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DRAFT Pan Am 2015 Science Plan

DRAFT Pan Am 2015 Science Plan.

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DRAFT Pan Am 2015 Science Plan

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  1. DRAFTPan Am 2015 Science Plan Paul Joe, Stephane Belair, Ismail Gultepe, David Sills, Stewart Cober, Veronique Bouchet, Jean-Pierre Charland, David Hudak, Norman Donaldson, George Isaac, Tsoi Yip, Ed Becker, Victor Chung, Mark Seifert, Sara, Wong, Helen Yang, George Isaac, Dave Henderson, Bill Appleby, Health Canada

  2. Outline • Introduction • Mandate, Constraints • Process • Themes - DRAFT • Status/Next Steps

  3. Introduction • Warnings for venues • Main operational mandate – large crowds, security • Infrastructure & Efficiency – good place for business • Legacy • Demonstrate advanced capabilities • Accelerate existing programs • Align and provide a focus for MSC Signature Projects • Coordinate the dependencies • Prototype key concepts • Early deliverable • Capacity build NL’s/Tech Transfer

  4. Themes • Demonstration and validation of emerging NWP and Nowcasting capabilities for urban forecasts, warnings and AQHI • Demonstration, evaluation of emerging monitoring technologies for validation of emerging prediction capabilities • Demonstration of use of new prediction and monitoring in the forecast/warning office of the future

  5. Theme - Prediction • 1 km and 250 model application and validation • Town Energy Balance model • Wind/wind shift nowcasting • AQ model • AQ nowcasting • Health Index

  6. Theme - Monitoring • Emerging monitoring technologies to validate high resolution models in urban environment • High temporal frequency measurements • Low cost sensors • AQ supersite concept • Validation of the Network of Network concepts, • Intercomparison for data quality knowledge and application • NoN Mesonet • Lower tropospheric profiling technologies (thermodyanmic, air quality) • Lightning Mapping Array • Unmanned Aeronautical Vehicles • Sodat

  7. 0 km 50 4 UPDATED + 4 More AiO 1 2 3 5 AiO 6

  8. Data Cube, Production db,, Meteocode Fcster Automatic products Theme – Office of the Future • Man-machine mix • When automation is good enough • When and how to intervene • Ownership of the end product in a “production data base” concept • metObjects • Event based warnings • Deployment and use of advanced NinJo features • Use of high res NWP, EPS • Need to prototype complex ideas before development of operational specification and deployment!

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