North Atlantic Oscillation response to transient greenhouse gas forcing and the impact on european winter climate : a CMIP2 multi-model assessment

• Published in: Climate dynamics 2006-09, Vol.27 (4), p.401-420
• Main Authors: STEPHENSON, D. B, PAVAN, V, COLLINS, M, JUNGE, M. M, QUADRELLI, R
• Format: Article
• Language: English
• Subjects: Carbon dioxide; Climate change; Climatology. Bioclimatology. Climate change; Earth, ocean, space; Exact sciences and technology; External geophysics; General circulation models; Geophysics. Techniques, methods, instrumentation and models; Greenhouse gases; Marine; Meteorology; Probability distribution
• ISSN: 0930-7575; 1432-0894
• DOI: 10.1007/s00382-006-0140-x

This study investigates the response of wintertime North Atlantic Oscillation (NAO) to increasing concentrations of atmospheric carbon dioxide (CO^sub 2^) as simulated by 18 global coupled general circulation models that participated in phase 2 of the Coupled Model Intercomparison Project (CMIP2). NAO has been assessed in control and transient 80-year simulations produced by each model under constant forcing, and 1% per year increasing concentrations of CO^sub 2^, respectively. Although generally able to simulate the main features of NAO, the majority of models overestimate the observed mean wintertime NAO index of 8 hPa by 5-10 hPa. Furthermore, none of the models, in either the control or perturbed simulations, are able to reproduce decadal trends as strong as that seen in the observed NAO index from 1970-1995. Of the 15 models able to simulate the NAO pressure dipole, 13 predict a positive increase in NAO with increasing CO^sub 2^ concentrations. The magnitude of the response is generally small and highly model-dependent, which leads to large uncertainty in multi-model estimates such as the median estimate of 0.0061±0.0036 hPa per %CO^sub 2^. Although an increase of 0.61 hPa in NAO for a doubling in CO^sub 2^ represents only a relatively small shift of 0.18 standard deviations in the probability distribution of winter mean NAO, this can cause large relative increases in the probabilities of extreme values of NAO associated with damaging impacts. Despite the large differences in NAO responses, the models robustly predict similar statistically significant changes in winter mean temperature (warmer over most of Europe) and precipitation (an increase over Northern Europe). Although these changes present a pattern similar to that expected due to an increase in the NAO index, linear regression is used to show that the response is much greater than can be attributed to small increases in NAO. NAO trends are not the key contributor to model-predicted climate change in wintertime mean temperature and precipitation over Europe and the Mediterranean region. However, the models' inability to capture the observed decadal variability in NAO might also signify a major deficiency in their ability to simulate the NAO-related responses to climate change.[PUBLICATION ABSTRACT]