NM USER FORUM 2014

Tzvetomir BlajevOperational Safety Coordinator

30/01/2014

Natural hazards and weather risk management: what’s new?

Network WX Resilience

2EUROCONTROL Operational Safety 2

One can’t do anything about the weather! ?

US NTSB – over 20% of the aviation accidents

More than 20% of the airport delays

Boeing survey – the highest training concern

Two thirds of the wx delays are avoidable (FAA)?

3EUROCONTROL Operational Safety 3

….But it is a complex stuff….

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The Network WX Resilience Roadmap

Translation:

• Thresholds

• Constraints

• Capacity Risks

Impact Assessment

• Actual Demand

• Actual Resources

• Configurations

Decision Making

• Options

• Simulation

• Execution

• Monitoring

3d Information • Nat Hazards• WX Forecast• WX Nowcast

3d Information • Nat Hazards• WX Forecast• WX Nowcast

70% likelihood for 45 knots wind at 3000ft at EDDF

70% likelihood for 45 knots wind at 3000ft at EDDF

High Risk of Capacity Reduction by 20%

High Risk of Capacity Reduction by 20%

Current RWY configuration and resources – 5% reduction

Current RWY configuration and resources – 5% reduction

Can be accommodated without regulation

Can be accommodated without regulation

SCOPE: WX RISK ASSESSMENT PROJECTSCOPE: WX RISK ASSESSMENT PROJECT

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WeatherForecastWeatherForecast

Natural Hazards

Information

Natural Hazards

Information

PROBABILITYMODELS

PROBABILITYMODELS

RISKASSESSMENT

MODELS

RISKASSESSMENT

MODELS

IMPACTMODELSIMPACTMODELS

INTERFACE FORNOP INTEGRATIONINTERFACE FOR

NOP INTEGRATION

STAND ALONEHMI DISPLAY

STAND ALONEHMI DISPLAY

TEXT OUTPUTSTEXT OUTPUTS

EUROCONTROL NM AND OTHERSTAKEHOLDERS CONSULTATIONEUROCONTROL NM AND OTHER

STAKEHOLDERS CONSULTATION

LFPG

EGLL

Print

Valid Time 10-Oct 2013 16ZLast updated 10-Oct 2013 12ZNext update 10-Oct 2013 18Z

Medium Risk

Medium Risk

High RiskHigh Risk

LFPG

EGLL

Sector1Hazard: ConvectionRisk Score: 0.83Risk Level: High

Print

Valid Time 10-Oct 2013 16ZLast updated 10-Oct 2013 12ZNext update 10-Oct 2013 18Z

Medium Risk

Medium Risk

High RiskHigh Risk

STAND ALONE HMI

VOLCANIC ASH HAZARD VALID 052114

------------RISK HIGH

VOLCANIC ASH HAZARD VALID 052114

------------RISK HIGH

The Architecture of the tool

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Offers a quick glance of important information and a point of entry for dynamically investigating detailed information about upcoming hazards

Risks due to meteorological hazards

Reported natural hazards, if any.

Medium Risk

High Risk

Landing Page

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Landing Page Only Map Only

Landing Page Over Map Map Over Landing Page

The user can select their desired layout

Map – customisable layout

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The map-based display of hazard information accompanies the Landing Page.

The user can apply various filters to customize the view.

Offers a complete view spanning from high-level down to fine detail to support quick and thorough assessments.

Map

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End = 2013-11-20T04:00:00Z

Natural Hazard: Fire

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Meta data shows the “Start Time” which might be renamed “time of occurrence”.

