Assimilating GOES‐16 ABI All‐Sky Brightness Temperature Into the HAFS Dual‐Resolution Self‐Consistent EnVar DA System: Methods for Observation Error Estimation and Impact on Hurricane Laura (2020)
Abstract This study investigates the impact of assimilating GOES‐16 all‐sky Advanced Baseline Imager (ABI) brightness temperature observations using a newly developed, continuously self‐cycled, dual‐resolution, 3DEnVar data assimilation system within the Hurricane Analysis and Forecast System. Focus...
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| Format: | Article |
| Language: | English |
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American Geophysical Union (AGU)
2025-07-01
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| Series: | Earth and Space Science |
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| Online Access: | https://doi.org/10.1029/2024EA004058 |
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| author | Xu Lu Xuguang Wang |
| author_facet | Xu Lu Xuguang Wang |
| author_sort | Xu Lu |
| collection | DOAJ |
| description | Abstract This study investigates the impact of assimilating GOES‐16 all‐sky Advanced Baseline Imager (ABI) brightness temperature observations using a newly developed, continuously self‐cycled, dual‐resolution, 3DEnVar data assimilation system within the Hurricane Analysis and Forecast System. Focusing on the pre‐rapid intensification period of Hurricane Laura, the results demonstrated that assimilating ABI observations without proper observation error treatment can be neutral or even detrimental. However, using a symmetric cloud impact approach to adaptively estimate observation errors enhances the Gaussianity of the Observation‐Minus‐Background Probability Distribution Functions, and significantly improves the analysis and predictions of Hurricane Laura. The improvements in the track forecasts can be attributed to better environmental analyses due to more effective use of clear sky observations, while the improved intensity forecasts stem from improved inner‐core dynamic and thermodynamic structures, achieved through the more effective use of cloudy‐sky observations. |
| format | Article |
| id | doaj-art-328bcb8306ac460da5b2f67718bfad53 |
| institution | Kabale University |
| issn | 2333-5084 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | American Geophysical Union (AGU) |
| record_format | Article |
| series | Earth and Space Science |
| spelling | doaj-art-328bcb8306ac460da5b2f67718bfad532025-08-20T03:58:41ZengAmerican Geophysical Union (AGU)Earth and Space Science2333-50842025-07-01127n/an/a10.1029/2024EA004058Assimilating GOES‐16 ABI All‐Sky Brightness Temperature Into the HAFS Dual‐Resolution Self‐Consistent EnVar DA System: Methods for Observation Error Estimation and Impact on Hurricane Laura (2020)Xu Lu0Xuguang Wang1School of Meteorology University of Oklahoma Norman OK USASchool of Meteorology University of Oklahoma Norman OK USAAbstract This study investigates the impact of assimilating GOES‐16 all‐sky Advanced Baseline Imager (ABI) brightness temperature observations using a newly developed, continuously self‐cycled, dual‐resolution, 3DEnVar data assimilation system within the Hurricane Analysis and Forecast System. Focusing on the pre‐rapid intensification period of Hurricane Laura, the results demonstrated that assimilating ABI observations without proper observation error treatment can be neutral or even detrimental. However, using a symmetric cloud impact approach to adaptively estimate observation errors enhances the Gaussianity of the Observation‐Minus‐Background Probability Distribution Functions, and significantly improves the analysis and predictions of Hurricane Laura. The improvements in the track forecasts can be attributed to better environmental analyses due to more effective use of clear sky observations, while the improved intensity forecasts stem from improved inner‐core dynamic and thermodynamic structures, achieved through the more effective use of cloudy‐sky observations.https://doi.org/10.1029/2024EA004058all‐sky brightness temperaturedata assimilationhurricaneHAFSself‐cycled EnVar |
| spellingShingle | Xu Lu Xuguang Wang Assimilating GOES‐16 ABI All‐Sky Brightness Temperature Into the HAFS Dual‐Resolution Self‐Consistent EnVar DA System: Methods for Observation Error Estimation and Impact on Hurricane Laura (2020) Earth and Space Science all‐sky brightness temperature data assimilation hurricane HAFS self‐cycled EnVar |
| title | Assimilating GOES‐16 ABI All‐Sky Brightness Temperature Into the HAFS Dual‐Resolution Self‐Consistent EnVar DA System: Methods for Observation Error Estimation and Impact on Hurricane Laura (2020) |
| title_full | Assimilating GOES‐16 ABI All‐Sky Brightness Temperature Into the HAFS Dual‐Resolution Self‐Consistent EnVar DA System: Methods for Observation Error Estimation and Impact on Hurricane Laura (2020) |
| title_fullStr | Assimilating GOES‐16 ABI All‐Sky Brightness Temperature Into the HAFS Dual‐Resolution Self‐Consistent EnVar DA System: Methods for Observation Error Estimation and Impact on Hurricane Laura (2020) |
| title_full_unstemmed | Assimilating GOES‐16 ABI All‐Sky Brightness Temperature Into the HAFS Dual‐Resolution Self‐Consistent EnVar DA System: Methods for Observation Error Estimation and Impact on Hurricane Laura (2020) |
| title_short | Assimilating GOES‐16 ABI All‐Sky Brightness Temperature Into the HAFS Dual‐Resolution Self‐Consistent EnVar DA System: Methods for Observation Error Estimation and Impact on Hurricane Laura (2020) |
| title_sort | assimilating goes 16 abi all sky brightness temperature into the hafs dual resolution self consistent envar da system methods for observation error estimation and impact on hurricane laura 2020 |
| topic | all‐sky brightness temperature data assimilation hurricane HAFS self‐cycled EnVar |
| url | https://doi.org/10.1029/2024EA004058 |
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