Satellite-Based Data Assimilation System for the Initialization of Arctic Sea Ice Concentration and Thickness Using CICE5

The satellite-derived sea ice concentration (SIC) and thickness (SIT) observation over the Arctic region are assimilated by implementing Ensemble Optimal Interpolation (EnOI) into Community Ice CodE version 5.1.2 (CICE5) model. observations derived from Special Sensor Microwave Imager/Sounder (SSMIS) for SIC, European Space Agency's (ESA) Soil Moisture Ocean Salinity mission (SMOS) SIT of thin ice, ESA's CryoSat-2 satellite thick ice. during 2000–2019, 2011–2019, respectively. quality reanalysis is evaluated comparing with modeled data. Three data assimilation experiments conducted: noDA without assimilation, Ver1 SIC Ver2 assimilation. climatological bias in was reduced 29% marginal zones boreal winter, 82% pan-Arctic ocean summer. simulating interannual variation extent (SIE) improved all months particularly root-mean-square errors (RMSEs) SIE anomaly August significantly compared to noDA. However, variations unrealistic which requires additional observation. further 28% winter that Ver1. variability anomalies realistically simulated reducing RMSEs 33% February, dominant extracted empirical orthogonal function (EOF) better than improves not only SIT, but also SIC. leading EOF those winter. improvements led assimilating clear summer, possible due lack available this season.