1. Welcome to the 2012 Warn-on-Forecast and High Impact Weather Workshop!

2. Agenda for Today Session 1: Warn-on-Forecast Overview and Status Reports Lunch Session 2: GOES-R Status and Applications Session3: The Future of Severe Weather Warnings Dinner Panel Discussion: Future of Severe and High Impact Weather Warnings

3. Agenda for Thursday Session 4: Verification of High-Resolution Forecasts Session 5: Ensemble Data Assimilation and Predictability Wrap-up Discussion End by 1 pm

4. Special Thanks Linda McGuckin, NSSL Joey Rodriguez, OU Conference Services Session chairs: Kevin Kelleher, Ralph Petersen, David Andra, Steve Weiss and Jason Otkin Panel Discussion Moderator: Liz Quetone Panelists: Kim Klockow, Mike Magee, Bob Roberts, Rick Smith

5. WiFi Access

6. Poster Presenters We will have a poster introduction session where everyone gets 1 minute to introduce themselves and tell us one important fact about your poster. Will start at 6:00 pm.

7. Introductions!

9. Convective-scale Warn-on-Forecast Vision Probabilistic tornado guidance: Forecast looks on track, storm circulation (hook echo) is tracking along centerline of highest tornadic probabilities Radar and Initial Forecast at 2100 CSTRadar at 2130 CST: Accurate Forecast Most Likely Tornado Path T=2120 CST T=2150 T=2130 T=2140 70% 50% 30% T=2200 CST Developing thunderstorm Most Likely Tornado Path T=2120 CST T=2150 T=2130 T=2140 T=2200 CST An ensemble of storm-scale NWP models predict the path of a potentially tornadic supercell during the next 1 hour. The ensemble is used to create probabilistic tornado guidance. 70% 50% 30% Stensrud et al. 2009 (October BAMS)

12. Probabilistic convective-scale analysis and forecast system Updated frequently and providing confidence information with focus on 0 to 1 h time frame

13. Recall that 2010 was our first year! Many new employees were hired during the first project year (staff and students) Started monthly Partners meeting WoF Webpage Collaborations strengthened Additional funding generated

14. Challenges Defined in 2010 Best assimilation technique to use Radar data quality control; value of other data Errors in environmental conditions Predictability of severe weather Model error How to use storm-scale ensemble data for warning operations How could probabilistic hazard information assist/support decision-making by the public

15. Radar Data QC Improvements Environmental Sensitivity, Improved Mesoscale Prediction Development of Data Assimilation Methods, Linkages to RR/HRRR How to best use probabilistic information: HWT, SDPG and SSWIM VORTEX2 Studies 2010 2015 2020 Model Physics Improvements Case Studies: Where are we now?

16. Talks this Morning 9:00 – Results of WoF Testing in the Hazardous Weather Testbed (Kristin Kuhlman) 9:30 – Radar Data Quality Control (Kevin Manross) 10:00 – Break 10:30 – Data Assimilation Technique Development (Ming Xue) 11:00 – Warn-on-Forecast Case Studies (Louis Wicker) 11:30 – Model Physics Sensitivities and Challenges (David Dowell)

17. Other WoF Talks 5:10 Wednesday – How university and school district officials anticipated and responded to NWS tornado warnings and their thoughts on extended lead time: Spring 2011 case studies (Stephanie Hoekstra, Amy Nichols and Eve Gruntfest) L OTS OF P OSTERS T ONIGHT 8:30 Thursday- Verification of Warn-on-Forecast (Adam Clark) 12:00 Thursday – Predictability of Supercell Thunderstorms (Rebecca Belobraydich, David Stensrud)

18. High Impact Prediction (HIP)… …is a Unifying Theme

19. Leadership and Partnerships cimms

20. WoF-supported Publications Published or in press Dawson, D. T., L. J. Wicker, E. R. Mansell, and R. L. Tanamachi, 2012: Impact from the environmental wind profile on ensemble forecasts of the 4 May 2007 Greensburg tornado and its associated mesoscyclones.. Mon. Wea. Rev., 140, 696-712. doi: DOI: 10.1175/MWR-D-11-00008.1.DOI: 10.1175/MWR-D-11-00008.1. Gao, J., and D. J. Stensrud, 2012: Assimilation of reflectivity data in a convective-scale, cycled 3DVAR framework with hydrometeor classification. J. Atmos. Sci., in press. doi: http://dx.doi.org/10.1175/JAS-D- 11-0162.1http://dx.doi.org/10.1175/JAS-D- 11-0162.1 Jones, T., and D. J. Stensrud, 2012: Assimilating AIRS temperature and mixing ratio profiles using an ensemble Kalman filter approach for convective-scale forecasts. Wea. Forecasting, in press. doi: http://dx.doi.org/10.1175/WAF-D-11-00090.1 http://dx.doi.org/10.1175/WAF-D-11-00090.1 Jung, Y., M. Xue, and M. Tong, 2012: Ensemble Kalman filter analyses of the 29-30 May 2004 Oklahoma tornadic thunderstorm using one- and two-moment bulk microphysics schemes, with verification against polarimetric data. Mon. Wea. Rev., in press. doi:http://dx.doi.org/10.1175/MWR-D-11-00032.1http://dx.doi.org/10.1175/MWR-D-11-00032.1 Marsh, P. T, J. S. Kain, A. J. Clark, V. Lakshmanan, N. M. Hitchens, and J. Hardy, 2012: A Method for Calibrating Deterministic Forecasts of Rare Events. Wea. Forecasting, in press. doi: http://dx.doi.org/10.1175/WAF-D- 11-00074.1http://dx.doi.org/10.1175/WAF-D- 11-00074.1 Wheatley, D.M., D. J. Stensrud, D. C. Dowell, and N. Yussouf, 2012: Application of a WRF mesoscale data assimilation system to springtime severe weather events 2007-2009. Mon. Wea. Rev., in press. doi: http://dx.doi.org.10.1175/MWR-D-11-00106.1 http://dx.doi.org.10.1175/MWR-D-11-00106.1 Yussouf, N., and D. J. Stensrud, 2012: Comparison of single-parameter and multiparameter ensembles for assimilation of radar observations using the ensemble Kalman filter. Mon. Wea. Rev., 140, 562–586. doi: http://dx.doi.org/10.1175/MWR-D-10-05074.1 http://dx.doi.org/10.1175/MWR-D-10-05074.1

21. In review Ge, G., J. Gao, and M. Xue, 2012: Diagnostic pressure equation as a weak constraint in a storm-scale three dimensional variational radar data assimilation system. J. Atmos. Ocean. Tech., in review. Snook, N., M. Xue, and Y. Jung, 2012: Ensemble probabilistic forecasts of a tornadic mesoscale convective system from ensemble Kalman filter analyses using WSR-88D and CASA radar data. Mon. Wea. Rev., in review. Potvin, C. K., and L.J. Wicker, 2012: Comparisons of kinematic retrievals within a simulated supercell: EnKF radar data assimilation versus dual-Doppler analysis. Mon. Wea. Rev., in review.