South Africa Airside Capacity Enhancement Study for Air Traffic Navigation Services

P U B L I C V E R S I O N

Task 2 Report: Technical Analyses

Metron Aviation, Inc. 45300 Catalina Court, Suite 101 Dulles, VA 20166

4 March 2013

Mailing and Delivery Address: 1000 Wilson Boulevard, Suite 1600, Arlington, VA 22209-3901 Phone: 703–875–4357 • Fax: 703–875–4009 • Web site: www.ustda.gov

The U.S. Trade and Development Agency

The U.S. Trade and Development Agency helps companies create U.S. jobs through the export of U.S. goods and services for priority development projects in emerging economies. USTDA links U.S. businesses to export opportunities by funding project planning activities, pilot projects, and reverse trade missions while creating sustainable infrastructure and economic growth in partner countries.

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REVISION HISTORY

Internal Document Approval Date Modified By Section, Process # Version # Page(s) and Revision Text Revised History CPS-C011-0113 1.0 14 January 2013 Metron Aviation Initial delivered version

CPS-C011-0113 2.0 4 March 2013 Metron Aviation Revised

CPS-C011-0113 2.1 30 April 2013 Metron Aviation Minor revisions

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TABLE OF CONTENTS

1 INTRODUCTION ...... 1 1.1 PURPOSE ...... 1 1.2 ORGANISATION OF THE TECHNICAL REPORT ...... 1

2 AIRPORT OPERATIONAL CHARACTERISTICS ...... 3 2.1 FAOR ...... 3 2.2 FALE ...... 6 2.3 FACT ...... 8 2.4 COMMON OBSERVATIONS ...... 10

3 VALIDATION OF BASELINE OPERATIONAL CAPACITY ...... 11 3.1 INTEGRATED AIRPORT CAPACITY MODEL ...... 11 3.2 INPUT PARAMETERS ...... 11 3.2.1 Weather Data and Runway Configuration ...... 12 3.2.2 Operational Standards and Procedures ...... 12 3.2.3 Runway Occupancy Times and Approach Speeds ...... 13 3.2.4 Demand Fleet Mix ...... 15 3.3 RESULTS ...... 16 3.3.1 FAOR Capacity Validation ...... 16 3.3.2 FALE Capacity Validation ...... 17 3.3.3 FACT Capacity Validation ...... 18

4 CANDIDATE CAPACITY ENHANCEMENTS AFFECTING AIRSPACE AND OPERATIONS ...... 21 4.1 DATA LINK (PDC/DCL) ...... 21 4.2 DATA LINK (CPDLC) ...... 21 4.3 GROUND SURVEILLANCE – TAXIWAYS AND RUNWAYS ...... 21 4.4 GROUND SURVEILLANCE – RAMP AREAS AND APRONS ...... 22 4.5 WIDE AREA AND SATELLITE-BASED AUGMENTATION SYSTEM ...... 22 4.6 CAT III APPROACH CAPABILITY ...... 22 4.7 APPLY MINIMUM AUTHORISED SEPARATION ON FINAL ...... 23 4.8 REDUCE MINIMUM SEPARATION TO 3 NM ...... 23 4.9 READINESS FOR IMMINENT DEPARTURE (IMPROVED PILOT REACTION TIMES) ...... 23

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4.10 DEPARTURE SEQUENCING ...... 23 4.11 GROUPING BY WAKE TURBULENCE CATEGORY ...... 23 4.12 MULTIPLE DEPARTURE LINE-UP QUEUES ...... 24 4.13 MULTIPLE INTERMEDIATE DEPARTURE HOLDING POINTS ...... 24 4.14 STANDARD (CODED) TAXI ROUTES...... 24 4.15 PERFORMANCE-BASED STANDARD INSTRUMENT DEPARTURE...... 24 4.16 SPEED CONTROL ...... 24 4.17 ARRIVAL/DEPARTURE BALANCING ...... 25 4.18 PERFORMANCE-BASED NAVIGATION ...... 25 4.19 AIRSPACE REVIEW AND REDESIGN ...... 25 4.20 REVIEW LOW-VISIBILITY OPERATIONS ...... 25 4.21 DEDICATED APRON (RAMP) CONTROL...... 26 4.22 INTERSECTION DEPARTURES ...... 26 4.23 CONDITIONAL CLEARANCES ...... 26 4.24 LIMIT OPERATIONS DURING PEAK PERIODS ...... 26 4.25 LIMIT OPERATIONS OF NON-STANDARD PERFORMANCE ...... 26 4.26 SLOT OPTIMISATION ...... 27 4.27 CTOT COMPLIANCE ...... 27 4.28 TOWER COORDINATOR...... 27 4.29 TRAFFIC MANAGEMENT COORDINATION ...... 27

5 SPECIFIC AIRPORT INFRASTRUCTURE CAPACITY ENHANCEMENTS ...... 28 5.1 FAOR ...... 29 5.1.1 RETs to RWY03L/21R ...... 31 5.1.2 Refine Taxiway Echo for RWY 03R and add additional RET to RWY21L . 32 5.1.3 Extended Taxiway Pavement at the End of RWY03L ...... 35 5.2 FALE ...... 36 5.2.1 Add Parallel Taxiway Access ...... 39 5.2.2 Add RETs to RWY 24 for direct access Alpha & Bravo Apron Gates ...... 43 5.3 FACT ...... 43 5.3.1 By-Pass Taxiways at Runway Thresholds ...... 47 5.3.2 Refinements of Taxiways Charlie and Echo Fillets for Runway Exits ...... 49

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6 STAKEHOLDER DISCUSSION FRAMEWORK ...... 51 6.1 STAKEHOLDER ENGAGEMENT ...... 51 6.2 DIVERSE STAKEHOLDER INTERESTS ...... 52 6.3 STAKEHOLDER MATERIAL ...... 52 6.3.1 Capacity Enhancements with CAPEX under R20 Million ...... 53 6.3.2 Capacity Enhancements with CAPEX over R20 Million ...... 54 6.4 SUMMARY ...... 54

7 CONCLUSIONS AND NEXT STEPS...... 55 7.1 CONCLUSIONS OF FAOR, FALE, AND FACT BASELINE OPERATIONAL CAPACITY VALIDATION ...... 55 7.2 CONCLUSIONS OF AIRSPACE AND OPERATIONAL CAPACITY ENHANCEMENTS ...... 56 7.3 CONCLUSIONS OF SPECIFIC AIRPORT INFRASTRUCTURE CAPACITY ENHANCEMENTS . 57 7.4 RECOMMENDED ENHANCEMENTS ...... 57 7.5 NEXT STEPS ...... 59

APPENDIX A BACKGROUND INFORMATION ON IACM DEVELOPMENT ...... 61 A.1. AIRPORT CAPACITY ...... 61 A.1.1 Definition of airport capacity ...... 61 A.1.2 Airport capacity estimation ...... 62 a) FAA Airfield Capacity Model ...... 63 b) Boeing Airport Capacity Constraints Model ...... 65 c) LMI Airport Capacity Model ...... 65 d) MACAD models ...... 67 A.2. WEATHER DATA ...... 68 A.2.1 Corridor Integrated Weather System ...... 68 A.2.2 Rapid Update Cycle ...... 68

APPENDIX B INTEGRATED AIRPORT CAPACITY MODEL ...... 69 B.1. OVERVIEW ...... 69 B.2. MAJOR INPUTS AND OUTPUTS ...... 70 B.2.1 Real-time inputs ...... 70 B.2.2 Pre-processed inputs ...... 71 a) Airport layouts and geometries ...... 71 b) Operational standards and procedures ...... 72 c) Weather forecast prediction error models ...... 72 d) Airport runway configurations ...... 73

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e) Runway occupancy times and approach speeds ...... 74 B.2.3 Outputs ...... 75 B.3. COMPONENTS ...... 75 B.3.1 Terminal Capacity Model ...... 75 B.3.2 Airfield Capacity Model ...... 77 a) Runway Configuration Estimator ...... 78 b) Runway Capacity Model ...... 79 B.3.3 Multi-Criteria Capacity Forecast Integrator ...... 80

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LIST OF TABLES

Table 1: Aircraft Aerodrome Design Codes (Wingspans in m) ...... 7 Table 2: Standard Aircraft Separation Minima on Arrival in NM ...... 12 Table 3: Standard Departure Separation Minima in Minutes ...... 13 Table 4: ROT Statistics for Arrivals in Seconds ...... 14 Table 5: ROT Statistics for Departures in Seconds ...... 14 Table 6: Runway Crossing Speeds in Knots...... 14 Table 7: Fleet Mix Proportions by Airport ...... 15 Table 8: Airside Capacity Enhancement Stakeholder Engagement Material ...... 53 Table 9: Recommended Enhancements ...... 58

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LIST OF FIGURES

Figure 1: Fleet Mix Charts by Airport ...... 15 Figure 2: FAOR Declared Capacity, Analytic Capacity, and Historical Demand ...... 17 Figure 3: FALE Declared Capacity, Analytic Capacity, and Historical Demand ...... 18 Figure 4: FACT Declared Capacity, Analytic Capacity, and Historical Demand ...... 19 Figure 5: FAOR Airport Layout Issues ...... 29 Figure 6: FAOR Master Plan for 55 MAP Capacity Level ...... 30 Figure 7: FAOR Near-Term Airfield Improvements ...... 31 Figure 8: RETs for RWY03L/21R ...... 32 Figure 9: FAOR Master Plan for 03R/21L at 55 MAP Capacity Level ...... 32 Figure 10: Refine Taxiway Echo for RWY 03R and add additional RET to RWY21L .... 32 Figure 11: FAOR Existing Taxiway Echo at RWY 03R/21L ...... 33 Figure 12: FAOR Proposed Taxiway Echo RET for 03R ...... 33 Figure 13: FAOR Change From Master Plan for Taxiway RE ...... 34 Figure 14: FAOR Add Master Plan RET for RWY 21L ...... 34 Figure 15: FAOR Taxiway Extension at RWY03L ...... 35 Figure 16: FAOR Aircraft Taxi Flows with Taxiway Extension at RWY03L ...... 35 Figure 17: FALE Airport Layout Issues ...... 37 Figure 18: FALE Airside Improvements ...... 38 Figure 19: FALE Master Plan with Overlay of Potential Airside Improvements ...... 39 Figure 20: FALE Additional Parallel Taxiways ...... 40 Figure 21: FALE North Flow Operations ...... 40 Figure 22: FALE Extension of Taxiway Golf ...... 41 Figure 23: FALE North flow Extension of Taxiway Golf & Taxiway Bravo ...... 41 Figure 24: FALE South flow Extension of Taxiway Golf & Taxiway Bravo ...... 42 Figure 25: FALE Existing South Flow Operations ...... 42 Figure 26: FALE Proposed RETs ...... 43 Figure 27: FACT Airport Layout Issues ...... 44 Figure 28: FACT Ultimate Master Plan Overlay ...... 45 Figure 29: FACT Master Plan Ultimate Apron area and Phase 1 Airfield Overlay ...... 46

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Figure 30: FACT with Potential Near-Term Improvements ...... 47 Figure 31: FACT By-Pass Taxiway RWY01/19 ...... 48 Figure 32: FACT North Flow Operations with By-Pass Taxiways ...... 48 Figure 33: FACT South Flow Operations with By-Pass Taxiways ...... 49 Figure 34: FACT Addition of RETs ...... 50 Figure 35: YMML Airport RETs, Parallel Taxiways and Extensions ...... 50 Figure 36: General form of arrival/departure capacity curve ...... 62 Figure 37: Shape of arrival and departure capacity curve for the FAA Airfield Capacity Model ...... 64 Figure 38: Shape of arrival and departure capacity curve for the LMI Airport Capacity Model ...... 66 Figure 39: Major IACM components and its inputs ...... 69 Figure 40: Primary IACM inputs and outputs ...... 70 Figure 41: Types of airport layout and geometry inputs ...... 71 Figure 42: Types of operational standards and procedures inputs ...... 72 Figure 43: Sources of data considered for determining sets of historical runway configurations ...... 73 Figure 44: Runway occupancy times and approach speed inputs ...... 75 Figure 45: Climb and descent profiles are considered by TCM when determining airspace blockages or “no fly” zones induced by the WAAF within the terminal airspace ...... 76 Figure 46: TCM identifies open fixes based on those where the available air lane width computed from the mincut exceeds 8 nm ...... 76 Figure 47: TCM prototype display showing predicted fix availability during 5-minute forecast increments ...... 77 Figure 48: Major elements of the Airfield Capacity Model ...... 78 Figure 49: MCFI integrates probabilistic capacity estimates produced by TCM and ACM into an overall probabilistic airport capacity forecast ...... 81

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ACKNOWLEDGEMENTS

The Metron Aviation Team wishes to thank all of the dedicated men and women at the Air Traffic and Navigation Services Company of South Africa and the Airports Company of South Africa for the time and effort provided in support of this effort.

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LIST OF ACRONYMS

AAR ...... Airport Arrival Rate AASA ...... Airlines Association of Southern Africa ACSA ...... Airports Company South Africa ADR ...... Airport Departure Rate ADS-B ...... Automatic Dependent Surveillance Broadcast AFT ...... Airport Flow Tool ALPA-SA ...... Air Line Pilots’ Association South Africa ANSP ...... Air Navigation Service Provider A-SMGCS ...... Advanced Surface Movement Guidance & Control System ATC ...... Air Traffic Control ATCT ...... Air Traffic Control Tower ATNS ...... Air Traffic Navigation Services CAA ...... Civil Aviation Authority CAMU ...... Central Airspace Management Unit CAPEX ...... Capital Expenditure CAT ...... ILS Category CPDLC ...... Controller-Pilot Data Link Communications CTOT ...... Calculated Take-off Time DCL ...... Departure Clearance DH ...... Decision Height EGNOS ...... European Geostationary Navigation Overlay Service FAA ...... Federal Aviation Administration FACT ...... Cape Town International Airport FAOR ...... OR Tambo International Airport FALA ...... Lanseria Airport FAPM ...... Pietermaritzburg Airport FALE ...... King Shaka International Airport

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FAVG ...... Virginia Airport FAYP ...... Ysterplaat Airport FBO ...... Fixed-base Operator FL ...... Flight Level GA ...... General Aviation GSE ...... Ground Service Equipment IACM ...... Integrated Airport Capacity Model ICAO ...... International Civil Aviation Organisation IFR ...... Instrument Flight Rules ILS ...... Instrument Landing System KBOS ...... Edward Lawrence Logan International Airport KIAD ...... Dulles International Airport KJFK ...... John F. Kennedy International Airport KLGA ...... LaGuardia Airport LVO ...... Low Visibility Operations MAP ...... Million Annual Passengers MARS ...... Multiple Aircraft Ramp Stands NASA ...... National Aeronautics and Space Administration NM ...... Nautical Mile NZAA ...... Auckland International Airport NZSX ...... Auckland International Airport Limited PBN ...... Performance Based Navigation PDC ...... Pre-Departure Clearance TFM ...... Traffic Flow Management TMA ...... Terminal Control Area R ...... South African Rand RNAV ...... Area Navigation ROT ...... Runway Occupancy Time RVR ...... Runway Visual Range

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RWY ...... Runway SBAS ...... Satellite Based Augmentation System SID ...... Standard Instrument Departure SSI ...... Station Standing Instructions STAR ...... Standard Terminal Arrival Route TMA ...... Terminal Control Area TMI ...... Traffic Management Initiative USTDA ...... U.S. Trade and Development Agency VFR ...... Visual Flight Rules VMC ...... Visual Meteorological Conditions WAAS ...... Wide Area Augmentation System YMML ...... Melbourne Airport ZGSZ ...... Shenzhen Bao’An International Airport

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1 Introduction

1.1 Purpose Air Traffic and Navigation Services (ATNS) and Airports Company South Africa (ACSA) have engaged Metron Aviation, Landrum & Brown, and ACA Associates to conduct a South Africa Airside Capacity Enhancement Study (SA ACES). The purpose of the study is to identify and validate capacity-enhancing technologies and procedural improvements that lead to reduced delays and increased efficiency and safety of air traffic movements at the O.R. Tambo International Airport (FAOR), King Shaka International Airport (FALE), and Cape Town International Airport (FACT). This study is funded by the U.S. Trade and Development Agency (USTDA).

A primary part of the technical analysis is to analyse the baseline airside infrastructure, facilities, technologies, operations, and procedures at each airport and assess their baseline capacities. An additional requirement of this report is to detail potential airside capacity enhancements or procedures that potentially reduce delay or increase efficiency. The study team was provided an initial list of candidate enhancements and airport Master Plans by ATNS and ACSA, which were used to develop Sections 4 and 5 of this document. 1,2,3,4

1.2 Organisation of the Technical Report This document is organised as follows:

• Section 2 covers the existing conditions at each airport through a summary of the information recorded in the SA ACES Task 1 Report.5

• Section 3 provides an independent analytic validation of the baseline operational capacities for each airport. The validation includes a description of the methodology, the baseline data used to derive the analytic capacity, and results on the impact of the data on the capacity model.

• Section 4 describes general airspace and air traffic management operational improvements suggested in the candidate airside capacity enhancements document. This section provides information about technical challenges and dependencies for full deployment of the candidate enhancements as well as real-world examples where applicable.

1 “Airside Capacity Enhancement Initiatives – Operations Draft,” working version developed by ATNS and ACSA. 2 “O.R. Tambo International Airport – Master Plan Update,” October 2006. 3 “King Shaka International Airport – Master Plan Update,” August 2011. 4 “Cape Town International Airport – Master Plan,” November 2007. 5 “South Africa Airside Capacity Enhancement Study for Air Traffic Navigation Services, Task 1 Report: Kickoff Meeting, Work Plan, Document Review, Site Visits,” report to USTDA, ATNS, and ACSA, December 2012.

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• Section 5 contains specific airport infrastructure improvements that are consistent with each airport’s Master Plan, and in collaboration with the airspace and ATC initiatives, offer the potential to increase capacity. This section details the advantages of airport capacity enhancements and provides real-world examples of such improvements where applicable.

• Section 6 includes an initial framework for stakeholder discussion of cost/benefit indicators. The purpose of the section is to identify those stakeholders whose support is needed for the capacity enhancements, and provides a basis for the cost-benefit rationale for each enhancement from those stakeholders’ perspectives.

• Finally, Section 7 summarises the conclusions based on the analysis done in Sections 3–5. This section provides information about the validated baseline capacities and their major contributors, suggests which enhancements may offer potential to increase capacity, and provides a final list of recommended capacity enhancements.

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2 Airport Operational Characteristics The SA ACES Task 1 report summarised the findings from the study kick-off meeting and airport site visits with ATNS and ACSA personnel in South Africa. The Task 1 report presented an overview of airside operations at FAOR, FALE, and FACT, which includes the recognition of operational issues that affect demand, and airport and airspace capacity. The observed operational characteristics are presented in this section and referenced in the subsequent analyses sections (3–5) of this report.

