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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ftuniparissaclay:oai:HAL:insu-03691499v1 2024-09-15T18:38:57+00:00 Retrieving the characteristics of slab ice covering snow by remote sensing Andrieu, François Schmidt, Frédéric Schmitt, Bernard Douté, Sylvain 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 ) 2016 https://insu.hal.science/insu-03691499 https://insu.hal.science/insu-03691499/document https://insu.hal.science/insu-03691499/file/tc-10-2113-2016.pdf https://doi.org/10.5194/tc-10-2113-2016 en eng HAL CCSD Copernicus info:eu-repo/semantics/altIdentifier/doi/10.5194/tc-10-2113-2016 insu-03691499 https://insu.hal.science/insu-03691499 https://insu.hal.science/insu-03691499/document https://insu.hal.science/insu-03691499/file/tc-10-2113-2016.pdf BIBCODE: 2016TCry.10.2113A doi:10.5194/tc-10-2113-2016 http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess ISSN: 1994-0424 EISSN: 1994-0416 The Cryosphere https://insu.hal.science/insu-03691499 The Cryosphere, 2016, 10, pp.2113-2128. ⟨10.5194/tc-10-2113-2016⟩ [SDU]Sciences of the Universe [physics] info:eu-repo/semantics/article Journal articles 2016 ftuniparissaclay https://doi.org/10.5194/tc-10-2113-2016 2024-08-30T01:48:53Z 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 Archives ouvertes de Paris-Saclay The Cryosphere 10 5 2113 2128 |
institution |
Open Polar |
collection |
Archives ouvertes de Paris-Saclay |
op_collection_id |
ftuniparissaclay |
language |
English |
topic |
[SDU]Sciences of the Universe [physics] |
spellingShingle |
[SDU]Sciences of the Universe [physics] Andrieu, François Schmidt, Frédéric Schmitt, Bernard Douté, Sylvain 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 ) |
format |
Article in Journal/Newspaper |
author |
Andrieu, François Schmidt, Frédéric Schmitt, Bernard Douté, Sylvain Brissaud, Olivier |
author_facet |
Andrieu, François Schmidt, Frédéric Schmitt, Bernard Douté, Sylvain 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://insu.hal.science/insu-03691499 https://insu.hal.science/insu-03691499/document https://insu.hal.science/insu-03691499/file/tc-10-2113-2016.pdf https://doi.org/10.5194/tc-10-2113-2016 |
genre |
The Cryosphere |
genre_facet |
The Cryosphere |
op_source |
ISSN: 1994-0424 EISSN: 1994-0416 The Cryosphere https://insu.hal.science/insu-03691499 The Cryosphere, 2016, 10, pp.2113-2128. ⟨10.5194/tc-10-2113-2016⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.5194/tc-10-2113-2016 insu-03691499 https://insu.hal.science/insu-03691499 https://insu.hal.science/insu-03691499/document https://insu.hal.science/insu-03691499/file/tc-10-2113-2016.pdf BIBCODE: 2016TCry.10.2113A doi:10.5194/tc-10-2113-2016 |
op_rights |
http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.5194/tc-10-2113-2016 |
container_title |
The Cryosphere |
container_volume |
10 |
container_issue |
5 |
container_start_page |
2113 |
op_container_end_page |
2128 |
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1810483349804810240 |