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Remote Sensing
Volume 18
Issue 3
10.3390/rs18030379
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Article

Assimilating FY4A AMV Winds with the Nudging–Forced–3DVar Method for Promoting the Numerical Nowcasting of “7.20” Rainstorm over Zhengzhou

by
Yakai Guo
1,
Aifang Su
1,
Changliang Shao
2,*,
Guanjun Niu
3,
Dongmei Xu
4 and
Yanna Gao
5
1
Henan Meteorological Observatory, China Meteorological Administration, Zhengzhou 450003, China
2
Meteorological Observation Centre, China Meteorological Administration, Beijing 100081, China
3
Meteorological Development and Planning Institute, China Meteorological Administration, Beijing 100081, China
4
School of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing 210044, China
5
Henan Provincal Zhengzhou Meteorological Bureau, China Meteorological Administration, Zhengzhou 450003, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2026, 18(3), 379; https://doi.org/10.3390/rs18030379
Submission received: 19 November 2025 / Revised: 8 January 2026 / Accepted: 20 January 2026 / Published: 23 January 2026
(This article belongs to the Section Atmospheric Remote Sensing)
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Abstract

Geostationary atmospheric motion vectors (e.g., FY4A AMVs) are routine mid-upper atmospheric observations used in numerical weather prediction (NWP) models, yet their complex spatiotemporal errors and assimilation limitations, i.e., high-temporal/coarse-spatial data and large-scale-adjustment/direct-assimilation scheme, leave unclear impacts of AMVs assimilation on nowcasting forecasts. To this end, a Nudging-Forced–3DVar scheme (NFV) is designed within a multi-scale (i.e., 12, 4, and 1 km) regional NWP framework to exploit AMVs characteristics; ablation experiments for the Zhengzhou “7.20” rainstorm isolate Nudging and 3DVar impacts on assimilation and nowcasting. Results show the following: (1) large-scale Nudging and high-resolution 3DVar both improve mid-upper analyses, with the former ingesting more observations; (2) Nudging retains large-scale background updates but yields significant misses, whereas 3DVar intensifies rainfall extremes yet blurs fine structures; (3) NFV merges its strengths, modulating deep convection through upper-level systems and markedly improving rainfall spatiotemporal patterns. Therefore, NFV is recommended for the FY4A AMVs’ future numerical nowcasting, which provides useful guidance for the regional application of geostationary 3D winds.
Keywords: FY4A AMVs; nudging; 3DVar; “7.20” rainstorm; nowcasting FY4A AMVs; nudging; 3DVar; “7.20” rainstorm; nowcasting
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MDPI and ACS Style

Guo, Y.; Su, A.; Shao, C.; Niu, G.; Xu, D.; Gao, Y. Assimilating FY4A AMV Winds with the Nudging–Forced–3DVar Method for Promoting the Numerical Nowcasting of “7.20” Rainstorm over Zhengzhou. Remote Sens. 2026, 18, 379. https://doi.org/10.3390/rs18030379

AMA Style

Guo Y, Su A, Shao C, Niu G, Xu D, Gao Y. Assimilating FY4A AMV Winds with the Nudging–Forced–3DVar Method for Promoting the Numerical Nowcasting of “7.20” Rainstorm over Zhengzhou. Remote Sensing. 2026; 18(3):379. https://doi.org/10.3390/rs18030379

Chicago/Turabian Style

Guo, Yakai, Aifang Su, Changliang Shao, Guanjun Niu, Dongmei Xu, and Yanna Gao. 2026. "Assimilating FY4A AMV Winds with the Nudging–Forced–3DVar Method for Promoting the Numerical Nowcasting of “7.20” Rainstorm over Zhengzhou" Remote Sensing 18, no. 3: 379. https://doi.org/10.3390/rs18030379

APA Style

Guo, Y., Su, A., Shao, C., Niu, G., Xu, D., & Gao, Y. (2026). Assimilating FY4A AMV Winds with the Nudging–Forced–3DVar Method for Promoting the Numerical Nowcasting of “7.20” Rainstorm over Zhengzhou. Remote Sensing, 18(3), 379. https://doi.org/10.3390/rs18030379

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