2.1 FAOR FAOR is the busiest airport in Africa. FAOR’s airspace challenges are characterised by a variety of factors: additional demand from satellite airports (e.g., Lanseria International Airport), military restrictions on the use of the airspace, a fleet mix representing a wide variety of wake categories, the need to share the airspace with recreational users, lack of situational awareness of the airspace of neighbouring countries, capacity management practices, lack of collaboration, and human resource shortages. FAOR airport operations are primarily impacted by the runway layout and location of the airport terminal complex. The following subsections summarise the observed FAOR airspace and airside shortfalls.

Terminal Area Operations affecting FAOR The FAOR Terminal Control Area (TMA) services FAOR and several satellite aerodromes. Specifically, demand from Lanseria International Airport (FALA) impacts the efficiency of the FAOR TMA due to the use of procedural separation of traffic routing into FALA by air traffic control (ATC). It is common to have separations into FALA increase from a common 10 nm (ten nautical miles), which is roughly three minutes, into a separation requiring ten minutes (or more) between arriving flights when aircraft must execute an instrument approach. The resulting congestion is managed by placing FALA-bound traffic into holding patterns, restricting departures out of FALA and other satellite aerodromes, or by reducing the FAOR Airport Arrival Rate (AAR) or Airport Departure Rate (ADR) to a level that allows relief from the airborne congestion. In general, effective terminal area airspace operations are characterized by the ability to maintain a capacity that is equal to or greater than the sum of the capacities of airports below the TMA. Therefore, a Traffic Management Initiative (TMI) has recently been implemented for arriving traffic at FALA in the afternoons which has been successful in flowing traffic into FALA thus reducing the demand placed on the FAOR TMA.

Noise abatement procedures require aircraft departing RWY03L/21R to fly on runway heading for a distance of 4 nm and 8 nm (due to the proximity of Rand Airport in the case of RWY21R departures), respectively. Traffic may only turn off the standard instrument departure (SID) once they have passed through flight level (FL) 85 during the day and FL 100 at night. This limits the departure efficiency, as a fast aircraft following a slow aircraft is delayed by up to 5 minutes to effect the correct separation.

Finally, military airport and airspace restrictions, parachute drop zones, instrument flight rules (IFR) traffic into and out of procedural environments, active gliding areas, aerobatic airspace, aerial surveys, aircraft mix, fog conditions, and conservative low visibility procedures add to the complexity of the FAOR TMA.

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TMA Radar Separations

The lateral separation standards in the FAOR TMA require explanation. The standard lateral radar separation between aircraft flying in the FAOR TMA is 3NM; however, other separation criteria are applied when aircraft are on final approach. Separation could be determined by the wake turbulence category of the aircraft; for example, a light or medium aircraft must be separated by 5NM behind a heavy when on final approach. In addition, Runway Occupancy Times (ROT) and allowing for departure spacing could determine that the separation on final approach is greater than 3NM.

Current capacity management practices Every flight either departing or arriving at FAOR is managed by the issuance of a Calculated Take-off Time (CTOT) to manage demand and capacity. This is done via Traffic Management Initiatives (TMI) on a 24-hour basis by the Central Airspace Management Unit (CAMU). There is a lack of common understanding by stakeholders regarding slot allocation procedures, for both airport and ATC slots. It was learned that schedule times are occasionally incompatible with the issued airport slot. This happens when the aircraft operator does not acquire the required airport slot and continues to operate at the originally- scheduled time, or when the agreed upon slot is not reconciled with the schedule or departure time. The Metron Aviation Airspace Flow Tool (AFT) schedule does not take into account the necessary wake turbulence separation requirements between successive departures. Lastly, Maestro, the arrival management tool used by ATC, is not integrated with AFT arrival times, nor are the AFT arrival times reflected in Maestro.

Fleet mix operational challenges There is a high level of mixed aircraft type operations, the majority of which are Medium-wake category aircraft. The airport operations also consist of Light and Heavy aircraft operating at the airport, including three Airbus A380s daily. General Aviation (GA) traffic adds to the FAOR airspace congestion. This combination of aircraft types poses separation and sequencing challenges for ATC.

Fleet equipage and procedures More precise routing into and out of FAOR will enable the use of dual independent approaches to the parallel runways. This will increase arrival capacity when there is a lull in departures. Equipping aircraft such that they are capable of performing area navigation (RNAV) and Performance-Based Navigation (PBN) procedures will require the development of new procedures and additional training for dual runway operations, and missed and staggered approaches.

Staffing constraints Staffing constraints at FAOR Air Traffic Control Centre (ATCC) include assigning one controller per sector and combining sectors during staffing shortages; both lead to increased workload or less efficient operations. Many of the experienced ATCC staff leaves South Africa to pursue other careers elsewhere. Overall, there is a lack of supervisory staff available. The presence of a supervisory staff could provide situational awareness between all sectors in the FAOR ATCC and adjoining ATCC, enabling better system-wide decision-making, particularly with regard to demand and capacity balancing and liaison with the CAMU.

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Lack of collaboration The ATCC lacks a permanent tactical flow management position (this could be a supervisory position), coordination plan, or proper facility available to liaison with the CAMU. This shortfall is exacerbated by the lack of staff with flow management experience available to fill these roles. This limits the available set of TMIs that can be safely implemented or changed, decreases traffic management consistency, and increases workload.

Lack of shared radar data between bordering nations South Africa does not have shared radar connectivity with its adjoining states, so there is little or no radar notice of flights arriving in South African airspace and flight plans often are not received for the incoming flights.

Runway use/Procedures Aircraft primarily arrive on RWY03R/21L and depart RWY03L/21R. Aircraft landing on RWY03R/21L must cross the inboard runway to reach the terminal area making it difficult to maintain consistent in-trail separation minima, as the ATC must supply spacing to allow traffic to cross RWY03L/21R. This also leads to long taxi times and increased fuel burn and emissions. The use of RWY03L/21R for arrivals is reserved for exceptional cases according to Station Standing Instructions (SSI). There is also a lack of a dedicated airspace arrival route to RWY03L/21R, which limits the efficiency of aircraft assignments to the inboard runway from the arrival fix. It is important to note that these issues are present during north and south flow operations, but the impacts are different due to the airfield geometry and airspace considerations.

North Flow Operations During north flow operations, the lack of adequate taxiway infrastructure near the threshold of RWY03L limits the ability of ATC to optimise the sequence of departures. The lack of a runway end hold pad reduces flexibility and makes it difficult for ATC to alternate east bound and west bound aircraft in the departure queue, and, as a result, optimal performance is difficult to achieve. Intersection departures could improve this performance; however, ATC cannot instruct a pilot to do so, as they are executed at the discretion of the pilot. Reduced power take-offs reduce the need for potential intersection departures, but require full runway length and increase ROTs. However, they have the added benefits of fuel savings for the flight operator and reduced emissions for all stakeholders.

Runway Crossing Procedures ATC regularly stages aircraft arriving on RWY03R on taxiways Juliet, Lima, and Echo for RWY03L crossing. However, congestion on taxiway Alpha and potential interference with the RWY03L departure queue further limits the efficiency of the runway crossing procedures. Furthermore, the single parallel taxiway Alpha also limits the use of the inboard RWY03L for arrivals, because arrivals on RWY03L would experience head-to-head operations with aircraft pushing back from the remote stands.

South Flow Operations The single parallel taxiway Alpha and the lack of a pushback zone for aircraft using the remote stands for both cargo and passenger operations influences the efficiency of operations when wind direction requires the use of RWY21L and RWY21R.

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Rapid Exit Taxiways Given the current fleet mix and operational procedures, the current locations of Rapid Exit Taxiways (RET) on the arrival runways are not conducive to minimising ROTs. Other factors, such as RET location, congestion on the parallel taxiways, location of the assigned gate, aircraft fleet mix, temperature, elevation of airfield (high approach speeds), and performance capability, also influence actual ROTs.

2.2 FALE FALE is characterised by high tourist traffic and some cargo operations. FALE has distinct challenges: capacity management practices, training and Visual Flight Rules (VFR) operations at nearby Virginia Airport (FAVG), fleet mix, and the notorious “hot spot” located at the intersections of taxiways Golf, Alpha, and November, which leads to increased taxi times during periods of peak demand. South flow operations at FALE result in long taxi times for departing aircraft due to the southern location of the terminal building. However, north flow operations result in long taxi times for arrival aircraft. Additional inefficiencies can result from single-access taxiways. The lack of GA facilities, especially in the occurrence of unscheduled flights (as FALE is the designated Port of Entry for the region) does lead to inefficiencies. Although too infrequent to require facilities changes, during major events, special procedures would need to address these issues. The following subsections summarise the observed FALE airspace and airside shortfalls.

Current capacity management practices Every flight either departing or arriving at FALE is controlled by an AFT-assigned CTOT. The AFT assigns runway usage times for departures in chronological order based on the schedule, should there be no constraint in effect. This creates three issues. (1) The CTOT is sometimes not the same as the issued airport slot, this is standard practice as there could be more than one slot allocated at the same time whereas the AFT will not allocate slots at the same time. A another reason could be as a result of the aircraft operators not filing flight plans with an ETD the same as the airport slot – compliance in this instance should be carried out. (2) The AFT does not take into account the necessary separation requirements between successive departures. There is no capability within the AFT (or any other air traffic flow management (ATFM) tool with similar capabilities.) This is normally managed by tactical manipulation of the departure sequence. (3) The CTOT is applied to flights when demand is significantly lower than capacity, which in some cases, produces unnecessary delays for flights departing from FALE and arriving at airports that do not have a TMI in place. It is recommended that flights departing from FALE to airfields without a TMI in place should not be required to be CTOT compliant. Unnecessary delay could be incurred as a result of flights departing from FALE to airfields where no TMI is in force and by ATC insisting aircraft comply with CTOTs.

Fleet mix operational challenges The aircraft mix at FALE poses sequencing challenges for ATC. The majority of IFR aircraft are Medium-wake category aircraft, commuter and business jets, and a small amount of heavy airframes.

Operations affecting FALE VFR GA flights and flight school traffic operating into and out of FAVG can affect the capacity of FALE because IFR flights into FAVG are required to complete Instrument Landing System (ILS) approaches at FALE with a “break off” for visual positioning into FAVG. There are no instrument arrival facilities or procedures for traffic arriving at FAVG. Most flights departing and arriving FAVG must communicate

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6 with FALE ATC adding to workload. Pietermaritzburg Airport (FAPM) traffic and parachuting activities further add to the complexity of the FALE TMA. The close proximity of Richards Bay Airport airspace is also a contributing factor.

Hot Spot The most significant airport operational issue is the “hot spot” at the intersection of taxiways Golf, Alpha and November. During south flow operations, departing aircraft must hold on taxiway Bravo when aircraft are landing on RWY24 until the arrival clears the runway exit at Golf onto Alpha. Once the arrival aircraft clears the exit, then the departing aircraft can proceed northbound on Alpha. This can add 3–4 minutes to a flight’s taxi time.

South and North Flow Operations FALE’s south flow operations lead to long taxi times for departing aircraft due to the location of the terminal at the south end of the runway, although most Code C and smaller aircraft can opt for intersection departures (at the discretion of the pilot). Additionally, aircraft held on Alpha awaiting departure clearance block other aircraft taxiing on Alpha, which impacts capacity during peak hours. Conversely, north flow operations result in long arrival taxi times. The lack of departure end hold pads at the runway thresholds makes it difficult for ATC to optimise the departure queue. Lastly, the distance between the ILS category (CAT) I hold line and the runway threshold leads to longer taxi times and unnecessary delays.

One Way In/One Way Out Aprons Several apron areas at FALE are accessed by a single taxiway, thereby resulting in the potential for head- to-head operations.

Code F Operations FALE is a Code F reliever airport with two designated aprons with a total of four Code F parking positions. Although not an issue with current fleet mix and activity levels, this could become a shortfall in the future should the activity shift to include more large aircraft. Code F aircraft are large planes with wingspans between 65 m and 80 m as shown in Table 1.6

Table 1: Aircraft Aerodrome Design Codes (Wingspans in m)

Aerodrome Code Wingspan A < 15

B 15 – 24

C 24 – 36

D 36 – 52

E 52 – 65

F 65 – 80

6 International Civil Aviation Organization, “Aerodrome Design Manual, Third Edition, 2006.

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GA Activity FALE has limited GA facilities and lacks a substantial Fixed-Base Operator (FBO). As FALE is a designated Port of Entry, it must also accommodate international GA arrivals to allow passengers to clear immigration and customs and then proceed to their destination airport.

Major Events During major events, FALE lacks apron space to accommodate the influx of charter aircraft operations. The aircraft are often required to drop off passengers then fly out without passengers to be parked at another airport until returning to collect their passengers. This effectively creates two arrival and two departures for a single flight, thereby placing additional pressure on FALE ATC and airport resources. Although too infrequent to require facilities changes, during major events, special operational procedures would need to be applied as needed to address these issues.

2.3 FACT FACT is the second largest and busiest airport in South Africa, and the third busiest in Africa. FACT is characterised by high GA demand (both VFR and IFR) and a mixed fleet with high sequencing complexity for ATC. The airspace is further constrained by mountainous terrain and military airspace. As capacity increases, the single taxi-lane layout, sub-optimal number and layout of RETs, and the lack of arrival and departure holding pads lead to increased ROTs, taxi times, and arrival and departure delays. Finally, hot spots, line-of site issues, gate allocation issues, and the amount of and location of airside real estate afforded to unscheduled aircraft may lead to increased delays and reduced operational efficiency.

Current capacity management practices FACT demand and capacity of scheduled and flight-planned activity is managed by the issuance of CTOTs by the AFT at the CAMU. The requirement to strictly comply with CTOTs can limit the controllers’ ability to tactically manage their traffic for efficient departure flows. More attention is being applied by the controllers to adhere to CTOTs rather than to tactically optimize departure flows. Unnecessary delay could be incurred as a result of flights departing from FACT to airfields where no TMI is in force and by ATC insisting aircraft comply with CTOTs.

Fleet mix operational challenges The variable fleet mix and the inconsistent application of PBN approaches pose sequencing challenges for ATC. FACT services the majority of the region’s GA traffic, which contributes to the fleet mixture and complicates separation and sequencing by ATC.

Mountainous Terrain The mountainous terrain limits the available airspace to use more precision approaches, facilitate and utilise direct routings for RNAV-equipped aircraft, and the development of SID and standard terminal arrival route (STAR) designs. Even the application of PBN will not fully solve this issue as the physical obstructions will still exist.

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Military airspace The Ysterplaat (FAYP) military facility further constrains the amount of civilian airspace available for sequencing traffic. All traffic arriving and departing from FAYP are managed by FACT terminal control. In IFR conditions, they are required to carry out instrument approaches at FACT with a “breakoff” to FAYP. Additionally, sections of FACT airspace are used to conduct naval firing and maneuvers.

VFR traffic VFR flights that do not file a flight plan are not factored into capacity and demand management via AFT, which could result in over-prescription of demand into the TMA and airport. This leads to increased holding and ground delays for flights into and out of FACT.

Single Taxi-lane for A, B, and C Aprons An increase in FACT activity and higher levels of delay are expected to occur as a result of the use of the single taxi lane as a substitute for a parallel taxiway to RWY01/19 through the A, B, and C aprons.

Rapid Exit Taxiways The lack of RETs and the sub-optimal location and number of taxiways on RWY01/19 result in longer than average runway occupancy and taxi times.

Arrival and Departure Holding Pads There is currently insufficient space within the airside boundary fence, directly parallel and adjacent to the RWY01/19 thresholds, for holding pads or by-pass taxiways parallel to the runway thresholds. This physically limits aircraft movement on the airport’s surface.7

Interactions with GA Activity There are four registered training schools within the FACT GA apron. This creates additional interaction between GA and commercial activity.

Airfield Hot Spots There are six hot spots on the FACT airfield. Two of these hot spots are the result of line-of-sight conflicts from the air traffic control tower (ATCT), while others relate to hold points and crossing conflicts. The interaction between taxiing aircraft and aircraft pushing back is a cause of delay and congestion in this area.

Line-of-site Issues The thresholds of RWY16 near taxiway Alpha, and the intersection of taxiways Charlie and Bravo, are two areas that are not directly visible from the ATCT. Special procedures are applied, and pilots are advised to exercise extreme caution in these areas.

7 Code E-capable bypass would require a minimum of 126 meters from the center line of the taxiway to the perimeter fence (80 m from centerline taxiway to centerline holdpad taxiway + 42.5m to ASR+ 3.5m for width of ASR). At RWY01 the available distance from centerline to perimeter fence is 74m to 108m. At RWY19, RWY16/34 would need to be decommissioned or crossings enabled to provide, a taxiway parallel to either runway 19 or parallel to taxiway A2.

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Intersection Departures Intersection departures on RWY 01/19 are used to reduce taxi times and distances.

CAT I/II Hold Lines As with FALE, the location of the ILS CAT II holding lines lead to less efficient performance and less flexibility for ATC.

Aircraft Gate Limitations The number and the size of aircraft parking positions throughout FACT will present additional constraints as activity increases. Additionally, gate dwell time constraints, limited parking, and limited Ground Service Equipment (GSE) staging will become constrained as demand increases.

2.4 Common Observations There are two common challenges that were identified in site visits to all three regions:

The first challenge is capacity management. Observations revealed the need to reassess how Airspace Flow Programmes (AFP) are applied as a fix for airport demand, for example instituting an AFP in the FAOR TMA because of demand at FALA. Additionally, the AFT does not take into account wake turbulence separation requirements between successive departures.

Secondly, miscommunication between CAMU and the facilities limits the effectiveness of TMIs, or results in the use of a TMI when it is not necessary. The lack of training on ATFM and Collaborative Decision Making (CDM), and additional staff to help facilitate capacity management activities, limits operational efficiency.

Lastly, technical staff at all three facilities are faced with similar challenges: airfield maintenance interferes with ILS operations; equipment is located in remote areas with less than adequate means of access; traffic levels impact the ability to conduct equipment calibration with regular frequency; there is a need for a more collaborative working relationship between ATNS and ACSA; and technicians do not have quick access to the airfield in normal or emergency situations.

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3 Validation of Baseline Operational Capacity In order to analyse and interpret the capacity enhancements proposed for any of the three study airports, an understanding of the operational bottlenecks associated with the airports’ throughput was required. As described in Section 2, each airport has unique operating characteristics. This section describes the methodology used to determine if the current declared capacity at each airport represents a reasonable physical capacity based on the operational characteristics.

3.1 Integrated Airport Capacity Model The Integrated Airport Capacity Model (IACM) is an analytical airport capacity model designed by Metron Aviation, Inc. to provide decision support for U.S. traffic flow management (TFM) planning.8 It considers the impact of both terminal airspace and runway system constraints on airport capacity, IACM and its input parameters are described in Appendix A and Appendix B. The inputs to IACM are airport layouts and geometries, airport runway configurations, weather forecasts, operational standards and procedures, runway occupancy times and approach speeds, and demand (considering fleet mix). IACM uses analytical models to produce three types of outputs for each combination of input parameters:

• Capacity optimised for arrivals

• Capacity optimised departures

• Capacity for alternating arrivals and departures

Depending on the demand profile (e.g., arrival push, departure push, or mix of arrival and departures), fleet mix, and other possible factors, decision-makers can use IACM to compute maximum achievable airport capacity.

