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Dr. Paul Croft 1 , Alan Cope 2 , Danielle Fadeski 3 , Alexis Ottati 3 , Jackie Parr 3 Faculty Research Advisor 1 Natio

Morphologic Investigation of Thunderstorm Initiates and GIS Attributes with Testing for Improved Operational Nowcasting of Thunderstorms & their Severity in New Jersey. Dr. Paul Croft 1 , Alan Cope 2 , Danielle Fadeski 3 , Alexis Ottati 3 , Jackie Parr 3 Faculty Research Advisor 1

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Dr. Paul Croft 1 , Alan Cope 2 , Danielle Fadeski 3 , Alexis Ottati 3 , Jackie Parr 3 Faculty Research Advisor 1 Natio

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  1. Morphologic Investigation of Thunderstorm Initiates and GIS Attributes with Testing for Improved Operational Nowcasting of Thunderstorms & their Severity in New Jersey Dr. Paul Croft1, Alan Cope2, Danielle Fadeski3, Alexis Ottati3, Jackie Parr3 Faculty Research Advisor 1 National Weather Service2 Undergraduate Student 3 To Improve… Skill Confidence Precision in Convective Forecasting

  2. Why Improve the convective initiation forecast? What We Forecast… What Really Happens… “…a 40% chance of showers and thunderstorms…”

  3. Convective Objectives • Determine Convective Initiation patterns PHI CWA and nearby region • Movement, Intensity and Coverage • Use online database to assist in enhanced operational forecasting of thunderstorm initiation, coverage, and severity in real-time • Establish operational archive and forecast database http://hurri.kean.edu/~keancast/thunder/thunder.html

  4. Data Collection & Methods • Study Period: 2000 – 2010 • 10 Summer Seasons: June, July & August (one test season) • Mapped daily radar every 3 hours between 12 UTC and 00 UTC • Recorded cell/area radar intensities of 30 & 50 dBz Classification of each day and identify initiation locations/patterns • 500mb flow, surface synoptic pattern, and combinations of the two

  5. Research to Operations: Thunder Dome • Preferred locations of initiation from archive • Empirical probabilities of occurrence developed • Critical threshold values and field patterns associated with activity • Discern an “E” from “C” or “Null” day with greater confidence • 500 flow • Sfc Synoptic • Probabilities • Locations • CDC Diagnostics • Pattern of parameters • Causative Factors http://hurri.kean.edu/~keancast/thunder/thunder.html

  6. Building an Operational Conceptual Model • Determine 500 mb flow type (e.g., West flow cases) 68% chance of initiation to occur with West flow

  7. Forecasting with Operational Conceptual Model • Determine Surface Feature (e.g., Cold Front) 86% chance of initiation to occur with surface cold front

  8. Applying the Operational Conceptual Model • Using a combination (500mb+Surface Feature) • e.g., West flow and Cold Front 83% chance of initiation with W-CF combination preferred region for initiation for event cold front and 500 mb flow Contaminate cold front cases show no preference for initiation location

  9. Use of Diagnostic Patterns/Thresholds… 32% Chance Event 64% Chance Contaminate 4% Chance Null PWAT Event PWAT Contaminate PWAT Null

  10. Operational Testing & Verification Outline areas of initiation; cells, areas, or lines & where for severe Indicate whether forecast day of interest will be: E, C, N & if Severe How successful? Date/Type: June 1, 2009/Event Observed 1 Predicted 2 1200 UTC 500 mb flow: NW Sfc Pattern: High P Severe: Yes What else can be added? Number sequence of cell initiation Student: Match location to highest MOS POP axis & compare with gridded/zone • Lightning Data • STP for Coverage • Severe versus Non-Severe

  11. Develop a Lightning Climatology Event Days, SW Flow Event Days, NW Flow Can break down hourly to show diurnal evolution… Can assist in verification and determining coverage/impacts…

  12. What’s the pattern in time? Event Days, SW Flow Event Days, NW Flow

  13. What’s the Coverage of Convective Activity?(short term forecasting: 0-6h & 6-12h) • Storm Total Precipitation (STP) • Consider the first (12-18z) and second (18-00z) halves of the day • See progression/development of cells after initiation locations • Mapped values from website products • 0.1 inch signifies “likely” precipitation related to day’s convection • 1.0+ inches suggest thunderstorm with heavy rainfall and intensity/severity • Composites of Coverage/Intensity • Suggests greater risk regions • Amounts and possible severe storms

  14. What about probability/location of Severity? 25.6% Severe One-fourth C-COLD create severe weather 48.5 % Severe Half E-COLD create Severe Weather

  15. Diagnosing Events: Non-Severe vs. Severe Omega at 700mb for Cold Front EVENT days: 00-09 Increased specificity of local forecasts! Omega at 700mb for Cold Front CONTAMINATE days: 00-09

  16. GIS tie-in to Models & NDFD: Explaining Convection • Use high resolution GIS-based grid with 1-km grid of study region with details of the forecast region and locations • Relate specific physiographic features in the area to the preferred locations of convective initiation and its severity • GIS grid calculations focus on land use and land cover, elevation, distance to coast, and slope and can be related to model output • Risk assessment and management; warning specificity & public information statements; visualizations in time and space • Automation and animation for response planning/preparation Establish Cause and Effect

  17. GIS Assisted Convective Forecasting If we know the synoptic regime & 500mb Flow (SW CF, etc.) If we know the characteristics of the Grid Box (Elevation, Land Cover, Population, etc.) Combine this information with CDC composite variable or parameter values (PWAT, Omega, etc.) GIS Assisted Prediction of Convective Initiation characteristics, impacts, & risks

  18. Summary & Conclusions • Comprehensive Prediction of Convective Initiation • We know: Who, What, Where, How, When, & Why of initiation • We can: Distinguish Coverage and Intensity/Severity • Now Provide: Operational Products with Online Archive • Now Identify: Operational Conceptual Model & Cause/Effect • Next: Refine, Enhance, Automate (GIS-based radar data) • Future steps: GIS-grid assisted forecasting • Future purposes: Risk assessment and management We have the ability to improve… Skill Confidence Precision in Convective Forecasting Acknowledgements Thanks to the Kean University Department of Geology & Meteorology Faculty & Staff, Student Majors, and Adam Gonsiewski, undergraduate student of Millersville University for their assistance with this project. This presentation was prepared by Kean University and the National Weather Service under a sub-award with the University Corporation for Atmospheric Research (UCAR) under Cooperative Agreement with the National Oceanic and Atmospheric Administration (NOAA), U.S. Department of Commerce (DOC).

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