1. Storm Prediction Center: Storm-Scale Ensemble of Opportunity Israel Jirak & Steve Weiss Science Support Branch Storm Prediction Center Norman, OK Acknowledgments: Andy Dean, Gregg Grosshans, and Chris Melick

2. Storm-Scale Ensemble of Opportunity Introduction DATA OVERLOAD!!! NSSL WRF-ARWHRW WRF-ARW CONUS WRF-NMMHRW WRF-NMM NAM CONUS NEST SSEO: An efficient way to summarize this information

3.  An operational ensemble of convection-allowing models (CAMs) may not be available for some time, so SPC is exploring the utility of blending existing CAMs into a “storm- scale ensemble of opportunity” (SSEO)  Advantages: Data already available onsite Efficient method of summarizing data from multiple deterministic models Data available year round, which allows for a large sample for calibration purposes  Disadvantages: Little to no control over configuration and/or model changes Likely insufficient diversity Storm-Scale Ensemble of Opportunity Introduction

4.  We can use what we’ve learned from working with the CAPS SSEF during the Spring Experiment.  Traditional ensemble probabilities of HMFs (Hourly Max Fields) from high-resolution models are not especially useful, owing to poor agreement among members at the grid point of these fields.  Applying a binary neighborhood approach to a storm-scale ensemble improves the statistical results of HMFs in forecasting severe weather ROI=20-40 km Sigma=30 grid points SSEO Neighborhood Method 03 May 2008 (Harless 2010)

5.  Using built-in ensemble functions in N- AWIPS/GEMPAK to minimize post-processing  Ensemble products include [MN]: Ensemble mean [MX]: Ensemble max [PC]: Percentile values [PR]: Traditional ensemble probability (@ grid point) [PRS]: Smoothed traditional ensemble probability [NPR]: Binary neighborhood ensemble probability – code written (C. Melick) to calculate neighborhood max [NPRS]: Smoothed binary neighborhood ens. probability [SP]: Spaghetti plots SSEO Processing and Products

6. SSEO NMAP – Spaghetti Plots

7. SSEO NMAP – Ensemble Fields  Ensemble selection window will pop up.  Select the appropriate cycle and hit accept.

8. 1) NSSL WRF-ARW 2) HRW WRF-ARW 3) HRW WRF-ARW -12 h 4) EMC WRF-NMM 5) HRW WRF-NMM 6) HRW WRF-NMM -12 h 7) NMMB Nest SSEO 00Z Membership

9. HM Updraft Helicity > 25 m 2 s -2 SSEO 24-hr fcst valid 00Z 28 April SSEO Severe [SP]:HM Updraft Helicity ≥25 m 2 s -2 SSEO forecasts of supercell tracks during 23-00z

10. Ensemble Maximum HM Updraft Helicity (m 2 s -2 ) SSEO 24-hr fcst valid 00Z 28 April SSEO Severe [MX]:HM Updraft Helicity The HMF UH values indicate tracks of intense, fast moving supercells during a 1-hr period.

11. Ensemble Probability HM Updraft Helicity >25 m 2 s -2 SSEO 24-hr fcst valid 00Z 28 April SSEO Severe [PR]:HM Updraft Helicity ≥25 m 2 s -2 Poor agreement at the grid point results in low traditional ensemble probabilities.

12. 40-km Neighborhood Probability HM Updraft Helicity >25 m 2 s -2 SSEO 24-hr fcst valid 00Z 28 April SSEO Severe [NPR]:HM Updraft Helicity ≥25 m 2 s -2 Unsmoothed neighborhood probability illustrates 40 km search radius around each grid point

13. 40-km Neighborhood Smoothed Prob HM Updraft Helicity >25 m 2 s -2 SSEO 24-hr fcst valid 00Z 28 April SSEO Severe [NPRS]:Updraft Helicity ≥25 m 2 s -2 Smoothing the 40-km neighborhood probability over 10 grid points better represents storm-scale predictability

14. 3-hr Ensemble Maximum HM Updraft Helicity (m 2 s -2 ) SSEO 24-hr fcst valid 00Z 28 April SSEO Severe [MX]:3-hr HM Updraft Helicity (m 2 s -2 ) Post-processing UH over 3-h periods provides information about persistent long-track supercell corridors

15. 3-hr spaghetti plot of UH ≥25 m 2 s 2 SSEO Severe Verification: 16 April 2011 (18-21Z)

16. 3-hr ensemble max of UH (m 2 s 2 )