The data also lists the “End Time”, which defines the latest time at which the Natural Hazard will be shown in the HMI (default 24 hours after occurrence)End = 2013-11-20T08:00:00Z

Natural Hazard: Chemical dispersion

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What do we need from the model

1. SUPPORT FOR CRISIS MANAGEMENT (Article 4 1. (h) 677/2011)

Single Network picture

Consistent impact assessment approach

Anticipating Network-wide impacts

2. MONITORING NETWORK PERFORMANCE (Article 20 1(a) 677/2011)

Calibrate the historical daily delays with the actual impact risk

3. COMMON REFERENCE PLATFORM (Article 4 3. (a) to (c) 677/2011)

Network alerts

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Numerical forecast model

6 hours refresh rate, starting at 0100 Z 48 hours (at least) look-ahead horizon Hourly temporal resolution

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Natural Hazards

This is deterministic and observation-based data:

1. Volcanic Ash

2. Nuclear Emissions

3. Hazardous Chemical Dispersion

4. Fire

5. Earthquake

6. Flooding

7. Space Weather

No risk score is calculated, map will indicate the location of the hazard, as defined by the authoritative source

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Weather

Airport

1. Ceiling and visibility

2. Surface winds

3. 3000ft wind

4. Winter weather

5. Terminal convection

En-route6. Convective weather en-route

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Ensemble prediction system

0

500

1000

1500

2000

2500

3000

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

800.0

900.0

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Aer

onau

tical

Vis

ibili

ty (m

)

Ceili

mng

(ft)

Ensemble Member

Ceiling and Visibility per Ensemble Member

Ceiling

Visibility

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Capacity Reduction

Capacity Reduction: Generic Airport

Cal IIIC Cat IIIB Cat IIIA Cat IIICAO Visibility

condition 2* IMC VMC(RVR<50) (RVR<200) (RVR<350) (RVR<550)

Ceiling (ft) <50 <200 <350 <800 <1500 <5000 > 5,000Cat IIIB <50 80% 60% 60% 60% 60% 60% 60%Cat IIIA <100 80% 60% 50% 50% 50% 50% 50%Cat II <200 80% 60% 50% 40% 40% 40% 40%VC2* <300 80% 60% 50% 40% 15% 15% 15%IMC <1500 80% 60% 50% 40% 15% 5% 5%VMC > 1500 80% 60% 50% 40% 15% 5% 0%

Aeronautical Visibility (m)

Visibility thresholds

Ceiling thresholds

Each cell contains performance reduction estimates (0 – 100%) provided by EUROCONTROL experts

Tables for each hazard and each airspace resource Performance reduction for each resource

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Geographical scope

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Maturity of the resilience process

DECISION MAKINGTRANSLATION IMPACT ASSESSMENTWEATHER

IMPLICIT DECISION

MAKING

BASELINE DATA

OPERATIONAL

EXPERIENCE

REACTIVELOCAL RESOURCES IMPACT ASSESSMENT

SEGREGATED

INFORMATION

SOURCES

GUIDANCE IS

AVAILABLE

BASED ON

REFERENCE

IMPACT DATA

PROACTIVEANTICIPATED IMPACT

CROSSCHECKED

INFORMATION

SOURCES

EXPLICIT DECISION

MAKING

BASED ON

DECISION IMPACT

DATA

NETWORK-WIDE IMPACT ASSESSMENT

COORDINATED INFORMATION SOURCES

SHARED DECISION

MAKING

PROGNOSTIC

TRANSLATION

PROCESS

PROGNOSTIC IMPACT ASSESSMENT

INTEGRATED

INFORMATION

SOURCES

M1

M1

M1

M1

M2

M2

M2

M2

M3

M3

M3

M3

M4

M4

M4

M4

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TRANSLATION

DATA BASED ON

OPERATIONAL

EXPERIENCE

BASED ON

REFERENCE

IMPACT DATA

BASED ON

DECISION IMPACT

DATA

PROGNOSTIC

TRANSLATION

PROCESS

M1

M1

M1

M1

M2

M2

M2

M2

M3

M3

M3

M3

M4

M4

M4

M4

• Data are based on NM previous operational experience

• No validation of the data against the actual operations.

• Both ATC capacity impact data and NM impact data are based on the ANSP decision triggers

• Periodic validation based on data

• Simulations or analytical models for the actual operational conditions

• Continuous validation of the data against the actual operations.

• Reference feedback from ANSP – credible to triger coordination

• NM Network impact data is based on analysis of historical data

• Periodic validation based on judgement supported with data

Maturity of the impact models

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Questions?