1. Quality Assessment and NEVS for NextGen Jennifer Mahoney NOAA/ESRL/GSD 2 Dec 2010 Interagency Aviation Meeting

2. Outline NextGen needs for forecast quality information Concepts in a user context NEVS – Delivery infrastructure Summary 2

3. NextGen Weather Integration Concept (Weather Integration Plan V1.0) 3

4. 4 NextGen Weather Performance Needs Advanced assessment techniques and metrics Integrated with key operational decision criteria Provided in the context of the FAA operational user A net-enabled framework that allows effective and timely distribution of automated quality assessment information to NextGen users

5. NEVS in NextGen Weather Integration NEVS Quality of Wx Quality of Translated Wx Information Exchange 4D Wx SAS Performance Feedback Other Services Translation of Wea Aviation Operations Other Services Translation of Wea Aviation Operations Weather Translation for ATM Decision Support Translation of Weather for use in Aviation Operations Weather Translation for ATM Decision Support Translation of Weather for use in Aviation Operations Performance Feedback NOAA Forecast Process 5

6. Concepts With a User-specific Focus 6

7. Roles for Quality Metrics MeteorWAFMincutDelay 7

8. Forecast Accuracy Variations Summary Statistics Seasonal and regional variations Traditional point of view 8 Summer Winter

9. Forecast Value to Planning Processes 9 Risk AssessmentPlanning Efficiency Lower Risk Higher Risk More Efficient Less Efficient Operational Criteria

10. Sector Impact Measures 21 Aug 2009; 1500 UTC, 6h lead 10

11. NEVS For Effective Delivery of Information 11

12. 12 NEVS Prototype 2010

13. 13

14. NEVS Services 14

15. NEVS Synthesis Input Service 15

16. NEVS Synthesis Service ATM DST ATM DST Forecast Weather IMPROVED Forecast Estimates of AFP Airspace Availability Forecast Synthesis CoSPA Pilot Deviation Prob Weather Avoidance Field (WAF) 35 kft CCFP LAMP NCWD Build historical performance for forecasts Decision support criteria is provided to NEVS WAF Forecast Synthesis Algorithm WAF Forecast Synthesis Algorithm NEVS provides scenario-specific synthesis input -10 min +10 min +20 min 0 min FCAA05 -10 min +10 min +20 min 0 min FCAA08 16

17. Weather Synthesis 8/21 15Z 6-h lead 17

18. NEVS Decision Matrix 18

19. Synthesis Input NEVS – Network Enabled Verification Service Forecast B Forecast A Synthesized A & B Verification Metrics 19

20. NEVS Alert Service 20

21. Forecast weather Actual weather Tolerance Thresholds defined by user Ongoing monitoring of weather Alert when actual weather exceeds thresholds Plan is created at t=0 for 6 hr Planning period NEVS Alert Service 21

22. Summary NextGen Needs: User-specific Concepts Effective net-enabled delivery of the quality information to forecast and planning processes GSD is: Building and testing concepts Developing NEVS as an information delivery infrastructure 22

23. Questions 23

24. NEVS Prototype 24 Sector maps of CoSPA, CCFP, and CIWS analysis along with verification statistics

25. NEVS Prototype 25 Detailed view of verification statistics

26. NEVS Prototype 26 Detailed view of ingest status

27. Planning Point Capacity Plot Onset Cessation % Blockage as derived from Mincut Bottleneck Technique 27

28. Sector Jetway Corridor Bottleneck Hazard Blockage Potential 0.5 Mincut Bottleneck Technique 28

29. QUESTIONS? 29

30. Why Weather Performance Information is Different Therefore, to develop and produce performance information continually, A mechanism for managing data is required Integrating operational criteria with performance information is critical Distribution of the performance information when needed is vital 30

31. Why Weather Performance Information is Different Weather forecast data valid short period of time and then replaced with next forecast Performance information requires the entire history of forecast data for computing the metrics 31 Forecast Data Performance metrics computed using historical archive of forecast data

32. Working Assumption NextGen requires an integrated approach for diagnostic monitoring and automated evaluation of weather information (both realtime and historic) for effective air traffic management 32