World Meteorological OrganizationWorld Meteorological Organization

Outcomes of the Symposium on Multi-Outcomes of the Symposium on Multi-Hazard Early Warning Systems for Hazard Early Warning Systems for

Integrated Disaster Risk Management, Integrated Disaster Risk Management, Geneva, May 2006Geneva, May 2006

Dr Maryam Golnaraghi, Chief of WMO DRR Programme

Expert Meeting on “National Meteorological and Hydrological Services’ Participation in Disaster Risk Reduction Coordination Mechanisms and Early Warning Systems”

27 November 2007

Economic Losses Related to Disasters are on the Way Up

Source: EM-DAT: The OFDA/CRED International Disaster Database - www.em-dat.net - Université Catholique de Louvain - Brussels - Belgium

4 11 1424

47

88

160

345

103

495

0

50

100

150

200

250

300

350

400

450

500

56-65 66-75 76-85 86-95 96-05

Geological

Hydrometeorological

Billions of USD per decade

decade

While Casualties related to Hydro-Meteorological Disasters are Decreasing

0.05

2.66

0.17

1.73

0.39

0.65

0.22 0.25

0.67

0.22

0

0.5

1

1.5

2

2.5

3

56-65 66-75 76-85 86-95 96-05

Geological

Hydrometeorological

Millions of casualties per decade

decade

Source: EM-DAT: The OFDA/CRED International Disaster Database - www.em-dat.net - Université Catholique de Louvain - Brussels - Belgium

Disaster Risk Managementand Hyogo Framework for Action 2005-2015

Risk TransferRisk Identification Risk Reduction

Governance and Organizational Coordination

Historical hazard data and analysis

Changing hazard trends

Vulnerability assessment

Risk quantification

Sectoral planning

Early Warning Systems

Emergency preparedness planning

Education and training

Cat Insurance and Bond Markets

Weather Derivatives

Knowledge Sharing

Increasing Risks under a Changing Climate

Intensity

Frequency

Heatwaves

Heavy rainfall / Flood

Tropical Cyclones

Coastal Marine Hazards

Strong Wind

Water ResourceWater ResourceManagementManagement

HealthHealth IndustryIndustry

Food Food securitysecurity

TransportTransport

EnergyEnergy

Urban areasUrban areas

Hazard

Exposure is increasing !

Need forPrevention

and Mitigation

Early Warning SystemsNational to local disaster risk reduction plans and legislation

Marine

Health (etc.)…

Geological

Communitiesat risk

warning

National to local governments

Hydrological

Meteorological

NATIONAL SERVICES

post-disaster

response

Meteorological

Hydrological

Geological

Marine

Health (etc.)

(coordination)

NATIONAL SERVICES

requirements

requirements

Community Preparedness

warning

National to local governments

supported by DRR plans, legislation

and coordination mechanisms

warning

requirements

Effective Early Warning Systems

warning

preventiveactions

First WMO Symposium ″Multi-Hazard Early Warning Systems″

WMO Headquarter, May 2006

• Goals:

1) To explore further the concept of “multi-hazard” approach to early warning systems,

2) To recommend examples of good practices

• Participants: 100 experts and practitioners from 20 agencies, NMHSs, WMO Programmes

• Co-Sponsored by: ISDR Secretariat, World Bank, UNDP, IFRC, UNESCO, OCHA

http://www.wmo.int/pages/prog/dpm/ews_symposium_2006

2) Risk Knowledge and Integration in Warning Messages

• Data gaps, quality, accessibility, sharing– Hazard

– Vulnerability (e.g. socio-economic, topographic…)

• Standardized methodologies and expertise (e.g. hazard analysis, risk modelling)

• Understanding of the changing patterns of risk (e.g. hazard, vulnerabilities)

• Local capacities

1) Early Detection, Monitoring and Warning Services

• Strengthen observation systems– Coverage– Sustainability– Inter-operability– Multi-use of networks (where practical)

– Built on "system of systems" concept– Data policies

• Prediction and forecasting– Methodologies, accuracy and lead time– Multi-disciplinary

3) Dissemination and Communication• Effective warning messages

– Incorporation of information about risks in warning messages

– Understandable warning messages– Authoritative warnings (Authentication of sources)

• Dissemination networks– Interoperability (use of international standards)

– Redundancy and resilience of networks– Same distribution channels for warnings of different hazards

(cost efficiency, reliability and effectiveness)

• Standard warning terminologies (nationwide, and across borders, traffic light concept)

4) Integration in Preparedness and Response Processes

• Education and awareness (emergency responders, authorities, risk managers, emergency

responders, media, public…):– Understanding of warnings and uncertainties– Awareness of less frequent events

• Cross-Training of Operational Agencies

• Operational planning– Drills– Community preparedness

Need for Strong Governance, Organizational Coordination and Operational Processes

Criteria for Good Practices in EWS

• Political commitment, DRR plans, legislation, roles and responsibilities (national to local)

• Overall Coordination and operational working mechanisms among agencies

• Capacity for delivery of “best available information” to address government demand in support of decision-making

• Authoritative, understandable warnings Combine hazard, risk and response information

