An Advanced Algorithm to Retrieve Total Atmospheric Water Vapor Content From the Advanced Microwave Scanning Radiometer Data Over Sea Ice and Sea Water Surfaces in the Arctic

International audience An advanced algorithm for atmospheric water vapor column (WVC) retrieval from the Advanced Microwave Scanning Radiometer (AMSR) measurements over the Arctic sea ice (SI) and open ocean waters is presented. The algorithm is built on the physical modeling of the brightness tempe...

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Published in:IEEE Transactions on Geoscience and Remote Sensing
Main Authors: Zabolotskikh, Elizaveta, V, Khvorostovsky, Kirill S., Chapron, Bertrand
Other Authors: Laboratoire d'Océanographie Physique et Spatiale (LOPS), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)
Format: Article in Journal/Newspaper
Language:English
Published: HAL CCSD 2020
Subjects:
Online Access:https://hal.science/hal-04202573
https://hal.science/hal-04202573/document
https://hal.science/hal-04202573/file/73597.pdf
https://doi.org/10.1109/TGRS.2019.2948289
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spelling ftinsu:oai:HAL:hal-04202573v1 2024-04-14T08:06:37+00:00 An Advanced Algorithm to Retrieve Total Atmospheric Water Vapor Content From the Advanced Microwave Scanning Radiometer Data Over Sea Ice and Sea Water Surfaces in the Arctic Zabolotskikh, Elizaveta, V Khvorostovsky, Kirill S. Chapron, Bertrand Laboratoire d'Océanographie Physique et Spatiale (LOPS) Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS) 2020-05 https://hal.science/hal-04202573 https://hal.science/hal-04202573/document https://hal.science/hal-04202573/file/73597.pdf https://doi.org/10.1109/TGRS.2019.2948289 en eng HAL CCSD Institute of Electrical and Electronics Engineers info:eu-repo/semantics/altIdentifier/doi/10.1109/TGRS.2019.2948289 hal-04202573 https://hal.science/hal-04202573 https://hal.science/hal-04202573/document https://hal.science/hal-04202573/file/73597.pdf doi:10.1109/TGRS.2019.2948289 info:eu-repo/semantics/OpenAccess ISSN: 0196-2892 IEEE Transactions on Geoscience and Remote Sensing https://hal.science/hal-04202573 IEEE Transactions on Geoscience and Remote Sensing, 2020, 58 (5), pp.3123-3135. ⟨10.1109/TGRS.2019.2948289⟩ [SDU]Sciences of the Universe [physics] info:eu-repo/semantics/article Journal articles 2020 ftinsu https://doi.org/10.1109/TGRS.2019.2948289 2024-03-21T17:04:55Z International audience An advanced algorithm for atmospheric water vapor column (WVC) retrieval from the Advanced Microwave Scanning Radiometer (AMSR) measurements over the Arctic sea ice (SI) and open ocean waters is presented. The algorithm is built on the physical modeling of the brightness temperature (BT) of the microwave radiation of the SI-open ocean-atmosphere system at the AMSR frequencies and polarizations. The BTs are calculated using a data set of the SI, atmospheric, and oceanic parameters changing in the range of their natural variability in the Arctic, and using the SI microwave emission coefficients varied according to the published experimental data. The inverse operator explores neural networks (NNs), trained on an ensemble of modeled BTs. The algorithm is applied both to the AMSR-E and to the AMSR2 measurement data. Validation of the algorithm is performed with radiosonde (r/s) WVC measurements from the four Arctic coastal stations at different SI conditions during 2014-2017. The results of the application of the new algorithm to satellite radiometer measurements are also compared with the Era-Interim reanalysis WVC, as well as with other satellite WVC products, based on the data of the Moderate Resolution Imaging Spectrometer (MODIS) and on the data of the Advanced Microwave Sounding Unit-B (AMSU-B) for 2008 and 2015. To justify the usage of the Era-Interim WVC as a reference data set for the algorithm accuracy estimation in the Arctic area, Era-Interim WVC is also compared with the r/s WVC measurements. Article in Journal/Newspaper Arctic Sea ice Institut national des sciences de l'Univers: HAL-INSU Arctic IEEE Transactions on Geoscience and Remote Sensing 58 5 3123 3135
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]
Zabolotskikh, Elizaveta, V
Khvorostovsky, Kirill S.
