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Ensembles and the Short Range Ensemble Guidance Website at the SPC

Ensembles and the Short Range Ensemble Guidance Website at the SPC. David Bright NOAA/NWS/Storm Prediction Center Norman, OK Southern Region Teletraining March 6, 2008. Where Americas Climate and Weather Services Begin. Outline Introduction Applications in High Impact Forecasting

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Ensembles and the Short Range Ensemble Guidance Website at the SPC

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  1. Ensembles and the Short Range Ensemble Guidance Website at the SPC David Bright NOAA/NWS/Storm Prediction Center Norman, OK Southern Region Teletraining March 6, 2008 Where Americas Climate and Weather Services Begin

  2. Outline • Introduction • Applications in High Impact Forecasting • Fire Weather • Severe Convective Weather • Winter Weather (via real-time webpage) • Summary

  3. Outline • Introduction • Applications in High Impact Forecasting • Fire Weather • Severe Convective Weather • Winter Weather (via real-time webpage) • Summary

  4. STORM PREDICTION CENTER HAZARDOUS PHENOMENA • Hail, Wind, Tornadoes • Excessive rainfall • Fire weather • Winter weather

  5. Hazardous Weather Forecasting • The Challenge: High impact events often occur on temporal and spatial scales below the resolvable resolutions of most observing and forecasting systems • Key premise: We must use knowledge of the environment and non-resolved processes to determine the spectrum of possible hazardous weather, where and when it may occur, and how it may evolve over time

  6. Ensemble Guidance at the SPC • Develop specialized guidance for the specific application (severe weather, fire weather, winter weather) • Design guidance that… • Helps blend deterministic and ensemble approaches • Facilitates transition toward probabilistic forecasts • Incorporates larger-scale environmental information to yield downscaled probabilistic guidance • Aids in decision support of high impact weather • Gauge confidence • Alert for potentially significant events National Weather Center, Norman OK

  7. Commonly Used Ensemble Guidance at the SPC • Mean, Median, Max, Min, Spread, Exceedance Probabilities, and Combined/Joint Probabilities • Basic Weather Parameters • Temperature, Height, MSLP, Wind, Moisture, etc. • Derived Severe Weather Parameters • CAPE, Shear, Supercell and Sig. Tornado Parameters, etc. • Calibrated Probability of Thunderstorms and Severe Thunderstorms • Goal of the SPC SREF webpage: Share some useful information that we have and others may not

  8. NCEP/EMC Short Range Ensemble Forecast (SREF) • EMC SREF system (21 members) • 87 hr forecasts four times daily (03, 09, 15, 21 UTC) • North American domain • Model grid lengths 32-45 km • Multi-model: Eta, RSM, WRF-NMM, WRF-ARW • Multi-analysis: NAM, GFS initial and boundary conds. • IC perturbations and physics diversity • Recently added bias-correction to some fields (not covered and not on SPC webpage)

  9. Note: All products shown are available in real-time at the SPC website http://www.spc.noaa.gov/exper/sref/

  10. Outline • Introduction • Applications in High Impact Forecasting • Fire Weather • Severe Convective Weather • Winter Weather (via real-time webpage) • Summary

  11. SREF 500 mb Mean Height, Wind, Temp

  12. SREF 700 mb Mean Height and SD (dash) SD

  13. SREF Mean PCPN, UVV, Thickness

  14. SREF Pr[P12I > .01”] and Mean P12I = .01” (dash)

  15. SREF Pr[RH < 15%] and Mean RH = 15% (dash)

  16. SREF Pr[WSPD > 20 mph] and Mean WSPD = 20 mph (dash)

  17. SREF Combined or Joint Probability Pr [P12I < 0.01”] X Pr [RH < 15%] X Pr [WSPD > 20 mph] X Pr [TMPF > 60F]

  18. SREF Combined or Joint Probability Pr [P12I < 0.01”] X Pr [RH < 10%] X Pr [WSPD > 20 mph] X Pr [TMPF > 60F]

  19. Diagnostics and Analysis • Example: Fosberg Fire Weather Index (FFWI) • A nonlinear empirical relationship between meteorological conditions and fire behavior. (Fuels are not considered!) • Derived to highlight the fire weather threat over “small” space and time scales • FFWI = F(Wind speed, RH, Temperature) • 0 < FFWI < 100 • FFWI > ~50-60  significant fire weather conditions • FFWI > ~75  extreme fire weather conditions

