Abstract

Atmospheric 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. For event attribution studies, 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.

Highlights

  • Attributing the changing probability of specific extreme events to human induced climate change is an emerging field

  • In this study we address the adequacy of event attribution systems directly, by comparing the simulation of relevant dynamical modes in the CMIP5 model-ensemble and the Weather@home framework (WAH) initial condition ensemble

  • The study of dynamical modes from a super-ensemble framework is a new direction for extreme event attribution, as traditionally it is the statistics of climate that are analysed

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Summary

Introduction

Attributing the changing probability of specific extreme events to human induced climate change is an emerging field. The ability to quantify human influences on events plays a vital role in academic and societal understanding of climate change impacts It is recognised in international climate change initiatives (IPCC, AR5) and in studies addressing wider atmospheric interactions (Hoskins and Woollings 2015). The use of an older model for event attribution, as in WAH, could be called into question. This is especially true as the WAH model poorly resolves a number of key atmospheric regions, including the boundary layer which is important for land-surface feedbacks (Jaeger and Seneviratne 2011), and the stratosphere, which is important for winter mid-latitude circulation patterns (Mitchell et al 2013). In this study we address the adequacy of event attribution systems directly, by comparing the simulation of relevant dynamical modes in the CMIP5 model-ensemble and the WAH initial condition ensemble.

Models
Jet latitude index
Blocking diagnostic
Storm track calculation
Results
Jet stream
Blocking
North Atlantic Oscillation
Storm tracks
Summary
Full Text
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