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Stratosphere-Troposphere Coupling and Links with Eurasian Land Surface Variability

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. Introduction.

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Stratosphere-Troposphere Coupling and Links with Eurasian Land Surface Variability

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  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: • Wave Activity Flux: • October Eurasian snowcover extent • Uses the Robinson/NSIDC dataset • January SLP • NCEP/NCAR Reanalysis Data

  4. 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

  5. 2013

  6. 2013 • 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:

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

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

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

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

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

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

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

  14. 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?

  15. 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!

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

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