IACM was selected to validate the study airports’ capacities due to its ease of use and configuration, fast- time simulation capabilities, and its continued validation through Federal Aviation Administration (FAA) and National Aeronautics and Space Administration (NASA) projects.9,10

3.2 Input Parameters To validate the capacity at the study airports, the parameters and measures from South African operational data were used as input to IACM. The SSI was obtained from ATNS for access to separation and spacing requirements in order to adjust the model to represent operations at the study airports, and ten years of fleet demand data for each airport was obtained from ACSA. However, not all data was available and

8 Kicinger, R., Cross, C., Myers, T., Krozel, J., Mauro, C., Kierstead, D., “Probabilistic Airport Capacity Prediction Incorporating the Impact on Terminal Weather,” 8th International American Institute of Aeronautics and Astronautics (AIAA) Guidance, Navigation, and Control Conference (GNC). Portland, Oregon, USA, August 2011. 9 Kicinger, R., Mauro, C., Cross, C., Myers, T., Kierstead, D., Kumar, V., Sherry, L., “Integrated Airport Capacity Model Final Report,” Final report to the FAA, December 2009. 10 Kicinger, R., Krozel, J., Steiner, M., Pinto, J.O., “Airport Capacity Prediction Integrating Ensemble Weather Forecasts,” Infotech@Aerospace 2012 Conference, American Institute of Aeronautics and Astronautics, Garden Grove, CA, USA, June 2012.

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11 those instances in which there was no representative data, its value was estimated using the method described in section 3.2.3.

3.2.1 Weather Data and Runway Configuration For the purposes of adapting IACM to validate the baseline capacity of the study airports, information applying to Visual Meteorological Conditions (VMC) is only considered, and the runway configurations of each of the airports was limited to either a “north” or “south” flow. The design criteria for this report are for full arrival and departure operations. Capacity may be reduced during low visibility conditions.

3.2.2 Operational Standards and Procedures Operational standards and procedures define constraints on minimum aircraft separation in the terminal airspace and along the common approach path. They also define required ceiling and visibility minima for the flight rules in which an airport operates, e.g., VFR and IFR, and maximum crosswind and tailwind thresholds for using airport runways. Each airport’s operating standards and procedures are contained in its SSI.11,12,13,14 These SSIs provide the requirements for spacing on final approach, and time sequencing between successive departures that are used by IACM.

The standard minimum wake vortex separations were gathered from each airport’s SSI. There exists a standard 5 nm separation between successive arrivals (see Table 2). Both the FAOR and the FACT SSI explicitly state that Light or Medium aircraft following a Heavy need an increased separation of 6 nm; this was not found in the FALE SSI. Furthermore, some SSIs contained airport-specific arrival separation requirements following specific aircraft types.

Table 2: Standard Aircraft Separation Minima on Arrival in NM

Leading Aircraft Following Aircraft FAOR FALE FACT Heavy Heavy 6 5 6

Heavy Medium 6 5 6

Heavy Light 6 5 6

Medium Heavy 5 5 5

Medium Medium 5 5 5

Medium Light 5 5 5

Light Heavy 5 5 5

Light Medium 5 5 5

Light Light 5 5 5

11 Station Standing Instructions for Johannesburg Radar, prepared by ATNS, September 2010. 12 Station Standing Instructions for King Shaka International, prepared by ATNS, October 2012. 13 Station Standing Instructions for Cape Town, prepared by ATNS, September 2011. 14 Station Standing Instructions for Central Airspace Management Unit, prepared by ATNS, September 2011.

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In addition to the standard requirements in the SSIs, some airports have aircraft-specific separation minima. Two examples of those requirements are as follows:

• At FACT, any aircraft following a Boeing-747 must be spaced 10 nm behind the Boeing-747. The FACT SSI specifically states that separation increases following a Boeing-747.

• Flights arriving at FAOR following Super Heavy aircraft (e.g., Airbus A380) must increase their separation to 6 nm if it is a Heavy aircraft, 7 nm if it is a Medium aircraft, and 8 nm if it is a Light aircraft; this is consistent with ICAO standards.

These more specific separation details will be used to adjust the overall separation requirement given the proportion of aircraft types in its wake vortex category.

Time sequencing and separation between departures is also contained in each airport’s SSI (see Table 3). These values provide the IACM with the necessary minimum time between successive departures that increases safety but constrains departure flow. Similar to the arrival separation requirements, there exist some aircraft-specific departure separation requirements. For example, at FACT if a flight has a runway- intersection departure behind a Boeing 747-800, then the flight must be separated by four minutes, instead of three. These aircraft-specific details will be used to adjust the overall departure separation requirement based on their proportion of the aircraft within their categories. However, with respect to current operations, FACT has officially determined not to provide Code F capabilities within the current or near- term future, and therefore, does not accept any Code F operations. Hence, this was not a factor in the simulations.

Table 3: Standard Departure Separation Minima in Minutes

Separation Minima Type FAOR FALE FACT Standard 2 2 2

Light behind Heavy 3 3 3

Medium behind Heavy 3 3 3

3.2.3 Runway Occupancy Times and Approach Speeds Capacity estimates produced by IACM are very sensitive to input ROTs and approach speed values. ROTs are computed for each arriving and departing aircraft using the three study airports in both the north and south configurations. The north configurations for the three airports are RWY03 for FAOR, RWY06 for FALE, and RWY01 for FACT. Similarly, the south configurations for the three airports are RWY21 for FAOR, RWY24 for FALE, and RWY19 for FACT. The arrivals and departures tables below show the means and standard deviations calculated for each runway’s ROT, and these are used as inputs to IACM. These values were only calculated for the data that was available; see Table 4 and Table 5. A hyphen appears for those categories for which adequate data was not available. Due to the lack of data for these categories, a surrogate was used. Given that the major contributor to the capacity was the separation minima, not the ROT, it was estimated that any changes to ROTs for these categories would not have a significant impact on the modeled results. In these cases, the calculated value of the Medium category for each airport was used, but as more data is made available, these categories and the analysis can be updated.

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Table 4: ROT Statistics for Arrivals in Seconds

Category Statistic FAOR(03) FAOR(21) FALE(06) FALE(24) FACT(01) FACT(19) Mean Heavy 53.8 72.4 - - 103.5 74.5

Standard Deviation Heavy 11.5 14.4 - - 37.0 6.9

Mean Medium 55.3 72.1 61.8 78.4 57.8 62.7

Standard Deviation Medium 19.4 20.9 10.9 32.8 21.3 9.7

Mean Light 67.7 53.1 60.2 81.3 - -

Standard Deviation Light 30.6 17.8 8.73 30.4 - -

Table 5: ROT Statistics for Departures in Seconds

Category Statistic FAOR(03) FAOR(21) FALE(06) FALE(24) FACT(01) FACT(19) Mean Heavy 130.8 130.1 - - 70.0 84.2

Standard Deviation Heavy 51.0 41.4 - - 14.3 31.3

Mean Medium 124.9 127.8 104.0 86.5 76.9 96.7

Standard Deviation Medium 54.0 58.2 39.82 24.1 37.4 59.5

Mean Light 102.7 101.0 71.4 57.3 - -

Standard Deviation Light 38.8 57.6 29.8 19.9 - -

At the time of this analysis, approach speeds were not available, therefore approach speeds were derived for the IACM validation analysis for Atlanta Hartsfield International Airport, and those values were increased by 10% for FAOR only (adding roughly 2% per every one-thousand feet above sea level15). The obtained values are subsequently grouped by operation type and aircraft weight class. Due to the lack of information for this characteristic, landing speeds are assumed to be similar in both the north and south configurations. The parameters for the study airports are recorded in Table 6.

Table 6: Runway Crossing Speeds in Knots

Category FAOR FALE FACT Mean Heavy 145.1 131.4 131.4

Standard Deviation Heavy 8.49 8.49 8.49

Mean Medium 150.1 135.9 135.9

Standard Deviation Medium 8.21 8.21 8.21

15 U.S. Department of Transportation, Federal Aviation Administration Flight Standard Service, “Pilot’s Handbook of Aeronautical Knowledge,” 2008.

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Category FAOR FALE FACT Mean Light 124.4 112.7 112.7

Standard Deviation Light 16.0 16.0 16.0

3.2.4 Demand Fleet Mix IACM uses the fleet mix to calculate the appropriate separation between aircraft based on actual operations at the airport and the required separation from the SSI. ACSA provided demand data for each of the study airports from January 2002 to August 2012. The most recent twenty months of data (from January 2011 to August 2012) was mined to derive the fleet mix for each airport, shown in Figure 1 and detailed in Table 7. Members of the “fleet mix” are defined by their wake vortex category, including helicopters.

Figure 1: Fleet Mix Charts by Airport

Table 7: Fleet Mix Proportions by Airport

Category FAOR FALE FACT Heavy 14.8% 1.5% 7.7%

Medium 73.8% 91.0% 67.1%

Light 11.3% 6.8% 21.6%

Helicopter 0.1% 0.4% 0.0%

Unknown (Z) 16 0.0% 0.3% 3.7%

These proportions are not representative of any particular hour in the study data (e.g., an hour consisting of eight arrivals into FALE cannot possibly have 1.5% of the arrivals being heavy), but are a normalisation of the type of demand using the three airports. For the purposes of this demand breakdown,

16 The Z category is assigned to unscheduled activity for which the aircraft type was not recorded, but in all cases would be Code B or Code A aircraft.

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15 the Airbus A380 has been designated as Heavy due to its small population in the data. Due to the small proportion of helicopters at each of the airports, they are not considered in IACM modelling. Furthermore, the unknown aircraft types in the base data were considered to be Light aircraft because they have little contribution at airports with little known Light aircraft traffic (i.e., FAOR and FALE) and have a significant contribution to FACT which is known for a high level of Light aircraft traffic.

3.3 Results The input parameters described in section 3.2 were entered into IACM for each of the three airports, for both the north and south configurations, to derive their analytically calculated capacity values. Those values are compared to the declared capacity for each airport and describe the major effects of the input on the overall capacities. The declared capacity and analytically derived capacity are compared to actual operational data by observing arrival and departure throughput for each operational hour from January 2011 to August 2012.

3.3.1 FAOR Capacity Validation The declared capacity for FAOR is 60 operations per hour, and more specifically an even split of 30 arrivals and 30 departures. From the input parameters, the IACM estimates the capacity for FAOR in both a north and south flow to be as follows:

• Arrival movements only = 27

• Departures movements only = 26

• Alternating arrival and departure movements = 27 arrivals plus 26 departures = 53

The IACM was able to derive arrival and departure capacities slightly lower than the 30 declared for either arrivals or departures at FAOR. Analysis of the parameters shows that the two-minute standard separation between consecutive departures is a major constraint on the departure capacity, because at best it will only allow for a theoretical maximum of 30 departures per hour. This theoretical maximum capacity of 30 departures combined with the increase of departure separation for flights trailing Heavy aircraft (which make up 14.8% of the demand) produce a decreased effective capacity of 26. A similar effect is observed for arrivals where the increased separation for flights trailing Heavy aircraft decreases the effective arrival capacity.

Figure 2 illustrates this conclusion. It shows the following elements:

• Analytic capacity (in the form of a arrival and departure trade-off curve) drawn by the brown lines

• Declared capacity drawn as the red circle

• Coloured contour of each demand-hour representing the number of arrivals and departures for every operational hour between January 2011 and August 2012.

Each contour band represents the frequency (by portions of 10) of operational hours at a recorded demand level, the demand value is represented by the intersection of the count of departures (horizontal) and count of arrivals (vertical). For example, there are 15 operational hours with a demand level of 13 departures and 14 arrivals for the duration of the sample data; therefore, it is placed in the 10-20 hour band (blue).

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Frequency of Operational Hours Declared Capacity

Contour of Historical Demand

Analytic Capacity/ Trade-off

Figure 2: FAOR Declared Capacity, Analytic Capacity, and Historical Demand

Figure 2 illustrates that the analytic capacity does not have a trade-off point between arrivals and departures. This is because the western runway, RWY03L in a north flow and RWY21R in a south flow, is used primarily for departures, while the other runway is used for arrivals. From the data, it is observed that there are some instances, but too few that will display on the graph, in which operational hours have exceeded both the declared and analytic capacity. These occurrences can be due to those operational hours having a more uniform fleet mix which removes some variance in separation. Approximately 88% of all operational hours with aircraft movements fall within the IACM-derived capacity, and just over 95% of operational hours fall within the airport’s declared capacity. The similarity between the low frequency in exceeding the declared airport capacity matched with the relative similarity between the declared capacity, and the IACM estimates proves that the 60-movement capacity is a valid estimate for current operations FAOR.

3.3.2 FALE Capacity Validation The declared capacity for FALE is 24, more specifically a split of 16 arrivals/departures and 8 arrivals/departures, depending on the demand. From the input parameters, the IACM estimates the capacity for FALE in both a north and south flow to be as follows:

• Arrival movements only = 20

• Departures movements only = 25

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• Alternating arrival and departure movements = 20 arrivals plus 20 departures = 40

The arrival-only capacity at 20 is lower than that of FAOR due to higher arrival ROTs and slower landing speeds. The departure-only capacity at FALE is consistent with that of FAOR. Unlike FAOR, fleet mix does not influence capacity because 91% of the demand is Medium aircraft.

Figure 3: FALE Declared Capacity, Analytic Capacity, and Historical Demand

Unlike the FAOR study, FALE does not have the level of demand that will offer a significant comparison with either the declared capacity or the analytic capacity—the sample data has no recorded operational hours that exceed the declared capacity. The analytically derived capacity at 40 is significantly higher than the declared capacity at 24. The standard operating procedures for arrival and departures coupled with the available operational data show that the declared capacity of the airport can increase, but further analysis is needed to investigate airspace design and interactions with surrounding airports.

3.3.3 FACT Capacity Validation The declared capacity for FACT is 30, and more specifically a split of 10 arrivals/departures and 20 arrivals/departures, depending on the demand. It is important to recognise that FACT has intersecting runways RWY01/19 and RWY16/34. The site visit interviews revealed that RWY16/34 is seldom used, therefore, FACT is modelled as a single-runway operation for validation purposes. From the input parameters, IACM estimates the capacity for FACT in both a north and south flow to be as follows:

• Arrival movements only = 20

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• Departures movements only = 23

• Alternating arrival and departure movements = 18 arrivals plus 17 departures = 35

Much like FAOR, IACM was able to derive an arrival capacity near to its declared capacity (see

Figure 4). The departure-only capacity is lower than that of FAOR or FALE due to the high mix of traffic, namely Light aircraft (22% of the demand) mixed with Medium and Heavy aircraft and the additional separation requirements for departure.

Figure 4: FACT Declared Capacity, Analytic Capacity, and Historical Demand

There is a trade-off between alternating arrivals and departures similar to that of FALE in its north flow. However, FALE has much higher ROTs in its north flow than that of FACT. This suggests that there exists a bottleneck other than ROT that must be remedied to increase the capacity of FACT. These other factors may be arrival separation minima, landing speeds, or departure separation minima.

Much like the FAOR study, FACT has ample operational hours that show levels reaching and sometimes exceeding the declared airport capacity and the analytically derived capacity. To reiterate, the operational hours that exceed both the declared and analytic capacity may have operational characteristics that are not fully described using the general operational parameters for the validation study. The analytically derived capacity and the declared capacity are relatively close in total operations. Approximately 87% of the

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19 operational hours falls within the declared capacity, while nearly 88% of the operational hours is within the analytically derived capacity. Much like the FAOR study, the similarity between the low frequency in exceeding the declared airport capacity matched with the relative magnitude of the declared capacity, and the IACM estimates prove the 30-movement capacity is a valid, but slightly lower, estimate for current operations at FACT.

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4 Candidate Capacity Enhancements Affecting Airspace and Operations This section discusses viable candidate enhancements for improving airside capacity and efficiency at FAOR, FALE, and FACT. This list provides information about the specific capacity-enhancement initiatives proposed by ATNS and ACSA from the Airside Capacity Enhancements Initiatives document. For each enhancement or groups of enhancements, this section provides a description of the capability, technical dependencies, and a real-world example (where applicable) of the enhancement. The examples given are for the purpose of demonstrating the potential solutions. In each case a more detailed analysis is needed to fully develop the recommendations.

4.1 Data Link (PDC/DCL) Data Link Pre-Departure Clearance (PDC)/Departure Clearance (DCL) provides for the request and delivery of departure clearance to flight crews through data link digital. PDC/DCL reduces verbal communication between ATC and pilots, reducing frequency congestion and delays in pilots obtaining clearances. To utilise PDC/DCL, aircraft must be equipped with pertinent data link avionics or procedures implemented to provide pilots with a printed version of their departure clearance. It is a widely deployed capability at major airports throughout the world. A domestic US example is Washington Dulles International (KIAD).

4.2 Data Link (CPDLC) Controller-Pilot Data Link Communications (CPDLC) reduces verbal communication between ATC and pilots, improves awareness, safety, and capacity, and allows proactive planning of taxiway exits and routes prior to departure. This initiative must be coordinated with airport operators to minimise bay changes to the same apron area. In addition, aircraft must be equipped to make use of this capability. CPDLC reduces verbal communication between ATC and pilots, reducing frequency congestion and delays in pilots obtaining clearances. CPDLC allows proactive planning of taxiway exits and routes prior to departure. This initiative must be coordinated with ACSA to minimise bay changes to the same apron area. In addition aircraft must be equipped with data link capabilities. This emerging capability not yet widely deployed.

4.3 Ground Surveillance – Taxiways and Runways Ground Surveillance Systems detect aircraft and vehicles on an airport’s surface. They are used by air traffic controllers to supplement visual observations, particularly to avoid runway incursions. Historically, they have been used primarily at night and during low visibility to support monitoring of aircraft and vehicles in the airport movement area (runways and taxiways). Early systems relied on radar technology as the basis for surveillance. These systems have evolved to augment the radar return with location information provided by aircraft and vehicles equipped with radar transponders or Automatic Dependent Surveillance Broadcast (ADS-B); some systems have abandoned radar entirely and rely exclusively on aircraft- or vehicle-provided data. More advanced systems have added automation capabilities to display information about the aircraft, its surface position and routing, and alerting logic of potential surface collision risks.

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Advanced Surface Movement Guidance and Control System (A-SMGCS) provides routing, guidance, and surveillance for the control of aircraft and vehicles in order to maintain the declared surface movement rate under all weather conditions within the aerodrome visibility operational level while maintaining the required level of safety.

Ground surveillance systems are widely deployed at major airports throughout the world. A domestic US example is Washington Dulles International (KIAD).

