Arctic sea ice and its snow cover characterization from multi-satellite microwave observations

• Main Author: Soriot, Clément
• Other Authors: Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres (LERMA), École normale supérieure - Paris (ENS-PSL), Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris Sciences et Lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-CY Cergy Paris Université (CY), Sorbonne Université, Catherine Prigent, Frédéric Frappart
• Format: Doctoral or Postdoctoral Thesis
• Language: French
• Published: HAL CCSD 2022
• Subjects: Sea Ice; Microwave observations; Satellite data; Remote Sensing; Arctic; Glace de mer; Observations micro-ondes; Observation satellite; Télédétection; Arctique; [SDU.OCEAN]Sciences of the Universe [physics]/Ocean; Atmosphere; Arctique*; banquise; Global warming; polar night; Sea ice
• Online Access: https://theses.hal.science/tel-04011507; https://theses.hal.science/tel-04011507/document; https://theses.hal.science/tel-04011507/file/SORIOT_Clement_these_2022.pdf

Sea ice plays a major role in ocean circulation as well as in the climate and weather system. In the context of global warming, the extent of the Arctic sea ice has been decreasing steadily over the last 40 years and monitoring of the Arctic is essential. Microwave instruments on board satellites allow the study of this region of the Earth under all weather conditions, and regardless of the day/night cycle. Particularly suited over polar regions with high cloud cover and a six-month polar night, microwave satellite provide key observations for estimating geophysical parameters of the sea ice. Nevertheless, the understanding of the physics underlying the observed microwave signatures is still partial. This thesis aims at improving our understanding of the microwave signals of the sea ice and is part of the preparation of two upcoming Earth observation missions led by the European Space Agency: the Copernicus Imager Microwave Radiometer (CIMR) and the Copernicus Polar Ice and Snow Topography ALtimeter (CRISTAL). In a first part, the covariabilities of passive microwave signals, highlighted by an unsupervised classification technique, will be analyzed and interpreted jointly with active microwave signals, using a microwave radiative transfer model. The results showed that it is possible to identify specific behaviors of sea ice concentration and thickness, and snow structure. The importance of metamorphism within the snowpack for the interpretation of passive microwave signals was highlighted. In a second part, an algorithm for estimating sea ice thickness from passive microwave observations was developed using an artificial intelligence technique. The results were compared to in situ sea ice thickness measurements and also showed good performance compared to other satellite-based sea ice thickness products. By applying the algorithm to a long collection of intercalibrated satellite data, a time series of Arctic sea ice thickness was constructed between 1992 and 2020, making it the longest to date. A final section ...