Modeling Snow and Ice Microwave Emissions in the Arctic for a Multi‐Parameter Retrieval of Surface and Atmospheric Variables From Microwave Radiometer Satellite Data
Abstract Monitoring surface and atmospheric parameters—like water vapor—is challenging in the Arctic, despite the daily Arctic‐wide coverage of spaceborne microwave radiometer data. This is mainly due to the difficulties in characterizing the sea ice surface emission: sea ice and snow microwave emis...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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American Geophysical Union (AGU)
2023-10-01
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| Series: | Earth and Space Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2023EA003177 |
| _version_ | 1797648007266566144 |
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| author | Janna E. Rückert Marcus Huntemann Rasmus Tage Tonboe Gunnar Spreen |
| author_facet | Janna E. Rückert Marcus Huntemann Rasmus Tage Tonboe Gunnar Spreen |
| author_sort | Janna E. Rückert |
| collection | DOAJ |
| description | Abstract Monitoring surface and atmospheric parameters—like water vapor—is challenging in the Arctic, despite the daily Arctic‐wide coverage of spaceborne microwave radiometer data. This is mainly due to the difficulties in characterizing the sea ice surface emission: sea ice and snow microwave emission is high and highly variable. There are very few data sets combining relevant in situ measurements with co‐located remote sensing data, which further complicates the development of accurate retrieval algorithms. Here, we present a multi‐parameter retrieval based on the inversion of a forward model for both, atmosphere and surface, for non‐melting conditions. The model consists of a layered microwave emission model of snow and ice. Since snow scattering and emission effects, as well as temperature gradients, are taken into account, a high variability in brightness temperatures can be simulated. For ocean regions and the atmosphere existing parameterized forward models are used. By using optimal estimation, the forward model can be inverted allowing for the simultaneous and consistent retrieval of nine variables: integrated water vapor, liquid water path, sea ice concentration, multi‐year ice fraction, snow depth, snow‐ice interface temperature and snow‐air interface temperature as well as sea‐surface temperature and wind speed (over open ocean). In addition, the method provides retrieval uncertainty estimates for each retrieved parameter. To evaluate the forward model as well as the retrieval, we use the extensive data sets acquired during the year‐long Arctic expedition Multidisciplinary drifting Observatory for the Study of Arctic Climate (2019–2020) as a reference. |
| first_indexed | 2024-03-11T15:25:53Z |
| format | Article |
| id | doaj.art-237b7ec85e7e4e428f26f0515f4e36e9 |
| institution | Directory Open Access Journal |
| issn | 2333-5084 |
| language | English |
| last_indexed | 2024-03-11T15:25:53Z |
| publishDate | 2023-10-01 |
| publisher | American Geophysical Union (AGU) |
| record_format | Article |
| series | Earth and Space Science |
| spelling | doaj.art-237b7ec85e7e4e428f26f0515f4e36e92023-10-27T17:48:33ZengAmerican Geophysical Union (AGU)Earth and Space Science2333-50842023-10-011010n/an/a10.1029/2023EA003177Modeling Snow and Ice Microwave Emissions in the Arctic for a Multi‐Parameter Retrieval of Surface and Atmospheric Variables From Microwave Radiometer Satellite DataJanna E. Rückert0Marcus Huntemann1Rasmus Tage Tonboe2Gunnar Spreen3University of Bremen Institute of Environmental Physics Bremen GermanyUniversity of Bremen Institute of Environmental Physics Bremen GermanyNational Space Institute Technical University of Denmark (DTU Space) Lyngby DenmarkUniversity of Bremen Institute of Environmental Physics Bremen GermanyAbstract Monitoring surface and atmospheric parameters—like water vapor—is challenging in the Arctic, despite the daily Arctic‐wide coverage of spaceborne microwave radiometer data. This is mainly due to the difficulties in characterizing the sea ice surface emission: sea ice and snow microwave emission is high and highly variable. There are very few data sets combining relevant in situ measurements with co‐located remote sensing data, which further complicates the development of accurate retrieval algorithms. Here, we present a multi‐parameter retrieval based on the inversion of a forward model for both, atmosphere and surface, for non‐melting conditions. The model consists of a layered microwave emission model of snow and ice. Since snow scattering and emission effects, as well as temperature gradients, are taken into account, a high variability in brightness temperatures can be simulated. For ocean regions and the atmosphere existing parameterized forward models are used. By using optimal estimation, the forward model can be inverted allowing for the simultaneous and consistent retrieval of nine variables: integrated water vapor, liquid water path, sea ice concentration, multi‐year ice fraction, snow depth, snow‐ice interface temperature and snow‐air interface temperature as well as sea‐surface temperature and wind speed (over open ocean). In addition, the method provides retrieval uncertainty estimates for each retrieved parameter. To evaluate the forward model as well as the retrieval, we use the extensive data sets acquired during the year‐long Arctic expedition Multidisciplinary drifting Observatory for the Study of Arctic Climate (2019–2020) as a reference.https://doi.org/10.1029/2023EA003177satellite retrievalArctic water vapormicrowave emission modelingmicrowave radiometryoptimal estimation methodsea ice and snow |
| spellingShingle | Janna E. Rückert Marcus Huntemann Rasmus Tage Tonboe Gunnar Spreen Modeling Snow and Ice Microwave Emissions in the Arctic for a Multi‐Parameter Retrieval of Surface and Atmospheric Variables From Microwave Radiometer Satellite Data Earth and Space Science satellite retrieval Arctic water vapor microwave emission modeling microwave radiometry optimal estimation method sea ice and snow |
| title | Modeling Snow and Ice Microwave Emissions in the Arctic for a Multi‐Parameter Retrieval of Surface and Atmospheric Variables From Microwave Radiometer Satellite Data |
| title_full | Modeling Snow and Ice Microwave Emissions in the Arctic for a Multi‐Parameter Retrieval of Surface and Atmospheric Variables From Microwave Radiometer Satellite Data |
| title_fullStr | Modeling Snow and Ice Microwave Emissions in the Arctic for a Multi‐Parameter Retrieval of Surface and Atmospheric Variables From Microwave Radiometer Satellite Data |
| title_full_unstemmed | Modeling Snow and Ice Microwave Emissions in the Arctic for a Multi‐Parameter Retrieval of Surface and Atmospheric Variables From Microwave Radiometer Satellite Data |
| title_short | Modeling Snow and Ice Microwave Emissions in the Arctic for a Multi‐Parameter Retrieval of Surface and Atmospheric Variables From Microwave Radiometer Satellite Data |
| title_sort | modeling snow and ice microwave emissions in the arctic for a multi parameter retrieval of surface and atmospheric variables from microwave radiometer satellite data |
| topic | satellite retrieval Arctic water vapor microwave emission modeling microwave radiometry optimal estimation method sea ice and snow |
| url | https://doi.org/10.1029/2023EA003177 |
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