4.4 Ground Surveillance – Ramp Areas and Aprons Surface surveillance capabilities in the ramp and apron areas provide additional information about the progress of aircraft movements, particularly as they progress towards departure, and about the gate occupancy and availability. The tracking and management of ramp equipment and vehicles can also result in improved apron operations, such as reduced turn-around times. These types of ground surveillance systems require cooperative information from aircraft and vehicles to be fully effective, especially those that do not include radar technology. Ramp and apron surveillance coverage is beginning to be deployed at major airports in the world. A domestic US example is KJFK.

4.5 Wide Area and Satellite-Based Augmentation System Wide Area Augmentation System (WAAS) is a Global Positioning System (GPS)-based navigation and landing system that provides precision guidance to aircraft at thousands of airports and airstrips where there is currently no precision landing capability.

This service is available free of charge to all civilian users and markets in Central and North America. Since FAOR has ILS capability to all runways, WAAS would provide such approach capabilities when an ILS was not available because of outages or maintenance.

WAAS falls into the broader category of Satellite-Based Augmentation Systems (SBAS). The primary benefit of SBAS is providing precision approach capabilities for runways without an operational ILS. SBAS capabilities for a specific airport are dependent on the existence of operational SBAS satellite coverage over the airport. Presently, the most promising effort to provide that coverage over South Africa is for extension of the European Geostationary Navigation Overlay Service (EGNOS) to South Africa. Numerous locations within the US and Europe have SBAS capabilities.

4.6 CAT III Approach Capability CAT III capabilities provide the ability to make approaches to a runway at lower minima than CAT I or CAT II procedures. With CAT III there is not a defined Decision Height (DH) for the procedure in which the runway environment must be seen. Instead, the minima for the procedure are dependent on the Runway Visual Range (RVR) values established for the procedure. There are three groupings of CAT III with the following typical minima: CAT IIIa – 700-feet RVR, CAT IIIb – 150-feet RVR, CAT IIIc – RVR 0-feet.

To establish CAT III approaches, the ground equipment must meet the technical performance capabilities with appropriate field lighting and electrical power stability. For pilots to use the CAT III procedures, the capability must be approved for use in airline operations manuals, the aircraft has to be certified for CAT III operations, and the flight crew must be appropriately trained and proficient. An example of an airport with this capability is KIAD.

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4.7 Apply Minimum Authorised Separation on Final Although a Civil Aviation Authority (CAA) has established minimum separation standards such that an Air Navigation Service provider (ANSP) must ensure that aircraft are not spaced closer than that minima, in actual practice ATC may space aircraft using greater minima to ensure that variations in speeds flown by various aircraft and encountered winds do not result in separation violations. This enhancement recommends that the ANSP space aircraft at the minima on final and in essence not provide additional buffers in spacing. Spacing aircraft at minimal increases the aircraft landing rate, and thereby increases an airport’s effective capacity. Spacing aircraft at minima frequently requires the ability to manage increased controller workload resulting from closer monitoring, more precise speed control, and increased communication with pilots. In addition, pilot adherence to assigned speeds is a necessary.

4.8 Reduce Minimum Separation to 3 nm Minimum IFR separation for operations in South Africa are typically 5 nm or greater. Minimum separation for non-heavy aircraft operations at various airports across the world is typically 4 nm. At some locations, the separation on final can be as low as 2.5 nm, with 3 nm relatively common place at most airports in the U.S. Reducing separation minima on final will increase the aircraft landing rate and as a result increase airport effective capacity. Use of lower separation is dependent on the ANSP systems presenting aircraft targets with the necessary accuracy, developing appropriate safety cases to the South Africa CAA, receiving CAA approval and training controllers on providing the reduced separation.

4.9 Readiness for Imminent Departure (Improved Pilot Reaction Times) Runway occupancy time is a key element in airport capacity. This enhancement is focused on ensuring that when pilots are instructed to occupy the runway in preparation for departure (line up and wait) or are cleared for take-off, that they do so without delay either resulting from having to perform tasks that could have been done earlier or from a slow reaction to ATC clearances. Minimising these reaction times reduces runway occupancy time and as a result increases an airport’s effective capacity. The effectiveness of this enhancement is dependent on pilots’ awareness of the impact that delays between receiving a clearance and their expeditious action has on airport capacity, and executing those clearances in a timely manner. Expeditious compliance with an ATC clearance is common at most major airports in the world.

4.10 Departure Sequencing ANSPs should consider all factors affecting spacing between aircraft during departure sequencing. This helps ensure improved runway utilisation by not having greater gaps between departures than needed. These factors include wake turbulence, assigned departure procedure, and aircraft initial departure performance. Procedures for assignment of airport slots and CTOT must support optimal sequencing. The ANSP must have available resources to accommodate the increased workload associated with optimising departure sequencing and its coordination. Optimised departure sequencing is common at most major airports in the world.

4.11 Grouping by Wake Turbulence Category Sequencing aircraft with similar wake turbulence separation requirements together improves runway utilisation in comparison to mixed wake turbulence category operations on a runway. The result is greater effective runway capacity. The process of group aircraft requires the availability of airport surface or airspace within which the grouping is accomplished. Operational personnel must have workload availability to perform the grouping function.

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4.12 Multiple Departure Line-up Queues There are often different departure spacing and route restrictions based on aircraft route, wake turbulence requirements, or performance. This enhancement involves the establishment of multiple physical departure queues so that controllers can draw the next departure from the queue that is most advantageous for maximising runway occupancy. Multiple, physical departure queues aid in maximising runway occupancy, increasing the number of departures in a given time frame, and increasing airport departure capacity. The use of multiple departure queues depends on supporting airport taxiways and ramps existing in proximity to the departure end of the runway. New York LaGuardia (KLGA) employs multiple physical departure queues.

4.13 Multiple Intermediate Departure Holding Points Related to the multiple physical departure queues addressed in section 4.12, this enhancement provides holding points or areas where aircraft can be held on a non-interfering basis as they wait for their CTOT. This provides easier sequencing of aircraft compared to queueing them at the runway departure end. This technique reduces controller workload and improves likelihood that the sequencing to the departure end of the runway is optimal, leading to increased runway utilisation. The capability is dependent on the physical availability of airport holding areas and support ANSP procedures to use them.

4.14 Standard (Coded) Taxi Routes The taxi route commonly used between gate areas and departure runways can involve many different taxiways. At a number of airports standard taxi routes have been formalised with a naming coding for each route. Use of standard taxi routes increases efficiency, reduces the potential for error, and reduces workload associated with communications and read-back of taxi clearance. Implementation of standard taxi routes requires formalisation, coordination, and publishing of the routes.

4.15 Performance-Based Standard Instrument Departure Under performance-based Standard Instrument Departures (SID), the ANSP develops and implements multiple departure procedures tailored to aircraft performance characteristics. Similar performance aircraft are assigned to one procedure while aircraft of a different performance grouping would be assigned a different procedure. The design of the procedures includes divergence of initial heading between the procedures. Grouping aircraft by performance similarity minimises the workload of separating aircraft within the performance group. Diverging initial headings allows for reducing the time between successive departures. Providing performance-based departure procedures with differing initial headings depends on environmental assessment of the resulting flight tracks and the development, approval, and publishing of the procedures. General Edward Lawrence Logan International (KBOS) has implemented differing departure procedures for turbojet and propeller performance aircraft.

4.16 Speed Control Assigning specific speeds to aircraft assists in achieving and maintaining required or desired spacing between aircraft. The use of speed control reduces the need for vectoring, and has a related reduction in controller workload. Pilots have the responsibility and prerogative to refuse speed adjustment that they consider excessive or contrary to the aircraft’s operating specifications. Speed control is an ATC technique employed at many high-activity airports across the world.

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4.17 Arrival/Departure Balancing Depending on the arrival and departure demands, changes can be made to runway configurations; e.g. arrivals only, departures only, or for runways where both arrival and departures are conducted, the mixture rates of arrivals in comparison to departures. Adjusting the use of a runway and the arrival/departure rates for mixed-use runways can improve overall airport efficiency and allocate delays more equitably. It can also help airport surface congestion and gate utilisation. Balancing of operations can result in some aircraft in wake turbulence categories encountering delays they would not have otherwise encountered; in such situations there must be available airport surface areas or airspace to absorb the delay and sufficient operational workload available.

4.18 Performance-Based Navigation PBN procedures provide the ability to define area navigation arrival, departure, and en-route navigation routes, altitude, and speed assignment not dependent on the location of ground-based navigation aids, including pilot navigation flight segments that would have to otherwise be conducted through the use of ATC communications of vectors, altitude assignment and speed control instructions. PBN increases airspace capacity by defining routes according to an aircraft’s navigational performance, not according to the location of ground-based sensors. The new procedures established under PBN necessitate appropriate fly-ability assessment and publishing. In addition, use of PBN must be approved for use in airline operations manuals, the aircraft has to be certified for the level of PBN associated with the procedure, and the flight crew must be appropriately trained and proficient. Because PBN routes often involve a change in arrival and departure routes, environmental assessments are often necessary. PBN procedures have been developed for and are in operation at many high-activity airports across the world.

4.19 Airspace Review and Redesign Airway route structure and the associated airspace sectorisation within a given airspace are periodically needed to be reviewed and redesigned as the traffic volumes and flows change and new procedural capabilities are added. Review and redesign of the airspace fosters optimal use and efficiency of that airspace. Airspace review and redesign is dependent on human resource availability to accomplish the review and redesign as well as the associated system and aeronautical information changes. Changes to airways and procedures will necessitate appropriate fly-ability assessment, approval and publishing. Comprehensive airspace review and redesign has occurred at many airports across the world. Examples of a major on-going redesign effort in the U.S. include the metroplex (multiple airports sharing a volume of terminal airspace) redesign activities for the Washington DC and Dallas-Ft. Worth areas and the PBN associated implementation at Las Vegas.

4.20 Review Low-Visibility Operations Low-Visibility Operations (LVO) has two main objectives: protect the ILS signals from interference, and protect aircraft and vehicle traffic from collision. LVO is required for CAT II/III operations as well as for all aerodromes where operations, including departures, take place under reduced visibility. The nature and complexity of all operations at an airport require that all agencies at the airport are involved in LVO. Having LVO procedures is a fundamental International Civil Aviation Organisation (ICAO) requirement for airports conducting such low-visibility operations and thereby it is essential that they periodically be assessed for currency. Reviewing LVO operations identifies areas that may require attention to reflect currency of information and operational efficiency. The primary dependency is on human resources to

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25 conduct the review and make identified modifications to procedures. LVO is a capability of many high- activity airports across the world.

4.21 Dedicated Apron (Ramp) Control Management of ramp and aprons involves the coordination of aircraft movements and gates where there are vehicle, equipment, personnel, and activities. Many of the activities involve direct coordination with airline operations personnel and are dependent on aircraft servicing activities. At many high-activity airports across the world, ramp management is provided by dedicated personnel, in many cases not part of the ANSP. Having dedicated personnel focused on ramp and apron management can reduce overall workload for ATCT personnel. Establishing dedicated ramp and apron control is predicated on having the physical space and equipment for such personnel as well as having the coordination capabilities with ATCT functions. Ramps at most U.S. high-activity airports are managed by personnel dedicated to that function and from a location other than the ATCT.

4.22 Intersection Departures Not all aircraft departing from a runway require the full runway length to meet operational take-off requirements. Aircraft can depart from intersections along the active runway that meet their performance requirements. Use of intersection departures can reduce taxi distance and time for those aircraft capable of departing from an intersection as well as precluding all aircraft being in the same physical departure queue delaying when they could have been airborne. Overall, use of intersection departures can increase airport utilisation and improve capacity and efficiency. Use of intersection departures is dependent on aircraft capabilities and application of additional wake turbulence requirements for aircraft departing intersections after a large or heavy aircraft has departed from the runway or a closely spaced parallel runway. Intersection departures are common at many airports; one example is the intersection Kilo-Kilo on RWY31R at KJFK.

4.23 Conditional Clearances Conditional clearances allow ATC to specify conditions that must be met before a pilot is authorised to take an action. Examples include “Line up and wait after landing traffic”. Use of conditional clearances can improve efficiency in comparison to positive control procedures, because a clearance can be provided without having to wait until conditions allow the clearance to be issued. Use of conditional clearances is dependent on safety assessment and CAA approval.

4.24 Limit Operations during Peak Periods This enhancement excludes certain classes of operations during certain time periods; e.g., GA during a crowded arrival period. Excluding dissimilar types of operations can reduce the complexity of managing different types of operations, thereby reducing ANSP workload. This enhancement generally requires the approval of the CAA. The exclusion must specify its scope. An example of scope may be to outline what GA operations are restricted at what times.

4.25 Limit Operations of Non-Standard Performance This enhancement precludes aircraft that cannot meet defined performance requirements from operating during certain time periods. Excluding dissimilar types of aircraft performance can reduce the complexity of managing air traffic operations and reduce ANSP workload. Excluding aircraft outside of performance

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26 ranges would generally require the approval of the CAA. The exclusion must specify its scope. An example of scope may be to outline what GA operations are restricted at what times.

4.26 Slot Optimisation The mixture of aircraft types and performance is related to what operations have been authorised at specific time periods (slots). Changes in the mix of aircraft have a direct relationship to the separation that must be provided as the types of operation differ. This enhancement proposes to optimise the slot assignments for overall airport utilisation. A key element includes adherence to the assigned slot times. Slot assignment is dependent on the agreement of numerous parties including airport authorities, airlines, and traffic management organisations. Its effectiveness is dependent on the level of compliance there is to the assigned times, both by pilots and by the ANSP.

4.27 CTOT Compliance A key aspect of effective air traffic management and overall aviation system performance relates to accuracy of the time an aircraft actually departs in comparison to its CTOT. This enhancement proposes that efforts be made to ensure compliance without exceptions. High levels of compliance reduce workload associated with peaks resulting from non-compliance. Managing compliance is primarily dependent on the actions of involved personnel.

4.28 Tower Coordinator In busy and complex ATCC environments, coordination among operational positions, adjacent operational facilities, the CAMU and operators can be extensive and affect optimized operations. To help manage such coordination, it is a common practice at high activity facilities to establish a dedicated position to assist in overall coordination and decision making. Establishment of an ATCC supervisor/coordinator can increase management and coordination effectiveness, reduce controller workload, reduce delays and improve overall ATC services. Use of an ATCC supervisor/coordinator is dependent on the physical establishment of the position with necessary equipment and establishment of operating procedures for its use. Qualified, experienced and appropriately compensated staff is a prerequisite for this position. ATCC supervisor/coordinator positions have been established at many high activity airports across the world.

4.29 Traffic Management Coordination This enhancement recommends improving coordination between operation ATC and Traffic Management organisations. Improved coordination increases operational effectiveness and efficiency of both organisations. Improving coordination is dependent on the recognition that improvement is necessary and a willingness to make improvements. Once fundamental areas of improvement have been identified, associated procedures and practices must be developed and implemented.

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5 Specific Airport Infrastructure Capacity Enhancements This section discusses potentially viable options for enhancing airside capacity and efficiency at FAOR, FALE, and FACT through physical changes to the airport surface. For each enhancement or groups of enhancements, this section provides a description of the enhancement, how the capacity and efficiency may be impacted, and a real-world example (where applicable). Each of the three airports has been developed to serve the volume and distributional characteristics of aviation demand which continue to evolve along with changes within the local and global aviation market. The types of aircraft served at each airport, as embodied in each airport’s fleet mix, is a major characteristic of demand that influences each airport’s existing and future capacity. The physical characteristics of each airport have been incrementally adapted over time to adjust to a fleet mix that includes wider wingspans, longer fuselages, increased wake vortex separation requirements, and other operational requirements. Making airfield changes on an incremental basis has enabled each of the airports to serve its developing markets. Various aspects of the current airfields are adequate at today’s levels of demand; however, they may not be optimal with expected increases in demand.

Many of the sub-optimal physical constraints can be “managed” through traffic management and other operational controls. However, any significant change in fleet mix and traffic growth that would result in multiple simultaneous additions of larger aircraft could severely constrain operational capacity. As such, moderate airfield enhancements provide an opportunity for incremental capacity enhancements to efficiently serve continued modifications in aircraft fleet mix without pursuing a large-scale political and economic approval process.

FAOR, FALE and FACT each have published Master Plans that include airfield improvements and expansion, and FALE is scheduled to develop a new Master Plan in the near future. However, the developmental phases of these Master Plans will need to be triggered by evidence of significant increases in demand relative to each airport’s physical capacity constraints. The gap between the initiation of operational changes and the completion of physical airfield improvements could result in capacity constraints that limit the increase in operational revenues. The operational revenues help fund airside improvements. Identification of near-term incremental improvements that are aligned with longer range Master Plan components could help to maintain higher levels of efficiency and capacity.

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5.1 FAOR The constrained taxiway geometry at FAOR limits capacity by requiring runway crossings for aircraft landing on RWY3R/21L to reach the western terminal precinct. The single parallel Taxiway Alpha also limits the ability for air traffic controllers to efficiently manoeuvre aircraft between the aircraft gates and RWY3L/21R. During peak departure periods, the lack of a second parallel taxiway or of a runway end hold pad makes it difficult for ATC to alternate east bound and west bound aircraft in the departure queue to maximise available runway capacity. Figure 5 illustrates the airfield layout of FAOR, and highlights some of the most critical issues influencing performance.

Figure 5: FAOR Airport Layout Issues

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The Master Plan for 55-to-60 Million Annual Passengers (MAP) level improvements addresses some of these issues through the development of a new Central Terminal complex, two additional runways, and extensive taxiway changes including an end-around taxiway at the RWY03L threshold (see Figure 6). The Master Plan identifies development to be implemented in phases:

• Phase 1 (Central Passenger and Cargo Terminals), • Phase 2 (addition of a 3rd runway, new aircraft maintenance facilities and expansion of the central terminal facilities), and • Ultimate development (addition of the 4th runways and full midfield build out)

However, the extent to which increases in aviation demand trigger each phase of development has not yet been completely determined. The identification of demand triggers is an important next step that requires further assessment of each element of the master plan (including those referenced herein) relative to detailed projections of forecast demand characteristics.

Figure 6: FAOR Master Plan for 55 MAP Capacity Level

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The full impact of runway crossings would not be eliminated without the addition of end around taxiways and the relocation of the majority of aircraft gates to a central airfield position. Nevertheless, taxiway constraints and aircraft manoeuvrability within the existing terminal area could be improved with a few less costly interim improvements. Figure 7 shows the potential for three airfield pavement projects that would result in potential improvements in capacity:

1. add extended taxiway pavement at the end of RWY03L; 2. add RETs to RWY03L/21R; and 3. add RETs to RWY 21L.

These potential improvements are further discussed in the following sections.

