Impacts of FY-4A Atmospheric Motion Vectors on the Henan 7.20 Rainstorm Forecast in 2021
Atmospheric motion vectors (AMVs) derived from images of the geostationary satellite, Fengyun-4A (FY-4A), can provide high-spatiotemporal-resolution wind observations in the atmospheric middle and upper levels. To explore the potential benefits of these data for the numerical forecasting of severe w...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/22/5637 |
| _version_ | 1797464092759293952 |
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| author | Yanhui Xie Min Chen Shuting Zhang Jiancheng Shi Ruixia Liu |
| author_facet | Yanhui Xie Min Chen Shuting Zhang Jiancheng Shi Ruixia Liu |
| author_sort | Yanhui Xie |
| collection | DOAJ |
| description | Atmospheric motion vectors (AMVs) derived from images of the geostationary satellite, Fengyun-4A (FY-4A), can provide high-spatiotemporal-resolution wind observations in the atmospheric middle and upper levels. To explore the potential benefits of these data for the numerical forecasting of severe weather events, the characteristics of FY-4A AMVs in different channels were analyzed and three groups of assimilation experiments were conducted in this study. The impacts of FY-4A AMVs on the forecasts of the rainstorm that occurred in Henan province in China on 20 July 2021, were investigated based on the Weather Research and Forecasting (WRF) model. The results show that FY-4A AMVs with a higher quality indicator (QI) exhibited a lower error characteristic at the cost of a reduced sample size. The assimilation of FY-4A AMVs reduced the error of the upper-level wind fields in 24 h forecasts. A positive impact could also be obtained for 10 m wind in 24 h forecasts, with an improvement of up to 9.74% for the mean bias and 3.0% for the root-mean-square error due to the inclusion of FY-4A AMVs with a QI > 70. Assimilating the AMVs with a QI > 80, there was an overall positive impact on the CSI score skills of 6 h accumulated precipitation above 1.0 mm in the 24 h forecast. A significant improvement could be found in the forecasting of heavy rainfall above 25.0 mm after 6 h of the forecast. The spatial distribution of the 24 h accumulated heavy rainfall zone was closer to the observations with the assimilation of the FY-4A AMVs. The adjustment of the initial wind fields resulting from the FY-4A AMVs brought a clear benefit to the quantitative precipitation forecasting skills in the event of the Henan 7.20 rainstorm; however, the AMV data assimilation still had difficulty in capturing the hourly maximum rainfall and intensity well. |
| first_indexed | 2024-03-09T18:02:58Z |
| format | Article |
| id | doaj.art-64820c29c99742b7889ad0c21bb711a5 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T18:02:58Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-64820c29c99742b7889ad0c21bb711a52023-11-24T09:48:02ZengMDPI AGRemote Sensing2072-42922022-11-011422563710.3390/rs14225637Impacts of FY-4A Atmospheric Motion Vectors on the Henan 7.20 Rainstorm Forecast in 2021Yanhui Xie0Min Chen1Shuting Zhang2Jiancheng Shi3Ruixia Liu4Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, ChinaInstitute of Urban Meteorology, China Meteorological Administration, Beijing 100089, ChinaInstitute of Urban Meteorology, China Meteorological Administration, Beijing 100089, ChinaNational Space Science Center, Chinese Academy of Sciences, Beijing 100190, ChinaChina Meteorological Administration (CMA) Earth System Modeling and Prediction Centre (CEMC), Beijing 100081, ChinaAtmospheric motion vectors (AMVs) derived from images of the geostationary satellite, Fengyun-4A (FY-4A), can provide high-spatiotemporal-resolution wind observations in the atmospheric middle and upper levels. To explore the potential benefits of these data for the numerical forecasting of severe weather events, the characteristics of FY-4A AMVs in different channels were analyzed and three groups of assimilation experiments were conducted in this study. The impacts of FY-4A AMVs on the forecasts of the rainstorm that occurred in Henan province in China on 20 July 2021, were investigated based on the Weather Research and Forecasting (WRF) model. The results show that FY-4A AMVs with a higher quality indicator (QI) exhibited a lower error characteristic at the cost of a reduced sample size. The assimilation of FY-4A AMVs reduced the error of the upper-level wind fields in 24 h forecasts. A positive impact could also be obtained for 10 m wind in 24 h forecasts, with an improvement of up to 9.74% for the mean bias and 3.0% for the root-mean-square error due to the inclusion of FY-4A AMVs with a QI > 70. Assimilating the AMVs with a QI > 80, there was an overall positive impact on the CSI score skills of 6 h accumulated precipitation above 1.0 mm in the 24 h forecast. A significant improvement could be found in the forecasting of heavy rainfall above 25.0 mm after 6 h of the forecast. The spatial distribution of the 24 h accumulated heavy rainfall zone was closer to the observations with the assimilation of the FY-4A AMVs. The adjustment of the initial wind fields resulting from the FY-4A AMVs brought a clear benefit to the quantitative precipitation forecasting skills in the event of the Henan 7.20 rainstorm; however, the AMV data assimilation still had difficulty in capturing the hourly maximum rainfall and intensity well.https://www.mdpi.com/2072-4292/14/22/5637atmospheric motion vectorsFY-4Adata assimilationrainstorm forecast |
| spellingShingle | Yanhui Xie Min Chen Shuting Zhang Jiancheng Shi Ruixia Liu Impacts of FY-4A Atmospheric Motion Vectors on the Henan 7.20 Rainstorm Forecast in 2021 Remote Sensing atmospheric motion vectors FY-4A data assimilation rainstorm forecast |
| title | Impacts of FY-4A Atmospheric Motion Vectors on the Henan 7.20 Rainstorm Forecast in 2021 |
| title_full | Impacts of FY-4A Atmospheric Motion Vectors on the Henan 7.20 Rainstorm Forecast in 2021 |
| title_fullStr | Impacts of FY-4A Atmospheric Motion Vectors on the Henan 7.20 Rainstorm Forecast in 2021 |
| title_full_unstemmed | Impacts of FY-4A Atmospheric Motion Vectors on the Henan 7.20 Rainstorm Forecast in 2021 |
| title_short | Impacts of FY-4A Atmospheric Motion Vectors on the Henan 7.20 Rainstorm Forecast in 2021 |
| title_sort | impacts of fy 4a atmospheric motion vectors on the henan 7 20 rainstorm forecast in 2021 |
| topic | atmospheric motion vectors FY-4A data assimilation rainstorm forecast |
| url | https://www.mdpi.com/2072-4292/14/22/5637 |
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