North Atlantic 20th century multidecadal variability in coupled climate models: sea surface temperature and ocean overturning circulation

• Published in: Ocean Science
• Main Authors: I. Medhaug, T. Furevik
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2011
• Subjects: geo; envir; North Atlantic; Sea ice
• Online Access: https://doi.org/10.5194/os-7-389-2011; http://www.ocean-sci.net/7/389/2011/os-7-389-2011.pdf; https://doaj.org/article/3526cbbf975c4d3e83ab49b855e4bdca

Output from a total of 24 state-of-the-art Atmosphere-Ocean General Circulation Models is analyzed. The models were integrated with observed forcing for the period 1850–2000 as part of the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report. All models show enhanced variability at multi-decadal time scales in the North Atlantic sector similar to the observations, but with a large intermodel spread in amplitudes and frequencies for both the Atlantic Multidecadal Oscillation (AMO) and the Atlantic Meridional Overturning Circulation (AMOC). The models, in general, are able to reproduce the observed geographical patterns of warm and cold episodes, but not the phasing such as the early warming (1930s–1950s) and the following colder period (1960s–1980s). This indicates that the observed 20th century extreme in temperatures are due to primarily a fortuitous phasing of intrinsic climate variability and not dominated by external forcing. Most models show a realistic structure in the overturning circulation, where more than half of the available models have a mean overturning transport within the observed estimated range of 13–24 Sverdrup. Associated with a stronger than normal AMOC, the surface temperature is increased and the sea ice extent slightly reduced in the North Atlantic. Individual models show potential for decadal prediction based on the relationship between the AMO and AMOC, but the models strongly disagree both in phasing and strength of the covariability. This makes it difficult to identify common mechanisms and to assess the applicability for predictions.