• Dissemination Mechanisms Match resources and culture Sustainability, interoperability, reliability

• Integration of warning information in emergency preparedness and response actions

• Community-based emergency preparedness and training programmes

• Feedback mechanisms to improve the system

WMO EWS Symposium Identified Examples of Good Practices

• France Vigilance system

• Shanghai Emergency Preparedness System

• Cuba tropical cyclone early warning system

• Bangladesh Cyclone Preparedness Programme

• Noted that there are other such good practices that need to be also identified

Example: Regional Cooperation for Tropical Cyclone Early Warning Systems

• 6 Regional Specialised Meteorological Centres

• 6 Regional Technical Commission Committees(involving all countries at-risk)

• Support to all countries at risk of Tropical Cyclone

Example: Cyclone Preparedness Programme in Bangladesh

Level 4

Level 3

Level 2

Level 1

France Vigilance System

Strong wind

Strong rainfall

Thunderstorm

Snow/Ice

Avalanches

Heat waves

Warnings activate cascades of preparedness and response plans, actions and responsibilities

Legislation

Planning

Authoritative WarningsOrganizational linkages

Training and feedback

+ NEW: Flood warning map

national to local authorities

Hazards

Level of warning

France Vigilance Strategy: 20 years of History in Tropical Islands

Shanghai City: Multi-Hazard Early Warning and Emergency Response Programme

Governance : (mega) city-level.

Organisational: Top-down (monitoring, forecasting, warning) and bottom-up

Operational: Community-based + high tech monitoring and alerting tools

Multi-Hazard Approach: Services are specialized but shared for alert dissemination and response mechanisms.

Multi-Hazard Early Warning Demonstration Projects

1) Documentation of governance, organizational coordination and operational processes;

• NMHSs’ support and response to national to local needs

2) Strengthening operational capacities and inter-agencies coordination and cooperation for

• Development, delivery and utilization of warnings

• Driven by priorities and requirements

3) Analysis of socio-economic benefits of early warning systems and sustainability of capacities

4) Sharing experiences and good practices• Publications, manuals, study tours, training workshops, symposia

(2)

Strengthened operational Technical capacities and inter-

agency cooperation

Warnings, specialized forecasts, and other Services

D

A

T

A

Internet

Protection

of

lives,

livelihood

and

property

Media

Internet

SMS

Other

Disaster Preparedness and Response

Systems

(1)Governance, Organizational Coordination and Operational Processes

(3)Cost-

BenefitsAnalysis

Coordination and Cooperation With Other Agencies for Early Detection, Development and Issuance of Warning

Increasing Level of coordination with technical agencies for early detection, monitoring and development of warnings

Type I Type II Type III

Hazard fully under the

mandate of NMHS

e.g. strong winds, strong rainfall, snow/ice, hail,

tropical cyclone

Hazard under joint mandate with another

technical agency

e.g. floods, landslides,

heat/health etc.

Hazard under mandate of

other agencies but NMHS contribute

e.g. locust, health epidemic, man-made hazards

Increasing Level of coordination with civil protection and risk management agencies for issuance of warnings

Symposium on ″Multi-Hazard Early Warning Systems″ to be held annually from Q1 2009

• Goals:1) To take stock of what would have been achieved through

demonstration projects, with respect to governance, organizational coordination and operational processes,

2) To exchange good practices and experiences

• Participants: Experts and practitioners from national and international agencies involved in EWS

• Q1 2009, the Second Symposium will be held in Toulouse, France

For more information please contact:Maryam Golnaraghi, Ph.D.Chief of Disaster Risk Reduction ProgrammeWorld Meteorological OrganizationTel. 41.22.730.8006Fax. 41.22.730.8023Email. MGolnaraghi@WMO.int

http://www.wmo.int/disasters

Thank You

Improving Warnings Quality and lead times

EmergencyPreparedness and Response

Preparedness Sectoral plans

Short- to Medium-Range

WeatherSeasonal Forecasts

Short-Term ClimateLong-Term

Climate

Status of Early Detection and Forecasting Capacities

• Drought– Predictability lead time: from weeks to seasons– Key factors: Timing, Geographical area, Intensity, Duration – Key indicators: Precipitation, groundwater and reservoir levels, soil

moisture, satellite observations, ENSO

• Floods and Related Hazards (Land-slides)– Predictability lead time: from minutes (flash floods) to weeks (riverine

flood)– Key factors: Timing, Geographical area, Water level, Velocity– Key indicators: precipitation, soil moisture, (snow cover + temperature),

Satellite observations, ENSO

• Tropical Cyclones, Severe Storms, Storm Surges– Predictability lead time: up to 72 hours– Key factors: Intensity (Saffir-Simpson Scale), Storm track, Landfall – Key indicators: Sea Surface Temperature (SST), Sea-Level Pressure,

Saharan Air Layer (SAL), Satellite observations, ENSO

• Other Climate-Related Hazards: e.g., Locust Swarms– Predictability lead time: up to six weeks– Key factors: Timing, Geographical area, Intensity, Duration– Breeding conditions indicators: Rainfall anomalies, Wind direction and

persistence, Soil moisture, Vegetation distribution, Satellite observations