FAA Air Traffic Organization (ATO)Weather and Operational Performance

Presented to:FPAW 2016 Summer Meeting

Presented by:John Gulding

Date:2 August 2016

2

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

• Low Visibility

• High wind• Convective weather

• Schedule Peaks

• Crew Scheduling

• Equip problems, etc.

• Airport Maintenance

• Airport Expansion

• ANSP Investment

• Traffic Management Initiatives

• Airspace Design

ATC/ATM performance

Capacity & Airport

Infrastructure

Weather

Operator Schedules &

Flight Preferences

New Technology

Schedule Delay

Other Drivers (SAA)

Metric Inter-Dependencies

4

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

5

ATFM Delay by Category - FY2016

6

ATFM Delay by Region - FY2016

7

ATFM Delay by Facility- FY2016

Largest Increases in DelayEWR-Wind & VisibilityZMA-VolumeMSP-Visibility & WindDCA-Visibility

Largest Decreases in DelayORD-EquipmentPHL-Visibility & Snow/IceJFK-Runway/TaxiBOS-Wind & Visibility

Other Important ChangesSFO-Increase in Wind delay-Decrease in Visibility delay

8

Total TMI Wind Delays FY2016

-

100,000

200,000

300,000

400,000

500,000

600,000SF

O

LGA

EWR

OR

D

JFK

LAS

MSP

DEN

BO

S

PH

L

IAH

MEM CLT

IAD

DC

A

LAX

SEA

DFW

DTW PH

X

SLC

De

lay

in M

inu

tes

Airport

TOTAL Delay (Core 30) FY2016

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

9

Most wind delays occurred in October, December, March, and April

-

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

01

-OC

T-1

5

02

-OC

T-1

5

04

-OC

T-1

5

18

-OC

T-1

5

23

-OC

T-1

5

28

-OC

T-1

5

10

-NO

V-1

5

12

-NO

V-1

5

13

-NO

V-1

5

14

-NO

V-1

5

18

-DEC

-15

22

-DEC

-15

27

-DEC

-15

29

-DEC

-15

12

-JA

N-1

6

11

-FEB

-16

13

-FEB

-16

16

-FEB

-16

14

-MA

R-1

6

17

-MA

R-1

6

18

-MA

R-1

6

24

-MA

R-1

6

28

-MA

R-1

6

29

-MA

R-1

6

31

-MA

R-1

6

01

-AP

R-1

6

03

-AP

R-1

6

07

-AP

R-1

6

08

-MA

Y-1

6

16

-MA

Y-1

6

De

lay

in M

inu

tes

Date

TMI wind delays (JFK) FY 2016

TMI Wind Delays - JFK

9

Wind42%

Low Ceilings

34%

Snow/Ice7%

Low Visibility

6%

Volume4%

Thunderstorms4%

Multi-taxi2%

Rwy Constructi

on1%

TMI Delays by cause (JFK)

10

Linking Wind Conditions to Delay

0

5

10

15

20

25

30

35

0

100

200

300

400

500

600

700

00:00 06:00 12:00 18:00 00:00 06:00

Win

d S

pe

ed

(K

no

ts)

TMI W

Ind

De

lay

(Min

ute

s)

Start Time (GMT)

TMI WIND DELAYS - JFK 28-Oct-2015

OPSNET_WIND_DELAYS METAR_WIND_SPEED

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 EfficiencyCalculating Demand

• Demand based on Filed Times or Empirically by a Best Achieved Trajectory

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37

Travel Time 40nm to Touchdown

Pe

rcen

tag

e

PHL Large Aircraft

Benchmark Time 13.6 Minutes

• Flight Demand is from Benchmark Arrival Time (un-impeded time) until Actual Arrival Time

12

JFK

Arrivals into JFKApril 30, 2016 HR 12:00 -1259 April 15, 2016 HR 19:00 -1959

13L, 22L - 30 Arrivals, TAER 100 22L, 22R - 39 Arrivals, TAER 88.64

40nm

JFK

40nm

Flight Efficiency KPI – EnRouteActual vs. Flight Plan vs. Great Circle vs Best Achieved vs. Wind Optimal

40nm

100nm

Actual

Flt Plan

14

Impact of Special Activity Airspace

15

March – 481 Flights8.3 nm Excess Dist.

June – 363 Flights32.6 nm Excess Dist.

Impact of Weather

16

Performance Metrics ReportingIs 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