Figure 7: FAOR Near-Term Airfield Improvements

5.1.1 RETs to RWY03L/21R The FAOR Master Plan does not include the addition of RETs to RWY03L/21R (Figure 8), likely because it is currently used primarily as a departure runway. Landings on 03L/21R do not currently exceed 5%

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31 during peak hours. However, pilots often request landing on this runway to save the long taxi distance from RWY03R/21L. Even with the addition of a third runway, RWY03C/21C, anticipated in the Master Plan, there will still likely be at least some arrivals directed to RWY03L/21R. Because of its primary use for departures, any arriving aircraft should be enabled to exit the runway as rapidly as possible. Such RETs should be strategically placed to function for both north and south flows. The placement shown should be analysed before the exact locations are confirmed.

Addition of RETs

Figure 8: RETs for RWY03L/21R

5.1.2 Refine Taxiway Echo for RWY 03R and add additional RET to RWY21L The FAOR Master Plan includes the addition of RETs on RWY03R/21L (Figure 9), although some of these, including the Master Plan refinements to Taxiway Echo, are based on the extension of the runway from 3,400 meters to 4,700 meters in the direction of the RWY21L threshold. Until such time as the runway is extended, the ROT for south flow operations would benefit from the addition of an RET for RWY21L and the refinement of the current fillets of the connection to Taxiway Echo to enable it to be better used as an RET, as it currently does not provide for high speed exit (Figure 10).

Figure 9: FAOR Master Plan for 03R/21L at 55 MAP Capacity Level

Figure 10: Refine Taxiway Echo for RWY 03R and add additional RET to RWY21L

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Figure 11: FAOR Existing Taxiway Echo at RWY 03R/21L

The existing fillets placed at the Taxiway Echo crossing of RWY03R/21L could enable a rapid exit except that at high speeds the aircraft would need to continue on parallel Taxiway Yankee, as the end point for the RET centerline extends past the alignment of Taxiway Echo (Figure 11). To facilitate a true rapid exit, the centerline of the RET would need to be 45 meters offset and to begin the exit 100 meters sooner to the south (Figure 12).

Figure 12: FAOR Proposed Taxiway Echo RET for 03R

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This would only require the addition of approximately 13,414 m2 of pavement, of which, only 9,263 m2 would be in addition to future pavement included within the Ultimate Master Plan (Figure 13).

Figure 13: FAOR Change From Master Plan for Taxiway RE RWY21L only has one existing RET (Taxiway RR), which initiates at approximately 705 meters beyond the runway centerline, just past Taxiway Tango. The Master Plan includes an additional RET at190 meters. The addition of this RET would decrease average ROTs, as more aircraft would be able to exit the runway before reaching the existing RET (Taxiway RR). As this proposed additional RET is included in the Master Plan, it would not require any additional paving or demolition in this area (Figure 14).

Figure 14: FAOR Add Master Plan RET for RWY 21L

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5.1.3 Extended Taxiway Pavement at the End of RWY03L Most of the current aircraft departures at FAOR are Code C or smaller aircraft, and therefore do not need the entire runway length. There are already many intersection departures to minimise taxi time and distance. The additional length planned to Taxiways Alpha and Charlie enables additional departure queuing distance, and the potential to optimise the sequence of departures as most aircraft could enter RWY03L at three separate taxiway connectors. See Figure 15.

Figure 15: FAOR Taxiway Extension at RWY03L

This extension of the taxiways provides queuing and entry options that work with the existing condition (Figure 16).

Figure 16: FAOR Aircraft Taxi Flows with Taxiway Extension at RWY03L

Melbourne Airport (YMML) planned an extension to taxiway Yankee to enable intersection departures on RWY34. As parts of a comprehensive airfield capacity study, this improvement combined with a new RET Lima was expected to increase annual capacity by 1.0-1.5%, while providing a net present value of aircraft delay savings ranging from US$70 to US$90 million. This level of savings has been confirmed in

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35 a recent update to that study, and is now included in YMML’s capital plan. The addition of RET Lima and Taxiway Yankee extension resulted in the following:

• Reduced arrival airborne delay through reduction of average runway occupancy time to less than 50 seconds, thus enabling reduced arrival separation to 2.5 nm during certain VFR conditions.

• Reduced departure queue delay due to shorter arrival runway occupancy time.

• Reduced runway crossing delay (achievable during northwest flow).

5.2 FALE FALE is currently serving less air traffic movements per hour than its design capacity; see Figure 3 in Section 3.3.2. Therefore, the airport can address significant increases in peak-hour air traffic movements before experiencing capacity constraints. The SA ACES Task 1 Report identified potential conflicts that could develop with increased activity, as well as opportunities to improve operational efficiency and enhance performance for individual aircraft. Figure 17 illustrates the airfield layout of FALE, and highlights some of the most critical issues influencing performance. These issues will most likely only become critical at higher levels of activity, and many could be managed on an interim basis through traffic management and operational controls. It was noted by ATNS and it is illustrated in Figure 17 that there are no stopways; however, this is not critical to this study.

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Figure 17: FALE Airport Layout Issues

The airport has been developed to support the majority of the fleet as Code C aircraft, with the ability to serve as a Code F reliever airport. Consequently, the gate positions are largely Code C (16 Code C on the Alpha Apron including 12 contact gates and 9 Code C remote gates on the Bravo Apron) and four Code F-capable Multiple Aircraft Ramp Stands (MARS) that could alternately accommodate up to eight smaller aircraft. These positions could accommodate two large aircraft: Code E or Code F contact positions on the Charlie Apron, and two large aircraft hard stands for cargo on the Delta Apron.

If the increase in activity continues to be primarily Code C aircraft, air traffic management of flight schedules could delay the need for airfield improvements. The initial needs to address an increase in the current activity mix would then be the addition of parallel taxiways to the Charlie and Delta Aprons. However, if in the future the fleet mix were to change to a larger proportion of Code D or larger aircraft, significant changes might be required.

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Figure 18: FALE Airside Improvements

The Master Plan for FALE would add aprons, taxiways and larger aircraft gates that would address all of these issues. However, with FALE demand currently well below capacity and environmental restrictions on expansion of the airfield beyond the current limits, there may be benefit in identifying potential efficiency enhancements that could occur within the existing airfield boundaries. These potential enhancements would need to occur within a near-term planning horizon (subject to increased demand and financial feasibility). The addition of parallel taxiways and the addition of RETs for Runway 24 could occur within areas ultimately identified in the existing Master Plan for new airfield pavement (see Figure 18 and Figure 19).

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Figure 19: FALE Master Plan with Overlay of Potential Airside Improvements

5.2.1 Add Parallel Taxiway Access These improvements may only be necessary with increases in activity that would result in flight delays that would exceed the established CTOT tolerance of 10 minutes, which is not anticipated in the near to mid-term. However, as more subtle activity increases might exacerbate the hot spot or increase head-to- head flows on certain taxiway segments, any segment of a parallel taxiway could be implemented separately based on the specific nature of the increase in activity. The time impact of conflict and delay events, even if only a few minutes, could be calculated to determine if there is substantial demand to justify the cost of the taxiway. A review of the taxi flows illustrated the possible conflicts and potential resolutions. See Figure 20 through Figure 26.

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Figure 20: FALE Additional Parallel Taxiways

Figure 21: FALE North Flow Operations

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Figure 22 through Figure 26 illustrate the head-to-head conflicts that can occur on the Foxtrot and November Taxiways, particularly at the intersections of taxiway November with Alpha, Bravo, and Golf. Regarding north flow aircraft movements, the addition of the parallel taxiways provide bypass opportunities to reduce conflicts, including a bypass opportunity for the primary hot spot at the intersections of Taxiways Alpha, Bravo, Golf, and November. Even without the full taxiway parallel to Taxiway November (or the planned extension to Taxiway Bravo), most of the head-to-head conflicts could be resolved by providing an extension of Taxiway Golf that provides a second connector between Taxiways Alpha and Bravo.

Figure 22: FALE Extension of Taxiway Golf

Figure 23: FALE North flow Extension of Taxiway Golf & Taxiway Bravo

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Figure 24: FALE South flow Extension of Taxiway Golf & Taxiway Bravo The need to move aircraft off the Alpha or Bravo Aprons to alternative parking positions could move taxiing aircraft north along the extension of Taxiway Bravo counter to the primary taxi direction south of arrivals from RWY06. Also, any movements to or from the Delta and Charlie Aprons could flow unimpeded, avoiding any head-to-head conflicts (see Figure 25) .

Figure 25: FALE Existing South Flow Operations

Study of the south flows indicates that in addition to providing the bypass of the hot spot, there is also the opportunity for an alternative arrival flow south on the extension of taxiway Bravo; the Alpha apron taxilane and taxiway Alpha can both have dedicated north departure flows.

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5.2.2 Add RETs to RWY 24 for direct access Alpha & Bravo Apron Gates This increase in ROTs in south flow is most likely due to the position of the passenger gates near the southern runway threshold. There is little incentive to exit at Taxiway Golf, since the aircraft will need to continue to taxi to the south to reach the gates. By remaining on the runway until the southern threshold exit, the pilot can reduce the need for brakes or thrusters. This results in operational constraints during periods of extended south flow operations. In north flow, there is a greater incentive to exit the runway at Taxiway Hotel, to save taxi distance to the gates.

Figure 26: FALE Proposed RETs The RETs shown in Figure 26 are included in the Master Plan, so implementation would be completely consistent with the ultimate development plans and would require no deconstruction in future phases of development.

5.3 FACT FACT has several significant sources of congestion that require extensive controller workload to efficiently manage traffic. Although the traffic managers have successfully limited delays within the current level of activity and flight schedules, as activity increases, higher levels of delay will likely occur.

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The limitations in the aircraft movement areas and aircraft stands will be addressed as part of Master Plan improvements. Until such time as the Master Plan is implemented, the current airfield layout provides little flexibility for ATC to respond to any increases in activity or anomalous conditions such as recovery from weather delays or special events that result in unusually high peak-hour operations. Figure 27 illustrates the airfield layout of FACT, and highlights some of the most critical issues influencing performance.

Figure 27: FACT Airport Layout Issues

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The ACSA FACT Master Plan improvements expands the airfield, terminal gates, and aprons to create a new airfield configuration that provides additional capacity with fewer constraints (Figure 28). This includes the realignment of RWY01/19 to an RWY18/36 orientation, with the northern threshold offset to the east and a second parallel runway with lateral spacing of 1,035 metres. This will enable dual simultaneous instrument approaches. As these new runways are east of existing RWY01/19, the terminal and apron can be expanded significantly to more than double the existing gates and provide multiple parallel taxi lanes.

The implementation of this Master Plan significantly enhances capacity, but it also requires a significant capital investment. While the airfield improvements can be added without directly impacting existing airfield operations, the terminal and gate expansion need careful phasing of construction to avoid impacting on-going passenger service to contact gates.

Figure 28: FACT Ultimate Master Plan Overlay

The current Master Plan had originally anticipated the initial phase to be implemented by 2010; there is the likelihood that initiation of Master Plan improvements may be further delayed until demand indicates significant benefits to offset capital investments. In the meantime, there may be some less extensive near- and medium-term improvements that are compatible with the long-term Master Plan vision but may be less costly to implement. There are limited pavement additions that could enhance the current airfield within the near term and could later be incorporated into Master Plan ultimate Terminal Apron Area pavement. See Figure 29.

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Figure 29: FACT Master Plan Ultimate Apron area and Phase 1 Airfield Overlay In the near term, possible interim enhancements to facilitate more efficient aircraft movement include the addition of By-pass taxiways at the thresholds of RWY 01/19 and refinements of Taxiways Charlie and Echo fillets for improved runway exits and better visibility for intersection departures. See Figure 30.

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Figure 30: FACT with Potential Near-Term Improvements

5.3.1 By-Pass Taxiways at Runway Thresholds To add Code E-capable by-pass taxiways parallel to the runways would require a minimum of 126 meters from the centerline of the taxiway to the perimeter fence.17 At RWY01, the available distance from centerline to perimeter fence is 74m to 108m. At RWY19, it would require RWY16/34 to be decommissioned, or runway crossings to be allowed for a parallel taxiway to be developed.

However, to add by-pass taxiways that are perpendicular to the existing runway threshold entry points at TWY A218 and TWY B3 would provide additional runway entry points and would only require the 80m

17 Code E bypass would require 80 m from centerline taxiway to centerline of any holdpad taxiway + 42.5m to ASR+ 3.5m for width of ASR. 18 As RWY16/24 is currently underutilized, it is assumed that crossings would be allowed at times by-pass resequencing would be needed.

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47 offset the parallel taxiway center line. Most of the current aircraft departures at FACT are Code C or smaller aircraft, and therefore do not need the entire runway length. There are already many intersection departures to minimise taxi time and distance. The addition of By-Pass taxiways at each of the RWY01/19 thresholds enable additional departure queuing distance, and the potential to optimise the sequence of departures as aircraft could enter the runway via the By-Pass Taxiway entry points, giving each runway an additional point of entry. See Figure 31.

Figure 31: FACT By-Pass Taxiway RWY01/19 These by-pass taxiways can also serve as hold pads, either for flights in the departure queues or for arriving aircraft that have arrived before their gate may be available. (See Figure 32 and Figure 33.)

Figure 32: FACT North Flow Operations with By-Pass Taxiways

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Figure 33: FACT South Flow Operations with By-Pass Taxiways

5.3.2 Refinements of Taxiways Charlie and Echo Fillets for Runway Exits The addition of RETs could further enhance efficiency with minimal added paving. However, as the Master Plan will ultimately decommission the existing runways, and repave that area as terminal apron, any pavement changes to accommodate near term enhancements would ultimately be removed. Still, the runway intersections with Taxiways Charlie an Echo can be enhanced to provide more rapid exits for either north or south flow. Currently these taxiways provide intersection exits that are slow at best in north flow, and extremely tight in south flow operations. The current south facing angles also make visibility difficult when needed for intersection departures. Increasing the fillet pavement to a radius of 95 meters would facilitate at least a 90 degree exit in south flow. The placement of even broader radius fillets on both north and south should be analysed before the exact radius locations for each are confirmed as part of Task 6. See Figure 34.

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Figure 34: FACT Addition of RETs As stated at the conclusion of Section 5.1, the benefits of optimised RETs were evaluated as part of the airfield capacity study at YMML (Figure 35). The most efficient RET improvements were expected to result in a net present value of delay savings as high as US$80 Million.

Figure 35: YMML Airport RETs, Parallel Taxiways and Extensions

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6 Stakeholder Discussion Framework This report has identified a significant number of capacity enhancements that vary from changes in operational procedures that could be implemented in the next few years to those that involve substantial cost and will take many years to implement. Moreover, the short term options vary on the level of impact they would have on different stakeholders. In this section, the study team proposes a summary framework for presenting these capacity enhancements in the stakeholder engagement process in a manner that is easily understood by all stakeholders. This approach will be applied to the enhancements that are selected for further consideration later in the study.

6.1 Stakeholder Engagement ATNS and ACSA are in business to provide safe and efficient air navigation services and airport infrastructure for their stakeholders, which for purposes of this study are considered to be:

• Department of Transportation (DOT) – both as their owner and the entity that determines South Africa’s transportation priorities; • CAA; • Aircraft operators, including the South African National Defence Force; • The traveling public; and • Local airport communities. This section describes a proposed approach for engaging stakeholders with metrics that explain the challenges and justify the recommended capacity enhancements. Appropriate metrics will depend on the specifics of the capacity enhancement, particularly cost, with the objective of providing useful but manageable levels of information relative to the size of the investment and change in operating cost. The goal of stakeholder engagement is to help all stakeholders understand the capacity constraints of an airport or airspace and the options for reducing those constraints in the near term, medium term, and long term.

The study team proposes that a recommended change in an operational procedure with no or minimal cost (defined as less than R20 million) will require little or no economic analysis (discussed in section 6.3.1). A capacity enhancement that requires substantial capital investment (greater than R 20 million) would be presented to stakeholders for initial consideration using a similar format to that used for operational improvements (section 6.3.2) but with more analysis of the benefits. However, it is anticipated that high CAPEX improvements may eventually require larger economic cost benefit analyses that capture greater societal benefits prior to their formal adoption, which is beyond the scope of this study.

This approach is not intended to be a substitute for additional analyses that any stakeholder may do for its own purposes or the analyses that ACSA and ATNS perform for economic, technical, or regulatory purposes. Moreover, it is not intended to replace or replicate the metrics that are used by ATNS and ACSA when measuring their own performance. The proposal is designed to facilitate collaborative engagement between the stakeholders while leaving each to determine the benefits of the capacity enhancement from its particular point of view.

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Finally, stakeholders are encouraged to use the next few years to evaluate their current cost benefit methodology to determine if it captures all the costs and benefits that are important to them.

6.2 Diverse Stakeholder Interests The primary objective of ACSA and ATNS is to provide their clients safe and cost efficient aviation infrastructure, systems, and procedures. Both are considered world class in meeting these dual objectives. However, each organization has its own focus – ATNS on aircraft operations within the airspace and on the airfield, and ACSA on the airfield and within the terminal and landside areas serving passengers, vehicles, goods, waste and employees.

The study team believes that all stakeholders recognize that aviation safety is paramount and that some capacity enhancements are made to satisfy this goal. However, numerous investments are made to solve an operational challenge, reduce ATC workload, or to provide improved service levels. The study team believes that stakeholder knowledge of the challenges as well as the solutions will facilitate collaborative decision making. The major challenge in designing a template for presenting capacity enhancements is that each stakeholder group has a unique focus and that focus should and does influence its perception of a project’s importance and its value.

This challenge arises because there can be legitimate differences of opinion about what constitutes an appropriate level of service or the need to rectify “suboptimal” service. These differences of opinion are unavoidable even within a stakeholder group such as the airlines because different airline business models are based on different levels of reliability – for instance, business travellers generally demand greater schedule reliability than pleasure travellers who tend to be more cost sensitive. Moreover stakeholders such as AASA and ALPA-SA, are membership organizations, not regulatory organizations, and must reflect the evolving concerns of their members.

Even the DOT in its multiple roles as regulator, economic administrator, and owner, can have differing points of view. The CAA focuses on safety and the Minister of Transportation on those policy issues that are delegated to DOT by law, which include providing guidance on priorities that reflect South Africa’s national interests and policies. All these entities influence ACSA and ATNS in many ways including their investments and operations. Moreover, 24.4% of ACSA is owned by individuals and entities which are important stakeholders whose interests need to be recognized.

6.3 Stakeholder Material The study team recommends that stakeholder engagement material be designed to provide all stakeholders an explanation of the problem and enough information about proposed capacity enhancements to allow all stakeholders to understand the need and the solution. The material should include a description of the recommended solution or solutions; information about the cost and the proposed timing.

The engagement process must meet stakeholder needs for it to be effective, and the engagement process is likely to evolve over time. As a result, the material that is prepared for each year’s consultative process should reflect current stakeholder concerns. Consideration should be given to having the stakeholder consultations confidential as a means of avoiding politicizing the discussions.

The proposed presentation format that will be used to summarize selected capacity enhancements is shown in Table 8; this will be further developed in Task 3 - Finance.

