1. Predictability of Stratospheric Sudden Warming of 2013 SPARC-SNAP Team Om P Tripathi, Andrew Charlton-Perez, Greg Roff, Mark Baldwin, Martin Charron, Stephen Eckermann, Edwin Gerber, David Jackson, Yuhji Kuroda, Andrea Lang, Ryo Mizuta, Michael Sigmond, Tim Stockdale, Seok-Woo Son

2. SPARC - Stratospheric Network for the Assessment of Predictability (SPARC-SNAP) SPARC-SNAP Introduction

3. SPARC – SNAP A network of research and operational communities aims to answer following questions: Are stratosphere-troposphere coupling effects important throughout the winter or only when major stratospheric dynamical events occur? How far in advance can major stratospheric dynamical events be predicted and usefully add skill to tropospheric forecasts? Which stratospheric processes need to be captured by models to gain optimal stratospheric predictability?

4. Team Leaders  Greg Roff Bureau of Meteorology, Australia  Andrew Charlton-Perez University of Reading Steering Committee  Mark Baldwin University of Exeter, UK  Martin Charron Environment Canada, Canada  Steve Eckermann NRL, USA  Edwin Gerber New York University, USA  Yuhji Kuroda Japan Met Agency, Japan  David Jackson Met Office, UK  Andrea Lang University at Albany, USA  Seok-Woo Son Seoul National University, S Korea  Om TripathiUniversity of Reading (Co-ordinator) (www.sparcsnap.org) SPARC-SNAP

5. SPARC-SNAP Activities A new multi-model experiment to quantify stratospheric predictability Stimulate the growth of a community of researchers interested in stratospheric predictability (workshop, web, newsletters etc). A review paper on current understanding of stratospheric predictability (accepted in QJ) A SPARC report and peer-reviewed articles on the findings of the experiment.

6. SPARC-SNAP Protocol Case-15-10-50+5 Phase 1: SSW NH 2013 23/12/201228/12/201202/01/201307/01/201312/01/2013 Phase 1: Final Warming SH 2012 05/10/201210/10/201215/10/201220/10/201225/10/2012 Run Length15-30 days No. of Ensemble members As many as possible Phase 0Current operational forecast for ONE year Phase 2TBD (Same as phase I for past cases)

7. SPARC-SNAP Operational Models and Database Met Office, UK (METO) Meteorological Research Institute (MRI), JAPAN Naval Research Laboratory, USA (NOGAPS) Bureau of Meteorology, Australia (CAWCR) Korea Air Force operational model, Korea Polar Research Institute, Korea (KOPRI) ECMWF Korea Meteorological Administration (KMA), Korea Environmental Canada (EC), CANADA

8. 1.Model failed to predict SSW 15 days before the event except some members of few models 2.All of the models were able to predict 10 days before the event 3.Models find it hard to sustain the eastely after the event -15 days-10 days KOPRI ECMWF METO NOGAPS MRI CAWCR

9. RMS Error Spread reduces once the model predicted the warming 10 days before the event

10. Best and Worst Members Some members of models have shown vortex weakening or even wind reversal 15 days before the events Best members of model are those that approached closest to the zero line wind at 10 hPa Worst members are those that were farthest away from the zero wind line These two sets are treated separately Upward component of EP flux (v’T’), and contribution from different wave components for these sets compared

11. CAWCR MRI NOGAPS METO KOPRI Epz TroposphereEpz Stratosphere U at 10 hPa 60N EP Flux (Upward component) – ALL Wave Numbers For initialization before 15 days

12. Epz TroposphereEpz Stratosphere U at 10 hPa 60N CAWCR MRI NOGAPS METO KOPRI EP Flux (Upward component) – Wave Numbers-1,2,3 For initialization before 15 days

13. Epz TroposphereEpz Stratosphere U at 10 hPa 60N CAWCR MRI NOGAPS METO KOPRI EP Flux (Upward component) – Wave Number-1 For initialization before 15 days

14. Epz TroposphereEpz Stratosphere U at 10 hPa 60N CAWCR MRI NOGAPS METO KOPRI EP Flux (Upward component) – Wave Number-2 For initialization before 15 days

15. Epz TroposphereEpz Stratosphere U at 10 hPa 60N CAWCR MRI NOGAPS METO KOPRI EP Flux (Upward component) – Wave Number-2 For initialization before 10 days

16. Summary Except a few ensemble members of MRI and METO, none of the models predicted the splitting by the 15 days lead time. A significant number of NOGAPS ensemble predicted a clear displacement type warming 15 days before the event. When NOGAPS is initialized 5 days before the event, it switched its SSW type from displacement to splitting. Detailed EP-flux analyses have shown that models struggle to simulate the amplification of wave-2 structure in the stratosphere despite being successfully generating wave-2 in the troposphere. This is in contrast to the amplification of wave-1 where all the models have shown a significant success in transmitting the wave-1 energy to the stratosphere Data is accessible at http://badc.nerc.ac.uk/help/jasmin_workspaces.htmlhttp://badc.nerc.ac.uk/help/jasmin_workspaces.html For info about SPARC-SNAP activity and data access: http://www.sparcsnap.org/http://www.sparcsnap.org/