Welcome to the2012 Warn-on-Forecast and

High Impact Weather Workshop!

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

Agenda for Thursday

• Session 4: Verification of High-Resolution Forecasts

• Session 5: Ensemble Data Assimilation and Predictability

• Wrap-up Discussion• End by 1 pm

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

WiFi Access

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.

Introductions!

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 CST Radar at 2130 CST: Accurate Forecast

MostLikelyTornadoPath

T=2120 CST

T=2150

T=2130T=2140

70%

50%

30%

T=2200 CST

Developing thunderstorm

MostLikelyTornadoPath

T=2120 CST

T=2150

T=2130T=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)

Probabilistic convective-scale analysis and forecast system

Updated frequently and providing confidence information with focus on 0 to 1 h time frame

• 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

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

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?

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)

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)

• LOTS OF POSTERS TONIGHT

• 8:30 Thursday- Verification of Warn-on-Forecast (Adam Clark) • 12:00 Thursday – Predictability of Supercell Thunderstorms

(Rebecca Belobraydich, David Stensrud)

HighImpactPrediction(HIP)…

…is a UnifyingTheme

Leadership and Partnerships

cimms

WoF-supported PublicationsPublished or in pressDawson, 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.

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-11-0162.1

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

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- 00032.1

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-11-00074.1

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

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

In reviewGe, 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.