Review of tc-2021-333 (SLICE)

Abstract

As changes to Earth’s polar climate accelerate, the need for robust, long–term sea ice thickness observation datasets for monitoring those changes and for verification of global climate models is clear. By coupling a recently developed algorithm for retrieving snow–ice interface temperature from passive microwave satellite data to a thermodynamic sea ice energy balance relation known as Stefan's Law, we have developed a new retrieval method for estimating thermodynamic sea ice thickness growth from space: Stefan’s Law Integrated Conducted Energy (SLICE). The advantages of the SLICE retrieval method include daily basin-wide coverage and a potential for use beginning in 1987. The method requires an initial condition at the beginning of the sea ice growth season in order to produce absolute sea ice thickness and cannot as yet capture dynamic sea ice thickness changes. Validation of the method against ten ice mass balance buoys using the ice mass balance buoy thickness as the initial condition show a mean correlation of 0.991 and a mean bias of 0.008 m over the course of an entire sea ice growth season. Estimated Arctic basin-wide sea ice thickness from SLICE for the sea ice growth seasons beginning between 2012 through 2019 capture a mean of 12.0 % less volumetric growth than a CryoSat-2 and Soil Moisture and Ocean Salinity (SMOS) merged sea ice thickness product (CS2SMOS) and a mean of 8.3 % more volumetric growth than the Pan-Arctic Ice–Ocean Modeling and Assimilation System (PIOMAS). The spatial distribution of the sea ice thickness differences between the retrieval results and those reference datasets show patterns consistent with expected sea ice thickness changes due to dynamic effects. This new retrieval method is a viable basis for a long–term sea ice thickness climatology, especially if dynamic effects can be captured through inclusion of an ice motion dataset.