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Estimation of the water vapor field by fusing GPS and surface meteorological observations on the Loess Plateau of China

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Abstract

Water vapor is one of the important atmospheric components of atmospheric circulation and dynamics, and its accurate and spatiotemporally continuous estimation is important for understanding the water vapor conveying mechanism and the hydrologic cycle. We proposed a new fusion strategy where the precipitable water vapor (PWV) derived from global positioning system (GPS) and surface meteorological observations was introduced. Compared to previous methods using radiosonde data, remote sensing satellite water vapor products, and atmospheric reanalysis products, our fusion strategy adopted the PWV calculated from the surface meteorological observations for the first time. It also has a potential near real-time capability for high temporal resolution water vapor monitoring in areas with sparse GPS station distribution (the average distance exceeds 100 km) such as mountainous areas, basins, and plateaus. Based on PWV data derived from 35 GPS and 237 surface meteorological stations, we established hourly fusion models through simplified spherical cap harmonic analysis for the Loess Plateau of China. The validation results show that when PWV data derived from ERA5 reanalysis and radiosonde in 2020 were used as reference values, the mean root-mean-square (RMS) of the PWV derived from fusion models based on GPS and surface meteorological observations were 3.87 and 2.51 mm, respectively. Compared to the strategy using only GPS observations, the accuracy of the model PWV was improved by approximately 60.4% by fusing GPS and surface meteorological PWV data when the ERA5 data is used as a references value. Compared to the strategy using only surface meteorological observations, the accuracy of the model PWV was respectively improved by approximately 16.0% and 32.7% after fusing GPS-derived PWV data when the ERA5 and radiosonde data are used as reference values. Therefore, through our fusion strategy, the accuracy of GPS PWV data and the spatial resolution of surface meteorological PWV data could be complementary in regard to water vapor field estimation. This study shows that the fusion strategy has a potential application prospect in near real-time water vapor monitoring for numerical weather predictions (NWP) data assimilation and short-term rainfall forecasting.

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Data availability

Radiosonde data before and after 2020 in China employed in this work are provided by the University of Wyoming at http://weather.uwyo.edu/upperair/sounding.html and http://weather.uwyo.edu/upperair/bufrraob.shtml, respectively. The CMONOC ZTD products are provided by the China Earthquake Administration at http://www.cgps.ac.cn. ERA5 reanalysis data are provided by ECMWF at https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-pressure-levels?tab=overview. The surface meteorological observations are provided by China Meteorological Data Service Center at http://data.cma.cn/.

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Acknowledgements

This work was supported by the Natural Science Research Start-up Foundation of Recruiting Talents of Nanjing University of Posts and Telecommunications (Grant No. NY221141) and the National Natural Science Foundation of China (Grant No. 42304027 and 41974026). We thank the ECMWF, University of Wyoming and IGRA, China Earthquake Administration, and China Meteorological Data Service Center for providing the ERA5 reanalysis data, radiosonde data, ZTD products, and hourly meteorological observations, respectively.

Funding

Natural Science Research Start-up Foundation of Recruiting Talents of Nanjing University of Posts and Telecommunications (Grant No.: NY221141); National Natural Science Foundation of China (Grant Nos.: 42304027, 41974026).

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Authors and Affiliations

  1. School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing, 210042, Jiangsu, China

    Liu Yang

  2. School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, 221116, Jiangsu, China

    Zengke Li, Yu Tian, Jingxiang Gao & Jianqing Fan

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  1. Liu Yang
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  2. Zengke Li
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Correspondence to Zengke Li.

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Yang, L., Li, Z., Tian, Y. et al. Estimation of the water vapor field by fusing GPS and surface meteorological observations on the Loess Plateau of China. GPS Solut 28, 55 (2024). https://doi.org/10.1007/s10291-023-01599-y

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