  20. SREF Pr[Fosberg Index > 60] and Mean FFWI = 60

  21. SREF Maximum Fosberg Index (any member) Extreme values

  22. SPC Operational Outlook(Uncertainty communicated in accompanying text) Flames are whipped by high winds as Odessa firefighters try to gain control of a grass fire that burned about 7,500 acres Monday afternoon, Feb. 25, 2008. Firefighters from Midland and volunteer firefighters from West Odessa, Gardendale and South Ector County assisted in fighting the fire.

  23. Outline • Introduction • Applications in High Impact Forecasting • Fire Weather • Severe Convective Weather • Winter Weather (via real-time webpage) • Summary

  24. SREF 500 mb Mean Height, Wind, Temp

  25. SREF 500 mb Mean Height and SD (dash)

  26. SREF 850 mb Mean Height, Wind, Temp

  27. SREF Pr[MUCAPE > 2000 J/kg] & Mean MUCAPE=2000 (dash)

  28. SREF Pr[ESHR > 40 kts] & Mean ESHR=40 kts (dash) “Effective Shear” (ESHR; Thompson et al. 2007, WAF) is the bulk shear in the lower half of the convective cloud

  29. SREF Combined or Joint Probability Probability of convection in high CAPE, high shear environment (favorable for supercells) Pr [MUCAPE > 2000 J/kg] X Pr [ESHR > 40 kts] X Pr [C03I > 0.01”]

  30. Diagnostics and Analysis • Example: Significant Tornado Parameter (STP) • A parameter designed to help forecasters identify supercell environments capable of producing significant (> F2) tornadoes (Thompson et al. 2003) • STP = F(MLCAPE, MLLCL, Helicity, Deep shear)* • STP > ~1 indicative of environments that may support strong or violent tornadoes (given that convection occurs) * An updated version (not shown) includes CIN and effective depth

  31. SREF Median STP, Union (red), Intersection (blue) Intersection of all members (STP = 1) Union of all members (STP = 1) Median STP

  32. SREF Combined or Joint Probability: STP Ingredients Probability of Significant Tornado Environment Pr [MLCAPE > 1000 J/kg] X Pr [MLLCL < 1000 m] X Pr [0-1KM HLCY > 100 m^2/s^2] X Pr [0-6 KM Shear > 40 kts] X Pr [C03I > 0.01”]

  33. SREF Probability of STP Ingredients: Time Trends 48 hr SREF Forecast Valid 21 UTC 7 April 2006 Prob (MLCAPE > 1000 Jkg-1) X Prob (6 km Shear > 40 kt) X Prob (0-1 km SRH > 100 m2s-2) X Prob (MLLCL < 1000 m) X Prob (3h conv. Pcpn > 0.01 in) Shaded Area Prob > 5% Max 40%

  34. SREF Probability of STP Ingredients: Time Trends 36 hr SREF Forecast Valid 21 UTC 7 April 2006 Prob (MLCAPE > 1000 Jkg-1) X Prob (6 km Shear > 40 kt) X Prob (0-1 km SRH > 100 m2s-2) X Prob (MLLCL < 1000 m) X Prob (3h conv. Pcpn > 0.01 in) Shaded Area Prob > 5% Max 50%

  35. SREF Probability of STP Ingredients: Time Trends 24 hr SREF Forecast Valid 21 UTC 7 April 2006 Prob (MLCAPE > 1000 Jkg-1) X Prob (6 km Shear > 40 kt) X Prob (0-1 km SRH > 100 m2s-2) X Prob (MLLCL < 1000 m) X Prob (3h conv. Pcpn > 0.01 in) Shaded Area Prob > 5% Max 50%

  36. SREF Probability of STP Ingredients: Time Trends 12 hr SREF Forecast Valid 21 UTC 7 April 2006 Prob (MLCAPE > 1000 Jkg-1) X Prob (6 km Shear > 40 kt) X Prob (0-1 km SRH > 100 m2s-2) X Prob (MLLCL < 1000 m) X Prob (3h conv. Pcpn > 0.01 in) Shaded Area Prob > 5% Max 50%

