Abstract
Global pressure and temperature (GPT) models are widely available and easy-to-use in tropospheric delay estimation and GNSS water vapor retrieval, but cannot capture the diurnal and semidiurnal variations that add uncertainty to tropospheric delay determinations. This paper introduces an improved global pressure and temperature model (IGPT) established using 10 years hourly ERA5 dataset provided by the European Centre for Medium-Range Weather Forecasts. This IGPT model effectively captures the diurnal and semidiurnal patterns as well as their seasonal variations in global pressure and temperature signals. The IGPT model also assimilates the radiosonde data to improve height correction, which extends the feasibility of the model from the earth surface to up to 15 km. The performance of the IGPT model was evaluated with four types of datasets: a 3-year ERA5 hourly dataset, a decade of radiosonde surface data, 1-year radiosonde upper-air data, and 1-year global navigation satellite system (GNSS) zenith troposphere delay (ZTD) products. By considering the intraday variations, the average RMS of pressure and temperature errors on the surface in IGPT were about 5.97 hPa and 3.68 K, with improvements of 1.8% and 22.4% as compared with the GPT3 model. By assimilating the radiosonde data, the accuracy of IGPT pressure and temperature at high altitude was 7.47 hPa and 7.22 K, achieving an improvement of 72.1% and 51.1%, respectively, relative to the GPT3 model. The IGPT model also slightly improved the computational accuracy of the GNSS ZTD as compared to calculations using the GPT3 model. The coefficients and the MATLAB source code of the IGPT model are available online (https://zenodo.org/record/3893412).
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Acknowledgements
We are grateful to the European Centre for Medium-Range Weather Forecasts for providing ERA5 reanalysis data (https://cds.climate.copernicus.eu/#!/search?text=ERA5&type=dataset), the Integrated Global Radiosonde Archive for providing radiosonde data (https://www1.ncdc.noaa.gov/pub/data/igra/data/data-por/), the University of Wyoming for providing radiosonde data (http://weather.uwyo.edu/upperair/sounding.html) and the International GNSS Service for providing ZTD data (https://cddis.nasa.gov/archive/gps/products/troposphere/zpd/). We also would like to thank TU Vienna for providing code and grid files of the GPT3 model (http://vmf.geo.tuwien.ac.at/codes/). This research is financially supported by the National Natural Science Foundation of China (No. 41704002, 91638203, 41604028), the Anhui Provincial Natural Science Foundation (No. 1708085QD83). The authors would like to thank two anonymous reviewers for their valuable comments on the manuscript.
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Li, T., Wang, L., Chen, R. et al. Refining the empirical global pressure and temperature model with the ERA5 reanalysis and radiosonde data. J Geod 95, 31 (2021). https://doi.org/10.1007/s00190-021-01478-9
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DOI: https://doi.org/10.1007/s00190-021-01478-9