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Alan Rezek National Weather Association Annual Meeting October 17, 2006

The Enhanced Short Term Program at WFO Charleston WV. Alan Rezek National Weather Association Annual Meeting October 17, 2006. Enhanced Short Term Operations. WHY. NWS has forecaster resources (100+ offices), local expertise and tools to forecast high resolution space and time

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Alan Rezek National Weather Association Annual Meeting October 17, 2006

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  1. The Enhanced Short Term Program at WFO Charleston WV Alan Rezek National Weather Association Annual MeetingOctober 17, 2006

  2. Enhanced Short Term Operations WHY • NWS has forecaster resources (100+ offices), local expertise and tools to forecast high resolution space and time • Private sector has analysis, interpretation and distribution expertise to use high resolution forecast data to provide services The Perfect Marriage Each Playing To Their Strength

  3. Enhanced Short Term Operations WHY • NWS has been making investments. Higher resolution modeling, WFO local high resolution model capability, increased frequency of model runs and local WFO model diagnostic capability, etc. have all been developed and are available to forecasters over the last several years. The Forecasters are ready to Accept The Challenge to use the tools to take forecast services To The Next Level • With a new level of services in place with ESTO, we will be positioned to use improved technology & organizational structure to take us to a second level of services by 2015.

  4. Enhanced Short Term Operations Key Elements • 12 to 18 Hour forecast focus • High Detail in space • Stress being deterministic as possible • Hourly Grids – High detail in time • Aviation forecast grids (ceiling and visibility) • Repeated three hour forecast preparation cycle • Analysis, model/guidance interpretation, build forecast grids, transmit forecast • Modified shift activities to have at least one forecaster dedicated 24/7 to short term forecast activities

  5. Enhanced Short Term Operations Key Elements • Focus off text onto meteorology • Prioritized forecaster efforts to maximize service through detail • increase emphasis on our role as detailed forecast data service providers • decrease emphasis on private role of creating “desirable, pleasant, focused use” text information • Full Automation of many text products from grids: AFM, PFM, SFP, FWF

  6. Enhanced Short Term Operations Key Elements • 90% Automation of 4 “primary” text products from grids • Alerted when produced – checked and sent • Adjusted wording to better facilitate computer generation and better match the role of the 4 “primary” text products in an operation oriented to high resolution forecast data. • ZFP: 4/day, Low detail, 1 Cnty/1 Zn, for general use • NOW: 8/day, 1 Cnty/1 Zn, four 3 hr periods, high detail text for short term decision making (next 12 hours) • NWR ZFP: Every 3HRs, 3 HR detail 1st 12 hrs, 6 hr detail period 2 and 3, then 12 hour detail, both general use and short term decision making text • TAF: data extracted from grids; TAFs are formatted, finalized and sent every 6 hours, updated every 3 hours

  7. SCIENCEForShort Term Three Primary Components • Consolidate and organize data and information availability to forecasters for their use to meet ESTO expectations • Improve high resolution model data availability • Develop model diagnostic techniques to assist in preparing high detail forecasts • Improve forecaster performance feedback • focus on short term forecast operations • real time/next day

  8. SCIENCEForShort Term * Improved MESONET CAPTURED ALL AVAILABLE DATA ADDED RIDGETOP SITE AT NWR COORDINATED WV IFLOWS MESONET 2 MET SENSOR SYSTEMS/COUNTY EXPANDED LOCAL LAPS DOMAIN FOR IMPROVED LOCAL MODELING INCREASED LAPS RESOLUTION - 5KM

  9. SCIENCEForShort Term • LOCAL SHORT RANGE MODELS/FCSTS • * WSETA FORECAST EVERY 6 HOURS • HRLY OUT 18 HR, 15KM RESOLUTION • * SHIFTED FINANCIAL RESOURCES TO CREATE • A CLUSTER TO SUPPORT LOCAL WRF • * WRF FORECAST EVERY 3 HOURS • HOURLY OUT 18 HR, 5KM RESOLUTION • HIGH LOW LEVEL LAYER RESOLUTION • INCLUDE PBZ (BACKUP PARTNER) IN DOMAIN • “HOT START” INITIALIZING ON LAPS • EXPERIMENTED WITH “LOCAL” PRODUCED • FIELDS

  10. SCIENCEForShort Term • Worked to assure availability and reliability of other operational short range and aviation models • HOURLY SHORT TERM MOS (LAMP) • HOURLY FORECASTS EVERY 3 HR • FWC BASED • MAV BASED • RUC40 AND RUC13 • NCV

  11. SCIENCEForShort Term • High Resolution model data made available in AWIPS and GFE (2.5 KM) • Enhanced the role of GFE in forecasting • Developed diagnostic capabilities and output • EX - Individual model diagnosis and short term model consensus forecasts of hourly precipitation, severe potential, winter weather • Developed SMART tools for the preparation of high detail forecasts in space and time– EX – fog in individual valleys/individual hours

  12. SCIENCEForShort Term • Real time model & Forecaster first period temperature and POP verification data • Available in AWIPS at end of first period • Verification data for each model and the forecaster • 2 and 10 day trends/rankings for each model and WFO • Higher resolution POP verification developed • 3 hour sub period of 12 hour forecast period • Local MOS and consensus MOS developed for 1st period • Review of verification of NDFD elements by hour undertaken and feedback provided to forecasters • Verification developed for station, forecast team and individual

  13. Thursday For more details regarding the aviation activities 0830 AM Generation and Application of Gridded Aviation Forecast Parameters in GFE and AvnFPS.Chris Leonardi, NOAA/NWS Charleston, WV. For more details regarding the use of GFE for model diagnostics 0115 PM Exploring a New Approach to Improving Severe Weather Warning Lead Times Using GFE. Andy Roche, NOAA/NWS Charleston, WV.

