Arctic sea ice is a critical component of the global climate system. It is sensitive to climate change due to strong positive feedbacks. Sea ice affects the climate system by radiating incident solar energy back into space and regulating ocean-atmosphere heat and momentum exchange (Dai, Luo et al. 2019, Thackeray and Hall 2019). According to the historical remote sensing datasets, the Arctic sea ice is getting younger and thinner (Comiso, Parkinson et al. 2008, Kwok 2018, Stroeve and Notz 2018). Basin-scale measurements of sea-ice thickness are currently carried out by satellite altimetry missions. Radar altimetry, such as CryoSat-2, measures the height of the ice surface above the sea level, which can be converted into sea-ice thickness. There exists significant uncertainty of CryoSat-2 freeboard over thin ice (Wingham, Francis et al. 2006, Ricker, Hendricks et al. 2014). On the other hand, the Soil Moisture and Ocean Salinity (SMOS) mission provides brightness temperature (TB) observations at L band, which can be used for thin ice thickness retrieval (Kaleschke, Tian‐Kunze et al. 2012, Tian-Kunze, Kaleschke et al. 2013).
The sea ice north of Greenland is usually one of the oldest and thickest in the Arctic. However, during late February - early March 2018, a polynya formed north of Greenland due to extreme southerly winds (Moore, Schweiger et al. 2018). We focus on retrieving sea ice and snow conditions during the polynya formation and closure. In general, SAR-based backscattering coefficients over leads and open water within ice pack are lower than those on ice floes (Longépé, Thibaut et al. 2019). Thus, we utilize daily coincident Sentinel-1 images to outline the polynya for each period of its development. Due to the complexity of polynya, where the mélange of thick ice, newly formed thin ice, and lead is present, we analyze the uncertainties of CryoSat-2 products and carry out the inter-comparison of sea ice thickness retrievals using SMOS and CryoSat-2/SMOS synergy and other methods. This study aims to evaluate the potential and deficiencies of various retrieval methods and datasets for the estimation of the thickness of Arctic sea-ice and its snow cover.
 

CryoSat-2,SMOS,sea ice thickness