1. WARN ON FORECAST AND HIGH IMPACT WEATHER WORKSHOP 09 February 2012 Use of Rapid Updating Meso‐ and Storm‐scale Data Assimilation to Improve Forecasts of Thunderstorms and Other High Impact Weather: The Rapid Refresh and HRRR Forecast Systems NOAA/ESRL/GSD Curtis Alexander, David Dowell, Steve Weygandt, Stan Benjamin, Ming Hu, Tanya Smirnova, Patrick Hofmann, Haidao Lin, Eric James and John Brown

2. ESRL/GSD/AMB Modeling System Overview

3. Hourly Updated NOAA NWP Models 13km Rapid Refresh (RAP) (mesoscale) 13km RUC (mesoscale) 3km HRRR (storm-scale) RUC – current oper Model, new 18h fcst every hour High-Resolution Rapid Refresh Experimental 3km nest inside RAP, new 15-h fcst every hour Rapid Refresh (RAP) replaces RUC at NCEP in 2012 WRF, GSI with RUC features 3

4. NOAA/ESRL/GSD/AMB Models ModelVersionAssimilation Radar DFI RadiationMicrophysics Cum Param PBLLSM RUC N/A RUC-3DVARYes RRTM/Dudh ia Thompson Grell- Devenyi Burk- Thompson RUC RAP WRF- ARW v3.2+ GSI-3DVARYes RRTM/Godd ard Thompson G3 + Shallow MYJRUC HRRR WRF- ARW v3.2+ None: RR I.C. No RRTM/Godd ard ThompsonNoneMYJRUC ModelRun at:Domain Grid Points Grid Spacing Vertical Levels Vertical Coordinate Boundary Conditions Initialized RUC GSD, NCO CONUS 451 x 337 13 km50 Sigma/ Isentropic NAM Hourly (cycled) RAP GSD, NCO North America 758 x 567 13 km50SigmaGFS Hourly (cycled) HRRRGSDCONUS 1799 x 1059 3 km50SigmaRR Hourly (no-cycle)

5. Model Configurations HRRR Primary CoSPA (FAA) NCEPESRL/GSD/AMB RAP Dev RAP Primary HRRR Dev RUC Oper RAP NCO RAP Dev2 RAP Retro HRRR Retro Retrospective Real-Time AMB RAP/HRRR verification system NWS

6. ESRL/GSD/AMB Model Verification CeilingVis 24-hr Precip (03-80 km) Reflectivity (03-80 km) Upper-AirSurface 0.5 – 3.0 kft 0.5 -5.0 mi0.01 – 3.00 in15-45 dBZTempRHWindHeightTempDewpt Wind CSI, Bias, PODy/n, FAR, TSS, HSS, Fcst Ratio, Obs Ratio RMS and Bias Convection (04 km, 80 km) Other Weather Events? 0 – 100 % CSI vs Bias, Reliability, ROC Deterministic Probabilistic

7. Spring 2011 Hourly HRRR Initialization from RAP Hourly RAP Lateral Boundary Conditions Interp to 3 km grid Hourly HRRR 15-h fcst Initial Condition Fields 11 z 12 z 13 z Time (UTC) Analysis Fields 3DVAR Obs 3DVAR Obs Back- ground Fields 18-h fcst 1-hr fcst DDFI 1-hr fcst 18-h fcst 1-hr fcst Interp to 3 km grid 15-h fcst Use 1-h old LBC to reduce latency Use most recent IC (post-DFI) to get latest radar info Reduced Latency: ~2h for 2011

8. - Hourly cycling of land surface model fields - 6 hour spin-up cycle for hydrometeors, surface fields Rapid Refresh Partial Cycling RAP Hourly cycling throughout the day RAP spin-up cycle GFS model GFS model RAP spin-up cycle 00z 03z 06z 09z 12z 15z 18z 21z 00z Observation assimilation Observation assimilation

9. ESRL/GSD/AMB Model Analysis/Forecast Bias Inherent in Model Physics? Non-Optimal Use of Obs? Limitations of Data Assimilation Method? Need Accurate Mesoscale Environment for High Impact Prediction

