Meteorological Event Lessons Learned Analysis (MELLA) – A Tool on Weather-Related Impacts for the Warning Preparedness Meteorologists Program of EC

Denis Gosselin

National Coordinator, WPM Program

Meteorological Service of Canada

CRHNet Symposium

Fredericton, October 2010

Page 2 – 23-4-18

Content

• The Warning Preparedness Meteorologists (WPM) Program – In Short

• Weather-Related Impacts: Why Bother?

• MELLA – Beyond Weather Conditions

• Basic Anatomy of a MELLA

• Examples: What Have We Learned So Far?

• What Else? – Comparing Cases

• Linking Weather and Impacts

Page 3 – 23-4-18

The WPM Program – In Short

• National program at the Meteorological Service of Canada (MSC) since 2003 (started as a regional pilot in 1998).

• Modest workforce: 15 people coast-to-coast either on part-time (WPM and Outreach) or full-time basis.

• WPM’s provide tailored high-impact weather information to various clients, namely:

– EMO’s (provincial, territorial and municipal levels)– Federal partners– Media

Page 4 – 23-4-18

The WPM Program – In ShortFocus is on High Impact Weather.

Page 5 – 23-4-18

The WPM Program – In Short

• However, high-impact weather implies knowledge of impacts.

• WPM’s are former weather forecasters and they were not trained to deal with impacts.

• So, except for a few particular types of weather event (rain with melting snow, hurricanes), impact information that can be passed on to clients by WPM’s is very limited.

Page 6 – 23-4-18

Weather-Related Impacts: Why Bother?

Hydrometeorological Geological Biological

Africa 1,30 0,37 7,31

Americas 6,23 0,31 1,13

Asia 5,19 7,54 0,39

Europe 4,77 0,23 0,03

Oceania 1,92 5,06 0,62

Average number of people reported killed, per million inhabitants and disaster origin 1991-2005

Source of data: EM-DAT: The OFDA/CRED International Disaster Database, UCL – Brussels, Belgium

Page 7 – 23-4-18

Weather-Related Impacts: Why Bother?

Total amount of reported economic damages per continent and disaster origin (2005 US$ billion) 1991-2005

Hydrometeorological Geological Biological

Africa 3,93 6,14 0,01

Americas 400,82 29,98 0,13

Asia 357,70 219,74 0,00

Europe 142,83 16,17 0,00

Oceania 14,51 0,87 0,14

Source of data: EM-DAT: The OFDA/CRED International Disaster Database, UCL – Brussels, Belgium

Page 8 – 23-4-18

Weather-Related Impacts: Why Bother?

• Auditor General of Canada – 2008 December Report of the Commissioner of the Environment and Sustainable Development – Chapter 2: Managing Severe Weather Warnings-Environment Canada

• Paragraph 2.74 - Recommendation. Environment Canada should regularly assess the effectiveness of severe weather warnings from a user's perspective, especially the effectiveness of the methods of delivery to users and how well the warnings are understood by key users and the public.

Page 9 – 23-4-18

MELLA – Beyond Weather Conditions

• The Meteorological Event Lessons Learned Analysis or MELLA is a tool that was designed to capture links between:

– weather forecasts– expected results– factual realities

• Capturing links = performance assessment.

• MELLA ≠ forecast verification

Page 10 – 23-4-18

MELLA – Beyond Weather Conditions

• A MELLA tries to determine answers to the following questions:

– What happened?– What worked/did not work well?– Why did it/did it not work well?– What lessons can we learn from that event?

• MELLA’s are/will be conducted on a pilot basis in the current fiscal year

– Issue with resources– Standardizing/streamlining process as much as possible

Page 11 – 23-4-18

MELLA – Beyond Weather Conditions

What happened – traditional approach (Case Studies, Storm Damage Surveys): aimed at weather forecast verification

Regular ForecastsSpecial Weather BulletinsWeather WatchesWeather WarningsOthers

Forecasts Issued

Observations

Regular Weather ObservationsOn-Site Measurements/EstimatesRadar/Satellite Imagery

VS

Performance of Atmospheric ModelsTechnological Problems and Issues

+

Other Issues

Page 12 – 23-4-18

MELLA – Beyond Weather Conditions

What happened – MELLA approach: aimed at forecast verification from a client’s perspective

Regular ForecastsSpecial Weather BulletinsWeather WatchesWeather WarningsOthers

Forecasts Issued

Observations

Regular Weather ObservationsOn-Site Measurements/EstimatesRadar/Satellite Imagery

VS

Performance of Atmospheric ModelsTechnological Problems and Issues

+

Other Issues

Impacts

SocialEnvironmentalEconomic

Social Science Elements

Risk CommunicationRisk PerceptionClient Response

Page 13 – 23-4-18

Basic Anatomy of a MELLA

• Summary of Meteorological Event

• Chronology of Weather Conditions (Forecast and Observed) and Related Events

• Event Determinants

• Lessons Learned (Meteorological and Social Perspectives)

– Documented knowledge on weather-impacts links– Documented “best practice” requirements to maintain/improve

performance

Page 14 – 23-4-18

Basic Anatomy of a MELLA

Location Camrose, Alberta

Type of Meteorological Event Strong winds associated with thunderstorm

Number of Casualties - Fatalities 1

Number of Casualties - Injuries 15 (3 in critical condition)

Estimated or severity of damages Main stage of Big Valley Music Jamboree completely collapsed

Was an EOC* opened by the local EMO?