17. SSEO Severe Verification: 16 April 2011 (18-21Z) 3-hr neighborhood prob of UH ≥25 m 2 s 2

18. SSEO Severe Verification: 27 April 2011 (18-00Z) 6-hr spaghetti plot of UH ≥25 m 2 s 2

19. SSEO Severe Verification: 27 April 2011 (18-00Z) 6-hr ensemble max of UH (m 2 s 2 )

20. SSEO Severe Verification: 27 April 2011 (18-00Z) 6-hr neighborhood prob of UH ≥25 m 2 s 2

21. SSEO Severe Verification: 22 May 2011 (21-00Z) 3-hr spaghetti plot of UH ≥25 m 2 s 2

22. SSEO Severe Verification: 22 May 2011 (21-00Z) 3-hr ensemble max of UH (m 2 s 2 )

23. SSEO Severe Verification: 22 May 2011 (21-00Z) 3-hr neighborhood prob of UH ≥50 m 2 s 2

24. SSEO Severe Verification: 24 May 2011 (21-00Z) 3-hr spaghetti plot of UH ≥25 m 2 s 2 * Two members missing

25. SSEO Severe Verification: 24 May 2011 (21-00Z) 3-hr ensemble max of UH (m 2 s 2 ) * Two members missing

26. SSEO Severe Verification: 24 May 2011 (21-00Z) 3-hr neighborhood prob of UH ≥25 m 2 s 2 * Two members missing

27.  The Fractions Skill Score (FSS) was calculated for smoothed binary neighborhood probability (ROI=40 km; σ=40 km) of updraft helicity ≥ 25 m 2 s -2 for the SSEO/SSEF versus practically perfect hindcasts of severe weather reports (ROI=40 km; σ=120 km) during SE2011.  The FSS is used here as a neighborhood approach to objectively assess the agreement between forecasts and observations. SSEO Severe UH Verification SE2011 SSEOSSEF – 24 memberFSS = 0.84FSS = 0.68 3-hr [NPRS]:UH ≥25 m 2 s -2 valid 06Z on 02 June 2011

28.  Although the distributions of FSS for individual 3-h forecasts were similar among the ensembles, the SSEO had the highest cumulative (i.e., weighted) FSS during SE2011.  The number of members included in the SSEF did not seem to have a strong impact on the statistical results for updraft helicity during SE2011 when verified against severe weather reports. SSEO Severe UH Verification SE2011 Cumulative FSSFSS Distribution of 3-h Forecasts

29.  A three-level classification based on storm attributes has been developed for the SSEF/SSEO: 1) updraft helicity - supercell 2) updraft speed – multicell, ordinary/pulse 3) 10-m wind speed – bow echo/MCS  These smoothed 40-km neighborhood probabilities (e.g., [NPRS] UH>25 m 2 s -2 ) of are paired with SSEO neighborhood probability of 1-km AGL simulated reflectivity >40 dBZ [all fields are HMFs]  The probabilities are then binned and associated with a historical frequency of severe weather within 25 miles of a point [NPRS] UH>25 = 30% and [NPRS] Refl >40 = 40% : >> 5% probability of severe weather SSEO Severe Calibrated Severe

30. If [NPRS] UH>25 m 2 s -2 >0%, then  Level 1 Predictor 1: [NPRS] UH>25 m 2 s -2 Predictor 2: [NPRS] 1-km AGL Refl >40 dBZ Else If [NPRS] Updraft>10 m/s >0%, then Level 2  Predictor 1: [NPRS] Updraft>10 m/s  Predictor 2: [NPRS] 1-km AGL Refl >40 dBZ Else If [ NPRS ] 10-m WS>30 kts>0% & [NPRS] 1-km AGL Refl >40 dBZ, then  Level 3: Predictor 1: [NPRS] 10-m WS>30 kts Predictor 2: [NPRS] 1-km AGL Refl >40 dBZ Else Probability of Severe = 0% SSEO Severe Calibrated Severe

31. SSEO Severe Calibrated Severe Verification SE2011

35. SSEO Dependent Calibration 18 days during SE2011 – HRW Domain – f18-f30 SSEO Independent Calibration 18 days during SE2011 – HRW Domain – f18-f30

36. SSEO Severe Calibrated Severe Example: 22 October 2011 SSEOSREF

37.  Allows for a quick overview to gauge whether an area deserves a closer look in NMAP.  Also can be used for evaluation of performance on previous days. SSEO Severe Website

38.  Experimental storm-scale ensembles have potential to provide unique and useful information about the likelihood of convective storm occurrence, mode, and intensity  Our initial subjective assessment during the spring months including intensive examination during the 2011 HWT Spring Experiment indicates that the SSEO is capable providing guidance that is comparable to the larger SSEF and better than SREF  Initial statistical verification of calibrated severe probability forecasts during the Spring Experiment period supports the subjective evaluations  Additional testing and evaluation will be performed over a wider range of convective regimes during the summer, fall, and winter seasons SSEO Severe Summary

