Quantifying the influence of snow over sea ice morphology on L-band passive microwave satellite observations in the Southern Ocean

• Published in: The cryosphere Vol. 18; no. 9; pp. 4399 - 4434
• Main Authors: Zhou, Lu, Stroeve, Julienne, Nandan, Vishnu, Willatt, Rosemary, Xu, Shiming, Zhu, Weixin, Kacimi, Sahra, Arndt, Stefanie, Yang, Zifan
• Format: Journal Article
• Language: English
• Published: Katlenburg-Lindau Copernicus GmbH 24.09.2024; Copernicus Publications
• Subjects: Analysis; Antarctic sea ice; Antarctic snow; Atmospheric data; Brightness; Brightness temperature; Brines; Climate change; Earth and Related Environmental Sciences; Emissions; Geovetenskap och miljövetenskap; Grain size; Heterogeneity; Ice; Ice cover; Ice thickness; Influence; Mass balance; Mass balance of sea ice; Moisture content; Ocean; Oceans; Precipitation; Radiation; Radiative transfer; Salinity; Satellite observation; Satellites; Sea ice; Sea ice concentrations; Sea level; Seawater; Slush; Snow; Snow accumulation; Snow and ice; Snow depth; Snowpack; Soil improvement; Soil layers; Soil moisture; Strata; Stratigraphy; Surface brightness; Surface radiation temperature; Temperature; Thickness; Antarctica; Weddell Sea; Southern Ocean
• ISSN: 1994-0424; 1994-0416; 1994-0424; 1994-0416
• DOI: 10.5194/tc-18-4399-2024

Antarctic snow on sea ice can contain slush, snow ice, and stratified layers, complicating satellite retrieval processes for snow depth, ice thickness, and sea ice concentration. The presence of moist and brine-wetted snow alters microwave snow emissions and modifies the energy and mass balance of sea ice. This study assesses the impact of brine-wetted snow and slush layers on L-band surface brightness temperatures (TBs) by synergizing a snow stratigraphy model (SNOWPACK) driven by atmospheric reanalysis data and the RAdiative transfer model Developed for Ice and Snow in the L-band (RADIS-L) v1.0 The updated RADIS-L v1.1 further introduces parameterizations for brine-wetted snow and slush layers over Antarctic sea ice. Our findings highlight the importance of including both brine-wetted snow and slush layers in order to accurately simulate L-band brightness temperatures, laying the groundwork for improved satellite retrievals of snow depth and ice thickness using satellite sensors such as Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP). However, biases in modelled and observed L-band brightness temperatures persist, which we attribute to small-scale sea ice heterogeneity and snow stratigraphy. Given the scarcity of comprehensive in situ snow and ice data in the Southern Ocean, ramping up observational initiatives is imperative to not only provide satellite validation datasets but also improve process-level understanding that can scale up to improving the precision of satellite snow and ice thickness retrievals.