  37. Severe Event of April 7, 2006 • First ever Day 2 outlook High Risk issued by SPC • More than 800 total severe reports • 3 killer tornadoes and 10 deaths • SREF severe weather fields aided forecaster confidence

  38. Outline • Introduction • Applications in High Impact Forecasting • Fire Weather • Severe Convective Weather • Winter Weather (via real-time webpage) [http://www.spc.noaa.gov/exper/sref/ ] • Summary

  39. Probability Matched Averaging [PM] • Calculate the ensemble mean on the grid (use PDF for location) • Create a ranked distribution of ensemble mean grid point data (use PDF for values) • Create a ranked distribution of the raw data from ALL MEMBERS (n members) • On the grid, replace the ranked value of the ensemble mean with every nth value of the ranked raw data • Location of the ensemble mean is retained, but value replaced with actual data Ebert, E.E., 2001: Ability of a Poor Man's Ensemble to Predict the Probability and Distribution of Precipitation. Mon. Wea. Rev., 129, 2461–2480. (i,j) (i,j) Raw data (all members) Rank (Min to Max) Ensemble mean Data Values

  40. Probability Matched Averaging [PM] 3h Precip - Probability Matched Mean 3h Precip - Arithmetic Mean

  41. Estimating the snowfall from the model QPF Available data: 3 hr 3 hr 3 hr 3 hr Forecast Time QPF: PCP Rate: Snow ratio is adapted from Boone and Etchevers (2001; AMS J. Hydrometeorlogy): Snow ratio = 1000 / (100 + 6T), where T is the maximum saturated temperature surface to 300 mb AGL [Allowable range: Min 7:1 and Max 40:1; 10:1 at 0 degC] Snowfall = Snow ratio at output time x precipitation over previous 3 hours Snow rate (inches per hour) = Snowfall / 3 hrs -or- Instantaneous precipitation rate is converted to an instantaneous snow rate per hour at the start and end times. If hourly snow rate > 3hr total snowfall, hourly rate = 3hr value.

  42. Diagnostics and Analysis • Example: Dendritic Growth Zone (DGZ) • Very efficient growth (assuming water vapor is replenished) • Peak growth rate -14 to -15C in low-to-mid troposphere • Accumulate rapidly • Search ensemble members for: • UVV > 3 cm/second • -11 C < Temp < -17 C • Layer depth > 50 mb • RH in layer > 85%

  43. MPV Moist Potential Vorticity Typical values of MPV AMS (Emanuel 1985) Enhancement in the upward branch of the frontal circulation in the presence of low MPV. Low values of MPV

  44. Outline • Introduction • Applications in High Impact Forecasting • Fire Weather • Severe Convective Weather • Winter Weather (via real-time webpage) • Summary • Interpreting Ensemble Means, Verification, and Storm-scale

  45. Be careful interpreting ensemble means F075 SREF - Valid 00 UTC 11 Nov 2007 Mean PMSL; Mean Wind; Mean Thickness Consider this location…mean wind ~10 kts (15 mph)

  46. Probability doesn’t appear to fit mean F075 SREF - Valid 00 UTC 11 Nov 2007 Probability wind speed > 30 mph Probability the wind speed > 30 mph ~70%

  47. Is the distribution positively skewed? F075 SREF - Valid 00 UTC 11 Nov 2007 Maximum speed (mph) at each grid point L L L L L Maybe, but doesn’t explain the apparent discrepancy.

  48. Low center spaghetti F075 SREF - Valid 00 UTC 11 Nov 2007 Spaghetti of low center positions Considerable uncertainty in the location of the low.

  49. Conditiional probability: Given U < 0 F075 SREF - Valid 00 UTC 11 Nov 2007 Probability wind speed > 30 mph (given u < 0) May need to consider “feature relative” averaging Probability the wind speed > 30 mph ~50%

  50. Calibrated Reliability (5 Aug to 5 Nov 2004) Frequency [0%, 5%, …, 100%] Perfect Forecast Perfect Forecast No Skill Climatology No Skill Calibrated Thunder Probability

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