Evaluation of Sea Ice Simulation of CAS-ESM 2.0 in Historical Experiment

• Published in: Atmosphere
• Main Authors: Xin Gao, Peng Fan, Jiangbo Jin, Juanxiong He, Mirong Song, He Zhang, Kece Fei, Minghua Zhang, Qingcun Zeng
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2022
• Subjects: CAS-ESM 2.0; sea ice; seasonal cycle; sea ice mass budget; Meteorology. Climatology; QC851-999; Antarctic; Arctic; The Antarctic; Antarc*; Sea ice
• Online Access: https://doi.org/10.3390/atmos13071056; https://doaj.org/article/299422d72c394366b4a61d2128ec2bfd

A sea ice model is an important component of an Earth system model, which is an essential tool for the study of sea ice, including its internal processes, interactions with other components, and projected future changes. This paper evaluates a simulation of sea ice by the Chinese Academy of Sciences Earth System Model version 2 (CAS-ESM 2.0), focusing on a historical simulation in the Coupled Model Intercomparison Project Phase 6 (CMIP6). Compared with the observations, CAS-ESM 2.0 reproduces reasonable seasonal cycle features and the climatological spatial distribution of Arctic and Antarctic sea ice, including sea ice extent (SIE), sea ice concentration, and sea ice thickness and motion. However, the SIE in CAS-ESM 2.0 is too large in winter and too low in summer in both hemispheres, indicating higher seasonal variations of the model relative to observations. Further sea ice mass budget diagnostics show that basal growth contributes most to ice increase in both hemispheres, basal melt and top melt make a comparable contribution to Arctic ice decrease, and basal melt plays a dominant role in Antarctic ice loss. This, combined with surface air temperature (SAT) and sea surface temperature (SST) biases, suggests that the excess of sea ice simulated in wintertime in both hemispheres and the lower SIE simulated in the Antarctic summer are mainly attributable to the bias in SST, whereas the lower SIE simulated in the Arctic summer is probably due to the combined effects of both the SST and SAT biases.