摘要
The Los Alamos sea ice model(CICE) is used to simulate the Arctic sea ice variability from 1948 to 2009. Two versions of CICE are validated through comparison with Hadley Centre Global Sea Ice and Sea Surface Temperature(Had ISST) observations. Version 5.0 of CICE with elastic-viscous-plastic(EVP) dynamics simulates a September Arctic sea ice concentration(SASIC) trend of –0.619 × 1012 m2 per decade from 1969 to 2009, which is very close to the observed trend(-0.585 × 1012 m2 per decade). Version 4.0 of CICE with EVP dynamics underestimates the SASIC trend(-0.470 × 1012 m2 per decade). Version 5.0 has a higher correlation(0.742) with observation than version 4.0(0.653). Both versions of CICE simulate the seasonal cycle of the Arctic sea ice, but version 5.0 outperforms version 4.0 in both phase and amplitude. The timing of the minimum and maximum sea ice coverage occurs a little earlier(phase advancing) in both versions. Simulations also show that the September Arctic sea ice volume(SASIV) has a faster decreasing trend than SASIC.
The Los Alamos sea ice model（CICE） is used to simulate the Arctic sea ice variability from 1948 to 2009. Two versions of CICE are validated through comparison with Hadley Centre Global Sea Ice and Sea Surface Temperature（Had ISST） observations. Version 5.0 of CICE with elastic-viscous-plastic（EVP） dynamics simulates a September Arctic sea ice concentration（SASIC） trend of –0.619 × 1012 m2 per decade from 1969 to 2009, which is very close to the observed trend（-0.585 × 1012 m2 per decade）. Version 4.0 of CICE with EVP dynamics underestimates the SASIC trend（-0.470 × 1012 m2 per decade）. Version 5.0 has a higher correlation（0.742） with observation than version 4.0（0.653）. Both versions of CICE simulate the seasonal cycle of the Arctic sea ice, but version 5.0 outperforms version 4.0 in both phase and amplitude. The timing of the minimum and maximum sea ice coverage occurs a little earlier（phase advancing） in both versions. Simulations also show that the September Arctic sea ice volume（SASIV） has a faster decreasing trend than SASIC.
基金
supported by the National Basic Research Program of China(Grant No.2010CB951804)
the China Meteorological Administration Special Fund for Scientific Research in the Public Interest(Grant No.GYHY201206008)
