1. Convective-Scale Numerical Weather Prediction and Data Assimilation Research At CAPS Ming Xue Director Center for Analysis and Prediction of Storms and School of Meteorology University of Oklahoma mxue@ou.edu September, 2010 ARPS Simulated Tornado

2. Future of NWP – also what’s happening in research and experimental realtime forecast mode at CAPS Global models running at < 10 km grid spacing, Continental-scale regional models and their ensembles running at ~1 km grid spacing, resolving individual thunderstorms and localized phenomena, and providing probabilistic information for decision making and response. Localized nested ensemble prediction systems running at < 1 km grid spacing, for tornado, turbulence, city-scale forecasts. Typhoon/hurricane track and intensity forecasts are much improved at convection-resolving resolutions Observations from radar, satellite and in-situ platforms are effectively assimilated into NWP models Need Peta-flop+ supercomputers!

3. Storm-Scale Convection-Allowing Ensemble and Convection-Resolving Deterministic Forecasting CAPS/OU has been carrying out a project since 2007 to develop, conduct and evaluate realtime high-resolution ensemble and deterministic forecasts for convective-scale hazardous weather. Forecasts were directly fed to the NOAA HWT (Hazardous Weather Testbed) and evaluated in realtime by forecasters and researchers in an organized effort. Goals: To determine the optimal design, configurations, and post- processing of storm-scale ensemble prediction, and to provide the products for evaluation by forecasters and researchers, and test storm- scale data assimilation methods. Spring 2010: 26-member 4-km ensemble and one 1-km forecasts for full CONUS domain. 30-hourly daily forecasts over 7 weeks. Assimilation of data from 120+ radars. Multi-model (WSR-ARW, WRF-NMM and ARPS), multi-physics, perturbed IC and LBC (from SREF).

4. CAPS SSEF Forecast Configurations of Past Four Years Spring 2007: 10-member WRF-ARW, 4 km, 33 h, 21Z start time, NAM+SREF ICs. 5 members physics perturbations only, 5 with Phy+IC+LBC perturbations. Single 2 km grid. 2/3 CONUS (Xue et al.; Kong et al.; 2007 NWP conf.) Spring 2008: larger domain, 00Z start, Phy+IC+LBC pert for all. Radar Vr and Z data assimilation for 4 and 2 km grids! (Xue et al.; Kong et al. 2008 SLS Conf.) Spring 2009: 20 members, 4 km, 3 models (ARW, NMM, ARPS), mixed physics/IC/LBCs. Single 1 km grid. Radar DA on native grids. 30 h forecasts from 0Z (Xue et al.; Kong et al. 2009 NWP Conf.) Spring 2010: 26 4-km and one 1-km forecasts. Full CONUS domain. Some members with physics difference only, and 3 with storm-scale and mesoscale IC perturbations only for studying error growth and predictability. About 1.5 months each spring season from mid-April through early June http://forecast.caps.ou.edu.

5. June 14, 2010 OKC Flooding

6. 1 km WRF-ARW forecasts of composite reflectivity Observed radar mosaic reflectivity 13h 13Z 14h 14Z 15h 15Z

7. June 14, 2010 OKC Flooding Max=151mm Max=141mm Max=125mm Max=71% Max=64% Raw probability of hourlyprecipitation >0.5 inch Probability-matched ensemble meanhourly accumulated precipitation (mm) 13h 13Z 14h 14Z 15h 15Z

8. 12–18Z accumulated precipitation: 18h (June 14, 2010 – OKC Flood Day) SSEF mean SSEF Prob match SREF mean SREF Prob match QPE NAM HWT images

9. 18–0Z accumulated precipitation: 24h (June 14, 2010 – OKC Flood Day) SSEF mean SSEF Prob match SREF mean SREF Prob match QPE NAM HWT images

10. ETS for 3-hourly Precip. ≥ 0.5 in 2008 (32-day) 2009 (26-day) Probability-matched score generally better than any ensemble member 2 km score no-better than the best 4-km ensemble member – may be due to physics 1-km score better than any 4-km member and than the 4 km PM score. Radar data clearly improves precipitation forecasts, up to 12 hours. High-resolution forecasts clearly consistently better than 12 km NAM. With radar no radar 12 km NAM With radar no radar 12 km NAM

11. Comparisons of reflectivity GSS (ETS) scores of SSEF, HRRR and NAM for Spring 2010 CAPS SSEF Ensemble PM Mean CAPS SSEF 1 km Model CAPS SSEF ARW-CN (control w/o radar assimilation ) CAPS SSEF ARW-C0 (control w/o radar assimilation ) HRRR NAM Corollary Lesson: To provide a “fair” comparison Between CAPS and HRRR, the 01Z and 13Z runs for HRRR should be used

12. Comparison of CAPS 4 km Cn/C0 2008 Forecasts with McGill 2-km MAPLE Nowcasting System and Canadian 15-km GEM Model Correlation for reflectivity CSI for 0.2 mm/h Courtesy of Madalina Surcel of McGill U. (Surcel et al. 2009 Radar Conf.) 4km with radar 4km no radar MAPLE

13. Future Plan (over the next three years) General direction: more emphasis on aviation weather (e.g., 3 weeks in June + May), more runs/day, shorter forecast ranges, fine-tuning of ensemble design, Multi-scale IC perturbations, EnKF-based perturbations More intelligent choices of physics suites, possibly introduce stochastic physics. Addition of Navy’s COAMPS model (4 models total) Improved control initial condition via advanced data assimilation Possible EnKF data assimilation Possible hybrid ensemble-variational analysis based on the operational GSI framework Produce calibrated storm-scale ensemble products. Post-analysis and probabilistic products: e.g., calibration, bias removal, detailed performance evaluation, cost-benefit/trade off assessment, effective products for end users (e.g., those for aviation weather, severe storms); Integration/coordination with national mesoscale ensemble efforts (DTC/DET collaborations). Possibly set up a CONUS-sized quasi-operational storm-scale ensemble forecasting system using university-based supercomputers.

14. CAPS Realtime Convection-Allowing-Resolution Hurricane Forecasts In fall 2010, CAPS is producing experimental single-large- domain 4-km hurricane forecasts over Atlantic 48 hour forecasts twice daily (00 and 12 TC) Two sets of WRF-ARW forecasts, using GFS and global EnKF analyses and corresponding LBCs. Global EnKF and forecasts produced by Jeff Whitaker of ESRL. Goals: Assessing convection-resolving model in predicting TC genesis, track, intensity and structure. Experiment ongoing and systematic evaluation to be performed.

15. 87 h Prediction of Hurricane Earl at 4 km dx

16. 42 hour forecast valid at 2 pm today Dx =4 km 1800x900x50 grid

17. HIGH-RESOLUTION NUMERICAL SIMULATIONS OF TYPHOON MORAKOT (2009) 17

18. 6h12h24h ARPS 2.5 km Forecast of Composite Reflectivity for Morokat with GFS IC + Radar obs 3h ARPS

19. observation Hourly Accumulated Precipitation 6 h fcst 12 h fcst 24 h fcst Radar Precipitation Estimate

20. Total Accumulated Precipitation 6 h fcst 12 h fcst 24 h fcst Radar Precipitation Estimate 1630mm 1530mm