A satellite snow depth multi-year average derived from SSM/I for high latitude regions
International audience The hydrological cycle for high latitude regions is inherently linked with the seasonal snowpack. Thus, accurately monitoring the snow depth and the associated aerial coverage are critical issues for monitoring the global climate system. Passive microwave satellite measurement...
Published in: | Remote Sensing of Environment |
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Main Authors: | , , , , |
Other Authors: | , , , , , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
HAL CCSD
2008
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Subjects: | |
Online Access: | https://hal.archives-ouvertes.fr/hal-00575478 https://hal.archives-ouvertes.fr/hal-00575478/document https://hal.archives-ouvertes.fr/hal-00575478/file/Biancamaria_etal_2008_RSE.pdf https://doi.org/10.1016/j.rse.2007.12.002 |
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Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) |
op_collection_id |
ftccsdartic |
language |
English |
topic |
ALGORITHM Taiga Tundra SSM/I Lakes GSWP2 Snow depth High latitude regions CLIMATOLOGY PARAMETERS COVER LAND-SURFACE WESTERN CANADA NORTHERN GREAT-PLAINS PASSIVE-MICROWAVE DATA SIMULATIONS [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology [SDE.MCG]Environmental Sciences/Global Changes [SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environment |
spellingShingle |
ALGORITHM Taiga Tundra SSM/I Lakes GSWP2 Snow depth High latitude regions CLIMATOLOGY PARAMETERS COVER LAND-SURFACE WESTERN CANADA NORTHERN GREAT-PLAINS PASSIVE-MICROWAVE DATA SIMULATIONS [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology [SDE.MCG]Environmental Sciences/Global Changes [SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environment Biancamaria, Sylvain Mognard, Nelly Boone, Aaron Grippa, Manuela Josberger, Edward A satellite snow depth multi-year average derived from SSM/I for high latitude regions |
topic_facet |
ALGORITHM Taiga Tundra SSM/I Lakes GSWP2 Snow depth High latitude regions CLIMATOLOGY PARAMETERS COVER LAND-SURFACE WESTERN CANADA NORTHERN GREAT-PLAINS PASSIVE-MICROWAVE DATA SIMULATIONS [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology [SDE.MCG]Environmental Sciences/Global Changes [SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environment |
description |
International audience The hydrological cycle for high latitude regions is inherently linked with the seasonal snowpack. Thus, accurately monitoring the snow depth and the associated aerial coverage are critical issues for monitoring the global climate system. Passive microwave satellite measurements provide an optimal means to monitor the snowpack over the arctic region. While the temporal evolution of snow extent can be observed globally from microwave radiometers, the determination of the corresponding snow depth is more difficult. A dynamic algorithm that accounts for the dependence of the microwave scattering on the snow grain size has been developed to estimate snow depth from Special Sensor Microwave/Imager (SSM/I) brightness temperatures and was validated over the U.S. Great Plains and Western Siberia. The purpose of this study is to assess the dynamic algorithm performance over the entire high latitude (land) region by computing a snow depth multi-year field for the time period 1987 - 1995. This multi-year average is compared to the Global Soil Wetness Project-Phase2 (GSWP2) snow depth computed from several state-of-the-art land surface schemes and averaged over the same time period. The multi-year average obtained by the dynamic algorithm is in good agreement with the GSWP2 snow depth field (the correlation coefficient for January is 0.55). The static algorithm, which assumes a constant snow grain size in space and time does not correlate with the GSWP2 snow depth field (the correlation coefficient with GSWP2 data for January is -0.03), but exhibits a very high anti-correlation with the NCEP average January air temperature field (correlation coefficient -0.77), the deepest satellite snow pack being located in the coldest regions, where the snow grain size may be significantly larger than the average value used in the static algorithm. The dynamic algorithm performs better over Eurasia (with a correlation coefficient with GSWP2 snow depth equal to 0.65) than over North America (where the correlation ... |
author2 |
Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS) Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP) Météo France-Centre National d'Études Spatiales Toulouse (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS) Groupe d'étude de l'atmosphère météorologique (CNRM-GAME) Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS) Centre d'études spatiales de la biosphère (CESBIO) Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3) Météo France-Centre National d'Études Spatiales Toulouse (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS) US Geological Survey Tacoma United States Geological Survey Reston (USGS) CNES/Noveltis grant |
format |
Article in Journal/Newspaper |
author |
Biancamaria, Sylvain Mognard, Nelly Boone, Aaron Grippa, Manuela Josberger, Edward |
author_facet |
Biancamaria, Sylvain Mognard, Nelly Boone, Aaron Grippa, Manuela Josberger, Edward |
author_sort |
Biancamaria, Sylvain |
title |
A satellite snow depth multi-year average derived from SSM/I for high latitude regions |
title_short |
A satellite snow depth multi-year average derived from SSM/I for high latitude regions |
title_full |
A satellite snow depth multi-year average derived from SSM/I for high latitude regions |
title_fullStr |
A satellite snow depth multi-year average derived from SSM/I for high latitude regions |
title_full_unstemmed |
