Retrieving the characteristics of slab ice covering snow by remote sensing

International audience We present an effort to validate a previously developed radiative transfer model, and an innovative Bayesian inversion method designed to retrieve the properties of slab-ice-covered surfaces. This retrieval method is adapted to satellite data, and is able to provide uncertaint...

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Main Authors: Andrieu, François, Schmidt, Frédéric, Schmitt, Bernard, Doute, S., Brissaud, Olivier
Other Authors: Géosciences Paris Sud (GEOPS), Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS), Institut de Planétologie et d'Astrophysique de Grenoble (IPAG), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes 2016-2019 (UGA 2016-2019 )-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes 2016-2019 (UGA 2016-2019 ), Université Grenoble Alpes 2016-2019 (UGA 2016-2019 )
Format: Article in Journal/Newspaper
Language:English
Published: HAL CCSD 2016
Subjects:
Online Access:https://hal.science/hal-01415947
https://hal.science/hal-01415947/document
https://hal.science/hal-01415947/file/tc-10-2113-2016.pdf
id ftinsu:oai:HAL:hal-01415947v1
record_format openpolar
spelling ftinsu:oai:HAL:hal-01415947v1 2024-04-28T08:40:20+00:00 Retrieving the characteristics of slab ice covering snow by remote sensing Andrieu, François Schmidt, Frédéric Schmitt, Bernard Doute, S. Brissaud, Olivier Géosciences Paris Sud (GEOPS) Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS) Institut de Planétologie et d'Astrophysique de Grenoble (IPAG) Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG ) Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes 2016-2019 (UGA 2016-2019 )-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes 2016-2019 (UGA 2016-2019 ) Université Grenoble Alpes 2016-2019 (UGA 2016-2019 ) 2016 https://hal.science/hal-01415947 https://hal.science/hal-01415947/document https://hal.science/hal-01415947/file/tc-10-2113-2016.pdf en eng HAL CCSD Copernicus hal-01415947 https://hal.science/hal-01415947 https://hal.science/hal-01415947/document https://hal.science/hal-01415947/file/tc-10-2113-2016.pdf http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess ISSN: 1994-0424 EISSN: 1994-0416 The Cryosphere https://hal.science/hal-01415947 The Cryosphere, 2016, 10 ((5)), pp.2113-2128 (IF 4,906) [SDU]Sciences of the Universe [physics] info:eu-repo/semantics/article Journal articles 2016 ftinsu 2024-04-05T00:35:45Z International audience We present an effort to validate a previously developed radiative transfer model, and an innovative Bayesian inversion method designed to retrieve the properties of slab-ice-covered surfaces. This retrieval method is adapted to satellite data, and is able to provide uncertainties on the results of the inversions. We focused on surfaces composed of a pure slab of water ice covering an optically thick layer of snow in this study. We sought to retrieve the roughness of the ice–air interface, the thickness of the slab layer and the mean grain diameter of the underlying snow. Numerical validations have been conducted on the method, and showed that if the thickness of the slab layer is above 5 mm and the noise on the signal is above 3 %, then it is not possible to invert the grain diameter of the snow. In contrast, the roughness and the thickness of the slab can be determined, even with high levels of noise up to 20 %. Experimental validations have been conducted on spectra collected from laboratory samples of water ice on snow using a spectro-radiogoniometer. The results are in agreement with the numerical validations, and show that a grain diameter can be correctly retrieved for low slab thicknesses, but not for bigger ones, and that the roughness and thickness are correctly inverted in every case. Article in Journal/Newspaper The Cryosphere Institut national des sciences de l'Univers: HAL-INSU
institution Open Polar
collection Institut national des sciences de l'Univers: HAL-INSU
op_collection_id ftinsu
language English
topic [SDU]Sciences of the Universe [physics]
spellingShingle [SDU]Sciences of the Universe [physics]
Andrieu, François
Schmidt, Frédéric
Schmitt, Bernard
Doute, S.
Brissaud, Olivier
Retrieving the characteristics of slab ice covering snow by remote sensing
topic_facet [SDU]Sciences of the Universe [physics]
description International audience We present an effort to validate a previously developed radiative transfer model, and an innovative Bayesian inversion method designed to retrieve the properties of slab-ice-covered surfaces. This retrieval method is adapted to satellite data, and is able to provide uncertainties on the results of the inversions. We focused on surfaces composed of a pure slab of water ice covering an optically thick layer of snow in this study. We sought to retrieve the roughness of the ice–air interface, the thickness of the slab layer and the mean grain diameter of the underlying snow. Numerical validations have been conducted on the method, and showed that if the thickness of the slab layer is above 5 mm and the noise on the signal is above 3 %, then it is not possible to invert the grain diameter of the snow. In contrast, the roughness and the thickness of the slab can be determined, even with high levels of noise up to 20 %. Experimental validations have been conducted on spectra collected from laboratory samples of water ice on snow using a spectro-radiogoniometer. The results are in agreement with the numerical validations, and show that a grain diameter can be correctly retrieved for low slab thicknesses, but not for bigger ones, and that the roughness and thickness are correctly inverted in every case.
author2 Géosciences Paris Sud (GEOPS)
Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS)
Institut de Planétologie et d'Astrophysique de Grenoble (IPAG)
Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG )
Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes 2016-2019 (UGA 2016-2019 )-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes 2016-2019 (UGA 2016-2019 )
Université Grenoble Alpes 2016-2019 (UGA 2016-2019 )
format Article in Journal/Newspaper
author Andrieu, François
Schmidt, Frédéric
Schmitt, Bernard
Doute, S.
Brissaud, Olivier
author_facet Andrieu, François
Schmidt, Frédéric
Schmitt, Bernard
Doute, S.
Brissaud, Olivier
author_sort Andrieu, François
title Retrieving the characteristics of slab ice covering snow by remote sensing
title_short Retrieving the characteristics of slab ice covering snow by remote sensing
title_full Retrieving the characteristics of slab ice covering snow by remote sensing
title_fullStr Retrieving the characteristics of slab ice covering snow by remote sensing
title_full_unstemmed Retrieving the characteristics of slab ice covering snow by remote sensing
title_sort retrieving the characteristics of slab ice covering snow by remote sensing
publisher HAL CCSD
publishDate 2016
url https://hal.science/hal-01415947
https://hal.science/hal-01415947/document
https://hal.science/hal-01415947/file/tc-10-2113-2016.pdf
genre The Cryosphere
genre_facet The Cryosphere
op_source ISSN: 1994-0424
EISSN: 1994-0416
The Cryosphere
https://hal.science/hal-01415947
The Cryosphere, 2016, 10 ((5)), pp.2113-2128 (IF 4,906)
op_relation hal-01415947
https://hal.science/hal-01415947
https://hal.science/hal-01415947/document
https://hal.science/hal-01415947/file/tc-10-2113-2016.pdf
op_rights http://creativecommons.org/licenses/by/
info:eu-repo/semantics/OpenAccess
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