Chapron, Bertrand
An Advanced Algorithm to Retrieve Total Atmospheric Water Vapor Content From the Advanced Microwave Scanning Radiometer Data Over Sea Ice and Sea Water Surfaces in the Arctic
topic_facet [SDU]Sciences of the Universe [physics]
description International audience An advanced algorithm for atmospheric water vapor column (WVC) retrieval from the Advanced Microwave Scanning Radiometer (AMSR) measurements over the Arctic sea ice (SI) and open ocean waters is presented. The algorithm is built on the physical modeling of the brightness temperature (BT) of the microwave radiation of the SI-open ocean-atmosphere system at the AMSR frequencies and polarizations. The BTs are calculated using a data set of the SI, atmospheric, and oceanic parameters changing in the range of their natural variability in the Arctic, and using the SI microwave emission coefficients varied according to the published experimental data. The inverse operator explores neural networks (NNs), trained on an ensemble of modeled BTs. The algorithm is applied both to the AMSR-E and to the AMSR2 measurement data. Validation of the algorithm is performed with radiosonde (r/s) WVC measurements from the four Arctic coastal stations at different SI conditions during 2014-2017. The results of the application of the new algorithm to satellite radiometer measurements are also compared with the Era-Interim reanalysis WVC, as well as with other satellite WVC products, based on the data of the Moderate Resolution Imaging Spectrometer (MODIS) and on the data of the Advanced Microwave Sounding Unit-B (AMSU-B) for 2008 and 2015. To justify the usage of the Era-Interim WVC as a reference data set for the algorithm accuracy estimation in the Arctic area, Era-Interim WVC is also compared with the r/s WVC measurements.
author2 Laboratoire d'Océanographie Physique et Spatiale (LOPS)
Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)
format Article in Journal/Newspaper
author Zabolotskikh, Elizaveta, V
Khvorostovsky, Kirill S.
Chapron, Bertrand
author_facet Zabolotskikh, Elizaveta, V
Khvorostovsky, Kirill S.
Chapron, Bertrand
author_sort Zabolotskikh, Elizaveta, V
title An Advanced Algorithm to Retrieve Total Atmospheric Water Vapor Content From the Advanced Microwave Scanning Radiometer Data Over Sea Ice and Sea Water Surfaces in the Arctic
title_short An Advanced Algorithm to Retrieve Total Atmospheric Water Vapor Content From the Advanced Microwave Scanning Radiometer Data Over Sea Ice and Sea Water Surfaces in the Arctic
title_full An Advanced Algorithm to Retrieve Total Atmospheric Water Vapor Content From the Advanced Microwave Scanning Radiometer Data Over Sea Ice and Sea Water Surfaces in the Arctic
title_fullStr An Advanced Algorithm to Retrieve Total Atmospheric Water Vapor Content From the Advanced Microwave Scanning Radiometer Data Over Sea Ice and Sea Water Surfaces in the Arctic
title_full_unstemmed An Advanced Algorithm to Retrieve Total Atmospheric Water Vapor Content From the Advanced Microwave Scanning Radiometer Data Over Sea Ice and Sea Water Surfaces in the Arctic
title_sort advanced algorithm to retrieve total atmospheric water vapor content from the advanced microwave scanning radiometer data over sea ice and sea water surfaces in the arctic
publisher HAL CCSD
publishDate 2020
url https://hal.science/hal-04202573
https://hal.science/hal-04202573/document
https://hal.science/hal-04202573/file/73597.pdf
https://doi.org/10.1109/TGRS.2019.2948289
geographic Arctic
geographic_facet Arctic
genre Arctic
Sea ice
genre_facet Arctic
Sea ice
op_source ISSN: 0196-2892
IEEE Transactions on Geoscience and Remote Sensing
https://hal.science/hal-04202573
IEEE Transactions on Geoscience and Remote Sensing, 2020, 58 (5), pp.3123-3135. ⟨10.1109/TGRS.2019.2948289⟩
op_relation info:eu-repo/semantics/altIdentifier/doi/10.1109/TGRS.2019.2948289
hal-04202573
https://hal.science/hal-04202573
https://hal.science/hal-04202573/document
https://hal.science/hal-04202573/file/73597.pdf
doi:10.1109/TGRS.2019.2948289
op_rights info:eu-repo/semantics/OpenAccess
op_doi https://doi.org/10.1109/TGRS.2019.2948289
container_title IEEE Transactions on Geoscience and Remote Sensing
container_volume 58
container_issue 5
container_start_page 3123
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