1. Predictability of cold spring seasons in Europe Mxolisi E. Shongwe, Christopher A. T. Ferro, Caio A. S. Coelho and Geert Jan van Oldenborgh

2. Outline • GCM skill in predicting MAM 2-m temperature in Europe • Snow – 2-m temperature relationships • Model representation of observed snow • Summary

3. GCMs used

4. Models • GCMs: Feb 1 analysis time (available Feb 15), Mar-May verification (mainly March) • Statistical model: Nov-Jan T2m, Feb 1 snow depth, ONC

5. GCM ROC scores

6. Brier skill scores

7. Highlights • GCMs show good skill in predicting 2-m temperature in Central and Eastern Europe • Higher skill for cold `extremes’ • Skill surpasses that of statistical model based on persistence and snow depth

8. No skill in SLP Maps directly from Climate Explorer climexp.knmi.nl

9. 2-m temperature –Snow relationship Coldest 2-m temperature related to widespread snow in eastern Europe

10. 2-m temperature –Snow relationship cont….

11. Highlights • There is evidence of a lag relationship between snow and 2-m temperature in eastern Europe • Related to snow-hydrological and snow-energy effects.

12. Model snow predictions

13. Feb. snow variability

14. Mar. snow variability

15. Apr. snow variability

16. Conclusion • There is potential to predict cold spring seasons in Europe, which is tied to accurate representation of snow processes in climate models.

17. THE END Thank you for your attention!