Arctic snowpack characterization, climate monitoring and microwaves remote sensing

• Main Author: Vargel, Céline
• Other Authors: Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Université Grenoble Alpes 2020-., Université de Sherbrooke (Québec, Canada), Ghislain Picard, Alain Royer
• Format: Doctoral or Postdoctoral Thesis
• Language: French
• Published: HAL CCSD 2020
• Subjects: Snowpack; Arctic; Modelisation; Climate change; Radiative transfer; Microwave remote sensing; Manteau neigeux; Arctique; Modélisation; Changement climatique; Transfert radiatif; Télédétection micro-Onde; [SHS.LANGUE]Humanities and Social Sciences/Linguistics; Arctique*; Ice; permafrost; Sea ice; Alaska; Siberia
• Online Access: https://theses.hal.science/tel-03185802; https://theses.hal.science/tel-03185802/document; https://theses.hal.science/tel-03185802/file/VARGEL_2020_archivage.pdf

Northern high-latitude regions are warming more intensely than the rest of the world. This phenomenon, called Arctic amplification, is due in part to the decrease in sea ice extent and snow cover. Snow, which is present 9 months of the year, could have a significant effect on the increase in land surface temperatures by changing its reflective and insulating properties. Thawing of permafrost which could release important amount of soil carbone into the atmosphere could have a significant positive feedback on the future climate of the Arctic. The objective of this research project is to improve the monitoring of Arctic snow cover and ground temperatures. Detailed models of snow cover evolution such as the Crocus multi-layered model are unable to reproduce the particular physics of Arctic snow, which leads to significant uncertainties in the modeling of ground temperatures. New physical parameterizations have been implemented within the Crocus model to improve the vertical stratification of the snowpack by introducing vegetation effects (less dense snow at the bottom) and wind effects (denser snow at the surface), as well as to modify the thermal conductivity of snow. These new parameterizations allow a better representation of ground temperatures under the snowpack, validated with a large dataset in Alaska, Canadian Arctic and Siberia. The simulations thus carried out using the modified Crocus model, driven by the ERA-Interim meteorological reanalysis over the last 39 years (1979-2018), at the pan-Arctic scale, show a significant increase in snow density in spring as well as in snow moisture, mainly in spring and fall, accompanied by a significant decrease in the duration of the snow cover. These effects, combined with the increase in air temperature, lead to an increase in ground temperature of up to +0.89 K per decade for the month of June. In order to improve monitoring the spatial and temporal evolution of the snow cover, the use of microwave satellite observation data is proposed. Based on the analysis of a ...