Serial clustering of extratropical cyclones in a multi‐model ensemble of historical and future simulations

• Published in: Quarterly journal of the Royal Meteorological Society 2015-10, Vol.141 (693), p.3076-3087
• Main Authors: Economou, T., Stephenson, D. B., Pinto, J. G., Shaffrey, L. C., Zappa, G.
• Format: Article
• Language: English
• Subjects: Atmospheric forcing; Climate change; Climate models; CMIP5; Cyclones; Dispersion; Extratropical cyclones; Meteorology; North Atlantic Oscillation; Ocean-atmosphere system; Poisson process; regional climate change; Sampling; Simulation; Statistical analysis; storm clustering; Storm tracks; Storms
• ISSN: 0035-9009; 1477-870X
• DOI: 10.1002/qj.2591

This study has investigated serial (temporal) clustering of extratropical cyclones simulated by 17 climate models participating in CMIP5. Clustering was estimated by calculating the dispersion (ratio of variance to mean) of 30 December–February counts of Atlantic storm tracks passing near each grid point. Results from single historical simulations of 1975–2005 were compared to those from historical ERA40 reanalyses from 1958 to 2001 and single future model projections of 2069–2099 under the RCP4.5 climate change scenario. Models were generally able to capture the broad features in reanalyses reported previously: underdispersion/regularity (i.e. variance less than mean) in the western core of the Atlantic storm track surrounded by overdispersion/clustering (i.e. variance greater than mean) to the north and south and over Western Europe. Regression of counts onto North Atlantic Oscillation (NAO) indices revealed that much of the overdispersion in the historical reanalyses and model simulations can be accounted for by NAO variability. Future changes in dispersion were generally found to be small and not consistent across models. The overdispersion statistic, for any 30‐year sample, is prone to large amounts of sampling uncertainty which obscures the climate change signal. For example, the projected increase in dispersion for storm counts near London in the CNRMCM5 model is 0.1 compared to a standard deviation of 0.25. Projected changes in the mean and variance of NAO are insufficient to create changes in overdispersion that are discernible above natural sampling variations.