10. RAP vs. RUC surface – cold season COLD WARM LOW HIGH 2m Temper- ature (K) 2m Dew Point (m/s) RAP RUC 3-week comparison 9 – 30 Jan 2012 Eastern US only RUC RAP Diurnal bias variation 6-h fcst RUC daytime quite cool, RAP good Both too moist, especially during day Steve Weygandt

11. RAP vs. RUC surface – warm season COLD WARM LOW HIGH 2m Temperature (K) 2m Dew Point (m/s) RAP RUC 2-month comparison 20 April – 20 July 2011 Eastern US only RUC RAP Diurnal bias variation 6-h fcst RUC daytime slightly cool, RAP warm, esp. overnight Both too moist, especially at night RUC worse than RAP Steve Weygandt

12. 13-km CONUS Comparison 2 X 12 hr fcst vs. CPC 24-h analysis 1 May – 15 July 2011 Matched RAP vs. RUC Precipitation Verification RAP RUC | | | | | | | | 0.01 0.10 0.25 0.50 1.00 1.50 2.00 3.00 in. | | | | | | | | 0.01 0.10 0.25 0.50 1.00 1.50 2.00 3.00 in. CSI (x 100) RUC RAP 100 (1.0) bias (x 100) SPRING/ SUMMER Steve Weygandt

13. RAP and RUC Humidity Bias CONUS All 00/12 UTC Raobs 08 July – 08 Sept 2011 RUC/RR drier/moister below 650 mb, opposite above RR a closer fit to the observations by 6 hrs in lower trop Water vapor is the dominant source of the RH bias RAP RUC RAP - RUC 00 hr (analysis)06 hr fcsts RAP RUC RAP - RUC

14. RAP and RUC Humidity Bias CONUS All 00/12 UTC Raobs 11-22 August 2011 NO RADAR DA Without radar DA, model bias even more pronounced RAP RUC RAP - RUC 00 hr (analysis)06 hr fcsts RAP RUC RAP - RUC

15. ESRL/GSD/AMB Model Analysis/Forecast Improvements 2012

16. Spring 2012 versions RAP (ESRL RAP and HRRR) ModelData Assimilation RAP (13 km)WRFv3.3.1+ Mods to physics (convection, microphysics, land-surface, PBL) Numerics changes (w-damp upper bound conditions, 5 th -order vertical advection) Soil adjustment, Temp-dep radar- hydrometeor building PW assim mods Cloud assim mods Tower/sodar observations Radial wind assim GSI merge with trunk HRRR (3 km)WRFv3.3.1+, Mods to physics (microphysics, land-surface, PBL) Numerics changes (w-damp upper bound conditions, 5 th -order vertical advection) Possible 3 km/15 min radar assimilation Possible 3km cloud cycling Possible 3km land- surface cycling 16 Changes evaluated in current RAP/HRRR 2012 change bundle

17. Rapid Refresh prim ( ) vs. dev ( ) RAP-dev has PBL-based pseudo-observations prim dev Residual mixed layer better depicted in RAP-dev (w/ PBL pseudo-obs) Observed 00z 7 July 2011 Albany, NY sounding 23z 6 July 2011 RAP sounding RAP PBL pseudo-obs assimilation

18. Dewpoint bias in 6h RAP forecasts, eastern US, Aug 2011 Reduced moisture bias as measured by 2-m dewpoint Dry Bias Moist Bias Real-time RAP 18 Retro RAP with soil adjustment and temp- dependent hydrometeor building from radar

19. Before DA After DA conserving θ v Before DA After DA NOT conserving θ v Improved cloud analysis by assuming conservation of virtual potential temperature

20. Latest 2012 Candidate HRRR Evaluation Reflectivity ≥ 35 dBZ, 03 km Scale Select Cases 11-22 August 2011 Eastern US Optimal HRRR 2010 HRRR 2011 HRRR 2012 – Reduced high BIAS in first 6 hours and improved CSI

21. Latest 2012 Candidate HRRR Evaluation Reflectivity ≥ 25 dBZ, 40 km Scale Select Cases 11-22 August 2011 NortheastSoutheast Optimal HRRR 2010 HRRR 2011 HRRR 2012

22. 12z + 4 hr fcsts Valid 16z 14 Aug 2011 NSSL mosaic RAP HRRR 2012 proto- type retro test RAP HRRR 2011 real- time HRRR improvements from RAP upgrades (for 2012 HRRR CoSPA – more accurate convection, reduced false alarm)