A satellite snow depth multi-year average derived from SSM/I for high latitude regions |
title_sort |
satellite snow depth multi-year average derived from ssm/i for high latitude regions |
publisher |
HAL CCSD |
publishDate |
2008 |
url |
https://hal.archives-ouvertes.fr/hal-00575478 https://hal.archives-ouvertes.fr/hal-00575478/document https://hal.archives-ouvertes.fr/hal-00575478/file/Biancamaria_etal_2008_RSE.pdf https://doi.org/10.1016/j.rse.2007.12.002 |
geographic |
Arctic Canada |
geographic_facet |
Arctic Canada |
genre |
Arctic taiga Tundra Siberia |
genre_facet |
Arctic taiga Tundra Siberia |
op_source |
ISSN: 0034-4257 EISSN: 1879-0704 Remote Sensing of Environment https://hal.archives-ouvertes.fr/hal-00575478 Remote Sensing of Environment, Elsevier, 2008, 112 (5), pp.2557-2568. ⟨10.1016/j.rse.2007.12.002⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.rse.2007.12.002 hal-00575478 https://hal.archives-ouvertes.fr/hal-00575478 https://hal.archives-ouvertes.fr/hal-00575478/document https://hal.archives-ouvertes.fr/hal-00575478/file/Biancamaria_etal_2008_RSE.pdf doi:10.1016/j.rse.2007.12.002 |
op_rights |
info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.1016/j.rse.2007.12.002 |
container_title |
Remote Sensing of Environment |
container_volume |
112 |
container_issue |
5 |
container_start_page |
2557 |
op_container_end_page |
2568 |
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1766349626998259712 |
spelling |
ftccsdartic:oai:HAL:hal-00575478v1 2023-05-15T15:19:26+02:00 A satellite snow depth multi-year average derived from SSM/I for high latitude regions Biancamaria, Sylvain Mognard, Nelly Boone, Aaron Grippa, Manuela Josberger, Edward Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS) Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP) Météo France-Centre National d'Études Spatiales Toulouse (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS) Groupe d'étude de l'atmosphère météorologique (CNRM-GAME) Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS) Centre d'études spatiales de la biosphère (CESBIO) Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3) Météo France-Centre National d'Études Spatiales Toulouse (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS) US Geological Survey Tacoma United States Geological Survey Reston (USGS) CNES/Noveltis grant 2008-05-15 https://hal.archives-ouvertes.fr/hal-00575478 https://hal.archives-ouvertes.fr/hal-00575478/document https://hal.archives-ouvertes.fr/hal-00575478/file/Biancamaria_etal_2008_RSE.pdf https://doi.org/10.1016/j.rse.2007.12.002 en eng HAL CCSD Elsevier info:eu-repo/semantics/altIdentifier/doi/10.1016/j.rse.2007.12.002 hal-00575478 https://hal.archives-ouvertes.fr/hal-00575478 https://hal.archives-ouvertes.fr/hal-00575478/document https://hal.archives-ouvertes.fr/hal-00575478/file/Biancamaria_etal_2008_RSE.pdf doi:10.1016/j.rse.2007.12.002 info:eu-repo/semantics/OpenAccess ISSN: 0034-4257 EISSN: 1879-0704 Remote Sensing of Environment https://hal.archives-ouvertes.fr/hal-00575478 Remote Sensing of Environment, Elsevier, 2008, 112 (5), pp.2557-2568. ⟨10.1016/j.rse.2007.12.002⟩ ALGORITHM Taiga Tundra SSM/I Lakes GSWP2 Snow depth High latitude regions CLIMATOLOGY PARAMETERS COVER LAND-SURFACE WESTERN CANADA NORTHERN GREAT-PLAINS PASSIVE-MICROWAVE DATA SIMULATIONS [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology [SDE.MCG]Environmental Sciences/Global Changes [SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environment info:eu-repo/semantics/article Journal articles 2008 ftccsdartic https://doi.org/10.1016/j.rse.2007.12.002 2021-10-24T17:59:16Z International audience The hydrological cycle for high latitude regions is inherently linked with the seasonal snowpack. Thus, accurately monitoring the snow depth and the associated aerial coverage are critical issues for monitoring the global climate system. Passive microwave satellite measurements provide an optimal means to monitor the snowpack over the arctic region. While the temporal evolution of snow extent can be observed globally from microwave radiometers, the determination of the corresponding snow depth is more difficult. A dynamic algorithm that accounts for the dependence of the microwave scattering on the snow grain size has been developed to estimate snow depth from Special Sensor Microwave/Imager (SSM/I) brightness temperatures and was validated over the U.S. Great Plains and Western Siberia. The purpose of this study is to assess the dynamic algorithm performance over the entire high latitude (land) region by computing a snow depth multi-year field for the time period 1987 - 1995. This multi-year average is compared to the Global Soil Wetness Project-Phase2 (GSWP2) snow depth computed from several state-of-the-art land surface schemes and averaged over the same time period. The multi-year average obtained by the dynamic algorithm is in good agreement with the GSWP2 snow depth field (the correlation coefficient for January is 0.55). The static algorithm, which assumes a constant snow grain size in space and time does not correlate with the GSWP2 snow depth field (the correlation coefficient with GSWP2 data for January is -0.03), but exhibits a very high anti-correlation with the NCEP average January air temperature field (correlation coefficient -0.77), the deepest satellite snow pack being located in the coldest regions, where the snow grain size may be significantly larger than the average value used in the static algorithm. The dynamic algorithm performs better over Eurasia (with a correlation coefficient with GSWP2 snow depth equal to 0.65) than over North America (where the correlation ... Article in Journal/Newspaper Arctic taiga Tundra Siberia Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) Arctic Canada Remote Sensing of Environment 112 5 2557 2568 |