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Table 8: Airside Capacity Enhancement Stakeholder Engagement Material

Name of project Report Section/page Proposal Reference in Task 2 Category Cost < or > R 20 million

Shortfall Describe operational shortfall project will address (from Task 1).

Responsible Either ACSA or ATNS Identify affected Airport Agency airport(s) Describe recommended solution based on the summary language in Task 2. If Proposed Action available, a trigger time based on time to implement will be included.

Summarize expected outcomes. Quantify as applicable for Cost > R20 million

ROT Average

Expected Taxi time Average Benefits Peak capacity Movement per hour

Delay Average or total minutes

Other

Capital:

Costs Implementation: Total over all stakeholders

Operational: Net total over all stakeholders

Major Stakeholder Benefits Costs Other Impact Workload, enhanced ATNS safety, capacity

ACSA Capacity; pax throughput Based on cost of aircraft Airlines delays; ROT; taxi time. Workload Pilots

Passenger Value of delay time Other e.g. Noise; emissions

6.3.1 Capacity Enhancements with CAPEX under R20 Million This study will recommend a number of capacity enhancements that are designed to increase the efficiency of existing infrastructure through operational changes and or modest capital expenditures. The

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53 study team recommends that the stakeholder engagement material explains the specific issues that the proposals are intended to address and provides estimates of the resulting improvements. The improvements would be measured in operational terms, for example, reduction in taxi time, reduced peak hour delays, reduction in air traffic controller workload, reduction in noise, etc. The cost of the enhancement will include capital costs (ground and aircraft equipage), significant training costs for ATNS, ACSA, and other stakeholders, and the net change in operating costs.

6.3.2 Capacity Enhancements with CAPEX over R20 Million Quantifying the monetary value of benefits to the various stakeholders will be undertaken for capacity enhancements that cost more than R20 million. The primary benefits for airlines and aircraft operators involve the avoidance of airport-related delays. For airlines, delays will be monetized based on savings in aircraft operating costs using an average cost per block hour. The economic value of reduced delays to passengers will be estimated based on Eurocontrol and FAA recommended metrics. It is acknowledged that there is monetary value connected with other stakeholder benefits, such as noise reduction or lower emissions; this will not be included in the analysis because it is beyond the scope of the study.

Estimating airport delay times based on capacity and demand involves complex and specialized modelling because each airport has a unique layout, geographic location, demand profile, weather conditions and other characteristics. As a result, the modelling requires the collection of data on current operations (e.g., ROT, taxi times, daily/seasonal aircraft arrival and departure profiles, fleet mix, weather, delay times, forecast demand characteristics); selection of and validation of the models using this current data; then rerunning the model to reflect proposed capacity enhancements against forecast traffic levels to estimate future delays. The study team has validated its models for current conditions at FAOR, FALE, and FACT in order to evaluate the capacity enhancements under consideration, but this process would likely need to be repeated when it is time to revisit these recommendations.

6.4 Summary The study team believes that the amount of analysis should be proportional to the size of the investment by all the stakeholders. Thus, an operational change that improves the efficiency of the existing infrastructure does not warrant extensive analysis. The stakeholder material will focus on identifying issues that are likely to be important to each stakeholder, but will not quantify the impact of the changes. Capacity enhancements that require significant investments, which are defined as those over R20 million, require greater analysis including the quantification of the benefits.

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7 Conclusions and Next Steps This section presents the study team’s conclusions regarding the baseline operational validation, proposed airspace enhancements, and proposed airport enhancements.

7.1 Conclusions of FAOR, FALE, and FACT Baseline Operational Capacity Validation The baseline operational capacity validation was completed through analysis of operational standards and procedures, data and statistical analysis of operational flight data provided by both ATNS and ACSA, and the modeling of general traffic flow through the study airports using Metron Aviation’s IACM.

Our conclusions about the declared baseline capacity for the study airports are as follows:

• FAOR declares a valid 60-movement hourly capacity. This capacity aligns with IACM’s analytical capacity and with the low number of instances in which demand actually exceeds the declared capacity.

• FALE declares a valid 24-movement hourly capacity. This declared capacity is significantly lower than the IACM declared capacity; therefore, the declared capacity is not validated through IACM, but this does not mean that the declared capacity is invalid. Further investigation is needed into the airspace constraints surround FALE and how these constraints affect the separation requirements for aircraft operating into and out of FALE.

• FACT declares a valid 30-movement hourly capacity. This capacity aligns with IACM’s analytical capacity and with the low number of instances in which demand actually exceeds the declared capacity.

Other conclusions about the study airport baseline capacities:

• The minimum separation for departures is two minutes; therefore the theoretical maximum number of departures on a single runway for an operational hour is 30. In order to increase departure capacity for a departure-only runway (e.g., FAOR) this value must be reduced.

• Arrival separation minima need to be reduced from 5 nm to increase arrival capacity for arrival-only runway operations (e.g., FAOR).

• Although the FALE departure ROTs using RWY06 differ from those at FACT and the demand mix is considerably different between the two airports, IACM showed a similar alternating arrival and departure capacity (40 movements per hour for FALE and 35 movements per hour for FACT). This result suggests that there exists a similar constraint at the two airports that is more of a factor for alternating operations. The factors to explore are arrival and departure separation minima.

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Conclusions about IACM:

• IACM provided a parameter-based, fast-time estimate of each study airport’s capacity. In all cases, IACM calculated operational capacities that were close to the airports’ declared capacities, even though the actual peak hour demand may be less (which is the case at FALE)

• Individual airport results from IACM can be compared to show similarities in capacity constraints (e.g., FALE and FACT having similar capacities, but different parameters) that can lead to specifically identifying overall throughput constraints (e.g., separation minima).

7.2 Conclusions of Airspace and Operational Capacity Enhancements The modeled results show that airspace capacity constraints are most affected by the separation minima for both the arrivals and departures. In order to effectively increase capacity at the airport, investment must be made to reduce these minima. Below are some possibilities for such investments:

• Safe reductions in the minima to 3 nm have been accepted at major airports around the world. This reduction was recently implemented in the Johannesburg TMA in 2012.19 If the 3NM separaton in the TMA (FAOR) can optimize ROTs, taking other separation criteria into consideration, then it should be investigated.

• The reduction of departure separation minima will need to be accompanied by improved techniques in departure readiness and sequencing. The development of more surface area for multiple departure queues and holding pads can enable techniques for capacity increase, such as grouping by wake turbulence and performance-based SIDs. The optimization of departure sequencing may also be facilitated through implementation of ramp control and traffic management coordination.

• In lieu of the reduction of separation minima on either arrival or departure, the long term ability to have runway assignments based in part by aircraft turbulence categories to achieve a more homogeneous sequencing of aircraft with similar performance capabilities could minimise the variance in separation between successive operations. This measure would only produce small capacity gains, and requires clear definitions on what aircraft are considered “the same.” Some of these practices may be adopted for airport slot assignments, but those efforts need to be recognised in CTOT assignment as well. Further to this, optimization of runway throughput could be gained by not exclusively reserving arriving and departure flights to a particular runway (RWY03L/21R – departures and R03R/21L – arrivals).

• Investments in data link and PBN have been shown to improve overall airspace capacity, thereby improving efficiency of flows into and out of the study airports, and would also contribute significantly to achieving the other separation-related benefits discussed above.

• Constraints in the TMAs could lead to capacity restrictions as more demand is placed on the TMAs by satellite airfields. Airspace redesign will mitigate some impact of this new demand, particularly in the case of the FAOR TMA; therefore investment in this capability would help optimise traffic flows.

19 See CAA Aeronautical Information Circular 40.15 for more information on the new separation minimum in the Johannesburg TMA.

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7.3 Conclusions of Specific Airport Infrastructure Capacity Enhancements The modeled results also show the impact of ROT on the airports’ capacities. Many of the suggested enhancements provide better surface flow that can ultimately reduce the ROT of operations, thereby increasing the airports’ capacity.

Observations that could increase efficiency at FAOR:

• Add RETs to RWY03L/21R. Although a primary departure runway, RWY03L/21R is seldom used for arrivals, but is expected to serve more arrivals as demand continues to increase. The RETs would reduce the ROT for any arrivals, thereby increasing efficiency of the airport’s operations.

• Add RETs to RWY03R/21L. As the primary arrival runway, south flow operations would benefit from the addition of an RET for RWY21L and north flow operations would benefit from the refinement of the current fillets of the connection to TWY Echo. These enhancements could reduce ROTs by enabling more high speed exits.

• Extend the pavement at the end of RWY03L to enable more effective departure queuing for wake vortex category and performance-based SIDs. More effective departure queuing can also help with managing multiple departures with CTOT and effectively reduce the average achieved in-trail departure separation.

Observations that could increase efficiency at FALE:

• Adding parallel taxiway access can reduce conflicts and facilitate taxi queuing. This will reduce the impact of the hot spot located at the intersection of Alpha, Bravo, Golf, and November taxilanes and reduce delays related to head-to-head taxing.

• Adding RETs to RWY24 can minimise arrival ROT by allowing direct access to Alpha and Bravo aprons instead of limiting the flights not capable of making an exit at taxiway Golf to use the full runway length to exit at taxiway Charlie Observations that could increase efficiency at FALE.

Observations that could increase efficiency at FACT:

• The addition of By-Pass Taxiways at each of the RWY01/19 thresholds enable additional departure queuing distance, and the potential to optimise the sequence of departures as aircraft could enter the runway via the By-Pass Taxiway entry points, giving each runway an additional point of entry.

• Increasing the fillet pavement for Taxiways Charlie and Echo to a radius of 95 would facilitate at least a 90 degree exit in south flow and better visibility for intersection departures.

7.4 Recommended Enhancements The airspace and airport analyses conducted in the previous sections, and collaboration with ATNS and ACSA resulted in the following agreed upon capacity and/or efficiency enhancements. The implication is that these enhancements will be the basis for further study and elaboration and will ultimately lead to the joint final capacity enhancement roadmap for ATNS and ACSA. Eventually, this list will help ATNS, ACSA, and other stakeholders make informed decisions regarding the implementation of the proposed

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57 capacity enhancements. Table 9 lists the enhancements and a brief description of the specific recommendations.

Table 9: Recommended Enhancements

Enhancement Description of Recommendation

Minimum required separation on final approach Separation on final approach will be optimized so as to allow maximum throughput at all airports.

Pilot reaction time (PRT) PRT will be measured and remedial action taken through collaborative action with aircraft operators

Departure sequencing Recommendations will be made to implement a departure sequencing tool which will be integrated with the AFT.

Multiple Line up Queues So as to facilitate tactical manipulation of departures recommendations will be made to expand holding point areas. This will include recommendations to increase the pavement areas at the RWY03L holding point.

Standard taxi routes Recommendations will be made to create standard taxi routes.

Performance based standard instrument PBN arrivals and departures will be departures and arrivals recommended.

Arrival/Departure Balancing Add RETs to RWY24 can minimise arrival ROT by allowing direct access to Alpha and Bravo aprons instead of flights vacating on taxiway Charlie.

Airspace Review and redesign Recommendations will be made where airspace review and redesign is required.

Low Visibility operations The present LVP are restrictive- recommendations will be made to optimize operations during LVPs.

Intersection Departures Recommendations will be made on promoting intersection departures.

Conditional Clearances Practices of conditional clearances will be recommended.

Limiting operations of certain aircraft Recommendations will be made on how to restrict categories during periods during the day. certain aircraft categories during peak periods to optimize operations. This could include performance and weight category criteria.

Slot Optimization and CTOT compliance Recommendations will be given on how to optimize slot allocation processes, procedures and tools.

Supervisory staff in ATCCC Recommendations will made on supervisory staff allocation in ATCCC for supervisory and better liaison within the ATCCC, CAMU, and adjoin sectors.

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Enhancement Description of Recommendation

Addition of RETs Recommendations for the addition of or repositioning of RETs at FAOR and FACT.

Airspace Flow Programs The current methodology of implementing Airspace Flow Programs at all 3 airports are not efficient, better application of software and/or procedures to be recommended.

VFR traffic included in traffic demand VFR traffic which do not file flight plans are not predictions included in demand predictions (particular reference to FACT) which leads to inaccurate predictions of demand leading to inefficiencies when TMI’s are implemented. Recommendations on flight planning procedures and adaptation of AFT procedures to be recommended.

Efficient Runway utilization RWY03L/RWY21R are used almost exclusively for departures and RWY03R/RWY21L for arrivals (as per SSI’s) Recommendations will be made to utilize mixed operations on the runways.

Near-term Implementation of Master Plan Master Plan TWY extensions for Alpha and elements to enhance taxiway systems Charlie to enable bypass sequencing and multiple runway entry points for RWY3L at FAOR

Utilization of remote gates (FALE) Assign unscheduled GA flights to specifically limited remote gates on the Bravo Apron.

Addition of holding point lines Recommendation to paint Cat 1 holding point lines at FALE and FACT as only Cat 2 lines exist presently.

Improved CDM practices Recommendations will be made on latest practices in CDM and how they can be applied in the South African environment.

Independent Parallel RWY Operations at FAOR Recommendation will be made on how to institute for RWY03 independent operations for RWY03

Segregated Parallel RWY Operations at FAOR Recommendation will be made on how to institute for RWY21 (due to negative threshold stagger) segregated Parallel operations for RWY21

7.5 Next Steps The technical analysis validates the current capacity of each of the three study airports and points to main contributors of their capacity constraints. The study also validates some best practices at other major airports around the world that have proven to increase efficiency of ATC operations. Finally, the study suggests some specific enhancements to each of the airport’s infrastructure that could increase overall efficiency.

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Implementing this study’s recommendations requires an understanding of how much relative capacity can be gained at each airport for each enhancement. The following tasks will be completed next:

• Assess the relative impact of changes to separation minima, ROTs, and fleet mix based on the suggestions and findings about the capacity enhancements in this document.

• Find the relative trade-offs and future bottlenecks of the study airports’ throughput by adjusting their parameters in IACM and validating such changes with additional analytic studies of the airports’ future states.

• Cross reference the suggested capacity enhancements at the study airports with regulatory policy and develop stakeholder impacts (see Section 6) to validate the ability to develop, deploy, construct, and use the capacity enhancements.

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Appendix A Background Information on IACM Development

A.1. Airport Capacity A.1.1 Definition of airport capacity A common definition of airport capacity is “the maximum number of operations (arrivals and departures) that can be performed during a fixed time interval at a given airport under given conditions such as runway configuration and weather conditions.”20 This definition is typically referred to as the maximum throughput definition of airport capacity [3]. However, most runways do not operate at their maximal capacities. Heavy fog can temporarily reduce a runway’s capacity to zero landings per hour for one hour. Noise restrictions can reduce a runway’s capacity to zero for several hours a day. Hence, alternative definitions of airport capacity have been proposed. They include: • Practical hourly capacity (PHCAP) which is defined as “the expected number of movements that can be performed in 1 hour on a runway system with an average delay per movement of 4 minutes.”21 • Sustained capacity defined as “the number of movements per hour that can be reasonably sustained over a period of several hours.” • Declared capacity which is defined as “the number of aircraft movements per hour that an airport can accommodate at a reasonable level of service.” The capacity of an airport is affected by a large variety of factors, including22 : • Number and geometric layout of runways • Weather conditions, which include the impact of tailwinds and crosswinds, ceiling and visibility, as well as convective weather in the vicinity of the airport • Air traffic management (ATM) separation requirements • Traffic demand (mix of aircraft using the airport and mix of movements on runways) • Environmental factors, such as noise restrictions • Access to corner posts, and en route flow constraints The overall capacity of an airport can be decomposed into two interdependent capacities: arrival capacity and departure capacity. The relationship between these capacities is a convex, nonlinear function,23,24,25 a general form of which is shown in Figure 36.

20 Gilbo, E.P., Airport capacity: Representation, estimation, optimization. IEEE Transactions on Control Systems Technology, 1993. 1(3): p. 144-154. 21 de Neufville, R. and Odoni, A.R., Airport systems: Planning, design, and management. 2003, New York: McGraw-Hill. 22 Stell, L., Airport configuration planner with optimized weather forecasts. 2007, Metron Aviation: Herndon, VA

23 Newell, G.F., Airport capacity and delays. Transportation Science, 1979. 13(3): p. 201-241. 24 Swedish, W.J., Upgraded FAA airfield capacity model. 1981, The MITRE Corporation: McLean, VA. 25 Gilbo, E.P., Optimizing airport capacity utilization in air traffic flow management subject to constraints at arrival and departure fixes. IEEE Transactions on Control Systems Technology, 1997. 5(5): p. 490-503.

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Departure capacity

Arrival capacity

Figure 36: General form of arrival/departure capacity curve

Airport capacity models, including those discussed in the following sections, make certain assumptions regarding the shape of this curve and attempt to estimate characteristic points defining this arrival/departure functional relationship. Furthermore, the impact of weather on airport capacity is frequently accounted for by clustering weather conditions into several operational categories depending on ceiling and visibility conditions at the airport. For example, if ceiling and visibility at an airport are within certain thresholds, a specific operational category is used at the airport, such as Visual Flight Rules (VFR), Marginal VFR (MVFR), Instrument Flight Rules (IFR), and Low IFR (LIFR). In practice, capacity curves are determined for each of these operational categories. Some models assume a smaller set of operational categories (e.g., just two – VRF and IFR), while some use a larger set obtained by dividing one or more categories into subcategories. A.1.2 Airport capacity estimation Over the years, a significant number of airport capacity models have been developed.26,27,28 These models can be roughly divided into two major groups: analytical and simulation. Analytical models use abstract mathematical representations of airport operations and derive estimates of capacity by evaluating these expressions.29 In contrast, simulation models create virtual components of airport operations and simulate their flow. Based on the measurements of the flow at specific locations, simulation models determine appropriate estimates of airport capacity.

26 Blumstein, A., An analytical investigation of airport capacity. 1960, Cornell Aeronautical Laboratory: Ithaca, NY. 27 Hockaday, S.L.M. and Kanafani, A.K., Developments in airport capacity analysis. Transportation Research, 1974. 8(3): p. 171-180. 28 Lee, D.A., Nelson, C., and Shapiro, G., The aviation system analysis capability: Airport capacity and delay models. 1998, Logistics Management Institute: McLean, VA. 29 Odoni, A.R., Bowman, J., Delahaye, D., Deyst, J.J., Feron, E., Hansman, R.J., Khan, K., Kuchar, J.K., Pujet, N., and Simpson, R.W., Existing and required modeling capabilities for evaluating ATM systems and concepts. 1997, Massachusetts Institute of Technology: Cambridge, MA.

