Microwave snow emission modeling uncertainties in boreal and subarctic environments

• Published in: The Cryosphere
• Main Authors: Roy, Alexandre, Royer, Alain, St-Jean-Rondeau, Olivier, Montpetit, Benoit, Picard, Ghislain, Mavrovic, Alex, Marchand, Nicolas, Langlois, Alexandre
• Other Authors: Centre d'Etudes Nordiques (CEN), Université Laval Québec (ULaval), Centre d'Applications et de Recherches en TELédétection Sherbrooke (CARTEL), Département de géomatique appliquée Sherbrooke (UdeS), Université de Sherbrooke (UdeS)-Université de Sherbrooke (UdeS), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Institut national des sciences de l'Univers (INSU - CNRS)-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 ), Laboratoire Chimie de l'environnement (LCE), Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2016
• Subjects: [SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology; Canada; Umiujaq; Subarctic; The Cryosphere; James Bay
• Online Access: https://hal-insu.archives-ouvertes.fr/insu-01388847; https://hal-insu.archives-ouvertes.fr/insu-01388847/document; https://hal-insu.archives-ouvertes.fr/insu-01388847/file/CRYOSPHERE%20-%20Microwave%20snow%20emission%20modeling%20uncertainties%20in%20boreal%20and%20subarctic%20environments.pdf; https://doi.org/10.5194/tc-10-623-2016

International audience 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 (TB). Grain size and density measurement errors can explain the errors at 37 GHz, while the sensitivity of TB 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 TB 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 TB 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 ...