Ben Harvey, Len Shaffrey NCAS-Climate, University of Reading Tim Woollings

1. Large-scale temperature gradients and the extratropical storm track responses in CMIP5 Ben Harvey, Len Shaffrey NCAS-Climate, University of Reading Tim Woollings AOPP, University of Oxford EMS Annual Meeting, Reading, September 2013

2. Data from 24 models One run per model Scenario: RCP8.5 – HISTORICAL Storm track measure: 2-6 day MSLP std dev CMIP5 storm track responses

3. Possible `drivers’ of the spread

4. Possible `drivers’ of the spread • Are there correlations between the responses of the storm tracks and the responses of the drivers inthe CMIP5 models? • Here, focus on equator-to-pole ∆T

5. Talk outline • Equator-to-pole ∆T in the CMIP5 models • The North Atlantic wintertime storm track • A quick look at other regions

6. CMIP5 temperature responses DJF North Atlantic only: 60W-10W Scenario: RCP8.5 – HISTORICAL See also… Harvey et al (2013)

7. CMIP5 temperature responses DJF North Atlantic only: 60W-10W Scenario: RCP8.5 – HISTORICAL See also… Harvey et al (2013)

8. CMIP5 temperature responses Perform a simple linear regression across the ensemble: DJF North Atlantic only: 60W-10W Scenario: RCP8.5 – HISTORICAL See also… Harvey et al (2013)

9. CMIP5 temperature responses DJF North Atlantic only: 60W-10W Scenario: RCP8.5 – HISTORICAL See also… Harvey et al (2013)

10. CMIP5 storm track regression Regression slopes (shading) and significance of correlation (p=0.05)

11. CMIP5 storm track regression Regression slopes (shading) and significance of correlation (p=0.05) Comparison with mean storm track response:

12. CMIP5 storm track regression Regression slopes (shading) and significance of correlation (p=0.05) Fraction of inter-model variance “explained”:

13. Summary – North Atlantic winter • There are largeregions with significant correlation between the storm track responses and both the ∆T850 and ∆T250 temperature difference responses. • The regression slopesare mostly positive, suggesting: • The storm track responses are driven by the responses of the baroclinicity • The impact of ∆T850 on the storm track response is negativeacross most of the hemisphere, whereas the impact of ∆T250 is positive but confined to the ocean basins. • Together, the two linear regression maps qualitatively capture the spatial pattern of the multi-model mean response. • These results suggest there is potential to reduce the spread in the storm track responses by constraining the relative magnitudes of the warming in the tropical and polar regions.

14. Other regions A similar analysis has been performed for both summer and winter of all the extratropical storm track regions – see Harvey et al (2013) e.g. NH summer

15. Other regions A similar analysis has been performed for both summer and winter of all the extratropical storm track regions – see Harvey et al (2013) e.g. SH summer

16. Summary - continued • The North Atlantic winter is unique in that both the ∆T850 and ∆T250 regressions are needed to capture the pattern of the mean response. This more complex behaviour may go some way towards explaining the particularly large inter-model spread in the North Atlantic region. • One limitation of this study is that the causality of the correlations cannot be determined. It is not clear whether the storm tracks respond directly to the equator-to-pole temperature difference, or instead to more local baroclinicity changes (e.g. SST, sea-ice or land-sea contrast changes), which may themselves be correlated with the equator-to-pole temperature difference.

17. Summary - continued • The North Atlantic winter is unique in that both the ∆T850 and ∆T250 regressions are needed to capture the pattern of the mean response. This more complex behaviour may go some way towards explaining the particularly large inter-model spread in the North Atlantic region. • One limitation of this study is that the causality of the correlations cannot be determined. It is not clear whether the storm tracks respond directly to the equator-to-pole temperature difference, or instead to more local baroclinicity changes (e.g. SST, sea-ice or land-sea contrast changes), which may themselves be correlated with the equator-to-pole temperature difference. Thank you for listening