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Global grid-based Tm model with vertical adjustment for GNSS precipitable water retrieval

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Abstract

Atmospheric weighted mean temperature, Tm, is a key parameter in ground-based GNSS precipitable water (PW) retrieval, especially for a real-time mode. Considering the seasonal variability of the Tm vertical gradient across the globe, a global grid-based Tm model with seasonal vertical adjustments was developed based on 6-hourly ERA-Interim pressure levels product from European Centre for Medium-Range Weather Forecasts (ECMWF) covering the period 2011–2017. The performance of the proposed global Tm model called GTm_R was evaluated by two kinds of data sources, including sounding profiles at 577 globally distributed radiosonde stations and ERA-Interim reanalysis product throughout the year 2018. Our results show the excellent performance of the developed model GTm_R against other models when compared with high-quality ERA-Interim product and radiosonde data, especially in the ocean area and regions with high-elevation terrain. GTm_R can generally achieve a global mean bias/RMSE of − 0.1/3.1 K in contrast to ERA-Interim-derived Tm and − 0.2/3.8 K in comparison with radiosonde-derived Tm, which is corresponding to a 5%-8% improvement against GPT2w and GTm_III across the globe. Moreover, GTm_R can achieve global mean \(\sigma_{{\text{PW}}}\) and \(\sigma_{{\text{PW}}}\)/PW values of 0.26 mm and 1.36%, respectively. For the proportion of PW uncertainty in terms of RMSE below 0.4 mm, GTm_R increased by about 6%, 3%, and 2% over Bevis formula, GTm_III, and GPT2w, respectively. Thus, the developed global Tm model GTm_R that considers seasonal vertical adjustments is capable of deriving accurate and reliable Tm values for real-time or near real-time PW retrieval from GNSS measurements, which will be of great significance to real-time or nowcasting extreme weather forecasting.

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All data and materials supporting the conclusions of this article are available; they are either deposited in publicly available repositories or presented in the related paper.

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Acknowledgments

We would like to acknowledge the National Oceanic and Atmospheric Administration (NOAA) for the provision of IGRA radiosonde measurements and appreciate the European Centre for Medium-Range Weather Forecasts (ECMWF) for providing ERA-Interim atmospheric reanalysis product. We also thank two anonymous reviewers for their constructive comments. This work was supported by the National Natural Science Foundation of China (Nos. 41374002 and 41404031). Linguo Yuan is funded by the National Program for Support of Top-notch Young Professionals.

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Authors and Affiliations

  1. Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 611756, China

    Qinzheng Li, Linguo Yuan & Zhongshan Jiang

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

    Peng Chen

  3. Deutsches Geodätisches Forschungsinstitut der Technischen Universität München (DGFI-TUM), Arcisstraße 21, 80333, Munich, Germany

    Peng Chen

  4. Institute of Earth Sciences, Academia Sinica, Taipei, 11529, Taiwan

    Zhongshan Jiang

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  1. Qinzheng Li
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  2. Linguo Yuan
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Correspondence to Linguo Yuan.

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Li, Q., Yuan, L., Chen, P. et al. Global grid-based Tm model with vertical adjustment for GNSS precipitable water retrieval. GPS Solut 24, 73 (2020). https://doi.org/10.1007/s10291-020-00988-x

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