Research on the Application of Atmospheric Motion Vector from MetOp Satellite Series in CMA-GFS.
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| Title: | Research on the Application of Atmospheric Motion Vector from MetOp Satellite Series in CMA-GFS. |
|---|---|
| Authors: | Ma, Jiali1,2 (AUTHOR), Liu, Yan1,2 (AUTHOR) liuyan@cma.gov.cn, Wan, Xiaomin1,2 (AUTHOR) |
| Source: | Remote Sensing. Nov2025, Vol. 17 Issue 21, p3519. 19p. |
| Subjects: | Data assimilation, Meteorological satellites, Atmospheric circulation, Forecasting, Weather forecasting, Numerical weather forecasting, Quality control, Cold regions |
| Abstract: | Highlights: What are the main findings? This study has developed assimilation techniques encompassing quality control and thinning schemes for MetOp-Dual, MetOp-B and MetOp-C based on CMA-GFS (China Meteorological Administration Global Forecast System), which fills the gap in the application of such data in CMA-GFS. MetOp AMV products, through quality control and thinning, have increased the AMVs in CMA-GFS by 25%. By effectively reducing the observational gaps in polar and oceanic areas, the one-month assimilation experiment of MetOp AMV improves CMA-GFS's backgrounds (particularly the polar and high-latitude regions) and advances the usable forecast lead time for global 500 hPa geopotential height by 0.22 days. What are the implications of the main findings? This study, for the first time, applies MetOp-Dual, MetOp-B and MetOp-C products in CMA-GFS, which significantly promotes the AMV data utilization rate in CMA-GFS. The one-month assimilation experiment of MetOp AMV products significantly improves the model background and forecasting performance of the CMA-GFS, which implies the MetOp AMV products can play a positive role in promoting the forecast performance of the operational CMA-GFS in the long run. 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. [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 189611861 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Research on the Application of Atmospheric Motion Vector from MetOp Satellite Series in CMA-GFS. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ma%2C+Jiali%22">Ma, Jiali</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Yan%22">Liu, Yan</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> liuyan@cma.gov.cn</i><br /><searchLink fieldCode="AR" term="%22Wan%2C+Xiaomin%22">Wan, Xiaomin</searchLink><relatesTo>1,2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Nov2025, Vol. 17 Issue 21, p3519. 19p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Data+assimilation%22">Data assimilation</searchLink><br /><searchLink fieldCode="DE" term="%22Meteorological+satellites%22">Meteorological satellites</searchLink><br /><searchLink fieldCode="DE" term="%22Atmospheric+circulation%22">Atmospheric circulation</searchLink><br /><searchLink fieldCode="DE" term="%22Forecasting%22">Forecasting</searchLink><br /><searchLink fieldCode="DE" term="%22Weather+forecasting%22">Weather forecasting</searchLink><br /><searchLink fieldCode="DE" term="%22Numerical+weather+forecasting%22">Numerical weather forecasting</searchLink><br /><searchLink fieldCode="DE" term="%22Quality+control%22">Quality control</searchLink><br /><searchLink fieldCode="DE" term="%22Cold+regions%22">Cold regions</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Highlights: What are the main findings? This study has developed assimilation techniques encompassing quality control and thinning schemes for MetOp-Dual, MetOp-B and MetOp-C based on CMA-GFS (China Meteorological Administration Global Forecast System), which fills the gap in the application of such data in CMA-GFS. MetOp AMV products, through quality control and thinning, have increased the AMVs in CMA-GFS by 25%. By effectively reducing the observational gaps in polar and oceanic areas, the one-month assimilation experiment of MetOp AMV improves CMA-GFS's backgrounds (particularly the polar and high-latitude regions) and advances the usable forecast lead time for global 500 hPa geopotential height by 0.22 days. What are the implications of the main findings? This study, for the first time, applies MetOp-Dual, MetOp-B and MetOp-C products in CMA-GFS, which significantly promotes the AMV data utilization rate in CMA-GFS. The one-month assimilation experiment of MetOp AMV products significantly improves the model background and forecasting performance of the CMA-GFS, which implies the MetOp AMV products can play a positive role in promoting the forecast performance of the operational CMA-GFS in the long run. 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. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/rs17213519 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 19 StartPage: 3519 Subjects: – SubjectFull: Data assimilation Type: general – SubjectFull: Meteorological satellites Type: general – SubjectFull: Atmospheric circulation Type: general – SubjectFull: Forecasting Type: general – SubjectFull: Weather forecasting Type: general – SubjectFull: Numerical weather forecasting Type: general – SubjectFull: Quality control Type: general – SubjectFull: Cold regions Type: general Titles: – TitleFull: Research on the Application of Atmospheric Motion Vector from MetOp Satellite Series in CMA-GFS. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ma, Jiali – PersonEntity: Name: NameFull: Liu, Yan – PersonEntity: Name: NameFull: Wan, Xiaomin IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: Nov2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 20724292 Numbering: – Type: volume Value: 17 – Type: issue Value: 21 Titles: – TitleFull: Remote Sensing Type: main |
| ResultId | 1 |
