Prediction of Weather Impacts on Air Traffic Through Flow Constrained Areas

1. Prediction of Weather Impacts on Air Traffic Through Flow Constrained Areas AMS Seattle Yi-Hsin Lin 25 January 2011

2. Outline • Forecast capacity model • Motivation • Algorithm • Example: 4 August 2011 case study • Results and verification • Summary and further work

3. Strategic and Tactical PlanningSynergism Airspace Flow Programs “Playbook” Reroutes Weather NY PHL Ground Delay Programs • Tactical Decision-Making • Managing pilot deviations • Safe management of airborne holding • Dynamic, locally-coordinated reroutes • Implementing local airspace restrictions • Balancing airport arrival / departure fixes • Strategic Decision-Making • Airspace Flow Programs • Playbook reroutes • Ground Delay Programs Good Strategic Planning Manageable Tactical Environment 2 – 6 Hours “National & Planned” 0 – 2 Hours “Local & Dynamic” Contributes to Successful Strategic Plan Good Tactical Planning

4. Capacity Truth Low Medium High AFP Capacity Matrix: 4 August 2010, FCAA05 Valid Time (UTC) Issuance Time (UTC) A05 Primary Decision Period

5. Estimating Capacity: Process Overview

6. Weather Avoidance Fields WAF: Probability of deviation Echo Tops 100 90 80 70 60 50 40 30 20 10 0 -22 -18 -14 -10 -6 -2 2 6 10 14 18 22 Flight Altitude – Echo Tops (16 km) 0 10 20 30 40 50 60 70 80 90 100 % VIL Coverage ≥ Level 3 (60 km) 0 5 25 50 75 95 100 Historically, what kind of weather do pilots tend to deviate around? As of summer 2009, WAFs have been integrated into the CoSPA shadow system. VIL

7. Blockage Algorithm Route Segment • Distance-weighted average of unavoidable WAF • Takes into account maneuverability along a route • Takes into account orientation of route • Takes into account unavoidable weather Typical maneuverability ( 40km ) Weighted average centered on least significantly impacted path: Severe Wx Center of Jet Route Preferred Route Least Significantly Impacted Path through Wx Time to coordinate deviation ( 4min* or 55km ) Sum ( Weight * Precip>=Threshold ) Blockage = where Weight = 1 / Normal Distance from Path Sum ( Weight ) Threshold = Maximum Precip along Path *based upon 825km/hr cruise speed

8. Resource Capacity • FCAs A05 and A08 chosen because they are the most frequently used AFPs. • Delays in the northeast can cause delays throughout the CONUS • Route capacity = minimum capacity along each route • AFP capacity = average of route capacities FCAA05 FCAA08

9. Outline • Forecast capacity model • Example: 4 August 2011 case study • AFP vs. route capacities • Analysis of forecast error • Results and verification • Summary and further work

10. Weather and Traffic on 4 August 2010 17Z 20Z 18Z 21Z 22Z 19Z 999999- XYZ 12/30/10

11. Capacity Truth Low Medium High 4 August 2010: CoSPA Forecasts Reflected in Matrix Capacity Forecasts Valid Time (UTC) 6-hr 6-hr Issuance Time (UTC) 5-hr 5-hr A05 Primary Decision Period Truth Truth 4-hr 4-hr Forecasts Valid at 19Z, 4 August 2010

12. Route vs. AFP Blockage Uncertainty • Forecasts are highly volatile at the route scale • Errors are averaged out at the AFP scale Matrix Capacity Forecasts Valid at 22Z All routes J191 AFP aggregate CoSPA forecasts valid at 22Z 5-hour forecast 4-hour forecast

13. Outline • Forecast capacity model • Example: 4 August 2011 case study • Results and verification • Overall statistics • Error model • Summary and further work

14. Overall Statistics Dataset: Summer 2010, except when CoSPA was down Forecast Error Distribution Forecast - Truth Forecast Time High capacity most of the time

15. Statistics by Impact and Time of Day 50-80 80-99 100 3-11Z 15-3Z 11-15Z

16. Observed CoSPA-based AFP Route Blockage Forecast Error Modes Forecast AFP Blockage • Analysis of both 2009 and 2010 CoSPA route blockage forecasts • AFP route blockage forecast error did not always decrease monotonically with shorter look-ahead times • Uncertainty modeling needs to focus both on predicting route blockage error and error behavior • Presenting model to predict route blockage error only Forecast Look-ahead (minutes) “Free and Clear” “The Dip” “The Climb” “The Fall” Truth value Forecast value

17. Factors, Predictors, and Results of AFP Blockage Error Modeling Regression Tree Model Error Predictors Route Blockage (0 – 1.0) Blockages affected by severity, scale, and organization of storms throughout the domain AFP Blockage Error Prediction Results from 2010 CoSPA Regression tree may also be used to improve the blockage prediction

18. Outline • Forecast capacity model • Example: 4 August 2011 case study • Results and verification • Summary and further work

19. Summary • Airspace Flow Programs are used to mitigate delays on strategic timescales • CoSPA forecast → statements of resource capacity • Forecast scoring method • Tool for air traffic managers • Capacities cannot be estimated at the scale of routes • AFP capacities can be broadly estimated • More work needs to be done on scoring and quantifying forecast uncertainty

20. Further work: AFP Forecast Scoring • Relate capacity forecasts to actual traffic counts • Incorporate error analysis to improve the forecast • Scaling vs. uncertainty – transition from strategic to tactical

21. Thanks • Josh Sulkin, Rich DeLaura • Bill Dupree • Mike Robinson • Joe Venuti • Marilyn Wolfson Questions?