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Science and Technology Infusion Plan for Winter Weather Services PowerPoint Presentation
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Science and Technology Infusion Plan for Winter Weather Services

Science and Technology Infusion Plan for Winter Weather Services

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Science and Technology Infusion Plan for Winter Weather Services

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  1. Science and Technology Infusion Plan for Winter Weather Services Sam Contorno NWS S&T Committee September 17, 2002

  2. Outline • Team Composition • Vision / Benefits • Goals / Targets • Key Information Gaps • Key Solutions • Outstanding R & D Needs • Summary

  3. Sam Contorno – NWS/OST Mark Tew – NWS/OCCWS Marty Ralph – OAR/ETL Jack Dostalek – NESDIS/CIRA John Cortinas – OAR/NSSL/CIMMS Andy Edman – NWS/WR SSD Paul Sisson – NWS/WFO BTV Jeff Waldstreicher – NWS/ER Peter Manousos – NWS/NCEP/HPC Allen White – OAR/ETL Paul Neiman – OAR/ETL Paul Stokols – NWS/OCCWS Winter Weather ServicesTeam Composition

  4. Winter Weather ServicesVision / Benefits • Vision • Winter Storm Warning Lead Time > 24 Hrs • Probabilistic Guidance Out to 10 Days • Large Winter Storms Result in Losses of $Billions and Influences Regional/National Economy. • Better Information = Better Decisions by Public Prior to Arrival of • Inclement Wx • $ Millions in Savings for Public Works & Transportation Sector

  5. On Track Low Risk High Risk Winter WeatherGoals/Targets to FY 12

  6. Winter WeatherKey Information Gaps • More Accurate Cyclone Track: More Precise Position of Precipitation Cutoff and Rain/Snow Line/Snow Level • Limited Coastal and Offshore Observations Aloft • Understanding of Model Guidance Uncertainty • More Accurate Identification of Precipitation Type, Cloud Microphysical Info, and Vertical Distribution of Moisture • More Accurate Identification of Mesoscale Snow Bands and Orographic Effects

  7. Winter WeatherKey S&T Solutions

  8. 10 02 05 06 07 08 04 09 11 12 03 Winter Weather Key S&T SolutionsCurrent Programmatic Phase Targeted Obs. Dual Polarization MDCRS-WVSS2 Observations GPS-IPW Satellite Upgrades Deployment 8km WRF* SR Ensembles Advanced Ensembles GFS DA/Models Weather-Climate Connection OTE Meso Snowband Technique DTE Forecast Techniques Snow Level Detection Algorithm R&D Precip Type Algorithms* Weather Event Simulator Training Winter Weather & NWP PDS

  9. Winter WeatherOutstanding R&D Needs • Develop Sensors that Accurately Detect Different Precipitation Types/Measure Snow Depth • Develop Ensemble Techniques for Probabilistic Forecasts of Severity of Large-Scale Winter Storms • Improve Understanding of Mesoscale and Microphysical Processes that Lead to Heavy Winter Precipitation Events • Improve Understanding of Orographic Effects on Mesoscale Distribution of Winter Precipitation • Develop Artificial Intelligence Systems to Forecast Snowbands/Heavy Snowfall/Significant Icing • Develop Improved Collaborative Forecast Tools • Develop Improved Verification Procedures

  10. Winter WeatherSummary Vision Lead Times > 24 Hrs; Prob. Guidance 10 Days • R&D Needs • Precipitation Type Sensors • Probabilistic Forecast Techniques • Artificial Intelligence to Detect Heavy Snowbands • Understanding of Mesoscale and Microphysical Processes Increasing Performance • Deploy High Resolution, More Accurate Models • Enhance Decision Assistance Tools • Expand Targeted Observations • Deploy Advanced Ensemble Techniques • Deploy Dual Polarization/Satellite Upgrades Continuous Training 2002 2007 2012

  11. Back-up Information

  12. Primary Customers/Partners • General Public • Emergency Managers • Federal/State/Local Governments • Transportation Industries • International Interests • Educational Organizations/Institutions of Higher Learning • Media • Private Sector Weather Forecasters

  13. Key Products/Services • Winter Weather Watches/Warnings • Zone Forecasts • Winter Weather Advisories/Outlooks • Public Information Statements • Heavy Snow/Icing Discussions • Probabilistic Heavy Snow/Icing Forecasts • Short-term (1-6h) Winter Weather Discussion

  14. Profiler Snow-Level DetectionSnow Advisory raised to Winter Storm Warning Prototype profiler snow-level product showed 2700 ft snow level at the coast, 1300 ft lower than the snow level that had been predicted before landfall. NWS’ Portland OR SOO (Bill Schneider) upgraded earlier Snow Advisory to a Winter Storm Warning based on this lower snow level and passes being at 4000 ft. Forecaster’s use of these data increased warning lead time by 15 h in this case and increased POD by avoiding a miss. Predicted snow level