Matthew Sardi and Jeffrey Tongue NOAA/NWS, New York, NY 4 November 2010

1. Predictability of High Impact Weather during the Cool Season over the Eastern U.S:CSTAR Operational Aspects Matthew Sardi and Jeffrey Tongue NOAA/NWS, New York, NY 4 November 2010

2. Outline • Who/Why • WFO Goals • Activities to Date: • Training Initiatives • Visualization Software

3. Who in NOAA • WFO’s • New York • Mt Holly • State College • Pittsburgh • NCEP • EMC • HPC • OPC • NOAA Earth System Research Laboratory

4. Motivation • Prediction of mesoscale phenomenon within extratropical storms remains a major challenge.

5. Goal for the WFO • Improvement in operational forecaster understanding of uncertainty/predictability. • Improve communication of uncertainties to users/customers.

6. Specifics • Upton, NY (KOKX): • Improved understanding of cyclone evolution and precipitation bands • Ensemble Forecast Systems (EFS) application to Aviation • Low-level winds • Precipitation type • Snowfall rate • Mentors to the SBU students • 1 SCEP • 1 STEP • 4 Volunteers

7. Specifics (cont) • WFO Philadelphia, PA (KPHI): • Storm surge • Coastal flooding • State College, PA (KCTP): • Visualization Software • Training • Data management • WFO Pittsburgh, PA (KPIT): • Training • Visualization • Graphical Forecast Editor (GFE) Applications

8. Specifics (cont) • Hydrometeorological Prediction Center (HPC): • Precipitation banding. • Cyclone track verification for the winter weather desk, medium range forecast products, as well as the snowfall and QPF products. • HPC will host visiting forecasters, scientists, and project students. • Ocean Prediction Center (OPC): • EFS application to cyclone track and intensity. • East Coast Marine impacts - high winds and waves.

9. Specifics (cont) • Environmental Modeling Center (EMC): • EFS sensitivities related to the Weather Storms Reconnaissance Program • Impacts of wave packets • Training of forecasters: • Impact of targeted observations • SREF system • Cyclone verification • Environmental System Research Laboratory (ESRL): • EFS sensitivities related to the Weather Reconnaissance Program • Training on the impact of targeted observations on predictability.

10. Current CSTAR Training Initiatives • Wave Packets • Targeted Observations • ALPS

11. Wave Packets

12. Target Observations

14. Advanced Linux Prototype System(ALPS) • Running on a “non-baseline” AWIPS Workstation. • Looks and Feels like D2D • Designed for probabilistic forecasting • Visualizing Ensemble Data • Weighting Ensemble Members • Generating Probabilistic Grids • Etc

15. ALPS

16. New Projections

17. Statistical Functionality

18. A Brief Example • The following are all 168 HR (7 Day) Forecasts from last Thursday • Valid at 8 AM this Morning – Thursday, Nov 4th

19. GEFS Members + ECMWF

20. ECMWF

21. GEFS Mean

22. GEFS Mean + ECMWF = MEAN

23. Example Statistics - 850 Temperatures

24. 850 Temperatures - cont

25. How do I get ALPS ? • Visit the SBU CSTAR Page: • http://dendrite.somas.stonybrook.edu/CSTAR/cstar.html

26. ALPS GFE - Future • Deployment of Probabilistic Products • Aviation Specific Examples • Wind Speed • Wind Direction • Gusts (probability of being reported) • No yet Loaded at OKX

27. Example Probabilistic Products

28. Example Probabilistic Products

29. BUFKIT 10 • SREF (21 Members) • WDTB WRF Ensemble • Resolution:  24 KM • Frequency:  00Z and 12Z • Members: 8 ensemble members (23) x 2 Initializations • NMM/ARW • NAM/GFS • KF/BMJ

31. Boundary Layer Winds - Aviation

32. Questions? • CSTAR E-Mail List • Send Jeff Waldstreicher an e-mail • CSTAR WEB PAGE: • http://dendrite.somas.stonybrook.edu/CSTAR/cstar.html