Arctic Sea Ice Thickness Variability and the Large-scale Atmospheric Circulation Using Satellite Observations, PIOMAS, and the CESM Large Ensemble

Arctic sea ice is an important component in the global climate system.  Declining sea ice in the last couple of decades is one of the primary contributors to enhanced Arctic warming, known as “Arctic amplification.”  Changes in sea ice extent and concentration are well documented through the satellite record (from 1979), but sea ice thickness (SIT) satellite measurements and therefore sea ice volume (SIV) estimates based on satellite data remain limited to within the last decade.  Furthermore, in many cases the estimates do not include the entire Arctic sea ice cover.  Even these recent estimates of SIT from satellites rely on a number of assumptions and are associated with large uncertainties making it difficult to quantify interannual variability and the long-term trend.

The Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) provides spatially and temporally complete values for SIT with areal averages validated to SIT satellite observations from ICESat and CryoSat-2. While PIOMAS can assimilate sea-ice concentration, sea-ice velocity, and sea surface temperature, it does not currently assimilate SIT from satellite observations. Here, we use a hierarchal model within a Bayesian statistical framework to incorporate SIT observations and PIOMAS sea ice output to improve upon the spatial distribution and temporal coverage of SIT. We provide a statistical method of integrating submarine, satellite, and modeled data with an emphasis in reducing the error and uncertainty which may arise by only using existing SIT datasets independently. This results in estimates that combine information regarding SIT from multiple sources and thus better examine the interannual variability and long-term trends of SIT and SIV in the Arctic.