Microwave snow emission modeling uncertainties in boreal and subarctic environments
This study aims to better understand and quantify the uncertainties in microwave snow emission models using the Dense Media Radiative Theory Multi-Layer model (DMRT-ML) with in situ measurements of snow properties. We use surface-based radiometric measurements at 10.67, 19 and 37 GHz in boreal fores...
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ftcopernicus:oai:publications.copernicus.org:tc32335 2023-05-15T18:28:15+02:00 Microwave snow emission modeling uncertainties in boreal and subarctic environments Roy, Alexandre Royer, Alain St-Jean-Rondeau, Olivier Montpetit, Benoit Picard, Ghislain Mavrovic, Alex Marchand, Nicolas Langlois, Alexandre 2018-09-27 application/pdf https://doi.org/10.5194/tc-10-623-2016 https://tc.copernicus.org/articles/10/623/2016/ eng eng doi:10.5194/tc-10-623-2016 https://tc.copernicus.org/articles/10/623/2016/ eISSN: 1994-0424 Text 2018 ftcopernicus https://doi.org/10.5194/tc-10-623-2016 2020-07-20T16:24:13Z This study aims to better understand and quantify the uncertainties in microwave snow emission models using the Dense Media Radiative Theory Multi-Layer model (DMRT-ML) with in situ measurements of snow properties. We use surface-based radiometric measurements at 10.67, 19 and 37 GHz in boreal forest and subarctic environments and a new in situ data set of measurements of snow properties (profiles of density, snow grain size and temperature, soil characterization and ice lens detection) acquired in the James Bay and Umiujaq regions of Northern Québec, Canada. A snow excavation experiment – where snow was removed from the ground to measure the microwave emission of bare frozen ground – shows that small-scale spatial variability (less than 1 km) in the emission of frozen soil is small. Hence, in our case of boreal organic soil, variability in the emission of frozen soil has a small effect on snow-covered brightness temperature ( T B ). Grain size and density measurement errors can explain the errors at 37 GHz, while the sensitivity of T B at 19 GHz to snow increases during the winter because of the snow grain growth that leads to scattering. Furthermore, the inclusion of observed ice lenses in DMRT-ML leads to significant improvements in the simulations at horizontal polarization (H-pol) for the three frequencies (up to 20 K of root mean square error). However, representation of the spatial variability of T B remains poor at 10.67 and 19 GHz at H-pol given the spatial variability of ice lens characteristics and the difficulty in simulating snowpack stratigraphy related to the snow crust. The results also show that, in our study with the given forest characteristics, forest emission reflected by the snow-covered surface can increase the T B up to 40 K. The forest contribution varies with vegetation characteristics and a relationship between the downwelling contribution of vegetation and the proportion of pixels occupied by vegetation (trees) in fisheye pictures was found. We perform a comprehensive analysis of the components that contribute to the snow-covered microwave signal, which will help to develop DMRT-ML and to improve the required field measurements. The analysis shows that a better consideration of ice lenses and snow crusts is essential to improve T B simulations in boreal forest and subarctic environments. Text Subarctic Umiujaq James Bay Copernicus Publications: E-Journals Canada Umiujaq ENVELOPE(-76.549,-76.549,56.553,56.553) The Cryosphere 10 2 623 638 |
institution |
Open Polar |
collection |
Copernicus Publications: E-Journals |
op_collection_id |
ftcopernicus |
language |
English |
description |
This study aims to better understand and quantify the uncertainties in microwave snow emission models using the Dense Media Radiative Theory Multi-Layer model (DMRT-ML) with in situ measurements of snow properties. We use surface-based radiometric measurements at 10.67, 19 and 37 GHz in boreal forest and subarctic environments and a new in situ data set of measurements of snow properties (profiles of density, snow grain size and temperature, soil characterization and ice lens detection) acquired in the James Bay and Umiujaq regions of Northern Québec, Canada. A snow excavation experiment – where snow was removed from the ground to measure the microwave emission of bare frozen ground – shows that small-scale spatial variability (less than 1 km) in the emission of frozen soil is small. Hence, in our case of boreal organic soil, variability in the emission of frozen soil has a small effect on snow-covered brightness temperature ( T B ). Grain size and density measurement errors can explain the errors at 37 GHz, while the sensitivity of T B at 19 GHz to snow increases during the winter because of the snow grain growth that leads to scattering. Furthermore, the inclusion of observed ice lenses in DMRT-ML leads to significant improvements in the simulations at horizontal polarization (H-pol) for the three frequencies (up to 20 K of root mean square error). However, representation of the spatial variability of T B remains poor at 10.67 and 19 GHz at H-pol given the spatial variability of ice lens characteristics and the difficulty in simulating snowpack stratigraphy related to the snow crust. The results also show that, in our study with the given forest characteristics, forest emission reflected by the snow-covered surface can increase the T B up to 40 K. The forest contribution varies with vegetation characteristics and a relationship between the downwelling contribution of vegetation and the proportion of pixels occupied by vegetation (trees) in fisheye pictures was found. We perform a comprehensive analysis of the components that contribute to the snow-covered microwave signal, which will help to develop DMRT-ML and to improve the required field measurements. The analysis shows that a better consideration of ice lenses and snow crusts is essential to improve T B simulations in boreal forest and subarctic environments. |
format |
Text |
author |
Roy, Alexandre Royer, Alain St-Jean-Rondeau, Olivier Montpetit, Benoit Picard, Ghislain Mavrovic, Alex Marchand, Nicolas Langlois, Alexandre |
spellingShingle |
Roy, Alexandre Royer, Alain St-Jean-Rondeau, Olivier Montpetit, Benoit Picard, Ghislain Mavrovic, Alex Marchand, Nicolas Langlois, Alexandre Microwave snow emission modeling uncertainties in boreal and subarctic environments |
author_facet |
Roy, Alexandre Royer, Alain St-Jean-Rondeau, Olivier Montpetit, Benoit Picard, Ghislain Mavrovic, Alex Marchand, Nicolas Langlois, Alexandre |
author_sort |
Roy, Alexandre |
title |
Microwave snow emission modeling uncertainties in boreal and subarctic environments |
title_short |
Microwave snow emission modeling uncertainties in boreal and subarctic environments |
title_full |
Microwave snow emission modeling uncertainties in boreal and subarctic environments |
title_fullStr |
Microwave snow emission modeling uncertainties in boreal and subarctic environments |
title_full_unstemmed |
Microwave snow emission modeling uncertainties in boreal and subarctic environments |
title_sort |
microwave snow emission modeling uncertainties in boreal and subarctic environments |
publishDate |
2018 |
url |
https://doi.org/10.5194/tc-10-623-2016 https://tc.copernicus.org/articles/10/623/2016/ |
long_lat |
ENVELOPE(-76.549,-76.549,56.553,56.553) |
geographic |
Canada Umiujaq |
geographic_facet |
Canada Umiujaq |
genre |
Subarctic Umiujaq James Bay |
genre_facet |
Subarctic Umiujaq James Bay |
op_source |
eISSN: 1994-0424 |
op_relation |
doi:10.5194/tc-10-623-2016 https://tc.copernicus.org/articles/10/623/2016/ |
op_doi |
https://doi.org/10.5194/tc-10-623-2016 |
container_title |
The Cryosphere |
container_volume |
10 |
container_issue |
2 |
container_start_page |
623 |
op_container_end_page |
638 |
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1766210639536062464 |