  14. Enhanced Short Term Operations What Are The Impacts?

  15. Percent Improvement Max/Min over MAVJanuary through SeptemberTraditional Period 1 First Year Short Term

  16. Percent Improvement Max/Min over MAVTraditional Period 1 • First convective season exceptional • Second convection season no improvement • First winter season good improvement

  17. Brier ScoresJune ‘05 through July ‘06Traditional Period 1 Zero being perfect

  18. Aviation POD IFR FY ‘06 Essentially about the same as the previous year

  19. Aviation FAR IFR FY ‘06 Large improvement over previous year

  20. What About The Users? User Research Service Verification Advisory Board • 15 to 20 representatives from varied WFO user groups • Ex. Aviation, Education, Construction, Media • They provide periodic feedback regarding services forming a “core” for a service verification program • They provide feedback regarding specific issues (ie. NWR, river forecast services)

  21. User Research Advisory Board What is the place of detail in the forecast? • Web products most used: Radar, AHPS, Hourly Wx Graph, Point and click forecast – Products with high detail in space and time • POPs of highest value to users: zero and 60 to 100 percent • POPs of lowest value to users: 10-50 percent • Ease of getting a detailed forecast on our web site = 4.1 out of 5 (being best)

  22. Biggest Challanges People Issues • Difficult to overcome organizational “can’t” biased culture and belief system which says: “we are not that good”, “we can’t predict summertime convection”, etc. • Historic examples where believing few overcame “can’t”: QPF, river forecasts based on QPF, hourly grid forecasts • Challenging for forecasters to change forecasting approach • Getting forecasters to shift from traditional “big period” approach of model interpretation • Getting forecasters to use new forecast models/tools • Getting forecasters to forecast more deterministically

  23. Biggest Challanges People Issues • Forecaster continuously engaged in short term during shift: lose of touch with long term, no training/focal pt “extra time” • During complex short term weather, Lead Forecaster must delegate “overseer” role or remove themselves from the short term desk • Collaboration difficult in rapidly changing situation

  24. Biggest Challanges Technical Issues • Days 4 through 7 forecasting taking from short term forecasting time • Poor cost/benefit for time spent forecasting for days 4 thru 7 relative to forecasting in short term • Lack of good low level modeling for aviation • ESTO technology dependent, susceptible to failure • Meso Networks, Local modeling, Network speed

  25. Enhanced Short Term Operations WFO Charleston, WV SOO – Jeffrey.Hovis@NOAA.gov WCM - Daniel.Bartholf@NOAA.gov MIC – Alan.Rezek@NOAA.gov IT – Kevin.Mcgrath@NOAA.gov

  26. Additional Background Information

  27. Enhanced Short Term Forecasts New forecast every 3 hours 7 AM/PM 10 AM/PM 1 AM/PM 4 AM/PM Deterministic Where it is and is not When it is and is not Focus Hourly Weather in first 12 to 24 hours

  28. Enhanced Short Term Operations Additional Thoughts on WHY Cost/Benefit ratio high with high detail forecasts • Customers have good detail for decision making • A better warning service/advance notice in both space and time of specific threat areas • With automation of text, more time to focus on, and provide, detail in the forecast • Skill/verification improves with more focus on detail in short term • Focus on the area in the forecast process where the technology and availability of the human/forecast resources of the NWS can enhance the information to the private sector for their use. • Additional aviation services available with aviation grids

  29. Timeline • July 04 – WFO Enhanced Short Term Team established • Aug 04-Mar 05 – Put in place hardware and software requirements, conducted training • Mar 05 – Began Enhanced Short Term Operations (ESTO) • Aug-Sep 05 - Put in place software requirements, conducted training for aviation grids • Oct 05 – Added aviation grids to ESTO

