Preprints
https://doi.org/10.5194/essd-2024-395
https://doi.org/10.5194/essd-2024-395
08 Oct 2024
 | 08 Oct 2024
Status: this preprint is currently under review for the journal ESSD.

A Global Terrestrial Precipitable Water Vapor Dataset from 2012 to 2020 Based on Microwave Radiation Imager Measurements from Three Fengyun Satellites

Xinran Xia, Rubin Jiang, Min Min, Shengli Wu, Peng Zhang, and Xiangao Xia

Abstract. A global terrestrial precipitable water vapor (PWV) dataset has been developed using observations from the MicroWave Radiation Imager (MWRI) aboard the FY-3 satellite series (FY-3B, FY-3C and FY-3D) spanning 2012 to 2020. The dataset offers twice-daily PWV records at a spatial resolution of 0.25° × 0.25°, aligned with the ascending and descending orbits of the FY-3 satellites. The dataset was generated using an automated machine learning (ML) model that leverages MWRI-based features characterizing surface conditions and an enhanced Global Position System (GPS) PWV dataset as a reference. Trained on over one million sampling points from more than ten thousand stations worldwide, the model ensures a robust representation of global PWV variations. Independent evaluations against SuomiNet GPS and Integrated Global Radiosonde Archive Version 2 (IGRA2) PWV products yielded root mean square error (RMSE) of 4.47 mm and 3.89 mm, respectively, with RMSE values ranging from 2.90 to 5.49 mm across various surface conditions. The dataset effectively captures both spatial and temporal PWV variations, allowing for precise examination of localized and abrupt changes in water vapor induced by extreme weather events. Representing a significant advancement in global terrestrial PWV monitoring, the MWRI PWV dataset provides an all-weather, high-precision data record that bridges gaps in global coverage of passive microwave-based terrestrial PWV observations. It is a valuable resource for atmospheric research, climate modeling, water cycle studies, and beyond. The dataset is available at: https://doi.org/10.6084/m9.figshare.26712709 (Xia et al., 2024). 

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Xinran Xia, Rubin Jiang, Min Min, Shengli Wu, Peng Zhang, and Xiangao Xia

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2024-395', Anonymous Referee #1, 22 Oct 2024
  • RC2: 'Comment on essd-2024-395', Anonymous Referee #2, 05 Nov 2024
Xinran Xia, Rubin Jiang, Min Min, Shengli Wu, Peng Zhang, and Xiangao Xia

Data sets

A Global Terrestrial Precipitable Water Vapor Dataset from 2012 to 2020 Based on Microwave Radiation Imager Measurements from Three Fengyun Satellites Xiangao Xia et al. https://doi.org/10.6084/m9.figshare.26712709

Xinran Xia, Rubin Jiang, Min Min, Shengli Wu, Peng Zhang, and Xiangao Xia

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Short summary
Based on the MicroWave Radiation Imager aboard FY-3 series satellites, we developed a global terrestrial precipitable water vapor dataset from 2012 to 2020. This dataset overcomes the limitations of infrared observations and provides accurate, all-weather PWV data ,spanning all types of land surface. Researchers are expected to leverage it to explore the role of water vapor in weather patterns, refine precipitation forecasting, and validate climate simulations. 
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