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. [email protected]
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