  30. Sample Realtime First Period Verification Products Available to forecasters when they return to work the next day

  31. Realtime First Period Max/Min Verification Product • THIS WRKVER PRODUCT COMPARES MOS FCSTS WITH CCF AND OBS DATA IN THE RTP RANKINGS LISTED AT THE BOTTOM VERIFICATION PRODUCT CREATED: 09/21/2006 at 13:00 UTC QUICK VIEW - ONE DAY MINIMUM BIASES FOR SELECT MODELS: • STN OBS CCF BIAS MAV BIAS MET BIAS FLP(L) BIAS LMOS BIAS • --- --- --- ---- --- ---- --- ---- ----- ---- --- ---- • BKW 37 | 37 0 | 35 -2 | 39 2 | 42 5 | 36 -1 • CKB 41 | 41 0 | 40 -1 | 43 2 | 999 MM | 42 1 • CRW 43 | 42 -1 | 38 -5 | 44 1 | 45 2 | 44 1 • EKN 41 | 39 -2 | 36 -5 | 38 -3 | 999 MM | 39 -2 • HTS 40 | 41 1 | 37 -3 | 43 3 | 44 4 | 44 4 • PKB 41 | 40 -1 | 38 -3 | 41 0 | 44 3 | 42 1 • --- --- --- --- --- • ABS SUMS: 5 | 19 | 11 | 14 | 10 • ...CCF-MOS Rankings...(ABS) • 2 DAY RANK: 10 DAY RANK • : ----------- ------------ • CCF 1.83 1. CCF 1.70 • MOS 2.08 2. CON 1.80 • FLE 2.25 3. MOS 1.80 • MEX 2.25 4. MET 1.90 • FLL 2.50 5. MEX 1.98 • FWC 2.50 6. FWC 2.18 • CON 2.60 7. MAV 2.35 • MET 2.92 8. FLL 2.58 • MAV 3.33 9. MEN 2.72 • MEN 3.67 10. FLE 2.80

  32. Realtime First Period POP Verification Product • THIS WRKPOP PRODUCT PROVIDES POPS SCORES FOR MOS AND CCF FCSTS RANKINGS LISTED AT THE BOTTOM VERIFICATION PRODUCT CREATED: 09/21/2006 at 13:00 UTC QUICK VIEW - ONE DAY POP VALUES AND VERIFICATIONS FOR SELECT MODELS: • STN PCP? CCF BIAS MAV BIAS MET BIAS FLP BIAS FWC BIAS • --- --- --- ---- --- ---- --- ---- --- ---- --- ---- • BKW N | 5 5 | 6 6 | 10 10 | 0 0 | 0 0 • CKB N | 5 5 | 5 5 | 11 11 | 2 2 | 0 0 • CRW N | 5 5 | 6 6 | 10 10 | 1 1 | 0 0 • EKN N | 5 5 | 6 6 | 14 14 | 1 1 | 0 0 • HTS N | 0 0 | 6 6 | 9 9 | 2 2 | 0 0 • PKB N | 0 0 | 5 5 | 10 10 | 0 0 | 0 0 • --- --- --- --- --- • ABS SUMS: 20 | 34 | 64 | 6 | 0 • BRIER SCORES FOR ALL SITES: • 2 DAY RANK: 10 DAY RANK: • ------------ ----------- • MOS 0.0000 1. MET 0.0946 • FLL 0.0020 2. CCF 0.0959 • FLE 0.0021 3. CON 0.0973 • MEN 0.0063 4. MOS 0.1000 • CCF 0.0083 5. FWC 0.1032 • FWC 0.0095 6. MAV 0.1042 • MAV 0.0112 7. MEN 0.1048 • MEX 0.0150 8. FLE 0.1072 • CON 0.0150 9. MEX 0.1147 • MET 0.0296 10. FLL 0.1149

  33. Realtime 3 HR POP Verification Product for the First 12 HR Period THE WRKTHR PRODUCT COMPARES POP FCSTS FROM THE PAST DAY WITH OBSERVED DATA AT VARIOUS GAGE SITES FOR THREE HOUR PERIODS..15Z PACKAGE. For ALL SITES/ALL TIMES: OverFcst UnderFcst MidPOP HitsPcp HitsNoPcp #/% #/% #/% #/% #/% ------- --------- ------- -------- --------- 3842/39.80 | 435/70.96 | 3494/34.03 | 178/29.04 | 5811/60.20 FOR SITE: 8137: DaysBack OverFcst UnderFcst MidPOP HitsPcp HitsNoPcp #/% #/% #/% #/% #/% ------- --------- ------- -------- --------- -------- 10 5/12.82 | 2/50.00 | 6/13.95 | 2/50.00 | 34/87.18 30 36/31.30 | 9/50.00 | 42/31.58 | 9/50.00 | 79/68.70 90 140/35.81 | 30/69.77 | 152/35.02 | 13/30.23 | 251/64.19 FOR SITE: 1234:………. Breakdown by 3 hour period also planned

  34. Traditional Second Period Verification In The Short Term Environment These have not suffered from a first period emphasis

  35. Percent Improvement over MAVJune ‘05 through July ‘06Period 2

  36. Brier ScoresJune ‘05 through July ‘06Period 2 Zero being perfect

  37. Typical Forecaster Shifts 10 forecasters Y - Short Term (12-24 hr) Z - Long Term Winter H - Short Term J – Extended (Day 4-7)/Extra K - “Mid Term” (Period 2 or 3 thru Day 3) Summer H - Short Term J - Extended then “Mid Term” L – Assist with forecast/Extra/Convection Q - Short Term

  38. Web Page Emphasis Of Short Term Forecast Program

  39. By going to grids we have increased the services to the aviation community without adversely impacting TAF forecasts

  40. Ability Of Atmosphere to Support Severe Weather Each Hour As Created in GFE

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