Preprints
https://doi.org/10.5194/tc-2021-353
https://doi.org/10.5194/tc-2021-353

  22 Nov 2021

22 Nov 2021

Review status: this preprint is currently under review for the journal TC.

Seasonal Sea Ice Prediction with the CICE Model and Positive Impact of CryoSat-2 Ice Thickness Initialization

Shan Sun1 and Amy Solomon2 Shan Sun and Amy Solomon
  • 1NOAA/Global Systems Laboratory
  • 2NOAA/Physical Sciences Laboratory and University of Colorado Boulder, Cooperative Institute for Research in Environmental Sciences

Abstract. The Los Alamos sea ice model (CICE) is being tested in standalone mode for its suitability for seasonal time scale prediction. The prescribed atmospheric forcings to drive the model are from the NCEP Climate Forecast System Reanalysis (CFSR). A built-in mixed layer ocean model in CICE is used. Initial conditions for the sea ice and the mixed layer ocean in the control experiments are also from CFSR. The simulated sea ice extent in the Arctic in control experiments is generally in good agreement with observations in the warm season at all lead times up to 12 months, suggesting that CICE is able to provide useful ice edge information for seasonal prediction. However, the ice thickness forecast has a positive bias stemming from the initial conditions and often persists for more than a season, limiting the model’s seasonal forecast skill. In addition, thicker ice has a lower melting rate in the warm season, both at the bottom and top, contributing to this positive bias. When this bias is removed by initializing the model using ice thickness data from satellite observations while keeping all other initial fields unchanged, both simulated ice edge and thickness improve. This indicates the important role of ice thickness initialization in sea ice seasonal prediction.

Shan Sun and Amy Solomon

Status: open (until 17 Jan 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Shan Sun and Amy Solomon

Shan Sun and Amy Solomon

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Short summary
We validate the standalone CICE sea ice model for application in the seasonal forecast, before it is used in the coupled atmosphere-ocean-ice model. We found the model did a better job in forecasting Arctic sea ice extent in the warm season than in the cold season at the seasonal time scale. A higher forecast skill is achieved when the model is initialized with ice thickness from satellite observations, indicating the importance of the ice thickness initialization.