Research on PWV fusion based on ERA5 PWV and FY-4A PWV in Chinese mainland

High precision and high spatiotemporal resolution of precipitable water vapor (PWV) serve as fundamental support for meteorological research , severe weather forecasting and warning systems, as well as long-term climate change trend analysis. The FY-4A PWV has been widely utilized in PWV research due to its high observational accuracy and superior spatial resolution. However, there are many missing values in the FY-4A PWV due to the influence of weather and cloud cover. The ERA5 PWV has the advantages of high temporal resolution, complete data, rapid updates, and a multitude of parameters, but its spatial resolution is relatively low at 0.25° × 0.25°. Therefore, the focus of this study is to integrate the advantages of multiple datasets to obtain high-precision PWV data with superior spatiotemporal resolution and completeness. This study takes the Chinese Mainland as research area, the ERA5 PWV was interpolated to the same spatial resolution as the FY-4A PWV (4km × 4 km) using the cubic convolution interpolation, and the interpolated ERA5 PWV was used to fill in the missing values of FY-4A PWV. Based on their respective precision weights, the datasets were integrated through the fusion model to generate a complete and high-accuracy PWV product. The results show that more than 55 % of the interpolated ERA5 PWV has a correlation coefficient of more than 0.9 with the GNSS PWV, and the difference in the ERA5 PWV accuracy before and after interpolation is within 3 mm in each region. By establishing regional and seasonal data fusion model, the RMSE of the PWV after fusion can be relatively improved by 0.34 %–24.96 %,0.36 %–29.39 %,0.78 %–27.94 %,0.78 %–34.31 % for the four seasons, respectively. The fusion effect is better in spring and winter, and the fusion PWV error is basically within 4 mm. This study achieves the acquisition of high-precision PWV data with a spatial resolution of 4km × 4 km on an hourly basis in Chinese mainland. The fused PWV can provide an important database for further applications and research. • Assessment of ERA5 PWV and FY-4A PWV by using GNSS PWV provided by CMONOC. • Interpolation of ERA5 PWV using cubic convolution interpolation improves the spatial resolution. • The interpolated ERA5 PWV is fused with the FY-4A PWV, and ERA5 fills the vacancy value of the FY-4A. A more complete PWV data can be obtained based on ensuring high resolution. • The fusion of PWV effectively utilizes the advantages of complementary observation of multiple technologies to provide high-precision water vapor.

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Publication Details

Journal
Journal of Atmospheric and Solar-Terrestrial Physics
Published
2025-04-24
DOI
https://doi.org/10.1016/j.jastp.2025.106526
Primary Topic
Magnetic confinement fusion research
Type
article
Field-Weighted Citation Impact
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article

Research on PWV fusion based on ERA5 PWV and FY-4A PWV in Chinese mainland

Yong Wang, Yanping Liu, Wei Du, Xiaoni Meng et al.
Journal of Atmospheric and Solar-Terrestrial Physics
Magnetic confinement fusion research
article

Research on PWV fusion based on ERA5 PWV and FY-4A PWV in Chinese mainland

Yong Wang, Yanping Liu, Wei Du, Xiaoni Meng, Xiao Liu, Jing Huang
article en

Abstract

High precision and high spatiotemporal resolution of precipitable water vapor (PWV) serve as fundamental support for meteorological research , severe weather forecasting and warning systems, as well as long-term climate change trend analysis. The FY-4A PWV has been widely utilized in PWV research due to its high observational accuracy and superior spatial resolution. However, there are many missing values in the FY-4A PWV due to the influence of weather and cloud cover. The ERA5 PWV has the advantages of high temporal resolution, complete data, rapid updates, and a multitude of parameters, but its spatial resolution is relatively low at 0.25° × 0.25°. Therefore, the focus of this study is to integrate the advantages of multiple datasets to obtain high-precision PWV data with superior spatiotemporal resolution and completeness. This study takes the Chinese Mainland as research area, the ERA5 PWV was interpolated to the same spatial resolution as the FY-4A PWV (4km × 4 km) using the cubic convolution interpolation, and the interpolated ERA5 PWV was used to fill in the missing values of FY-4A PWV. Based on their respective precision weights, the datasets were integrated through the fusion model to generate a complete and high-accuracy PWV product. The results show that more than 55 % of the interpolated ERA5 PWV has a correlation coefficient of more than 0.9 with the GNSS PWV, and the difference in the ERA5 PWV accuracy before and after interpolation is within 3 mm in each region. By establishing regional and seasonal data fusion model, the RMSE of the PWV after fusion can be relatively improved by 0.34 %–24.96 %,0.36 %–29.39 %,0.78 %–27.94 %,0.78 %–34.31 % for the four seasons, respectively. The fusion effect is better in spring and winter, and the fusion PWV error is basically within 4 mm. This study achieves the acquisition of high-precision PWV data with a spatial resolution of 4km × 4 km on an hourly basis in Chinese mainland. The fused PWV can provide an important database for further applications and research. • Assessment of ERA5 PWV and FY-4A PWV by using GNSS PWV provided by CMONOC. • Interpolation of ERA5 PWV using cubic convolution interpolation improves the spatial resolution. • The interpolated ERA5 PWV is fused with the FY-4A PWV, and ERA5 fills the vacancy value of the FY-4A. A more complete PWV data can be obtained based on ensuring high resolution. • The fusion of PWV effectively utilizes the advantages of complementary observation of multiple technologies to provide high-precision water vapor.

Journal of Atmospheric and Solar-Terrestrial PhysicsVol. 271
Tianjin Chengjian University (CN), China Earthquake Administration (CN), Anhui University of Technology (CN)
Openalex Percentile: Top 96%
Magnetic confinement fusion research
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