year 124–150, 2013 show that the internal accuracy of the tomographic model based on the proposed method increases by 9.8% when compared to the conventional method. The RMS errors of the integrated water vapor derived from the proposed method are 4.1 and 4.6 mm, respectively, while the values derived from the conventional method are 5.0 and 5.4 mm, respectively, when compared to the radiosonde and European Centre for Medium-Range Weather Forecasts (ECMWF) products. In addition, compared to the conventional method, the accuracy of the water vapor density profile derived from the tomographic result of the proposed method has been enhanced by 25% and 12.5% when the radiosonde and ECMWF data are considered as the reference, respectively. Such results indicate a good performance of the proposed method for GNSS troposphere tomography.

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Acknowledgement

The authors would like to thank IGRA and ECMWF for providing access to the web-based meteorological data, the International GNSS Service (IGS) for providing precise GPS satellite orbit data and IGS observations, the Survey and Mapping Office of Lands Department in Hong Kong for providing the GPS and meteorological observations. This research was supported by the National Natural Science Foundation of China (41904036).

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Authors and Affiliations

  1. College of Geomatics, Xi’an University of Science and Technology, Xi’an, 710054, China

    Qingzhi Zhao & Wanqiang Yao

  2. School of Geodesy and Geomatics, Wuhan University, Wuhan, 430072, China

    Yibin Yao

  3. College of Geology Engineering and Geomatics, Chang’an University, Xi’an, 710054, Shanxi, China

    Xin Li

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  1. Qingzhi Zhao
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  2. Wanqiang Yao
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  4. Xin Li
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Correspondence to Qingzhi Zhao.

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Zhao, Q., Yao, W., Yao, Y. et al. An improved GNSS tropospheric tomography method with the GPT2w model. GPS Solut 24, 60 (2020). https://doi.org/10.1007/s10291-020-0974-4

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