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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 Slide 2 Outline Introduction Applications in High Impact Forecasting Fire Weather Severe Convective Weather Winter Weather (via real-time webpage) Summary Slide 3 Outline Introduction Applications in High Impact Forecasting Fire Weather Severe Convective Weather Winter Weather (via real-time webpage) Summary Slide 4 Hail, Wind, Tornadoes Excessive rainfall Fire weather Winter weather STORM PREDICTION CENTER HAZARDOUS PHENOMENA Slide 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 Slide 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 Slide 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 Slide 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) Slide 9 Note: All products shown are available in real-time at the SPC website http://www.spc.noaa.gov/exper/sref/ Slide 10 Outline Introduction Applications in High Impact Forecasting Fire Weather Severe Convective Weather Winter Weather (via real-time webpage) Summary Slide 11 SREF 500 mb Mean Height, Wind, Temp Slide 12 SREF 700 mb Mean Height and SD (dash) SD Slide 13 SREF Mean PCPN, UVV, Thickness Slide 14 SREF Pr[P12I >.01] and Mean P12I =.01 (dash) Slide 15 SREF Pr[RH < 15%] and Mean RH = 15% (dash) Slide 16 SREF Pr[WSPD > 20 mph] and Mean WSPD = 20 mph (dash) Slide 17 SREF Combined or Joint Probability Pr [P12I < 0.01] X Pr [RH < 15%] X Pr [WSPD > 20 mph] X Pr [TMPF > 60F] Slide 18 Pr [P12I < 0.01] X Pr [RH < 10%] X Pr [WSPD > 20 mph] X Pr [TMPF > 60F] SREF Combined or Joint Probability Slide 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 Slide 20 SREF Median Fosberg Index + Union (red) Union of all members (Fosberg = 50) Median Fosberg Index Intersection of all members (Fosberg = 50) Slide 21 SREF Pr[Fosberg Index > 60] and Mean FFWI = 60 Slide 22 SREF Maximum Fosberg Index (any member) Extreme values Slide 23 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. Slide 24 Outline Introduction Applications in High Impact Forecasting Fire Weather Severe Convective Weather Winter Weather (via real-time webpage) Summary Slide 25 SREF 500 mb Mean Height, Wind, Temp Slide 26 SREF 500 mb Mean Height and SD (dash) Slide 27 SREF 850 mb Mean Height, Wind, Temp Slide 28 SREF Precipitable Water (Spaghetti = 1) Slide 29 SREF Pr[MUCAPE > 2000 J/kg] & Mean MUCAPE=2000 (dash) Slide 30 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 Slide 31 SREF Pr[C03I >.01] and Mean C03I =.01 (dash) C03I = 3hr Convective Precipitation Slide 32 SREF Combined or Joint Probability Pr [MUCAPE > 2000 J/kg] X Pr [ESHR > 40 kts] X Pr [C03I > 0.01] Probability of convection in high CAPE, high shear environment (favorable for supercells) Slide 33 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 Slide 34 SREF Median STP, Union (red), Intersection (blue) Union of all members (STP = 1) Median STP Intersection of all members (STP = 1) Slide 35 SREF Pr[STP > 5] and Mean STP = 5 (dash) Slide 36 SREF Pr[0-1KM HLCY > 150 m^2/s^2] & Mean 0-1KM HLCY=150 m^2/s^2(dash) Slide 37 SREF Pr[MLLCL < 1000m] & Mean MLLCL = 1000 m (dash) Slide 38 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] SREF Combined or Joint Probability: STP Ingredients Probability of Significant Tornado Environment Slide 39 SREF 12h Calibrated Probability of Severe Thunderstorms Severe Thunderstorm = > 1 CG Lightning Strike in 40 km grid box and Wind > 50 kts or Hail > 0.75 or Tornado Slide 40 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 m 2 s -2 ) X Prob (MLLCL < 1000 m) X Prob (3h conv. Pcpn > 0.01 in) Shaded Area Prob > 5% Max 40% Slide 41 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 m 2 s -2 ) X Prob (MLLCL < 1000 m) X Prob (3h conv. Pcpn > 0.01 in) Shaded Area Prob > 5% Max 50% Slide 42 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 m 2 s -2 ) X Prob (MLLCL < 1000 m) X Prob (3h