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In general, analytical models are typically macroscopic in nature. They use abstract, simplified, and aggregate quantities of interest, and model airport operations at a relatively low level of detail. Hence, the estimates produced by these models are typically approximate and more suitable for strategic decision support rather than tactical support. The benefits of analytical models include their speed (they do not require extensive computations) and relatively modest setup requirements. In contrast, simulation models provide much greater level of detail in modeling airport operations at the expense of significantly longer computational time. An extensive survey of available airport capacity models, including their advantages and limitations. As Integrated Airport Capacity Model (IACM) is an analytical airport capacity model, the comparisons presented in this report focus on analytical airport capacity models for strategic decision support. Thus, several of the most prominent examples of analytical models are described in more detail below. The selection of the reported models was based on their incorporation of weather factors (ceiling, visibility, wind) in the process of developing capacity estimates.

a) FAA Airfield Capacity Model The FAA Airfield Capacity Model is one of the earliest stochastic analytical models for airport capacity. The model was initially developed in the late 1970s and later modified by the FAA and the MITRE Corporation. The model takes as input runway configuration and operating procedures in use and estimates the capacity of the runway system. The model’s output is hourly capacity estimates for 15 typical airfield configurations. These configurations range from a single active runway configuration to up to four active runways. The FAA model assumes that each of the 15 considered configurations can be represented as a combination of four fundamental configurations: • Single runway configuration • Closely-spaced parallel runway configuration • Intermediate-spaced parallel runway configuration • Intersecting runway configuration For each fundamental configuration, a capacity estimate is produced using the underlying single-runway model. The single-runway model assumes that the shape of the general arrival/departure capacity curve discussed earlier can be defined by three points: • Point 1—Runway is dedicated to departures. • Point 2—Runway is dedicated to arrivals. • Point 3—Runway serves the same number of arrivals as at Point 2, but also inserts a number of departures in the arrival stream. The shape of the FAA Airfield Capacity arrival/departure capacity curve is shown in Figure 37.

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Departure capacity

Point 1: All departures

Point 3: Freely inserted departures

Point 2: All arrivals

Arrival capacity

Figure 37: Shape of arrival and departure capacity curve for the FAA Airfield Capacity Model

The FAA Airfield Capacity Model requires the following inputs: • Runway configuration in use • Types of operations assigned to each runway (arrivals, departures, mixed) • Aircraft mix on each runway • Separation requirements for each runway • Aircraft characteristics (speed, runway occupancy times, etc.) and their associated standard deviations • Length of final approach for each runway • Weather inputs (ceiling and visibility) to determine flight rules The model produces hourly estimates of the runway configuration capacity for any arrival-departure ratio, ranging from all arrivals (100% arrivals, 0% departures) to all departures (0% arrivals, 100% departures), and departures injected into the arrival stream at a rate of 10%. The advantages of the FAA Airfield Capacity Model include its maturity and ability to model most commonly occurring runway configurations. The model has also been thoroughly validated throughout the 1970s and 1980s. One of the model’s significant drawbacks is its inferior logic for inserting departures between two arrivals which, may lead to inaccurate capacity estimates. This is particularly evident in the case when a runway handles approximately equal numbers of arrivals and departures.

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b) Boeing Airport Capacity Constraints Model The Boeing Airport Capacity Constraints Model starts with the “single runway capacity constraints model” which produces arrival, departure and mixed operation capacities at each of the 35 OEP airports in visual, marginal visual and instrument meteorological conditions.30 The “runway interaction and airfield constraints” model introduces 16 multiplicative parameters associated with runway interaction, airfield and airspace conditions that are identified as potentially reducing airport capacity. For each airport in each weather condition the single runway capacities, corresponding to the most commonly used operating configuration (as identified from the 2004 Airport Capacity Benchmark Report31), are multiplied by all of the applicable parameters, and their sum is taken. The FAA Benchmark’s hourly capacities for each airport in each weather condition are used to calibrate these equations and solve for a single set of parameter values that is optimal (in a least squares sense) for all the airports modeled.

c) LMI Airport Capacity Model Logistics Management Institute (LMI) Airport Capacity Model is also an example of an analytical stochastic model for determining the capacity of an airport.32 It considers two primary constraints on airport capacity: runway occupancy time (ROT) (the time when an arriving aircraft crosses the end of runway until it turns off the runway), and separation that must be maintained between any two airborne craft in the terminal environment. The LMI model provides estimates of airport capacity that can be achieved with 95% confidence in the presence of continuous demand. As with the FAA Airfield Capacity model (Section a) ), it uses the general arrival/departure capacity curve, but defines its shape by the following four points: • Point 1—Runway is dedicated to arrivals. • Point 2—Runway serves the same number arrivals as at Point 1, but also inserts a number of departures in the arrival stream. • Point 3—Equal numbers of arrivals and departures. • Point 4—Runway is dedicated to departures. The shape of the LMI Airport Capacity arrival/departure capacity curve is shown in Figure 38.

30 Alcabin, M.S., Schwab, R.W., Coats, M.L., Berge, M.E., and Kang, L.S. Airport capacity and NAS-wide delay benefits assessment of near-term operational concepts. in 6th AIAA Aviation Technology, Integration and Operations Conference (ATIO), September 25-27, 2006. 2006. Wichita, Kansas. 31 Federal Aviation Administration, FAA airport capacity benchmark report, U.S. Department of Transportation, Editor. 2004: Washington, DC. p. URL: http://www.faa.gov/events/benchmarks. 32 Lee, D.A., Kostiuk, P.F., Hemm, R.V., Wingrove, E.R., and Shapiro, G., Estimating the effects of the terminal area productivity program. 1997, Logistics Management Institute: McLean, VA.

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Departure capacity

Point 4: All departures

Point 3: Alternating arrivals and departures

Point 2: Freely inserted departures

Point 1: All arrivals

Arrival capacity

Figure 38: Shape of arrival and departure capacity curve for the LMI Airport Capacity Model

The model provides capacity curves for five weather conditions depending on inputs: visual approaches (VMC1), radar approaches with visual completion (VMC2), and three categories of instrument approaches (IMC1, IMC2, and IMC3). The LMI Airport Capacity Model explicitly takes into account the probabilistic nature of airport operations. This is achieved by modeling the factors impacting the airport capacity as random variables. These factors include weather, traffic characteristics, and level of technology available. In particular, the model requires the following inputs: • Aircraft mix • The mean and standard deviation of the approach speed for each aircraft type • The mean and standard deviation of the arrival runway occupancy times for each aircraft type for all weather conditions (Instrument Meteorological Conditions [IMC], Visual Meteorological Conditions [VMC]) • The mean and standard deviation of the departure runway occupancy times for each aircraft type • The miles-in-trail (MIT) separation minima for all pairs of aircraft types and weather conditions (IMC, VMC1, VMC2) • The length of the common approach path • The uncertainty of the position of the aircraft specified by the standard deviation of its location • The mean and standard deviation of the communication time delay • The standard deviation of the wind speed encountered by aircraft on the final approach path • The ceiling and visibility minima for all weather conditions (VMC1, VMC2, IMC1, IMC2) The initial version of the LMI model considered only individual runways. It was later extended and renamed to the ASAC Airport Capacity Model to account for the airport’s geometry and the strategy employed, i.e., which airport runways are used and how they are used (arrivals, departures, mixed). The overall capacity is then derived by combining capacity curves obtained for active runways in this

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66 configuration. This is done by successively combining pairs of capacity curves, assuming that all of the frontiers are piecewise linear. This extended model provides estimates of airport capacity with closely- spaced parallel runways, including “staggered” departures and arrivals. The advantages of the LMI Airport Capacity Model include its comprehensive and rigorous approach to modeling a wide variety of operational conditions as well as its “controller-based view” of airport operations. The disadvantages include non-satisfactory logic for inserting departures between arrivals (it does not include a minimum distance separation between the departure and the following arrival) and unconventional definition of capacity (95% confidence instead of traditionally used maximum throughput rate), which may result in obtaining lower capacity estimates.

d) MACAD models A new class of integrated analytical airport capacity and delay models has been recently proposed and implemented in a support system called MAN-TEA Airfield Capacity And Delays (MACAD).33 These models attempt to provide strategic decision-support for modeling airfield operations as a whole by encompassing the interactions among various elements of the airfield. Thus, they provide estimates of the capacity and delays associated with major elements of the airfield, including arrival runways, arrival taxiways, gate/apron area, departure taxiways, and departure runways. MACAD requires the following inputs for its integrated models: • Possible runway configurations for an airport • Separation requirements for aircraft • Airfield’s operational characteristics • Demand profile for 24-hour period Given these inputs, the model first defines capacity bounds for all possible runway sets and configurations, which are subsequently used for estimating delays to arriving aircraft. Next, these estimated delays are used to compute a revised schedule of arrivals at the apron area. This revised schedule is subsequently utilized for determining the departure times of departing aircraft from their apron stands. A subset of the MACAD models includes stochastic analytical models supporting analysis of single runway configurations as well as configurations with two simultaneously active runways. They also utilize the same set of points as the LMI Airport Capacity Model (see Figure 38). The MACAD airport capacity model is similar to the LMI model. Some key differences include: • Includes an additional constraint that does not allow a departure to start to roll unless the next arrival is farther than a user-specified distance from the runway threshold • Uses a simpler approach to the all-departures capacity, just computing the weighted average of inter-departure separation times at the runway threshold • Models the position uncertainty of an aircraft by adding an appropriate length to the miles-in-trail requirements of approaching aircraft rather than by adding a value into the computation of the standard deviation of the inter-arrival times

33 Stamatopoulos, M.A., Zografos, K.G., and Odoni, A.R., A decision support system for airport strategic planning. Transportation Research Part C, 2004. 12: p. 91-117.

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A.2. Weather data This section presents brief descriptions of two weather forecast systems, namely Corridor Integrated Weather System (CIWS) and Rapid Update Cycle (RUC). The weather data produced by both systems are utilized by the components of the IACM. More extensive overviews of both systems and weather data they produce can be found in our previous report.34 A.2.1 Corridor Integrated Weather System CIWS is a fully-automated weather analysis and forecasting system developed by MIT Lincoln Laboratory (MIT-LL).35 It extends the functionality of the Integrated Terminal Weather System (ITWS), also developed by MIT-LL, by considering not only weather conditions in the terminal area but also en route weather constraints. CIWS integrates data from weather radars, satellites, surface observations, and numerical models. It provides state-of-the-art, high-resolution, three-dimensional storm forecasts (precipitation and echo tops values), including explicit detection of storm growth and decay. CIWS currently provides 0-2 hour convective weather forecasts for the entire contiguous United States (CONUS). It offers nowcasts and forecast of the precipitation (Vertically Integrated Liquid (VIL)) and echo tops fields. The spatial resolution is equal to 1 km and the update time is 2.5 minutes. Thus, CIWS provides high quality convective weather analysis and forecasts which are utilized by the IACM’s Terminal Capacity Model. The only drawback of CIWS is the length of the forecast interval, which is currently limited to only 2 hours. On the other hand, TFM planning generally requires up to at least a 6- hour forecast. A.2.2 Rapid Update Cycle RUC is an operational weather prediction system developed by the National Oceanic & Atmospheric Administration (NOAA) and the National Centers for Environmental Protection (NCEP). The RUC system consists of two major components36, 37: • A numerical forecast model • An analysis/assimilation system that initializes this model RUC was designed to provide numerical forecasts for users who require accurate weather data in the time period from 0 to 12 hours into the future. The 12-hour forecasts are produced every 3 hours while 0-9 hour forecasts are generated on an hourly basis. RUC offers a variety of other weather products, including surface winds (speed, direction, and gusts), and ceiling and visibility forecasts. These RUC products have been incorporated into IACM’s Airfield Capacity Model.

34 Myers, T., Brennan, M., Ermatinger, C., Kicinger, R., Neskovic, D., Swol, D., and Stell, L., TFM domain integration research: FY2007 final report. 2007, Metron Aviation, Inc.: Herndon, VA. 35 Evans, J.E. and Ducot, E.R., Corridor Integrated Weather System. Lincoln Laboratory Journal, 2006. 16(1): p. 59-80 36 Benjamin, S.G., Brown, J.M., Brundage, K.J., Devenyi, D., Grell, G.A., Kim, D., Schwartz, B.E., Smirnova, T.G., Smith, T.L., Weygandt, S.S., and Manikin, G.S., RUC20 - The 20-km version of the Rapid Update Cycle. NWS Technical Procedures Bulletin, 2002. 490. 37 Benjamin, S.G., Smirnova, T.G., Brundage, K.J., Weygandt, S.S., Smith, T.L., Schwartz, B.E., Devenyi, D., Brown, J.M., and Grell, G.A. A 13-km RUC and beyond: Recent developments and future plans. in 11th Conference on Aviation, Range and Aerospace Meteorology. 2004. Hyannis, MA: American Meteorological Society.

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Appendix B Integrated Airport Capacity Model

B.1. Overview The Integrated Airport Capacity Model (IACM) is an analytical airport capacity model which provides probabilistic decision support for TFM planning. It considers the impact of both terminal airspace and runway system constraints on airport capacity. IACM computes and displays probabilistic airport capacity estimates that take into account weather forecasts and predicted demand. This is achieved by three major IACM components as shown in Figure 39: 1. Terminal Capacity Model (TCM) 2. Airfield Capacity Model (ACM) 3. Multi-criteria Capacity Forecast Integrator (MCFI) TCM takes into account predicted weather conditions in the terminal airspace, including precipitation and echo tops forecasts, and produces probabilistic capacity estimates (one probability distribution per look- ahead hour) for the terminal airspace. ACM computes probabilistic capacity estimates of the runway system based on predicted weather conditions at the airport surface (i.e., ceiling, visibility, and winds). These independently-obtained capacity distributions from TCM and ACM are subsequently integrated by the MCFI component, which produces an integrated probabilistic airport capacity forecast for each look- ahead hour.

Figure 39: Major IACM components and its inputs

Figure 39 shows that IACM incorporates two major groups of inputs: • Real-time inputs, which include weather data (ceiling, visibility, wind, precipitation, and echo tops) and projected demand (number of arrivals and departures, and their weight class mix).

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• Pre-processed inputs based on analysis of historical data which include forecast prediction error (FPE) models defining probabilistic error distributions for weather forecasts and airport surface data providing historically used runway configurations at an airport, expected runway occupancy times and approach speeds as well as their variations. These inputs are discussed in more detail in the following subsection.

B.2. Major inputs and outputs Figure 40 illustrates primary IACM inputs and presents its major outputs.

Figure 40: Primary IACM inputs and outputs

Real-time inputs are shown on the left-hand side of Figure 40 and are discussed in Section B.2.1. In addition to real-time inputs, IACM incorporates five major types of pre-processed inputs: airport layouts and geometries (Section B.2.2a) ), operational standards and procedures (Section B.2.2b) ), weather forecast prediction error models (Section B.2.2c) ), airport runway configurations (Section B.2.2d) ), and runway occupancy times and approach speeds (Section B.2.2e) ). IACM produces three major types of outputs (Section B.2.3): probabilistic airport capacity estimates optimized for arrivals, probabilistic airport capacity estimates optimized for departures, and probabilistic airport capacity estimates optimized for predicted demand. Individual types of inputs and outputs are discussed below. B.2.1 Real-time inputs This group of IACM inputs includes real-time weather forecast data providing ceiling, visibility, wind, precipitation, and echo tops data used by IACM components. In particular, at the current stage of model development, the following sources of weather forecast data are used: • Forecasted precipitation and echo tops fields spanning the entire terminal airspace surrounding an airport at each look-ahead hour • Point estimates of forecasted ceiling, visibility, and wind at airport surface at each look-ahead hour

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Real-time demand prediction provides IACM with projected numbers of arrivals, departures, and their weight class mix in hourly bins. One hourly bin with predicted demand data is created for each capacity forecast hour. The demand predictions are subsequently incorporated within the ACM component and utilized to produce probabilistic airport capacity estimates of the runway system. In addition to the real-time inputs, IACM incorporates several other types of pre-processed inputs, which are discussed below. B.2.2 Pre-processed inputs Figure 40 shows five major types of pre-processed inputs utilized by IACM: airport layouts and geometries, operational standards and procedures, weather FPE models, airport runway configurations, and runway occupancy times and approach speeds. They are obtained by either processing historical data or by extracting relevant pieces of information from ATC manuals, FAA documents, standards, and operational procedures.

We describe each of these pre-processed inputs below.

a) Airport layouts and geometries Airport layout and geometry inputs provide basic information, required by IACM components, about an airport and its surroundings. In particular, Figure 41 shows types of inputs included in this group: geospatial data and Traffic Flow Management System (TFMS) data.

Figure 41: Types of airport layout and geometry inputs Geospatial data obtained from geographic information systems (GIS) (e.g., Google Earth38) provide information on the geospatial location and orientation of an airport’s runways and its departure and arrival fixes. These data, combined with information available in airport diagrams obtained from FAA’s Operational Information System (OIS)39, were used to define airport adaptation files. An airport

38 Google Inc., Google Earth. 2009: Mountain View, CA. 39 Federal Aviation Administration. Operational Information System. 2009 [cited 2009 December 3, 2009]; Available from: http://www.fly.faa.gov/ois/

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71 adaptation file is an XML file that defines a basic model of the airport’s runway system, including the number and names of its runways and their length, width, and spatial orientation. Besides airport adaptation data, ACM’s Runway Capacity Model (RCM) requires information about the length of an airport’s common approach path. In order to calculate it, we used historical TFMS data and analyzed flights’ tracks in the vicinity of the airport.

Air Traffic Air Traffic Finally, the TCM component requires data Airport Capacity ICAO/FAA Control Control Benchmark recommendations on the most frequently used arrival and Handbook Report Handbook departure fixes at an airport, which are subsequently included in this terminal Arrival and Ceiling and Wake Crosswind airspace model. We analyzed historical departure visibility vortex and tailwind TFMS data for a month-long period of time separations thresholds separations thresholds to determine the busiest fixes at each of the modeled airports. Operational Standards and Procedures b) Operational standards and procedures Operational standards and procedures define Figure 42: Types of operational standards and constraints on minimum aircraft separation procedures inputs in the terminal airspace and along the common approach path. They also define required weather minima (ceiling and visibility minima) for the flight rules in which an airport operates, i.e., VFR, MVFR, and IFR, and maximum crosswind and tailwind thresholds for using airport runways. Figure 42 shows the types of operational standards and procedures used as inputs to IACM and the sources from which the data were extracted. Specifically, the ATC handbook40 provides required arrival and departure separations as well as wake vortex separations incorporated in the ACM. All values for the assumed separation standards. Ceiling and visibility minima defining airport’s flight rules are defined independently for each major airport. IACM incorporates ceiling and visibility minima from the 2004 Airport Capacity Benchmark Report. Finally, the International Civil Aviation Organization (ICAO)41 and FAA42 provide recommendations for crosswind and tailwind thresholds, which define usability of airport runways.

c) Weather forecast prediction error models IACM explicitly incorporates weather uncertainty in capacity estimation through the use of FPE models compiled using historical weather data, including convective weather in the terminal airspace, and surface winds (direction and strength), cloud ceiling height, and visibility at the airfield. FPE models are statistical error models that characterize the forecast accuracy for a specific weather product (e.g., ceiling) by forecast period. The FPE models are pre-processed and provided as inputs to the ACM and TCM components.

