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Storm Prediction Center: Storm-Scale Ensemble of Opportunity

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. Storm-Scale Ensemble of Opportunity Introduction. NSSL WRF-ARW. HRW WRF-ARW.

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Storm Prediction Center: Storm-Scale Ensemble of Opportunity

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  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 OpportunityIntroduction NSSL WRF-ARW HRW WRF-ARW DATA OVERLOAD!!! NAM CONUS NEST SSEO: An efficient way to summarize this information CONUS WRF-NMM HRW WRF-NMM

  3. Storm-Scale Ensemble of OpportunityIntroduction • 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

  4. SSEONeighborhood Method • 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 03 May 2008 (Harless 2010)

  5. SSEOProcessing and Products • 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

  6. SSEONMAP – Spaghetti Plots

  7. SSEONMAP – Ensemble Fields • Ensemble selection window will pop up. • Select the appropriate cycle and hit accept.

  8. SSEO00Z Membership • NSSL WRF-ARW • HRW WRF-ARW • HRW WRF-ARW -12 h • EMC WRF-NMM • HRW WRF-NMM • HRW WRF-NMM -12 h • NMMB Nest

  9. SSEO Severe[SP]:HM Updraft Helicity ≥25 m2s-2 SSEO forecasts of supercell tracks during 23-00z HM Updraft Helicity > 25 m2s-2 SSEO 24-hr fcst valid 00Z 28 April

  10. SSEO Severe[MX]:HM Updraft Helicity The HMF UH values indicate tracks of intense, fast moving supercells during a 1-hr period. Ensemble Maximum HM Updraft Helicity (m2s-2) SSEO 24-hr fcst valid 00Z 28 April

  11. SSEO Severe[PR]:HM Updraft Helicity ≥25 m2s-2 Poor agreement at the grid point results in low traditional ensemble probabilities. Ensemble Probability HM Updraft Helicity >25 m2s-2 SSEO 24-hr fcst valid 00Z 28 April

  12. SSEO Severe[NPR]:HM Updraft Helicity ≥25 m2s-2 Unsmoothed neighborhood probability illustrates 40 km search radius around each grid point 40-km Neighborhood Probability HM Updraft Helicity >25 m2s-2 SSEO 24-hr fcst valid 00Z 28 April

  13. SSEO Severe[NPRS]:Updraft Helicity ≥25 m2s-2 Smoothing the 40-km neighborhood probability over 10 grid points better represents storm-scale predictability 40-km Neighborhood Smoothed Prob HM Updraft Helicity >25 m2s-2 SSEO 24-hr fcst valid 00Z 28 April

  14. SSEO Severe[MX]:3-hr HM Updraft Helicity (m2s-2) Post-processing UH over 3-h periods provides information about persistent long-track supercell corridors 3-hr Ensemble Maximum HM Updraft Helicity (m2s-2) SSEO 24-hr fcst valid 00Z 28 April

  15. SSEO SevereVerification: 16 April 2011 (18-21Z) 3-hr spaghetti plot of UH ≥25 m2s2

  16. SSEO SevereVerification: 16 April 2011 (18-21Z) 3-hr ensemble max of UH (m2s2)

  17. SSEO SevereVerification: 16 April 2011 (18-21Z) 3-hr neighborhood prob of UH ≥25 m2s2

  18. SSEO SevereVerification: 27 April 2011 (18-00Z) 6-hr spaghetti plot of UH ≥25 m2s2

  19. SSEO SevereVerification: 27 April 2011 (18-00Z) 6-hr ensemble max of UH (m2s2)

  20. SSEO SevereVerification: 27 April 2011 (18-00Z) 6-hr neighborhood prob of UH ≥25 m2s2

  21. SSEO SevereVerification: 22 May 2011 (21-00Z) 3-hr spaghetti plot of UH ≥25 m2s2

  22. SSEO SevereVerification: 22 May 2011 (21-00Z) 3-hr ensemble max of UH (m2s2)

  23. SSEO SevereVerification: 22 May 2011 (21-00Z) 3-hr neighborhood prob of UH ≥50 m2s2

  24. SSEO SevereVerification: 24 May 2011 (21-00Z) * Two members missing 3-hr spaghetti plot of UH ≥25 m2s2

  25. SSEO SevereVerification: 24 May 2011 (21-00Z) * Two members missing 3-hr ensemble max of UH (m2s2)

  26. SSEO SevereVerification: 24 May 2011 (21-00Z) * Two members missing 3-hr neighborhood prob of UH ≥25 m2s2

  27. SSEO SevereUH Verification SE2011 • The Fractions Skill Score (FSS) was calculated for smoothed binary neighborhood probability (ROI=40 km; σ=40 km) of updraft helicity ≥ 25 m2s-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. 3-hr [NPRS]:UH ≥25 m2s-2 valid 06Z on 02 June 2011 SSEO FSS = 0.84 SSEF – 24 member FSS = 0.68

  28. SSEO SevereUH Verification SE2011 • 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. FSS Distribution of 3-h Forecasts Cumulative FSS

  29. SSEO SevereCalibrated Severe • 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 m2s-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

  30. SSEO SevereCalibrated Severe If [NPRS] UH>25 m2s-2 >0%, then • Level 1 • Predictor 1: [NPRS] UH>25 m2s-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%

  31. SSEO SevereCalibrated Severe Verification SE2011

  32. SSEO SevereCalibrated Severe Verification SE2011

  33. SSEO SevereCalibrated Severe Verification SE2011

  34. SSEO SevereCalibrated Severe Verification SE2011

  35. SSEO SevereCalibrated Severe Verification SE2011 SSEO Dependent Calibration18 days during SE2011 – HRW Domain – f18-f30 SSEO Independent Calibration18 days during SE2011 – HRW Domain – f18-f30

  36. SSEO SevereCalibrated Severe Example: 22 October 2011 SSEO SREF

  37. SSEO SevereWebsite • 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.

  38. SSEO SevereSummary • 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

  39. SSEO ThunderOverview • 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.

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

  41. SSEO QPFOverview • 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 favored over CAPS ensemble Pairwise Difference from Tara Jensen, DTC

  42. SSEO Fire WeatherOverview • 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

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

  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 SSEO SREF

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

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

  49. SSEO Fire WeatherVerification using SFCOA Fosberg SSEO Mean Fosberg ≥50 SREF Mean Fosberg ≥50

  50. SSEO Fire Weather Enhanced Temporal Resolution Over SREF

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