Modelling snow and ice microwave emissions in the Arctic for a multi-parameter retrieval of surface and atmospheric variables from microwave radiometer satellite data

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...

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Main Authors: Rückert, Janna Elisabeth, Huntemann, Marcus, Tonboe, Rasmus, Spreen, Gunnar
Format: Other/Unknown Material
Language:unknown
Published: Authorea, Inc. 2023
Subjects:
Online Access:http://dx.doi.org/10.22541/essoar.169111779.99469597/v1
id crwinnower:10.22541/essoar.169111779.99469597/v1
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spelling crwinnower:10.22541/essoar.169111779.99469597/v1 2024-06-02T08:01:15+00:00 Modelling snow and ice microwave emissions in the Arctic for a multi-parameter retrieval of surface and atmospheric variables from microwave radiometer satellite data Rückert, Janna Elisabeth Huntemann, Marcus Tonboe, Rasmus Spreen, Gunnar 2023 http://dx.doi.org/10.22541/essoar.169111779.99469597/v1 unknown Authorea, Inc. posted-content 2023 crwinnower https://doi.org/10.22541/essoar.169111779.99469597/v1 2024-05-07T14:19:30Z 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 datasets 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 datasets acquired during the year-long Arctic expedition MOSAiC (2019-2020) as a reference. Other/Unknown Material Arctic Sea ice The Winnower Arctic
institution Open Polar
collection The Winnower
op_collection_id crwinnower
language unknown
description 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 datasets 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 datasets acquired during the year-long Arctic expedition MOSAiC (2019-2020) as a reference.
format Other/Unknown Material
author Rückert, Janna Elisabeth
Huntemann, Marcus
Tonboe, Rasmus
Spreen, Gunnar
spellingShingle Rückert, Janna Elisabeth
Huntemann, Marcus
Tonboe, Rasmus
Spreen, Gunnar
Modelling snow and ice microwave emissions in the Arctic for a multi-parameter retrieval of surface and atmospheric variables from microwave radiometer satellite data
author_facet Rückert, Janna Elisabeth
Huntemann, Marcus
Tonboe, Rasmus
Spreen, Gunnar
author_sort Rückert, Janna Elisabeth
title Modelling 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 Modelling 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 Modelling 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 Modelling 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 Modelling 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 modelling snow and ice microwave emissions in the arctic for a multi-parameter retrieval of surface and atmospheric variables from microwave radiometer satellite data
publisher Authorea, Inc.
publishDate 2023
url http://dx.doi.org/10.22541/essoar.169111779.99469597/v1
geographic Arctic
geographic_facet Arctic
genre Arctic
Sea ice
genre_facet Arctic
Sea ice
op_doi https://doi.org/10.22541/essoar.169111779.99469597/v1
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