Enhanced Moisture Retrieval Near Boundary Layer From Satellite Sounder Data Through Atmospheric‐Surface Radiance Separation
Abstract Accurate satellite‐based retrieval of boundary‐layer water vapor over land is crucial for understanding the Earth‐atmosphere system but remains challenging due to the interaction of surface parameters on low‐level atmosphere‐sensitive channels. This study proposes a novel approach to explic...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2025-03-01
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| Series: | Geophysical Research Letters |
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| Online Access: | https://doi.org/10.1029/2024GL113404 |
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| _version_ | 1850187481552519168 |
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| author | Ronglian Zhou Di Di Jun Li Zhenglong Li |
| author_facet | Ronglian Zhou Di Di Jun Li Zhenglong Li |
| author_sort | Ronglian Zhou |
| collection | DOAJ |
| description | Abstract Accurate satellite‐based retrieval of boundary‐layer water vapor over land is crucial for understanding the Earth‐atmosphere system but remains challenging due to the interaction of surface parameters on low‐level atmosphere‐sensitive channels. This study proposes a novel approach to explicitly extract the upwelling atmospheric radiance (Ra) from the total radiance (Rt) observed by the Infrared Atmospheric Sounding Interferometer (IASI), using a Residual Multi‐Layer Perceptron model. A modified one‐dimensional variational algorithm for surface‐free radiances is also developed. The radiance extraction model, trained on simulated IASI radiances, is applied to IASI observations over mainland Australia in January and February of 2022. Validated against ERA5 and radiosonde observations, compared with the traditional Rt‐based method, the Ra‐based atmospheric profile retrievals show distinct improvements in boundary‐layer humidity retrieval with at least 20% error reduction. This approach provides a new thought to enhance humidity retrievals from hyperspectral sounders and benefits other quantitative applications such as data assimilation. |
| format | Article |
| id | doaj-art-dad468c870b543d7bd279cd0c85dfdc0 |
| institution | OA Journals |
| issn | 0094-8276 1944-8007 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | Geophysical Research Letters |
| spelling | doaj-art-dad468c870b543d7bd279cd0c85dfdc02025-08-20T02:16:05ZengWileyGeophysical Research Letters0094-82761944-80072025-03-01525n/an/a10.1029/2024GL113404Enhanced Moisture Retrieval Near Boundary Layer From Satellite Sounder Data Through Atmospheric‐Surface Radiance SeparationRonglian Zhou0Di Di1Jun Li2Zhenglong Li3Chinese Academy of Meteorological Sciences China Meteorological Administration Beijing ChinaCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science and Technology Nanjing ChinaKey Laboratory of Radiometric Calibration and Validation for Environmental Satellites National Satellite Meteorological Center (National Center for Space Weather) China Meteorological Administration Beijing ChinaCooperative Institute for Meteorological Satellite Studies University of Wisconsin–Madison Madison WI USAAbstract Accurate satellite‐based retrieval of boundary‐layer water vapor over land is crucial for understanding the Earth‐atmosphere system but remains challenging due to the interaction of surface parameters on low‐level atmosphere‐sensitive channels. This study proposes a novel approach to explicitly extract the upwelling atmospheric radiance (Ra) from the total radiance (Rt) observed by the Infrared Atmospheric Sounding Interferometer (IASI), using a Residual Multi‐Layer Perceptron model. A modified one‐dimensional variational algorithm for surface‐free radiances is also developed. The radiance extraction model, trained on simulated IASI radiances, is applied to IASI observations over mainland Australia in January and February of 2022. Validated against ERA5 and radiosonde observations, compared with the traditional Rt‐based method, the Ra‐based atmospheric profile retrievals show distinct improvements in boundary‐layer humidity retrieval with at least 20% error reduction. This approach provides a new thought to enhance humidity retrievals from hyperspectral sounders and benefits other quantitative applications such as data assimilation.https://doi.org/10.1029/2024GL113404moisture retrievalplanetary boundary layerhyperspectral infrared sounder |
| spellingShingle | Ronglian Zhou Di Di Jun Li Zhenglong Li Enhanced Moisture Retrieval Near Boundary Layer From Satellite Sounder Data Through Atmospheric‐Surface Radiance Separation Geophysical Research Letters moisture retrieval planetary boundary layer hyperspectral infrared sounder |
| title | Enhanced Moisture Retrieval Near Boundary Layer From Satellite Sounder Data Through Atmospheric‐Surface Radiance Separation |
| title_full | Enhanced Moisture Retrieval Near Boundary Layer From Satellite Sounder Data Through Atmospheric‐Surface Radiance Separation |
| title_fullStr | Enhanced Moisture Retrieval Near Boundary Layer From Satellite Sounder Data Through Atmospheric‐Surface Radiance Separation |
| title_full_unstemmed | Enhanced Moisture Retrieval Near Boundary Layer From Satellite Sounder Data Through Atmospheric‐Surface Radiance Separation |
| title_short | Enhanced Moisture Retrieval Near Boundary Layer From Satellite Sounder Data Through Atmospheric‐Surface Radiance Separation |
| title_sort | enhanced moisture retrieval near boundary layer from satellite sounder data through atmospheric surface radiance separation |
| topic | moisture retrieval planetary boundary layer hyperspectral infrared sounder |
| url | https://doi.org/10.1029/2024GL113404 |
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