40 U.S. Department of Transportation, Order JO 7110.65S: Air traffic control, U.S. Department of Transportation and Federal Aviation Administration, Editors. 2008: Washington, DC. 41 International Civil Aviation Organization, Performance-based navigation manual. 2008, ICAO: Montréal, Canada. 42 U.S. Department of Transportation and Federal Aviation Administration, Airport design. Advisory circular 150/5300-13, U.S. Department of Transportation and Federal Aviation Administration, Editors. 1989: Washington, DC.

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For RUC weather data, FPE models were created for surface wind, cloud ceiling height, and visibility. The parameters of each error model were estimated separately for each airport using a historical database of RUC forecast and analysis (i.e., nowcast) data. For analysis purposes, data was combined from all RUC grid points that are within a specified distance (e.g., 200 km) of the airport. For surface wind and visibility predictions, forecast accuracy distributions were determined based on an analysis and evaluation of the historical data in terms of bias and standard deviation of the forecast accuracy, by look-ahead time. Ceiling forecast accuracy was characterized using a categorical logistic regression model. To evaluate the accuracy of the RUC forecast data, we used the RUC hourly nowcasts, which were based on the most recent observational and assimilated meteorological data available, as the baseline against which we compared the RUC forecasts. For example, for a 3-h forecast valid at 1200Z, the forecasted values of surface wind, Airport Runway Configurations ceiling, and visibility were compared with the respective RUC nowcast analysis values at 1500Z. Runway Runway Runway Historical Preferred configurations configurations configurations FPE models for precipitation and echo runway runway and their and their and their configurations configurations tops data are defined differently. frequencies frequencies frequencies The TCM component relies on an FPE model of the predicted available National Traffic Operational Traffic Flow air lane width at each fix in the Management Information ASDE-X Management ASPM terminal airspace. Available air lane Log (NTML) System (OIS) System (TFMS) width is a measure of the lateral spacing between regions of significant Figure 43: Sources of data considered for determining convective weather activity within the sets of historical runway configurations climb or descent profiles of aircraft in the terminal area based on the Weather Avoidance Altitude Field (WAAF).43 A fix is deemed open for use only when the available air lane width exceeds the minimum required threshold, nominally eight nautical miles. Air lane width prediction accuracy was estimated empirically by comparing predicted and actual air lane widths from June 2008.

d) Airport runway configurations

In order to develop and test methods for estimating available runway configurations from weather forecasts, we require a source of historical configurations at selected airports. Figure 43 shows types of data sources considered in the process of defining historically used runway configurations at each of the modeled airports. We originally considered using the Aviation System Performance Metrics (ASPM) database, but it did not provide sufficient completeness or accuracy for our needs.

We next investigated deducing configuration from historical surface surveillance (Airport Surface Detection Equipment, Model X [ASDE-X]) data. We developed a simple algorithm to extract arrivals and

43 Evans, J.E., Weber, M.E., and Moser, W.R., Integrating advanced weather forecast technologies into air traffic management decision support. Lincoln Laboratory Journal, 2006. 16(1): p. 81-96.

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73 departures from the ASDE-X data. The result was an historical record of the times that each runway (and direction) was actually used for arrivals and/or departures. This record is not quite the same as a record of configurations in use. The distinction is that if a given runway was not in use at some time, there is no way to determine whether that was because it was not part of the then-current configuration or because no flights chose to use it. For example, runways far from the terminal might not be used if a closer runway is available and not congested. While the ASDE-X-based approach worked well, acquiring sufficient ASDE historical ASDE-X data proved to be too difficult. We also considered estimating configurations from archived TFMS data, which is readily available. For our analysis we used only SMA TZs from the TRACONs. These are sent at approximately 20-second intervals and appear to be highly accurate, as opposed to TFMS TZs from other sources, which are sent approximately every minute and have lower accuracy. For arrivals, we found that it was relatively easy to deduce the runway from the TZ data. This was because arrivals tend to align with the runway from moderately far out and SMA tracks them all the way to the runway. Departures were much more challenging. The biggest problem is that TFMS does not appear to report TZs until after the flight’s departure (DZ) message is generated. While SMA presumably tracks departures on the surface and through takeoff, the data is not published by TFMS until well after takeoff (often several kilometers away). Moreover, departures tend to turn away from the runway immediately after takeoff. The combination of early maneuvering and delayed reporting made it very difficult to project the flight’s trajectory back to a particular runway. After some experimentation, we settled on an approach that used a constant-acceleration model to project the flight’s trajectory backward in time and then selected the runway that was most consistent with the projected trajectory. The technique worked quite well at ATL and DFW, where the departure streams from different runways are well separated. At ORD, there are several pairs of runways whose departure streams intersect (or would if both runways were in use at the same time). There the technique was only marginally successful. Eventually, we settled on using National Traffic Management Log (NTML) data for historical configurations merged with sets of preferred runway configurations reported in FAA OIS. NTML is a manual-entry system, and therefore subject to human error, but spot checks showed the configuration data to be quite consistent with what we deduced using ASDE-X and TFMS data. OIS is an online information system (http://www.fly.faa.gov/ois/) which provides real-time status of the National Airspace System (NAS). It also contains preferred runway configurations for major airports together with their associated airport arrival rates (AARs). The preferred runway configurations listed on the OIS website were extracted and converted into text-based input files.

e) Runway occupancy times and approach speeds Runway occupancy times (ROTs) and approach speeds are utilized by the Runway Capacity Model (RCM), one of the key modules within the ACM component (see Figure 44). As capacity estimates produced by RCM are very sensitive to input ROTs and approach speeds values, we developed and compared two methods for their estimations: a network-based method, which utilizes airport adaptation files, and a grid-based method, which divides the area of the runway system into a grid of uniform cells.

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ROTs and approach speeds are computed for each arriving and departing aircraft using the ASDE-X data. The obtained values are subsequently grouped by operation type and aircraft weight class. Means and standard deviations are calculated for each runway and are used as inputs to IACM. B.2.3 Outputs The IACM incorporates real-time and pre-processed inputs, and utilizes its analytical models to produce three types of outputs for each look-ahead time (see Figure 40): • Probabilistic arrival and departure capacity forecasts optimized for arrivals • Probabilistic arrival and departure capacity forecasts optimized for departures • Probabilistic arrival and departure capacity forecasts optimized for predicted demand The motivation behind reporting these three types of outputs is to Figure 44: Runway provide decision makers with options when setting Airport Arrival occupancy times and Rates (AARs) and Airport Departure Rates (ADRs) for TFM planning approach speed inputs purposes. Depending on the predicted demand profile (e.g., arrival push, departure push, or mix of arrival and departures) and possibly other factors they may consider, decision makers can use IACM compute maximum achievable airport capacity. The next subsection describes major components of IACM.

B.3. Components B.3.1 Terminal Capacity Model TCM produces capacity estimates of terminal airspace around an airport. It uses the WAAF, an extension of the Maxflow/Mincut theory, and computational geometry algorithms44,45 to identify bottlenecks in a flow in the terminal airspace. The idea behind the Maxflow/Mincut approach is to compute the capacity reduction those bottlenecks introduce. TCM takes into account the different climb and descent profiles when identifying airspace blockages or “no fly” zones for departing and arriving flights as illustrated in Figure 45. These no fly zones are then used in computing the mincut for each fix.

44 Mitchell, J.S.B., On maximum flows in polyhedral domains. Journal of Computer and System Sciences, 1990. 40(1): p. 88- 123. 45 Krozel, J.A., Mitchell, J.S.B., Polishchuk, V., and Prete, J.M. Capacity estimation for airspaces with convective weather constraints. in AIAA Guidance, Navigation and Control Conference and Exhibit, August 20-23, 2007. 2007. Hilton Head, SC: American Institute of Aeronautics and Astronautics.

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Figure 45: Climb and descent profiles are considered by TCM when determining airspace blockages or “no fly” zones induced by the WAAF within the terminal airspace

If any segment of the mincut exceeds 8 nautical miles (nm) in length, then the fix is deemed to be “open”, otherwise the fix is “closed” due to weather blockage as shown in Figure 46. In this example, the HUSKY fix is predicted to be closed because the available air lane width computed from the mincut does not exceed the required 8 nm. The threshold of 8 nm was chosen as a generalized Required Navigation Performance (RNP) value to safely navigate through the weather. TCM has the ability to model capacity for any arbitrary RNP value.

Figure 46: TCM identifies open fixes based on those where the available air lane width computed from the mincut exceeds 8 nm

The TCM display is shown in Figure 47, where the availability of each fix is shown during 5-minute intervals. Available fix air lanes are indicated with a “1” to designate open status, while a “0” indicates a fix is closed. We assumed at most one air lane per fix. Red shading is used to highlight time periods when a fix is closed. Gray indicates that the mincut is being reduced close to the threshold level. The total number of available air lanes during each time step is displayed along with the total capacity of the terminal airspace. Total capacity is estimated by assuming a minimum minutes-in-trail separation between aircraft. For this example, we assumed three minutes-in-trail, which means that each open fix can handle 1.7 flights per 5-minute time bin. There are 13 total departure and arrival fixes in the example above, which correlates to a maximum terminal capacity of 22 flights per 5-minute time period or 264 operations per hour.

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Figure 47: TCM prototype display showing predicted fix availability during 5-minute forecast increments

B.3.2 Airfield Capacity Model The second component of IACM is the Airfield Capacity Model (ACM), which computes capacity estimates at the airport surface as a function of projected demand and forecasted weather conditions, specifically surface winds, cloud ceiling height, and visibility. Ceiling and visibility conditions directly affect the meteorological conditions at the airport, determining the separation rules to be used. Wind conditions impart both crosswind and tailwind components upon aircraft, influencing how runway operations are configured. An input to the ACM is a list of historical runway configurations, from which the ACM determines the configurations with highest capacities optimized for arrivals, for departures, and for accommodating predicted demand (characterized as a mix of arrival/departure and weight class counts). Figure 48 shows that the ACM is composed of two component modules, the Runway Configuration Estimator (RCE) and Runway Capacity Model (RCM). In the RCE, statistical models of forecast accuracy are used to generate Monte Carlo simulations of actual weather conditions (wind/ceiling/visibility) for each forecast period. The weather conditions are used to determine runway wind restrictions in each runway configuration, eliminating runways expected to experience crosswinds or tailwinds that are too strong. The RCM takes as input the simulated weather conditions and the projected demand to compute the capacity of each configuration. Depending on the extent of variation in the simulated weather conditions, capacity will vary probabilistically and dynamically across the Monte Carlo simulations, forming a (probability) distribution of capacity values.

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Figure 48: Major elements of the Airfield Capacity Model

Each runway configuration that is evaluated in the RCM is first decomposed into a set of “runway primitives” (e.g., independent, closely-spaced parallel, and crossing runways). The RCM computes a capacity estimate for each of the component primitives using a simple stochastic analytical model. The capacity of the full configuration is obtained by adding the capacities of the component primitives. In this model the controller strategy is to separate adjacent aircraft in time at specified points—at the start of the common path for arrivals, and at the runway threshold for departures—in such a way that all subsequent required separation rules will be satisfied with specified confidence levels. The separation rules to be used are determined from the simulated ceiling and visibility conditions. After finding the minimal controller- imposed separation times between aircraft, the “inter-operation” time is computed as the expected time between adjacent operations (arrivals and departures) crossing the runway threshold. Finally, the capacity is given as the inverse of the inter-operation time.

a) Runway Configuration Estimator The primary inputs to the RCE are pre-processed forecast prediction error (FPE) models, airport runway configurations, and real-time weather forecast data. For the developmental version of IACM, airport runway configurations were obtained using NTML data for historical configurations and OIS data for preferred runway configurations (Section B.2.2d) ). Weather input data, both for FPE development and real-time data, was supplied by the 20-km horizontal resolution version of the RUC weather prediction model (Section A.2.2). The RCE uses a Monte Carlo simulation to generate simulated weather conditions for each forecast look- ahead time. In general, there are greater inaccuracies in forecast predictions with larger look-ahead times. The runways in each runway configuration are checked by the RCE for applicable crosswind and tailwind restrictions, before capacity computations are made by the RCM.

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Real-time weather forecast data The RCE obtains real-time weather forecast data from the RUC weather prediction model. Gridded forecast data is available at hourly cycle times. At each cycle time (i.e., update) RUC provides a nine-hour forecast horizon (at hourly intervals); a 12-hour forecast horizon is available at every three-hour cycle time. The IACM currently only uses up to six-hour time forecast horizons. The RUC weather products used by RCE include surface visibility, cloud ceiling height, and 10-m height horizontal u (east-west) and v (north-south) wind components. For forecasting the weather at an airport, the RCE uses the most recent forecast for the RUC grid point nearest the airport’s location.

Monte Carlo Simulation The RCE uses Monte Carlo methods to generate simulated weather conditions of wind, ceiling, and visibility at the airport for each forecast lead time. For a given forecast and lead time, the RCE samples the uncertainty in RUC forecast accuracy, as characterized by the historically-based FPE model (Section B.2.2c) ), to provide future weather conditions at the look-ahead time. Each simulation (also called a replication) provides independent and slightly different weather conditions, which are used by the RCE and RCM in capacity computations. The RCE uses the simulated wind conditions to evaluate runway wind restrictions. The RCM uses the simulated ceiling and visibility conditions to determine the applicable meteorological conditions and aircraft separation rules.

Wind Restrictions Before the capacity of a prospective runway configuration is computed by the RCM, the RCE checks each runway in the configuration for wind restrictions. A runway can be used only when the magnitudes of the crosswind and tailwind components are within specified limits. The crosswind component is the component of wind velocity that acts at a right angle to the runway direction; the tailwind component is the component of wind velocity in the direction of the runway heading. Runways whose crosswind or tailwind components exceed the specified limits are dropped from the configuration.

b) Runway Capacity Model The second major module of the ACM is the Runway Capacity Model (RCM). It a reduced and simplified version of the MACAD model described in Section A.1.2d) RCM is based on the proposition that all arrivals at a given runway will follow a common approach path from a metering point to the runway threshold, and that controllers will organize the flow over the metering point so that various safety criteria are enforced. For example, one safety criterion is that no flight should cross the runway threshold while another flight is still on the runway. Another is that all flights should maintain a safe separation distance throughout the common approach path. In order to satisfy these criteria, controllers will consider such factors as the types (for wake-turbulence separation) and relative speeds (for estimating separation along the common path and threshold-crossing times) of the aircraft involved. Given the vagaries of flight, controllers will build safety margins into their calculations. Our model accounts for these factors, including the projected mix of aircraft types, in estimating the rate at which flights will cross the metering point. Our model estimates the rate at which flights can land by calculating the mean inter-operation time, ∆, at which flights will cross the metering point, estimating that 1/∆ flights will cross the metering point per unit time, and then estimating that flights will land at that same rate a few minutes later. During our research the question arose of whether we needed to consider random variation in the time that flights take to traverse the common approach path. For example, if flight i were to exceed its estimated time by some amount, δ, would that delay all future flights by δ? We concluded that future flights would

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79 not be delayed, reasoning as follows. By the time it is determined that flight i will exceed its estimated flight time, flight i+1 will already be approaching the metering point, ready to cross the point at its assigned time. The delay in flight i will mean that the time difference between flights i−1 and i arriving at the runway threshold will be greater than planned by the amount δ, and the difference between flights i and i+1 will be smaller than planned by the same amount. Our model assumes that when controllers space flights over the metering point, they build in a safety margin to account for random variation in flight times. Thus, though the spacing between flights i and i+1 will be somewhat less than planned, it will still meet the safety requirements. In summary, flights will cross the metering point at the planned rate and therefore, barring rare circumstances such as missed approaches, will land at that same rate. Figure 48 shows how RCM integrates with RCE within the ACM component. Namely, RCM is called by the RCE and obtains from it a usable runway configuration for the airport (as determined by crosswind and tailwind thresholds), and ceiling and visibility values generated within the RCE. It also incorporates real-time and pre-processed inputs, including the predicted demand defined as arrival and departure demand counts for the given look-ahead hour (broken down by weight class: small, large, and heavy), the operational standards and procedures (Section B.2.2b) ) and runway occupancy times and approach speeds computed for the airport using historical data (Section B.2.2e) ). Using this information, RCM first uses the provided ceiling and visibility values to determine the meteorological conditions in which the airport operates: VMC, MVMC, and IMC. Next, RMC determines the set of runway primitives corresponding to the usable runway configuration obtained as an input: independent arrival, departure and mixed-use runways, closely-spaced parallel runways, and crossing runways. The RCM then computes arrival and departure capacity of each primitive independently. These capacities are then aggregated and returned as the airfield arrival and departure capacities. B.3.3 Multi-Criteria Capacity Forecast Integrator The MCFI integrates capacity outputs from the ACM and TCM into an overall probabilistic forecast of airport capacity (see Figure 49). The probabilistic forecast of capacity produced by the MCFI is in the form of a distribution of capacity values produced using a Monte Carlo simulation. The MCFI uses a combination of Monte Carlo techniques to combine ACM and TCM outputs.

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Figure 49: MCFI integrates probabilistic capacity estimates produced by TCM and ACM into an overall probabilistic airport capacity forecast

As described in Section B.3.1, the TCM produces discrete probability distributions on the numbers of available departure and arrival air lanes in the terminal airspace. For example, if there are 4 arrival fixes, the TCM will estimate the probability pk , for k= 0, 1, 2, 3, and 4, that exactly k arrival air lanes will be available. Using these distributions, the MCFI, through Monte Carlo methods, generates a joint sample46 of size m for the numbers of available departure and arrival air lanes. To obtain capacity estimates for the terminal airspace, the number of available air lanes is multiplied by the nominal flights per hour per air lane. As described in Section B.3.2, the ACM generates simulated weather conditions based on forecasted future conditions and forecast accuracy distributions. For each simulation of weather conditions, the RCM estimates the runway arrival and departure capacities, accounting for wind, ceiling, and visibility conditions. Let n denote the number of simulations generated by the ACM. To produce an overall probabilistic forecast of airport capacity, the MCFI must consider the capacity distributions produced by both the TCM and the ACM. In any given case, the overall airport capacity will

46 The MCFI assumes that the distributions produced by the TCM for the numbers of available departure and arrival air lanes are statistically independent.

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81 equal the ACM or TCM capacity, whichever is smaller. To fuse together the TCM and ACM capacity distributions, the MCFI pairs every TCM capacity estimate in combination47 with every ACM capacity estimate, producing c= mn ⋅ pairs of arrival and c pairs of departure capacities. For each pair, MCFI uses the minimum of the two capacities. The resulting c estimates of arrival and departure capacities provide Monte Carlo distributions of the respective capacities, which MCFI uses to represent the overall arrival and departure capacities.

47 This scheme is a form of “forced” Monte Carlo sampling. The MCFI assumes that the TCM and ACM outputs are independent and equally likely.

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