The Role of the Mean State of Arctic Sea Ice on Near-Surface Temperature Trends

• Published in: Journal of Climate
• Main Authors: van der Linden, E.C., Bintanja, R., Hazeleger, W., Katsman, C.A.
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2014
• Subjects: albedo feedback; amplification; climate model sensitivity; extent; future; gcm; inversion; predictability; thickness; variability; Arctic; albedo; Sea ice
• Online Access: https://research.wur.nl/en/publications/the-role-of-the-mean-state-of-arctic-sea-ice-on-near-surface-temp; https://doi.org/10.1175/JCLI-D-12-00617.1

Century-scale global near-surface temperature trends in response to rising greenhouse gas concentrations in climate models vary by almost a factor of 2, with greatest intermodel spread in the Arctic region where sea ice is a key climate component. Three factors contribute to the intermodel spread: 1) model formulation, 2) control climate state, and 3) internal climate variability. This study focuses on the influence of Arctic sea ice in the control climate on the intermodel spread in warming, using idealized 1% yr(-1) CO2 increase simulations of 33 state-of-the-art global climate models, and combining sea ice-temperature relations on local to large spatial scales. On the Arctic mean scale, the spread in temperature trends is only weakly related to ice volume or area in the control climate, and is probably not dominated by internal variability. This suggests that other processes, such as ocean heat transport and meteorological conditions, play a more important role in the spread of long-term Arctic warming than control sea ice conditions. However, on a local scale, sea ice-warming relations show that in regions with more sea ice, models generally simulate more warming in winter and less warming in summer. The local winter warming is clearly related to control sea ice and universal among models, whereas summer sea ice-warming relations are more diverse, and are probably dominated by differences in model formulation. To obtain a more realistic representation of Arctic warming, it is recommended to simulate control sea ice conditions in climate models so that the spatial pattern is correct.