Articles | Volume 9, issue 1
The Cryosphere, 9, 399–409, 2015
The Cryosphere, 9, 399–409, 2015

Research article 20 Feb 2015

Research article | 20 Feb 2015

Assessment of sea ice simulations in the CMIP5 models

Q. Shu2,1, Z. Song2,1, and F. Qiao2,1 Q. Shu et al.
  • 1First Institute of Oceanography, State Oceanic Administration, Qingdao, 266061, China
  • 2Key Lab of Marine Science and Numerical Modeling, SOA, Qingdao, 266061, China

Abstract. The historical simulations of sea ice during 1979 to 2005 by the Coupled Model Intercomparison Project Phase 5 (CMIP5) are compared with satellite observations, Global Ice-Ocean Modeling and Assimilation System (GIOMAS) output data and Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) output data in this study. Forty-nine models, almost all of the CMIP5 climate models and earth system models with historical simulation, are used. For the Antarctic, multi-model ensemble mean (MME) results can give good climatology of sea ice extent (SIE), but the linear trend is incorrect. The linear trend of satellite-observed Antarctic SIE is 1.29 (±0.57) × 105 km2 decade−1; only about 1/7 CMIP5 models show increasing trends, and the linear trend of CMIP5 MME is negative with the value of −3.36 (±0.15) × 105 km2 decade−1. For the Arctic, both climatology and linear trend are better reproduced. Sea ice volume (SIV) is also evaluated in this study, and this is a first attempt to evaluate the SIV in all CMIP5 models. Compared with the GIOMAS and PIOMAS data, the SIV values in both the Antarctic and the Arctic are too small, especially for the Antarctic in spring and winter. The GIOMAS Antarctic SIV in September is 19.1 × 103 km3, while the corresponding Antarctic SIV of CMIP5 MME is 13.0 × 103 km3 (almost 32% less). The Arctic SIV of CMIP5 in April is 27.1 × 103 km3, which is also less than that from PIOMAS SIV (29.5 × 103 km3). This means that the sea ice thickness simulated in CMIP5 is too thin, although the SIE is fairly well simulated.

Short summary
We evaluated all CMIP5 sea-ice simulations with more metrics in both the Antarctic and the Arctic, in an attempt to provide the community a useful reference. Generally speaking, our study shows that the performance of an Arctic sea-ice simulation is better than that of an Antarctic sea-ice simulation, that sea-ice extent simulation is better than sea-ice volume simulation, and that mean-state simulation is better than long-term trend simulation.