Snow-Covered Soil Temperature Retrieval in Canadian Arctic Permafrost Areas, Using a Land Surface Scheme Informed with Satellite Remote Sensing Data
High-latitude areas are very sensitive to global warming, which has significant impacts on soil temperatures and associated processes governing permafrost evolution. This study aims to improve first-layer soil temperature retrievals during winter. This key surface state variable is strongly affected...
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ftmdpi:oai:mdpi.com:/2072-4292/10/11/1703/ 2023-08-20T04:04:25+02:00 Snow-Covered Soil Temperature Retrieval in Canadian Arctic Permafrost Areas, Using a Land Surface Scheme Informed with Satellite Remote Sensing Data Nicolas Marchand Alain Royer Gerhard Krinner Alexandre Roy Alexandre Langlois Céline Vargel agris 2018-10-29 application/pdf https://doi.org/10.3390/rs10111703 EN eng Multidisciplinary Digital Publishing Institute Biogeosciences Remote Sensing https://dx.doi.org/10.3390/rs10111703 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 10; Issue 11; Pages: 1703 soil temperature permafrost passive microwave thermal infrared snow cover Land Surface Model Radiative Transfer Model Canadian arctic Text 2018 ftmdpi https://doi.org/10.3390/rs10111703 2023-07-31T21:48:32Z High-latitude areas are very sensitive to global warming, which has significant impacts on soil temperatures and associated processes governing permafrost evolution. This study aims to improve first-layer soil temperature retrievals during winter. This key surface state variable is strongly affected by snow’s geophysical properties and their associated uncertainties (e.g., thermal conductivity) in land surface climate models. We used infrared MODIS land-surface temperatures (LST) and Advanced Microwave Scanning Radiometer for EOS (AMSR-E) brightness temperatures (Tb) at 10.7 and 18.7 GHz to constrain the Canadian Land Surface Scheme (CLASS), driven by meteorological reanalysis data and coupled with a simple radiative transfer model. The Tb polarization ratio (horizontal/vertical) at 10.7 GHz was selected to improve snowpack density, which is linked to the thermal conductivity representation in the model. Referencing meteorological station soil temperature measurements, we validated the approach at four different sites in the North American tundra over a period of up to 8 years. Results show that the proposed method improves simulations of the soil temperature under snow (Tg) by 64% when using remote sensing (RS) data to constrain the model, compared to model outputs without satellite data information. The root mean square error (RMSE) between measured and simulated Tg under the snow ranges from 1.8 to 3.5 K when using RS data. Improved temporal monitoring of the soil thermal state, along with changes in snow properties, will improve our understanding of the various processes governing soil biological, hydrological, and permafrost evolution. Text Arctic Global warming permafrost Tundra MDPI Open Access Publishing Arctic Remote Sensing 10 11 1703 |
institution |
Open Polar |
collection |
MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
soil temperature permafrost passive microwave thermal infrared snow cover Land Surface Model Radiative Transfer Model Canadian arctic |
spellingShingle |
soil temperature permafrost passive microwave thermal infrared snow cover Land Surface Model Radiative Transfer Model Canadian arctic Nicolas Marchand Alain Royer Gerhard Krinner Alexandre Roy Alexandre Langlois Céline Vargel Snow-Covered Soil Temperature Retrieval in Canadian Arctic Permafrost Areas, Using a Land Surface Scheme Informed with Satellite Remote Sensing Data |
topic_facet |
soil temperature permafrost passive microwave thermal infrared snow cover Land Surface Model Radiative Transfer Model Canadian arctic |
description |
High-latitude areas are very sensitive to global warming, which has significant impacts on soil temperatures and associated processes governing permafrost evolution. This study aims to improve first-layer soil temperature retrievals during winter. This key surface state variable is strongly affected by snow’s geophysical properties and their associated uncertainties (e.g., thermal conductivity) in land surface climate models. We used infrared MODIS land-surface temperatures (LST) and Advanced Microwave Scanning Radiometer for EOS (AMSR-E) brightness temperatures (Tb) at 10.7 and 18.7 GHz to constrain the Canadian Land Surface Scheme (CLASS), driven by meteorological reanalysis data and coupled with a simple radiative transfer model. The Tb polarization ratio (horizontal/vertical) at 10.7 GHz was selected to improve snowpack density, which is linked to the thermal conductivity representation in the model. Referencing meteorological station soil temperature measurements, we validated the approach at four different sites in the North American tundra over a period of up to 8 years. Results show that the proposed method improves simulations of the soil temperature under snow (Tg) by 64% when using remote sensing (RS) data to constrain the model, compared to model outputs without satellite data information. The root mean square error (RMSE) between measured and simulated Tg under the snow ranges from 1.8 to 3.5 K when using RS data. Improved temporal monitoring of the soil thermal state, along with changes in snow properties, will improve our understanding of the various processes governing soil biological, hydrological, and permafrost evolution. |
format |
Text |
author |
Nicolas Marchand Alain Royer Gerhard Krinner Alexandre Roy Alexandre Langlois Céline Vargel |
author_facet |
Nicolas Marchand Alain Royer Gerhard Krinner Alexandre Roy Alexandre Langlois Céline Vargel |
author_sort |
Nicolas Marchand |
title |
Snow-Covered Soil Temperature Retrieval in Canadian Arctic Permafrost Areas, Using a Land Surface Scheme Informed with Satellite Remote Sensing Data |
title_short |
Snow-Covered Soil Temperature Retrieval in Canadian Arctic Permafrost Areas, Using a Land Surface Scheme Informed with Satellite Remote Sensing Data |
title_full |
Snow-Covered Soil Temperature Retrieval in Canadian Arctic Permafrost Areas, Using a Land Surface Scheme Informed with Satellite Remote Sensing Data |
title_fullStr |
Snow-Covered Soil Temperature Retrieval in Canadian Arctic Permafrost Areas, Using a Land Surface Scheme Informed with Satellite Remote Sensing Data |
title_full_unstemmed |
Snow-Covered Soil Temperature Retrieval in Canadian Arctic Permafrost Areas, Using a Land Surface Scheme Informed with Satellite Remote Sensing Data |
title_sort |
snow-covered soil temperature retrieval in canadian arctic permafrost areas, using a land surface scheme informed with satellite remote sensing data |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2018 |
url |
https://doi.org/10.3390/rs10111703 |
op_coverage |
agris |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Global warming permafrost Tundra |
genre_facet |
Arctic Global warming permafrost Tundra |
op_source |
Remote Sensing; Volume 10; Issue 11; Pages: 1703 |
op_relation |
Biogeosciences Remote Sensing https://dx.doi.org/10.3390/rs10111703 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs10111703 |
container_title |
Remote Sensing |
container_volume |
10 |
container_issue |
11 |
container_start_page |
1703 |
_version_ |
1774714791059783680 |