Arctic Sea Ice Volume and Mass from Data Fusion of CryoSat-2 and SMOS

• Main Authors: Hendricks, Stefan, Kaleschke, Lars, Tian-Kunze, Xiangshan, Paul, Stephan, Ricker, Robert, De la Fuente, Antonio
• Format: Conference Object
• Language: unknown
• Published: 2022
• Subjects: Arctic; Arctic Ocean; Sea ice
• Online Access: https://epic.awi.de/id/eprint/56167/; https://epic.awi.de/id/eprint/56167/1/03_Hendricks-pdf-version.pdf; https://hdl.handle.net/10013/epic.11e41ca9-918e-4365-a3e8-491ea43788a8; https://hdl.handle.net/

The quantification of the sea ice mass balance as the marine part of the cryosphere by satellite observations depend on sea ice thickness data records for the entire ice-covered oceans. The challenges to this task are numerous. Sea ice itself is a highly dynamic medium with a significant variability at meter scale and a strong seasonal cycle which significantly impacts it remote sensing signature. Satellite sensors must therefore provide precise observations at high spatial resolution to observe the full spread of the sea ice thickness distribution and its governing processes such as the dynamic deformation. Average thickness values for larger areas are sufficient for mass balance estimates, however, available methods such as satellite altimetry and passive microwave remote sensing rely on indirect methods and auxiliary information and are often not able to provide information with an acceptable uncertainty for certain or thickness categories or during the presence of surface melt. In addition, suitable satellite sensors in orbits that enabling sea ice thickness retrieval in the inner Arctic Ocean have been in service only until recently in comparison to satellites capable of observing sea ice area. Thus, the assessment of the sea ice mass balance for longer time series is often based on reanalysis models and not Earth Observation data. The sea ice community also traditionally expresses the total sea ice budget volume and not mass. We will therefore present an available sea ice volume data record that is derived by data fusion of CryoSat-2 radar altimeter and SMOS L-Band passive microwave-based sea ice thickness information. Both methods have a complementary sensitivity to different thickness classes and optimal interpolation is employed for gap-less sea ice thickness information in the northern hemisphere since November 2010. The data record is generated for the ESA funded MOS & CryoSat-2 Sea Ice Data Product Processing and Dissemination Service (CS2SMOS-PDS). We discuss the characteristics of the data set ...