Concept of a NinJo smart tool for aviation forecasters

1. www.ec.gc.ca Fog Remote Sensing and Modeling Workshop,Halifax, Nova Scotia, Canada, 21-22 May 2008www.chebucto.ca/Science/AIMET/fog Concept of a NinJo smart tool for aviation forecasters Science and Technology Branch • Acknowledgements: • Stewart Cober • Jack Dunnigan • Erik de Groot • Ismail Gultepe • Steve Laroche • Bruno Larochelle • Alister Ling • Jim Murtha Bjarne Hansen

2. Dashboard Definition: “A dashboard is a visual display of the most important information needed to achieve one or more objectives; consolidated and arranged on a single screen so the information can be monitored at a glance.” * • What exactly are the objectives? • Weather watch, monitoring “TAF health.” • Finding “needles in haystacks” • important, helpful information • quickly and easily • Making forecasts efficiently and effectively • What is the most important information? * Stephen Few, 2006: Information Dashboard Design: The Effective Visual Communication of Data, O'Reilly Media.

3. Forecaster“Over the loop”Has knowledge and situational awareness; Can interact and intervene Integrated TAFMonitoring and Editing Battleboard: Maintain situational awareness GUI: Leverage forecaster actions Adjust concepts Edit text Guidance Display(observations, NWP, etc.) Editor Actual Weather Map (animated) Integrated Weather Concepts(visualize,manipulate) DSS / “4H” :Health, Heads-up,Help, Heuristics DF1 Comments Edit Send Dashboard

4. D1:METAR D4: Lightning Data Management System (raw real-time observations) D5: Radar D6: Satellite D7: Upper Air D8: PIREPs Forecaster“Over the loop”Has knowledge and situational awareness; Can interact and intervene Integrated TAFMonitoring and Editing Battleboard: Maintain situational awareness GUI: Leverage forecaster actions Adjust concepts Edit text Guidance Display(observations, NWP, etc.) Editor Actual Weather Map (animated) Integrated Weather Concepts(visualize,manipulate) DSS / “4H” :Health, Heads-up,Help, Heuristics DF1 Comments Edit Send Dashboard Engine Model Post-process D3: NWP DataAssimilation Guidance“interest fields”

5. D1:METAR D4: Lightning Data Management System (raw real-time observations) D5: Radar D6: Satellite D7: Upper Air D8: PIREPs Raw QC’edWeather Forecaster“Over the loop”Has knowledge and situational awareness; Can interact and intervene Integrated TAFMonitoring and Editing DF1: TAF ! Battleboard: Maintain situational awareness GUI: Leverage forecaster actions DF0: Trend 0 time Adjust concepts Edit text Heads-up Alert and Display Guidance Display(observations, NWP, etc.) Editor Actual Weather Map (animated) Integrated Weather Concepts(visualize,manipulate) DSS / “4H” :Health, Heads-up,Help, Heuristics DF1 Comments Edit Send Dashboard Engine Model Post-process DF0: TAFGuidance (0-30 h) D3: NWP Check DF0-DF1Consistency Feedbackadvice DataAssimilation Guidance“interest fields” Produce (encode) AI Integrate (make coherent) AI DA1: Static Aviation Nowcast (minimal model) ATM DA1: limits, thresholds DA2: planned arrivals and departures,timing sensitivities,runway configurations,traffic problems,preferred alternates, NOTAM DA3: cost-loss model for decision-making (rules for weighting) DA2: Variable AI DA3: Cost-loss model Expected Conditions (0-6 h) data and information• up-to-the-minute intelligent data fusion• abstract features• derived fields• intelligently composed “interest fields” Weather Concepts Forecast (translate) D2: ClimateArchive on ECONET Quality Control TAF AI Verification Proposed architecture for Integrated TAF Editing and Monitoring, revised 28 March 2008, based on notes from NinJo / Workstation Workshop for Aviation Weather Services, Montreal, 19-21 Feb. 2008. Address any comments toBjarne.Hansen@ec.gc.ca.

6. D1:METAR D4: Lightning Data Management System (raw real-time observations) D5: Radar D6: Satellite D7: Upper Air D8: PIREPs Raw QC’edWeather Forecaster“Over the loop”Has knowledge and situational awareness; Can interact and intervene Integrated TAFMonitoring and Editing DF1: TAF ! Battleboard: Maintain situational awareness GUI: Leverage forecaster actions DF0: Trend 0 time Adjust concepts Edit text Heads-up Alert and Display Guidance Display(observations, NWP, etc.) Editor Actual Weather Map (animated) Integrated Weather Concepts(visualize,manipulate) DSS / “4H” :Health, Heads-up,Help, Heuristics DF1 Comments Edit Send Dashboard Engine Model < 5 seconds Post-process DF0: TAFGuidance (0-30 h) D3: NWP Check DF0-DF1Consistency Feedbackadvice DataAssimilation Guidance“interest fields” Produce (encode) AI Integrate (make coherent) AI DA1: Static Aviation Nowcast (minimal model) ATM DA1: limits, thresholds DA2: planned arrivals and departures,timing sensitivities,runway configurations,traffic problems,preferred alternates, NOTAM DA3: cost-loss model for decision-making (rules for weighting) DA2: Variable AI DA3: Cost-loss model Expected Conditions (0-6 h) data and information• up-to-the-minute intelligent data fusion• abstract features• derived fields• intelligently composed “interest fields” Weather Concepts Forecast (translate) D2: ClimateArchive on ECONET Quality Control TAF AI Verification Proposed architecture for Integrated TAF Editing and Monitoring, revised 28 March 2008, based on notes from NinJo / Workstation Workshop for Aviation Weather Services, Montreal, 19-21 Feb. 2008. Address any comments toBjarne.Hansen@ec.gc.ca.