Acta Geodaetica et Cartographica Sinica ›› 2023, Vol. 52 ›› Issue (6): 904-916.doi: 10.11947/j.AGCS.2023.20210717

• Geodesy and Navigation • Previous Articles     Next Articles

Using FY-4A GIIRS data and ERA5 reanalysis data to build a regional atmospheric weighted mean temperature model in China

WANG Xinzhi1,2,3, CHEN Fayuan1   

  1. 1. School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China;
    2. Wuxi Institute, Nanjing University of Information Science and Technology, Wuxi 214100, China;
    3. Experimental Teaching Center for Meteorology and Environment, Nanjing University of Information Science and Technology, Nanjing 210044, China
  • Received:2021-12-30 Revised:2022-10-17 Published:2023-07-08
  • Supported by:
    The Key Research and Development Program of Jiangsu Province (No. BE2021622); The Natural Science Foundation of Jiangsu Province(No. BK20211037);Higher Education Reform Project of Jiangsu Province(No. 2021JSJG219);Postgraduate Practice Innovation Program of Jiangsu Province(No. SJCX21_0373);Science and Technology Development Fund Project of Wuxi city(No. N20201011)

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Abstract: The accuracy of atmospheric weighted mean temperature (Tm) directly affects the results of Global Navigation Satellite System (GNSS) precipitable water vapor inversion.For the existing Tm model parameters, modeling data sources to be optimized and the model construction only relies on a single sounding site or single grid point data. It is proposed to fuse FY-4A GIIRS data with ERA5 reanalysis data. A sliding window algorithm is introduced to process the fused data while taking into account the longitude, latitude and elevation factors to construct an empirical Tm model (FY-ETm model) with a spatial resolution of 0.5°×0.5°. Bias and root mean square error (RMS) are used as accuracy metrics, combined with the 2020 sounding data, ERA5 reanalysis data, and zenith tropospheric delay (ZTD) products that are not involved in the modeling. Subsequently, the accuracy of the FY-ETm model and its inverse precipitable water vapor (PWV) are evaluated. The results show that the average annual Bias and RMS of FY-ETm model are -0.02、 5.79 K, respectively, which are 3.62(Bias)、 0.8(RMS)、 2.54(Bias) and 0.63 K (RMS) higher than those of Bevis and GPT3 models. With the reanalysis data of ERA5 as the reference value, the average annual Bias and RMS of FY-ETm model are 0.01、 3.32 K, respectively, which are 0.97(Bias)、 0.13(RMS)、 2.94(Bias) and 1.71 K(RMS) higher than those of Bevis and GPT3 models. Compared with GPT3 model with excellent accuracy, FY-ETm model also shows obvious accuracy improvement in western and northern China. With the PWV obtained from GNSS station as the reference value, the accuracy of PWV inversion from FY-ETm model is similar to that from GNSS station, Bias ranges from -0.5 mm to 0.5 mm.The FY-ETm model has high accuracy and good stability. It can obtain the Tmof the target point only by inputting the position and time information, and it can play an important role in GNSS precipitable water vapor inversion.

Key words: FY-4A GIIRS, ERA5, atmospheric weighted mean temperature, GPT3

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