No

*Emergency Operation Center

Summary of Weather Event

Page 15 – 23-4-18

Basic Anatomy of a MELLA

Chronology

Page 16 – 23-4-18

Page 17 – 23-4-18

Basic Anatomy of a MELLA

• Meteorological Elements– Early Synoptic Signature

– Precipitation (type, amount, duration)

– Wind

– Temperature

– Etc.

• Vulnerabilities

• Impacts

• Risk Communication Elements

• Risk Perception Elements

• Response Elements

• Natural Catastrophe Ranking

• And more…

Event Determinants

Page 18 – 23-4-18

Basic Anatomy of a MELLA

ImpactsSocial Environmental Economic

Disruption of family life due to property losses

Death Injuries Loss of critical facilities Loss of cultural sites Loss of recreational facili

ty

Water quality and/or quantity

Quality of air Loss of plant life Loss of wildlife life Loss of natural resource Destruction of ecosyste

m

Structural damages to buildings, to private property and infrastructures

Non structural damages to private property and/or infrastructures

Job losses Revenue losses Loss of services Loss of crops Loss of livestock After event care

Page 19 – 23-4-18

Basic Anatomy of a MELLA

Natural catastrophe ranking (based on UNISDR, Munich Re. and PSA categories)

Yes/Present = 1

No/Absent = 0 Comments

Natural event No casualty/ No property damage

Small Scale loss event1-9 fatalities and /or hardly any damage

Moderate loss event10-19 death and /or damage to building and property (overall losses 5

m.)

Disaster10-19 fatalities and/or overall losses $ 25 m.

Severe Disaster20+ fatalities and/or overall losses $ 50 m.

Major catastrophe100+ fatalities, overall losses $ 200 m.

Devastating catastrophe500+ fatalities, overall losses $ 500 m.

Great natural catastropheThousands of fatalities and economy severely affected

Page 20 – 23-4-18

Basic Anatomy of a MELLA

Observation Roof collapses (either partial or total) resulted from the association of many risk factors and/or vulnerabilities.

Discussion Meteorological risk factors are:1) The formation of snow drifts due to strong winds associated to successive winter storms.2) Variation of snow density in snow drifts following successive frost and thaw cycles as well as successive variations in precipitation types (snow, rain, ice pellets and freezing rain).

Lessons Learned The quick succession of winter storms characterized by various weather elements (precipitation, temperature) has a cumulative effect. Successive sequential weather conditions may contribute to a substantial increase in risks of impacts.

Recommendation Cumulative effects of successive meteorological elements should be assessed. Risks that are posed by those effects should be assessed as well and incorporated in any related risk communication.

Lessons Learned

Page 21 – 23-4-18

Basic Anatomy of a MELLA

Observation Roof collapses (either partial or total) resulted from the association of many risk factors and/or vulnerabilities.

Discussion Associated risk factors (vulnerabilities) are:1) Flat roofs with obstacles favouring the formation of snow drifts.2) Flat roofs which structural strength has been negatively affected by successive fixes, water percolation and age are at greater risk to collapse (partially or totally).

Lessons Learned The association of meteorological risk factors (snow, snow drifts, weight increase resulting from freeze/thaw cycles and various precipitation types) and structural vulnerabilities greatly increase risks of direct and indirect impacts.

Recommendation The cumulative effect of risks from weather elements and their association with socio-economic and environmental vulnerabilities (associated risk factors) should be incorporated in any risk communication related to a given weather event.

Lessons Learned

Page 22 – 23-4-18

Examples: What Have We Learned So Far?

Page 23 – 23-4-18

Examples: What Have We Learned So Far?

Page 24 – 23-4-18

Examples: What Have We Learned So Far?

WATCHES AND WARNINGS - PAGE VIEWS TOTAL PAGE VIEWS

SAT June 5 (11:00 PM) to SUN June 6 (4:00 AM)  

Watches and Warnings: Windsor, Ontario                  3,557

Watches and Warnings: Windsor - Leamington - Essex County                  1,039

Watches and Warnings: Windsor - Essex - Chatham-Kent                    962

Watches and Warnings: Leamington, Ontario                    194

Watches and Warnings: Essex, Ontario                      96

TOTAL WATCHES AND WARNING PAGE VIEWS                     5,848

Population for Windsor – Leamington – Essex County: ~ 390 000

Page 25 – 23-4-18

Lessons Learned

Page 26 – 23-4-18

Examples: What Have We Learned So Far?