conv. Pcpn > 0.01 in) Shaded Area Prob > 5% Max 50% Slide 43 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 m 2 s -2 ) X Prob (MLLCL < 1000 m) X Prob (3h conv. Pcpn > 0.01 in) Shaded Area Prob > 5% Max 50% Slide 44 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 Slide 45 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/ ]http://www.spc.noaa.gov/exper/sref/ Summary Slide 46 SREF 500 mb Mean Height, Wind, Temp Slide 47 Probability Matched Averaging [PM] 1)Calculate the ensemble mean on the grid (use PDF for location) 2)Create a ranked distribution of ensemble mean grid point data (use PDF for values) 3)Create a ranked distribution of the raw data from ALL MEMBERS (n members) 4)On the grid, replace the ranked value of the ensemble mean with every n th value of the ranked raw data 5)Location of the ensemble mean is retained, but value replaced with actual data Rank (Min to Max) Data Values (i,j) Ebert, E.E., 2001: Ability of a Poor Man's Ensemble to Predict the Probability and Distribution of Precipitation. Mon. Wea. Rev., 129, 24612480. Ensemble mean Raw data (all members) Slide 48 Probability Matched Averaging [PM] 3h Precip - Arithmetic Mean 3h Precip - Probability Matched Mean Slide 49 Estimating the snowfall from the model QPF Forecast Time 3 hr 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. Available data: Slide 50 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% Diagnostics and Analysis Slide 51 AMS (Emanuel 1985) Enhancement in the upward branch of the frontal circulation in the presence of low MPV. Typical values of MPV Low values of MPV MPV Moist Potential Vorticity Slide 52 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 Slide 53 Be careful interpreting ensemble means Consider this locationmean wind ~10 kts (15 mph) F075 SREF - Valid 00 UTC 11 Nov 2007 Mean PMSL; Mean Wind; Mean Thickness Slide 54 F075 SREF - Valid 00 UTC 11 Nov 2007 Probability wind speed > 30 mph Probability the wind speed > 30 mph ~70% Probability doesnt appear to fit mean Slide 55 F075 SREF - Valid 00 UTC 11 Nov 2007 Maximum speed (mph) at each grid point L L L L L Maybe, but doesnt explain the apparent discrepancy. Is the distribution positively skewed? Slide 56 F075 SREF - Valid 00 UTC 11 Nov 2007 Spaghetti of low center positions Low center spaghetti Considerable uncertainty in the location of the low. Slide 57 F075 SREF - Valid 00 UTC 11 Nov 2007 Probability wind speed > 30 mph (given u < 0) Conditiional probability: Given U < 0 Probability the wind speed > 30 mph ~50% May need to consider feature relative averaging Slide 58 Perfect Forecast No Skill Perfect Forecast No Skill Calibrated Reliability (5 Aug to 5 Nov 2004) Calibrated Thunder Probability Climatology Frequency [0%, 5%, , 100%] Slide 59 Hail >.75Wind > 50 ktsTornado All 24h forecasts F24 F63 from 15 April to 15 October 2005 SevereVerification 09 UTC and 21 UTC SREF ROC Area=.84 Ave Hit = 15% Ave Miss= 2% Slide 60 Verification Reliability Diagram: All 3 h forecasts (F00 F63); 35 days (Oct 1 Apr 30) Economic Potential ValueReliability Slide 61 SREF 3h Calibrated Probability of Thunderstorms Thunderstorm = > 1 CG Lightning Strike in 40 km grid box What about dry thunderstorms? Photo from John Saltenberger Slide 62 SREF 3h Calibrated Probability of Dry Thunderstorms Dry thunderstorms = CG Lightning with < 0.10 precipitation Slide 63 F027: Valid 00 UTC 15 May 2007 6hr UH > 50 + 25 mi Supercell Detection Probability Updraft Helicity > 50 m 2 /s 2 Slide 64 F027: Valid 00 UTC 15 May 2007 6hr Linear mode + 25 miles Squall Line Detection Probability Linear Mode Exceeding 200 miles Slide 65 Radar 00 UTC 15 May 2007 Radar Reflectivity Valid 02 UTC 15 May 2007 Slide 66 Radar 00 UTC 15 May 2007 > 35 dbZ Radar Reflectivity Valid 02 UTC 15 May 2007 Slide 67 SPC SREF Products on WEB http://www.spc.noaa.gov/exper/sref/ Questions/Comments david.bright@noaa.gov