FAA Air Traffic Organization (ATO) Weather and Operational Performance Date: 2 August 2016 Presented to: FPAW 2016 Summer Meeting Presented by: John Gulding

Management Objectives Can FAA identify/prioritize the constraints in the system? Air Traffic Flow Management Delay, Taxi-Out Delay Is FAA making the most efficient use of capacity? Capacity, Throughput, Capacity Efficiency Is FAA providing efficient flight trajectories to operators? En-Route Additional Distance, Level Flight How will FAA respond to questions of Airline schedule delay, on-time performance? On Time Performance, Change in Block Time

Metric Inter-Dependencies ANSP Investment Traffic Management Initiatives Airspace Design Airport Maintenance Airport Expansion ATC/ATM performance Capacity & Airport Infrastructure Schedule Delay New Technology Other Drivers (SAA) Operator Schedules & Flight Preferences Weather Schedule Peaks Crew Scheduling Equip problems, etc. Low Visibility High wind Convective weather

Data Sources Archived Trajectory and Flight Plan Data Aviation System Performance Metrics (ASPM) Key Event Times: Scheduled Filed Actual, Basic METAR Air Traffic Flow Management Delay (OPSNET) National Traffic Management Log (NTML) Weather Sources METAR NCAR Wind Data at 6-hour intervals

ATFM Delay by Category - FY2016 For comparison, here is FY2015 to May: Visibility 29.4% Wind 20.7% T-Storms/Severe 15.1% Volume 14.8% Snow/Ice/Winter Ops 7.2% Equipment 6.1% Runway/Taxi 4.6% Other 2.1% Rain 0.0% GREATEST CHANGES IN PERCENT SINCE LAST COO BRIEF: The greatest increase has been in t-storms/severe (+5.1%) and the greatest decrease has been in wind (-2.5%).

ATFM Delay by Region - FY2016 Northeast -BOS, EWR, HPN, JFK, LGA, N90, PHL, TEB, ZBW, ZNY   Chicago -MDW, ORD, ZAU DC Area -DCA, BWI, IAD, ZDC GREATEST INCREASES IN PERCENT SINCE LAST COO BRIEF Chicago- t-storms/severe (+1.08%) NE- t-storms/severe (+0.91%) DFW- t-storms/severe (+0.64%) GREATEST DECREASES IN PERCENT SINCE LAST COO BRIEF SFO- wind (-0.93%) Chicago- snow (-0.90%) Chicago- wind (-0.66%)

ATFM Delay by Facility- FY2016 Largest Increases in Delay EWR-Wind & Visibility ZMA-Volume MSP-Visibility & Wind DCA-Visibility Largest Decreases in Delay ORD-Equipment PHL-Visibility & Snow/Ice JFK-Runway/Taxi BOS-Wind & Visibility Other Important Changes SFO -Increase in Wind delay -Decrease in Visibility delay LARGEST INCREASES IN DELAY -EWR 1) Wind- February, March, and April were worse this year compared to last year. 2) Visibility- February and May of this year were worse when compared to last year. -ZMA Volume- 12/26/2015 was a particularly bad day. Both December and January had increase delay for FY16 compared to FY15. -MSP 1) Visibility- December was worse this FY. So far, all months for MSP in FY16 have had higher visibility delays than their corresponding FY15 months. 2) Wind- December was worse this FY. -DCA Visibility- December and February worse in this FY. LARGEST DECREASES IN DELAY -ORD Equipment- fire greatly impacted the beginning of FY15 -PHL 1) Visibility- November and January main drivers of improvement. 2) Snow/Ice- January and March see improvement. -JFK Runway/Taxi- March, April, and May were better this year -BOS Wind & Visibility- improvement in several months, but mostly in October. SFO DELAY CANCELS OUT It is important to note that although SFO does not show a large change in the second graph, it had a significant shift in its charged delay. Comparing FY16 to May with FY15 to May, we see a large increase in wind delay (251,134 minutes) as well as a large decrease in visibility delay (-216,235 minutes). GREATEST INCREASES SINCE LAST COO BRIEF (1) LGA increased by 320,834 minutes, (2) SFO increased by 265,528 minutes, and (3) EWR increased by 177,812 minutes.

Total TMI Wind Delays FY2016 The top 5 airports highlighted in red constitute 89% of total TMI wind delays.

TMI Wind Delays - JFK Most wind delays occurred in October, December, March, and April

Linking Wind Conditions to Delay OPSNET and METAR data are showing similar patterns. However, not exactly matching. To be further examined by looking at different days Trajectory characteristics, arrival fix, runway used… etc.

Capacity Efficiency Calculating Demand Demand based on Filed Times or Empirically by a Best Achieved Trajectory Flight Demand is from Benchmark Arrival Time (un-impeded time) until Actual Arrival Time

Arrivals into JFK April 15, 2016 HR 19:00 -1959 40nm 40nm 13L, 22L - 30 Arrivals, TAER 100 22L, 22R - 39 Arrivals, TAER 88.64

Flight Efficiency KPI – EnRoute Actual vs. Flight Plan vs. Great Circle vs Best Achieved vs. Wind Optimal 40nm Actual Flt Plan 100nm

Impact of Special Activity Airspace

Impact of Weather March – 481 Flights 8.3 nm Excess Dist. June – 363 Flights 32.6 nm Excess Dist.

Performance Metrics Reporting Is the metric/process useful? Does it lead to improvements in the system? Data mining identifies specific scenarios for mitigation. Will decision makers trust what is presented? Weather, Airline Schedules, Airport Capacity What are similar days? Capabilities beyond local METAR ASPM like tables for Terminal/EnRoute ASPM like tables for Forecast Weather