MSC PSPCYVR

Ground Ops YVR

De-Icing

YVRSnow removal

Weather Warning

Fig. 1: Simplified weather warning “value chains”Based on the Dec. 20, 2008 Snow event in YVR

MSC CMAC NavCanada Airlines

Page 27 – 23-4-18

Examples: What Have We Learned So Far?

CMACTAF – TAF+

VCMAC

WPM

Fig. 2: A Simple Aviation “Value Network”:

Meteorological Private Sector

DISSEMINATIONSpecial Weather Bull

Warnings

NavCanNational Ops

AirlinesNational

Dispatch/Ops

AirlinesAirport Station

NavCanAirport Ops

AIRPORTGround Ops

AIRPORTGround

Contractors

RegionalSPC

Page 28 – 23-4-18

Examples: What Have We Learned So Far?

• Heat Wave and Severe Thunderstorms – Early July in Montreal

– Special Weather Statement issued 2-3 days prior to first day of heat wave

– Risk of severe thunderstorms at end of heat wave included in SWS

– Regular contacts between EMO’s and WPM’s for updates during event (exchange of information)

– Feedback indicates positive response from EMO’s (health authorities, municipal authorities)

– Clear demonstration of impact mitigation

Page 29 – 23-4-18

What Else? – Comparing Cases

Weather Elements

Vulnerabilities(associated risk factors)

Direct ImpactsRisk

Perception

Type

Cycles of various types

of precipitations

Successive snowfalls

Wind speeds >80km/h

Freeze and thaw

cycles

Formation of snow

driftsFlat roofs

Partial or total roof collapses

Casualties

BavariaWinter Storm

Yes Yes Yes Yes Yes Yes Yes Yes No

Montréal03/08

Winter Storm

Yes Yes Yes Yes Yes Yes Yes Yes No

Vernon 01/09 ? Yes Yes Yes Yes Yes No Yes

Meteorologically similar cases

Page 30 – 23-4-18

What Else? – Comparing Cases

Weather Elements Vulnerabilities Direct ImpactsIndirect Impacts

Combined Impacts

PcpnWind

Gusts> 120km/h

Storm Surge

High Tide

Coeff.

Weak Flood

Barriers

Loss of Services

Broken Flood

Barriers Floods Deaths Social Eco. Enviro.

KATRINA(New Orleans)

Hurr. 1 1 1 ? 1 1 1 1 1 1 1 1

XYNTHIA(SW France)

Winter Storm

1 1 1 1 1 1 1 1 1 1 1 1

Meteorologically different cases

Page 31 – 23-4-18

What Else? – Comparing Cases

• With a database (Meteorological Event Analysis Database – MEvA DBase)

– Project proposal submitted a few months ago, development work ongoing

– Boolean-type (truth table)

– Could be built from MELLA’s and from former regional case studies with the addition of data on impacts and vulnerabilities

• Potential benefits– Establish factual relationships between weather elements and related

impacts

• MEvA DBase would not only be an analytical tool but also a knowledge management and knowledge sharing tool

– Available at operational desks (compatible with operational workstations that are used by forecasters)

Page 32 – 23-4-18

What Else? – Comparing Cases

• Some examples of the database’s qualitative determinants

– Weather Elements– Forecast Verification and Lead Time– Geographical Elements– Impacts– Natural Catastrophe Ranking– Risk Communication Elements– Risk Communication Response

• Work in progress: determinants will be added as project unfolds

Page 33 – 23-4-18

What Else? – Comparing Cases

• Summarize data

• Check for data consistency

• Corroborate current assumptions and theories

• Elaborate and test new assumptions and theories

• Establish potential causation links between a series of successive elements and a particular impact

Qualitative Comparative Analysis (QCA)

Page 34 – 23-4-18

What Else? – Comparing Cases

• Are the 4 cognitive determinants of response to threats important in hazardous weather risk communication?

• Are there “configurational causation” relationships between the dynamic or synoptic signature of the weather event, the “determinants” (components) of the weather event, the ensuing impact(s)?

• Which determinant(s) is (are) always present when a particular outcome is present/absent?

Assumptions and Theories

Page 35 – 23-4-18

What Else? – Comparing Cases

• Are current « binary » weather warnings from EC adequate in helping Canadians to make informed safety-related decisions?

• Can EC observe a clear response to weather warnings from clients (does EC have appropriate tools to measure it)?

• Would an early warning system (such as Vigilance) be more efficient in giving rise to a response from clients?

Assumptions and Theories

Page 36 – 23-4-18

25% increase in peak gusts=

650% increase in structural damages

Incr

ease

in

dam

ages

Peak Gusts

X 100

X 200

X 300

X 400

X 500

X 600

X 700

>37. 04 km/h >74.08 km/h >92.06 km/h >111.12 km/h

Linking Weather and Impacts

Page 37 – 23-4-18

denis.gosselin@ec.gc.ca