Assessing mid-latitude dynamics in extreme event attribution systemsMitchell, D., Davini, P., Harvey, B. ORCID: https://orcid.org/0000-0002-6510-8181, Massey, N., Haustein, K., Woollings, T., Jones, R., Otto, F., Guillod, B., Sparrow, S., Wallom, D. and Allen, M. (2017) Assessing mid-latitude dynamics in extreme event attribution systems. Climate Dynamics, 48 (11-12). pp. 3889-3901. ISSN 0930-7575
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1007/s00382-016-3308-z Abstract/SummaryAtmospheric modes of variability relevant for extreme temperature and precipitation events are evaluated in models currently being used for extreme event attribution. A 100 member initial condition ensemble of the global circulation model HadAM3P is compared with both the multi-model ensemble from the Coupled Model Inter-comparison Project, Phase 5 (CMIP5) and the CMIP5 atmosphere-only counterparts (AMIP5). The use of HadAM3P allows for huge ensembles to be computed relatively fast, thereby providing unique insights into the dynamics of extremes. The analysis focuses on mid Northern Latitudes (primarily Europe) during winter, and is compared with ERA-Interim reanalysis. The tri-modal Atlantic eddy-driven jet distribution is remarkably well captured in HadAM3P, but not so in the CMIP5 or AMIP5 multi-model mean, although individual models fare better. The well known underestimation of blocking in the Atlantic region is apparent in CMIP5 and AMIP5, and also, to a lesser extent, in HadAM3P. Pacific blocking features are well produced in all modeling initiatives. Blocking duration is biased towards models reproducing too many short-lived events in all three modelling systems. Associated storm tracks are too zonal over the Atlantic in the CMIP5 and AMIP5 ensembles, but better simulated in HadAM3P with the exception of being too weak over Western Europe. In all cases, the CMIP5 and AMIP5 performances were almost identical, suggesting that the biases in atmospheric modes considered here are not strongly coupled to SSTs, and perhaps other model characteristics such as resolution are more important. It is recommended that rather than taking statistics over the entire CMIP5 or AMIP5 available models, only models capable of producing the relevant dynamical phenomena be employed for event attribution analyses.
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