Assimilation of Fengyun-4A Atmospheric Motion Vectors and Its Impact on China Meteorological Administration—Beijing System Forecasts
The ever-increasing capacity of numerical weather prediction (NWP) models requires accurate flow information at higher spatial and temporal resolutions. The atmospheric motion vectors (AMVs) extracted from the Advanced Geostationary Radiation Imager (AGRI) mounted on the Fengyun-4A (FY-4A) satellite...
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MDPI AG
2024-12-01
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| author | Yanhui Xie Shuting Zhang Xin Sun Min Chen Jiancheng Shi Yu Xia Ruixia Liu |
| author_facet | Yanhui Xie Shuting Zhang Xin Sun Min Chen Jiancheng Shi Yu Xia Ruixia Liu |
| author_sort | Yanhui Xie |
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| description | The ever-increasing capacity of numerical weather prediction (NWP) models requires accurate flow information at higher spatial and temporal resolutions. The atmospheric motion vectors (AMVs) extracted from the Advanced Geostationary Radiation Imager (AGRI) mounted on the Fengyun-4A (FY-4A) satellite can provide information about atmospheric flow fields on small scales. This study focused on the assimilation of FY-4A AMVs and its impact on forecasts in the regional NWP system of the China Meteorological Administration—Beijing (CAM-BJ). The statistical characterization of FY-4A AMVs was firstly analyzed, and an optimal observation error in each vertical level was obtained. Three groups of retrospective runs over a one-month period were conducted, and the impact of assimilating the AMVs with different strategies on the forecasts of the CMA-BJ system were compared and evaluated. The results suggested that the optimal observation errors reduced the standard deviation of the background departures for U and V wind, leading to an improvement in the standard deviation in the corresponding analysis departures of about 8.3% for U wind and 7.3% for V wind. Assimilating FY-4A AMV data with a quality indicator (QI) above 80 and the optimal observation errors reduced the error of upper wind forecast in the CMA-BJ system. A benefit was also obtained in the error of surface wind forecast after 6 h of the forecasts, although it was not significant. For rainfall forecast with different thresholds, the score skills increased slightly after 6 h of the forecasts. There was an overall improvement for the overprediction of 24 h accumulated precipitation forecast including the AMVs, even when conventional observations were relatively rich. The application of FY-4A AMVs with a QI > 80 and adjustment to observation errors has a positive impact on the upper wind forecast in the CMA-BJ system, improving the score skill of rainfall forecasting. |
| format | Article |
| id | doaj-art-df2783648cb24793b624b8d4b9da7b21 |
| institution | OA Journals |
| issn | 2072-4292 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-df2783648cb24793b624b8d4b9da7b212025-08-20T01:55:31ZengMDPI AGRemote Sensing2072-42922024-12-011623456110.3390/rs16234561Assimilation of Fengyun-4A Atmospheric Motion Vectors and Its Impact on China Meteorological Administration—Beijing System ForecastsYanhui Xie0Shuting Zhang1Xin Sun2Min Chen3Jiancheng Shi4Yu Xia5Ruixia Liu6Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, ChinaInstitute of Urban Meteorology, China Meteorological Administration, Beijing 100089, ChinaInner Mongolia Meteorological Observatory, Inner Mongolia Meteorological Service, Hohhot 010051, ChinaInstitute of Urban Meteorology, China Meteorological Administration, Beijing 100089, ChinaNational Space Science Center, Chinese Academy of Sciences, Beijing 100190, ChinaInstitute of Urban Meteorology, China Meteorological Administration, Beijing 100089, ChinaChina Meteorological Administration (CMA) Earth System Modeling and Prediction Centre (CEMC), Beijing 100081, ChinaThe ever-increasing capacity of numerical weather prediction (NWP) models requires accurate flow information at higher spatial and temporal resolutions. The atmospheric motion vectors (AMVs) extracted from the Advanced Geostationary Radiation Imager (AGRI) mounted on the Fengyun-4A (FY-4A) satellite can provide information about atmospheric flow fields on small scales. This study focused on the assimilation of FY-4A AMVs and its impact on forecasts in the regional NWP system of the China Meteorological Administration—Beijing (CAM-BJ). The statistical characterization of FY-4A AMVs was firstly analyzed, and an optimal observation error in each vertical level was obtained. Three groups of retrospective runs over a one-month period were conducted, and the impact of assimilating the AMVs with different strategies on the forecasts of the CMA-BJ system were compared and evaluated. The results suggested that the optimal observation errors reduced the standard deviation of the background departures for U and V wind, leading to an improvement in the standard deviation in the corresponding analysis departures of about 8.3% for U wind and 7.3% for V wind. Assimilating FY-4A AMV data with a quality indicator (QI) above 80 and the optimal observation errors reduced the error of upper wind forecast in the CMA-BJ system. A benefit was also obtained in the error of surface wind forecast after 6 h of the forecasts, although it was not significant. For rainfall forecast with different thresholds, the score skills increased slightly after 6 h of the forecasts. There was an overall improvement for the overprediction of 24 h accumulated precipitation forecast including the AMVs, even when conventional observations were relatively rich. The application of FY-4A AMVs with a QI > 80 and adjustment to observation errors has a positive impact on the upper wind forecast in the CMA-BJ system, improving the score skill of rainfall forecasting.https://www.mdpi.com/2072-4292/16/23/4561FY-4Aatmospheric motion vectorsassimilation strategyCMA-BJforecasts |
| spellingShingle | Yanhui Xie Shuting Zhang Xin Sun Min Chen Jiancheng Shi Yu Xia Ruixia Liu Assimilation of Fengyun-4A Atmospheric Motion Vectors and Its Impact on China Meteorological Administration—Beijing System Forecasts Remote Sensing FY-4A atmospheric motion vectors assimilation strategy CMA-BJ forecasts |
| title | Assimilation of Fengyun-4A Atmospheric Motion Vectors and Its Impact on China Meteorological Administration—Beijing System Forecasts |
| title_full | Assimilation of Fengyun-4A Atmospheric Motion Vectors and Its Impact on China Meteorological Administration—Beijing System Forecasts |
| title_fullStr | Assimilation of Fengyun-4A Atmospheric Motion Vectors and Its Impact on China Meteorological Administration—Beijing System Forecasts |
| title_full_unstemmed | Assimilation of Fengyun-4A Atmospheric Motion Vectors and Its Impact on China Meteorological Administration—Beijing System Forecasts |
| title_short | Assimilation of Fengyun-4A Atmospheric Motion Vectors and Its Impact on China Meteorological Administration—Beijing System Forecasts |
| title_sort | assimilation of fengyun 4a atmospheric motion vectors and its impact on china meteorological administration beijing system forecasts |
| topic | FY-4A atmospheric motion vectors assimilation strategy CMA-BJ forecasts |
| url | https://www.mdpi.com/2072-4292/16/23/4561 |
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