1. STORM-SCALE DATA ASSIMILATION AND ENSEMBLE FORECASTING WITH THE NSSL EXPERIMENTAL WARN-ON-FORECAST SYSTEM 40 th National Weather Association Annual Meeting Dusty Wheatley, Kent Knopfmeier, Thomas Jones, and Gerry Creager Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and NOAA/National Severe Storms Laboratory, Norman Oklahoma 20 October 2015

2. Warn-on-Forecast The NOAA Warn-on-Forecast research project is tasked with the development of very short-range (0-1 h) probabilistic forecasts that accurately predict convective hazards -Paradigm shift in warning process, as NWP plays major role -Ensemble-based design, so information rich -Primary goal: Extend tornado, severe thunderstorm, and flash flood warning lead times (Stensrud et al. 2009)

3. Warn-on-Forecast (cont.) Storm-scale data assimilation and ensemble forecasting in a future WoF system will most likely be performed on very- high-resolution (grid spacing ~1 km or less), event- dependent grids Frequent assimilation of conventional + radar + satellite data Development and testing of sub-hourly storm-scale data assimilation with a Weather Research and Forecasting (WRF) model-based system has begun on somewhat coarser convection-allowing grids (grid spacing 3 km)

4. NEWS-e domain 675 km Radar Sites WRF-ARW v3.6.1;56 vertical levels Parent/nested grids run simultaneously in a 1-way nest Event dependent

5. Ensemble Design 36-member ensemble with physics diversity – Microphysics: Thompson – Cumulus (15 km grid only): Kain-Fritsch, Grell, Tiedtke – PBL: YSU, MYJ, MYNN – Radiation (SW/LW): Dudhia/RRTM, RRTMG/RRTMG – Land surface: RAP (and Noah) IC/BCs for *both* parent/nested grids downscaled from 21- member Global Ensemble Forecast System (GEFS) – No IC/BC perturbations – Initialized at 1800 UTC (previous day); followed by a 6-h free forecast

6. Data assimilation system DART – Ensemble Kalman filter (EnKF) Mesoscale DA: On parent and nested grids – 1-h assimilation cycle (until storm-scale experiments begin) – ‘Conventional’ observations -- METAR, mesonet (on nested grid only), marine, radiosonde, ACARS, GOES satellite – wind only – No radar DA in producing background Storm-scale DA: On nested grid only – 15-min assimilation cycle (started in the 1800 – 2100 UTC time period) – Multi-Radar Multi-Sensor (MRMS) reflectivity (> 10 dBZ); includes radar ‘zeros’ 10 levels (1-10 km AMSL) – Level II radial velocity (from 5 radars with “best” anticipated coverage) – Cloud water path retrievals from GOES Imager; includes satellite ‘zeros’ – Mesonet

7. 5) 1) 4) 2) 3)6) Retrospective work: 1)20 May 2013 – Central OK tornado event 2)20 May 2013 – Moore, OK tornado 3)31 May 2013 – El Reno, OK tornado 4)27 April 2014 – High Risk for Arkansas 5)28 April 2014 – MS/AL tornado outbreak 6)11-12 May 2014 – Supercell (NE) to MCS (IA) transition

8. May 20, 2013: 1-h forecasts of vorticity swaths Darker reds = Higher probabilities ~60-min before touchdown ~30-min before touchdownRight at touchdown BLACK lines = Outline of observed thunderstorm (at initial time) BLUE lines = Tornado tracks - Approx. start / end time: 1956 UTC / 2040 UTC 8

9. 2015 HWT NEWS-e Experiment Run in realtime each day from 4 May – 5 June 2015 – Placement of nested grid guided by convective outlook products issued from the Storm Prediction Center – Enhanced risk or greater Storm-scale analyses generated every 15 min – Used to initialize storm-scale forecasts 90-min storm-scale forecasts (5-min output) launched twice hourly (:00/:30) following storm-scale analyses Between 45-60 min of “useful” forecast due to latency

10. 1)9 April 2015 – Northern IL 2)26 April 2015 – North central TX 3)6 May 2015 – Central OK – Central KS 4)16 May 2015 – Southwestern OK – Western north TX 2015 Severe Weather Events 4) 1) 2) 3)

11. May 6, 2015: Central Oklahoma tornado event First storm-scale data assimilation (radar + satellite) at 1900 UTC Ensemble forecasting began at 1930 UTC (after 3 updates) 2030 UTC0230 UTC

12. 90-min forecast initialized 1930 UTC LEFT PANEL: Ensemble maximum updraft helicity MIDDLE PANEL: Prob( updraft helicity > 25 m 2 s -2 ) RIGHT PANEL: Probability of 0-2 km vertical vorticity > 0.005 s -1 Blue polygons == NWS tornado warnings issued during forecast period Black triangles == Tornado reports during forecast period

13. 90-min forecast initialized 2230 UTC LEFT PANEL: Ensemble maximum updraft helicity MIDDLE PANEL: Prob( updraft helicity > 25 m 2 s -2 ) RIGHT PANEL: Probability of 0-2 km vertical vorticity > 0.005 s -1 Forecast captures secondary development to the southwest of the Oklahoma City metropolitan area

14. 90-min forecast initialized 0130 UTC LEFT PANEL: Ensemble maximum updraft helicity MIDDLE PANEL: Prob( updraft helicity > 25 m 2 s -2 ) RIGHT PANEL: Probability of 0-2 km vertical vorticity > 0.005 s -1 Tornado threat begins to diminish after 0000 UTC, but high probabilities of rotation persist

15. May 16, 2015: Southwest Oklahoma tornado event First storm-scale data assimilation (radar + satellite) at 1800 UTC Ensemble forecasting began at 1800 UTC (after 1st update)

16. 90-min forecast initialized 2130 UTC LEFT PANEL: Ensemble maximum updraft helicity MIDDLE PANEL: Prob( updraft helicity > 25 m 2 s -2 ) RIGHT PANEL: Probability of 0-2 km vertical vorticity > 0.005 s -1 Forecast captures mixed-mode convection ahead of dryline, with some suggestion of a significant event over southwest Oklahoma

17. 90-min forecast initialized 2230 UTC LEFT PANEL: Ensemble maximum updraft helicity MIDDLE PANEL: Prob( updraft helicity > 25 m 2 s -2 ) RIGHT PANEL: Probability of 0-2 km vertical vorticity > 0.005 s -1 Measures of rotation still displaced to the north of tornado reports, even with additional storm-scale assimilation

18. Broadening focus to non-supercell modes 11-12 May, 2015: Supercell-to-MCS transition VORTICITY SWATHS 40-dBZ contour Still some useful information 8 h into experiment

19. Much work remains… WoF project has demonstrated skill predicting storm tracks and rotational intensities for 0-2 hours for real-data case studies, but… -Discriminating between tornadic and nontornadic storms remains a challenge! Improved forecasts from assimilation of MPAR data relative to 88D data Understanding how WoF output could/would be used by operational forecasters -How to post-process ensemble data output into probabilistic forecasts? -How can forecasters feedback guide our research emphasis? For WoF to reach its full potential requires a more accurate measurement of the storm-scale environment than the current observational network permits.