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Climate Dynamics

, Volume 46, Issue 3–4, pp 1241–1256 | Cite as

How well do CMIP5 climate models reproduce explosive cyclones in the extratropics of the Northern Hemisphere?

  • C. SeilerEmail author
  • F. W. Zwiers
Article

Abstract

Extratropical explosive cyclones are rapidly intensifying low pressure systems with severe wind speeds and heavy precipitation, affecting livelihoods and infrastructure primarily in coastal and marine environments. This study evaluates how well the most recent generation of climate models reproduces extratropical explosive cyclones in the Northern Hemisphere for the period 1980–2005. An objective-feature tracking algorithm is used to identify and track cyclones from 25 climate models and three reanalysis products. Model biases are compared to biases in the sea surface temperature (SST) gradient, the polar jet stream, the Eady growth rate, and model resolution. Most models accurately reproduce the spatial distribution of explosive cyclones when compared to reanalysis data (R = 0.94), with high frequencies along the Kuroshio Current and the Gulf Stream. Three quarters of the models however significantly underpredict explosive cyclone frequencies, by a third on average and by two thirds in the worst case. This frequency bias is significantly correlated with jet stream speed in the inter-model spread (R \(\ge\) 0.51), which in the Atlantic is correlated with a negative meridional SST gradient (R = −0.56). The importance of the jet stream versus other variables considered in this study also applies to the interannual variability of explosive cyclone frequency. Furthermore, models with fewer explosive cyclones tend to underpredict the corresponding deepening rates (R \(\ge\) 0.88). A follow-up study will assess the impacts of climate change on explosive cyclones, and evaluate how model biases presented in this study affect the projections.

Keywords

Explosive cyclones CMIP5 climate models Model biases 

Notes

Acknowledgments

The authors gratefully acknowledge the financial support of the Marine Environmental Observation Prediction and Response Network (MEOPAR) for this research. We thank Dr. Kevin Hodges from the University of Reading (UK) for supporting our application of his cyclone tracking algorithm. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Table 2 of this paper) for producing and making available their model output. For CMIP the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We thank the respective centers for providing their reanalysis data products ERA-Interim, NCEP-CFSR and NASA-MERRA. We are grateful for the constructive comments from two anonymous reviewers. Please contact Christian Seiler (cseiler@uvic.ca) for obtaining the output data presented in this research.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Pacific Climate Impacts ConsortiumUniversity of VictoriaVictoriaCanada

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