23. NSSL mosaic Observations Valid 02z 18 Aug 2011 HRRR 2011 HRRR 2012HRRR 2010 18z 17 Aug 2011 Initializations 8 hr forecasts

24. ESRL/GSD/AMB Radar Data Assimilation

25. Forward integration, full physics Apply latent heating from radar reflectivity, lightning data Diabatic Digital Filter Initialization (DDFI) -40 min -20 min Init +20 min RUC/RR model forecast Backwards integration, no physics Obtain initial fields with improved balance, vertical circulations associated with ongoing convection Radar reflectivity assimilation in RUC and Rapid Refresh

26. Rapid Refresh (GSI + ARW) reflectivity assimilation example Low-level Convergence Upper-level Divergence K=4 U-comp. diff (radar - norad) K=17 U-comp. diff (radar - norad) NSSL radar reflectivity (dBZ) 14z 22 Oct 2008 Z = 3 km

27. RAP – No radar data RAP – Radar data HRRR Reflectivity 00z 12 August 2011 00 hr forecasts Convergence Cross-Section

28. RAP – No radar data RAP – Radar data Convergence Cross-Section 01z 12 August 2011 01 hr forecasts HRRR Reflectivity

29. HRRR Reflectivity Verification DDFI in 13-km RAP (parent model) AND in 3-km HRRR Eastern US, Reflectivity > 25 dBZ 14-24 July 2010 Application of DDFI at both scales results in spurious convection Significant loss of skill 2x Latent heating rate in RAP 1x Latent heating rate in RAP 1/3x Latent heating rate in RAP 1x Latent heating in RR and HRRR CSI 40 km BIAS 03 km Optimal 2x Latent heating rate in RAP 1x Latent heating rate in RAP 1/3x Latent heating rate in RAP 1x Latent heating in RR and HRRR

30. HRRR Reflectivity Verification Eastern US, Reflectivity > 25 dBZ 11-20 August 2011 Reflectivity DA in RAP/RUC increases HRRR forecast skill HRRR bias depends strongly on parent model CSI 40 km RUC->HRRR Radar RAP->HRRR Radar RAP->HRRR No Radar RUC->HRRR No Radar RAP->HRRR Radar RAP->HRRR No Radar RUC->HRRR Radar RUC->HRRR No Radar BIAS 03 km Optimal

31. Reflectivity DA on 3-km (HRRR) Grid interpolation from RAP, hydrometeor specification t 0  60 min t 0  45 min t 0  30 min t 0  15 min t0t0 reflectivity-based temperature tendency NSSL 3D mosaic HRRR composite reflectivity David Dowell t 0 45 mint 0 30 min t 0 15 mint0t0 HRRR (3-km) grid produces convective storms explicitly Reflectivity-based temp. tendencies are applied during sub- hourly cycling (forward model integration only, no digital filtering)

32. ESRL/GSD/AMB HRRR Forecast Post-Processing Time-Lagged (TL) Ensemble

33. Spatio-temporal scale of probabilities 10-11 hr fcst 09-10 hr fcst 08-09 hr fcst 11-12 hr fcst 10-11 hr fcst 09-10 hr fcst Forecasts valid 21-22z 27 April 2011Forecasts valid 22-23z 27 April 2011 All six forecasts summed to form probabilities valid 22z 27 April 2011 HRRR 11z Init HRRR 12z Init HRRR 13z Init

34. The HCPF and HTPF HRRR Convective/Tornado Probabilistic Forecast (HCPF/HTPF) Estimate likelihood of convection and tornado production Intensity – ≥ 25 m 2 s -2 Maximum Updraft Helicity 2-5 km AGL Time – Two hour search window centered on valid times Location – 45 km (15 gridpoints) search radius of each point Members – Three consecutive HRRR initializations HTPF = # grid points matching criteria over all members total # grid points searched over all members Caveats: Refinement needed to discriminate surface/elevated rotation Evaluate additional environmental fields that support tornado formation Evaluate additional diagnostic fields Tornado scale not resolved

