Research on the Application of Atmospheric Motion Vector from MetOp Satellite Series in CMA-GFS

Atmospheric motion vector (AMV) products from EUMETSAT’s MetOp satellite series, including MetOp-B, MetOp-C, and the MetOp-B/C tandem (MetOp-Dual), have been assimilated at many numerical weather prediction centers worldwide. However, they have not yet been applied in the China Meteorological Administration’s Global Forecast System (CMA-GFS). This study addresses this gap by developing assimilation techniques, including quality control and thinning methods for MetOp AMVs. Based on these techniques, one-month assimilation and forecasting experiments reveal that MetOp AMVs increased the AMV volume in CMA-GFS by 25%, filling certain gaps over polar and oceanic areas. Notable and steady improvements in the background of CMA-GFS have been found, particularly in polar and high-latitude regions. The usable forecast lead time for the global 500 hPa geopotential height is extended by 0.22 days, enhancing the reliability of medium-range forecasts. Furthermore, the more substantial improvements in short-range (0–3 days) forecasting, potentially benefit severe weather alerting. This study marks the first to successfully apply MetOp-B, MetOp-C and MetOp-Dual products in CMA-GFS, confirming their value for improving the performance of the system.

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Publication Details

Journal
Remote Sensing
Published
2025-10-23
DOI
https://doi.org/10.3390/rs17213519
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
0.00

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article

Research on the Application of Atmospheric Motion Vector from MetOp Satellite Series in CMA-GFS

Xiaomin Wan, Jiali Ma, Yan Liu
Remote Sensing
Meteorological Phenomena and Simulations
article

Research on the Application of Atmospheric Motion Vector from MetOp Satellite Series in CMA-GFS

Xiaomin Wan, Jiali Ma, Yan Liu
article en

Abstract

Atmospheric motion vector (AMV) products from EUMETSAT’s MetOp satellite series, including MetOp-B, MetOp-C, and the MetOp-B/C tandem (MetOp-Dual), have been assimilated at many numerical weather prediction centers worldwide. However, they have not yet been applied in the China Meteorological Administration’s Global Forecast System (CMA-GFS). This study addresses this gap by developing assimilation techniques, including quality control and thinning methods for MetOp AMVs. Based on these techniques, one-month assimilation and forecasting experiments reveal that MetOp AMVs increased the AMV volume in CMA-GFS by 25%, filling certain gaps over polar and oceanic areas. Notable and steady improvements in the background of CMA-GFS have been found, particularly in polar and high-latitude regions. The usable forecast lead time for the global 500 hPa geopotential height is extended by 0.22 days, enhancing the reliability of medium-range forecasts. Furthermore, the more substantial improvements in short-range (0–3 days) forecasting, potentially benefit severe weather alerting. This study marks the first to successfully apply MetOp-B, MetOp-C and MetOp-Dual products in CMA-GFS, confirming their value for improving the performance of the system.

Remote SensingVol. 17(21)
China Meteorological Administration (CN), Chinese Academy of Meteorological Sciences (CN)
National Natural Science Foundation of China, China Meteorological Administration
Openalex Percentile: Top 65%
Meteorological Phenomena and Simulations
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