Extreme Events: Developing a Research Agenda for the 21st Century

Breakout Groups

Breakout Group Assignments

In light of the workshop goals of developing a forward-looking extreme event research agenda,

  1. Make a list of the major themes, questions, and problems, that have emerged in the workshop and describe the significant of each. Prioritize if possible.
  2. In the final ten minutes of the breakout sessions, develop a second list of major issues that have NOT been addressed at this workshop.

BLUEBIRDS (Chapman Room)
James Brown
Ronald Brunner
Margaret Davidson
Art Lerner-Lam
Ken Mitchell
Judith Parrish (Chair)
Charles Perrow
John Rundle
Robert Shuchman
Rob Wesson

ROBINS (Main Seminar Room)
Aaron Andersen
Mike Atallah (Chair)
David Krantz
Richard Eisner
Robert Harriss
Dale Jamieson
Maria Lemos
Mary Fran Myers
Andrew Norman
Roger Pielke Sr.

Workshop Overview

Integrated Summary

Workshop Participants

Other Workshop Attendees

Workshop Agenda

Workshop Logistics

Contributed Papers

Breakout Groups

Appendix: Research Topics

Workshop Proposal

Workshop Background

WRENS (Cafeteria East)
Susan Avery
Lewis Gilbert
Grant Heiken
Howard Kunreuther
Chris Landsea (Chair)
Betty Morrow
Chester Moore
Rutherford Platt
Ellis Stanley

Notes from white boards:


  • Cascading/complex interactions
  • Risk assessment
  • Do classical science techniques explore such extreme events?
  • Secondary impacts, ie, emotional health
  • Non-linearity
  • Policy incentives/disincentives
  • Human activity (development) increasing potential impact of extreme events
  • Trade-off between sustainability and tolerable level of risk
  • Cultural differences
  • Who decides? Level of risk
  • Impact of high levels of consumption
  • Appropriateness and use of models: accuracy, precision, validation – only 1/3 of the problem
  • Are extreme events large versions of small events?
  • Prediction
  • Context
  • Language/communication "knowledge distribution"
  • Complexity
  • "Luck" – avoiding worst case
  • Perception – large scale events vs. widespread/frequent smaller events
  • Event perception vs. event reality
  • Trust in fiduciary responsibilities, eg, Alaska Airlines
  • Experience unmediated by science
  • Convergence of events/places/vulnerabilities
  • "End-to-end" specialization & integration
  • Capacity building – how to do most effectively?
  • Data acquisition: what happened?
  • Common terminology for defining extreme events
  • Why extreme events?
  • Why are extreme events fascinating?
  • How to parse question of extreme events?
  • Is there a "worst case"?
  • Nuclear war
  • Costs/how to quantify
  • Failures splendid opportunities for learning; under what circumstances can we learn from extreme events?



  • What are types of extreme events and frequencies and costs?
  • What are prediction/types:
    Preventable    Unpreventable
    Limit Consequences   Limit Consequences
    Clean up    Clean up
  • Meteors/hurricanes
    1. Reset scientific agenda to raise salience of extreme events research
    2. Raise profile of science in public D.M. about extreme events
    3. Broaden discourse among participant groups in extreme events discourse
    4. Find new ways of communicating more effective ways of addressing extreme events
  • Short term/Long term
    [related search exists]
  • Natural vs. human-made
  • Timing (episodic vs. chronic)
  • Qualitative vs. quantitative assessments
  • Impact of values
  • Resource allocation (prevention, mitigation)
  • Need for integration/melding of many disciplines
  • Root causes of more armed conflicts, etc. [keynote talk]
  • Benefits of risk-taking behavior of extreme events
  • Decisions under uncertainty; better understanding of actual decision heuristics]
  • Disconnect between producers and consumers of knowledge
  • Limits of possibilities of planning, prediction, control
  • Value of folk knowledge
  • Perceptions of decisions under environmental problems, events
  • Assessments: impacts, assets, vulnerabilities
  • Accountability
  • Overselling of prediction
  • Seductions/dangers of oversimplification
  • Distributed decision-making
  • Economics of disasters (who wins/loses)
  • Investigate the impacts of mitigation


Unaddressed (inadequately addressed) issues:

1. Environmental impact
4. Tension and synergies among stakeholders
1. Long-term impacts
1. Historic impacts and analyseis
3. Fostering user/researcher interrelations/develop programs before the extreme event
3. Share results (better protocol) with end users
(no number) Develop and testing of scenarios and involve stakeholders

2. Credibility/legitimation

  • "Cry wolf" issues
  • Exaggerated claims
  • Export disagreements
  • Role of Media and scientists

2. False alarms/surprises

  • Communicating probability and uncertainty

3. Consequences

  • Integration of social and physical sciences (working on problems together)

1. Taxonomy of extreme events

2. Human Dimensions Aspect

  • Risk tolerance
  • "Winners and losers"–distribution issues
  • Risk adaptation (living to learn to live with hazards and co-existence)
  • Risk mitigation (beforehand public and private policy and planning)
  • Decision making
  • Communication
  • Categories of vulnerability (poor, minority, women, elderly, children)
  • Levels of responsibility
    – individual (self-reliance)
    – corporate
    – community
  • TRUST (and mistrust)
  • Planning (event vs. general sustainability)
  • Response and recovery

5. All Users Theme

  • Many different end users (emergency managers, individuals, companies)
  • Lack of appreciation for end users' needs
  • Need to foster cross-pollination
    – Advisory committeees
    – Cross-disciplinary funding
    – Internships with end users
    – Personnel exchange between modelers and end users

4. Uncertainty – all extreme events

  • Risk probs., modeling, physical process, of effects and data
  • Communicating
  • Work between organizations
  • Human behavior

1. Data Issues

  • Quality/uncertainty (probability error bars)/Accessibility
  • Communication

3. Linkages: Science and public and private policy

3. Modeling

  • Types (physical, statistical, numerical)
  • Application (physical-natural hazards, human systems)
  • Assumptions (physical laws vs. parameterization, constant vs. man-made constructs
  • Limitations–error

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