35. Case Selection from 2011 DateRegion # Tornado Reports Max SPC Risk Category* Max SPC Tornado Probability* 14-Apr-2011OK-AR38MDT15% 15-Apr-2011MS-AL146MDT15% 16-Apr-2011NC-SC-VA139HIGH30% 26-Apr-2011TX-AR-LA-MS-AL-TN126HIGH30% 27-Apr-2011MS-AL-TN-GA292HIGH45% 28-Apr-2011NC-SC-VA-MD15SLGT10% 22-May-2011OK-MO75MDT15% 23-May-201122MDT10% 24-May-2011OK-TX-AR57HIGH45% 25-May-2011MO-IL-IN127HIGH30% *Note: Maximum SPC forecast categories through 20z Day 1

36. ESRL/GSD/AMB HRRR Deterministic Skill In Outbreaks

37. Tornado Periods Stronger Forcing 14-16 April 2011 CSI 25 dBZ, 40 km 40 dBZ, 40 km 25 dBZ, 03 km 40 dBZ, 03 km 03 hr fcsts 06 hr fcsts 09 hr fcsts12 hr fcsts

38. 25 dBZ, 40 km 40 dBZ, 40 km 25 dBZ, 03 km 40 dBZ, 03 km 26-28 April 2011 CSI Tornado Periods Stronger Forcing 03 hr fcsts 06 hr fcsts 09 hr fcsts12 hr fcsts

39. 25 dBZ, 40 km 40 dBZ, 40 km 25 dBZ, 03 km 40 dBZ, 03 km 22-25 May 2011 CSI Tornado Periods Stronger Forcing 03 hr fcsts 06 hr fcsts 09 hr fcsts12 hr fcsts

40. ESRL/GSD/AMB HRRR TL Ensemble Probabilistic Comparison In Outbreaks

41. 27 April 2011 HTPF 13z + 09hr fcst Valid 22z 27 April 2011 1630z SPC Tornado Probability 27 April 2011 Storm Reports Tornado = Red Dots Tornado Probability (%)

42. 27 April 2011 Tornado Probability (%) Reflectivity (dBZ) HTPF 13z + 09hr fcst Valid 22z 27 April 2011 27 April 2011 Storm Reports Tornado = Red Dots Observed Reflectivity 22z 27 April

43. 22 May 2011 HTPF 13z + 11hr fcst Valid 00z 23 May 2011 1300z SPC Tornado Probability 22 May 2011 Storm Reports Tornado = Red Dots Tornado Probability (%)

44. 22 May 2011 Tornado Probability (%) Reflectivity (dBZ) 22 May 2011 Storm Reports Tornado = Red Dots HTPF 13z + 11hr fcst Valid 00z 23 May 2011 Observed Reflectivity 00z 23 May

45. 23 May 2011 HTPF 13z + 11hr fcst Valid 00z 24 May 2011 1300z SPC Tornado Probability 23 May 2011 Storm Reports Tornado = Red Dots Tornado Probability (%)

46. 23 May 2011 HTPF 13z + 11hr fcst Valid 00z 24 May 2011 1300z SPC Tornado Probability 23 May 2011 Storm Reports Tornado = Red Dots Tornado Probability (%) With MUCAPE LPL < 50 mb AGL

47. 23 May 2011 Tornado Probability (%) Reflectivity (dBZ) 23 May 2011 Storm Reports Tornado = Red Dots HTPF 13z + 11hr fcst Valid 00z 24 May 2011 Observed Reflectivity 00z 24 May

48. 24 May 2011 HTPF 13z + 11hr fcst Valid 00z 25 May 2011 1630z SPC Tornado Probability 24 May 2011 Storm Reports Tornado = Red Dots Tornado Probability (%)

49. 24 May 2011 Tornado Probability (%) Reflectivity (dBZ) HTPF 13z + 11hr fcst Valid 00z 25 May 2011 24 May 2011 Storm Reports Tornado = Red Dots Observed Reflectivity 00z 25 May

50. Summary 50 HRRR Challenges from a WOF/HIP perspective Reduce latency from 2 hrs to 1 hr, 30 min, etc…? Tradeoff between assimilating latest mesoscale observations (more latency) and some radar observations (less latency) Model moisture (and other) bias dominates convective forecast behavior: initial condition error, model error, both? Mesoscale environment remains a strong driver of storm-scale predictability Weaker (stronger) forcing and smaller (larger) favorable environments do translate to lower (higher) skill forecasts Small (large) run-to-run variability doesn’t always translate to a higher (lower) skill forecast