39.  Can utilize Refl ≥40 dBZ ([SP],[NPRS]) as proxy for thunderstorms.  Has limitations, but may be used to add temporal and spatial resolution to enhanced thunder when examined in conjunction with other data. SSEO Thunder Overview

40.  Examined the SSEO for 6-hr QPF during the 2011 Spring Experiment.  Subjective impressions were positive as noted in the graph below. SSEO QPF Overview from Dave Novak, HPC

41.  Objective verification (below) validates subjective impressions during the Spring Experiment  SPC has been providing HPC with SSEO data since May, and they have been using it operationally for Day 1 QPF. SSEO QPF Overview from Tara Jensen, DTC Pairwise Difference SSEO favored over CAPS ensemble

42.  Started exploring the utility of SSEO in fire weather applications during Fire Weather Experiment this summer.  Ensemble Products: [PR] Hourly Max 10-m Wind Speed [PR] 2-m RH [CPR] 10-m Wind Speed AND 2-m RH [MN], [MX], [PR] Fosberg Fire Wx Index SSEO Fire Weather Overview

43. SSEO Fire Weather [PR]:10-m Wind Speed ≥20 mph Western Boundary Notice high-resolution features, such as higher wind speeds over gulfs and bays.

44. SSEO Fire Weather [PR]:2-m RH <20%

45. SSEO Fire Weather [CPR]:10-m Wind Speed >20 mph & 2-m RH <20%

46. SSEO Fire Weather [MN]:Fosberg Fire Weather Index SSEOSREF

47. SSEO Fire Weather [MX]:Fosberg Fire Weather Index SSEOSREF Notice local maxima in Fosberg, resulting from thunderstorm gusts.

48. SSEO Fire Weather [PR]:Fosberg Fire Weather Index >50 SSEOSREF With low probabilities in those areas.

49. SREF Mean Fosberg ≥50 SSEO Mean Fosberg ≥50 SSEO Fire Weather Verification using SFCOA Fosberg

50. SSEO Fire Weather Enhanced Temporal Resolution Over SREF

51. SSEO Fire Weather Enhanced Spatial Resolution Over SREF

52.  The SSEO provides enhanced temporal and spatial resolution over the SREF.  Subjective impressions from a few late summer and fall cases have been positive on providing useful additional or confirming information.  00Z SSEO data available shortly after 36-h forecast of NSSL WRF-ARW comes in, which is typically ~815Z, but can vary on the day.  Drawbacks: Domain does not cover entire CONUS with no coverage over WA, ORE, CA, & NV. HRW runs are often pre-empted during the hurricane season, limiting the SSEO membership. SSEO Fire Weather Overview

53.  Planning to explore the utility of SSEO for winter weather applications over the next few months.  Ensemble Products: [PR] Precipitation Type [MN], [PC] 1-km Refl (shaded by dominant p-type) [MN], [PC] 1-hr Prec (shaded by dominant p-type) [CPR] Refl>25 dBZ AND p-type = snow [CPR] Refl>15 dBZ AND p-type = fzrn SSEO Winter Overview

54. SSEO Winter [MN]:1-hr Precip by Dominant P-Type More than ½ members predicting rain More than ½ members predicting zr More than ½ members predicting snow The residual – labeled as MIXED/IP

55. SSEO Winter [PC]:1-km Median Refl by Dominant P-Type

56. SSEO Winter [PR]:Precipitation Type

58. SSEO Winter Verification

60.  The use of high-resolution ensembles for winter weather forecasting is essentially a new application. HPC is planning on evaluating the 4-km AFWA 10- member WRF-ARW ensemble during their Winter Weather Experiment.  We would appreciate feedback on the utility of the SSEO winter products for the issuance of winter MDs when applicable. SSEO Winter Overview

61.  Experimental storm-scale ensembles have potential to provide unique and useful probabilistic information: convective storm occurrence, mode, and intensity  Possible uses: 13Z, 1630Z, & 20Z Day 1 Outlooks, Enhanced Thunder Outlooks, Convective MDs fire weather conditions  Possible uses: Day 1 Fire Weather Outlooks winter weather precipitation rate and type  Possible uses: Winter Weather MDs  Things to keep in mind: Experimental 2 ! Experimental processing of experimental models. Domain does not cover full CONUS, excludes WA, OR, CA, & NV. HRW runs are often pre-empted during the hurricane season, limiting SSEO membership. Check spaghetti plot on website to verify members available.  00Z SSEO currently available ~0815Z after 36-hr NSSL WRF forecast is processed.  12Z SSEO – essentially updates the 00Z SSEO with four 12Z members (HRW WRF-ARW, HRW WRF-NMM, CONUS WRF-NMM, & NAM CONUS NEST) – available ~1745Z after the 12Z HRW runs are processed.  There are numerous exciting possibilities with the SSEO! We are interested in your feedback: comments, suggestions, criticisms, etc. SSEO Summary