1. Stratosphere-Troposphere Coupling and Links with Eurasian Land Surface Variability Cohen et. al, 2007: Journal of Climate, 20, 5335-5343 Adam Turchioe 2 Dec 2013 ATM 525

2. Introduction Stratosphere-Troposphere annular-mode events are always preceded by an anomalous lower-stratospheric planetary wave activity flux, but lower-tropospheric wave activity signatures of these events are more difficult to find Difficulty is due to the variability of the troposphere in relation to the variability to the stratosphere Goal to use these precursors to improve long-term forecasts

3. Method Uses three metrics to diagnose relationship: 1. Wave Activity Flux: 2. October Eurasian snowcover extent Uses the Robinson/NSIDC dataset 3. January SLP NCEP/NCAR Reanalysis Data

8. Conclusion December WAF has a strong center of action over a sector extending from eastern Europe to eastern Asia This corresponds to the climatologically greatest variance in October snow extent The January SLP strongly resembles the Arctic Oscillation (AO) The strong relationship (R=0.79, 0.77) between the WAF/SLP and Oct Snow/SLP shows tropospheric conditions can be used to predict stratospheric  tropospheric interactions weeks to months in advance

10. 2013

11. 2013 has had a phenomenally fast start to snowfall growth. Total Eurasian snow cover extent is well above the 30-year climatological norm Results with AO correlation have shown there is a MUCH greater importance with snow growth east of 70°E than west. Notice how the last 3 weeks of October Asian snow cover anomaly tailed off dramatically, as seen in the weekly 2013 snow anomaly maps:

12. Week 38 2013 vs 10-Year Avg Sept 23

14. Week 39 2013 vs 10-Year Avg Sept 30

16. Week 40 2013 vs 10-Year Avg Oct 07

18. Week 41 2013 vs 10-Year Avg Oct 14

20. Week 42 2013 vs 10-Year Avg Oct 21

22. Week 43 2013 vs 10-Year Avg Oct 28

24. Week 44 2013 vs 10-Year Avg Nov 04

26. 2013 As a result, any early snowfall positive anomaly was greatly offset by a very benign rate of increase of snowfall Also, in order to finalize the remaining slope, used the current 2-week snowfall projection and visually identified the year that most closely matched the expected snowfall pattern (which turned out to be 2002) Thus, the 2013 Snow Growth Parameter Index number is 0.816 Where does this rank vs other years?

29. 2013 Once again, this is still very new research and the first- ever use of this index as a predictor However, with statistically significant correlation values, this year’s winter appears to be headed towards a positive AO state Will continue to monitor daily snowfall and verify that 2002 is a good analog year for the next two weeks Will continue working on getting this index to use the daily snowfall data Thank you!

30. Adam Turchioe University at Albany 1600 Washington Ave Albany, New York 12203 aturchioe@albany.edu 630.337.1999