Why do people continue to suffer and die due to entirely predictable natural hazards? The remarkable progress in science and technology over recent decades allows us to anticipate future conditions, communicate early warnings and take early action to avoid losses, yet many recent disasters are evidence of a dreadful gap between climate science and the humanitarian sector. Combining presentations, participatory simulation games and plenary discussions, this course will familiarize students with recent developments in both climate-related forecasts and decision capacity, which together enable new ways to manage risks associated with extreme events and changing climate conditions.

Teaching Strategy
Class sessions combine lectures, games that simulate decision-making processes, analysis of case studies, group work and plenary discussions.


Build the capacity of humanitarian practitioners to manage increasingly serious climate risks. Specifically, students will
1. Understand the basics of how science, technology and organizational innovations can help the humanitarian sector understand and address climate-related hazards. Focus on the strengths and limitations of forecasts at different time scales.
2. Learn about approaches to work with experts from other disciplines in order to jointly identify the constellation of means, relationships, and processes that can enable forecast-based decisions to save lives and livelihoods.


  • New challenges in humanitarian work
    • Introduction
      • The evolving nature of hazards, vulnerabilities, and capacities: an overview    
      • Game time: making decisions with incomplete information  
    • Key trends affecting vulnerability
      • main factors in humanitarian decisions
      • Climate change and environmental degradation
      • Urbanization, HIV/AIDS, demographic changes and more
  • Towards forecast-based humanitarian decisions
    • New science-based tools for predicting hazards at different timescales
      • Basics of science-based prediction
      • Short lead times: extreme hydrometeorological events
      • Seasonal timescales: rainfall and temperature forecasts based on El Niño
      • Longer lead times: decadal variability, global climate change
      • Integration of forecasts across timescales
    • Case Study: IFRC flood preparedness in West Africa
      • Background: the 2007 rainy season in West Africa
      • Seasonal precipitation forecast issued on May 2008
      • Forecast-based disaster preparedness
      • Results: avoided losses, and lessons about institutions
    • Progress in knowledge-based decision capacity
      • Information and communication technologies
      • Academia as humanitarian partner
      • Financial instruments
    • Identifying key stocks, flows and parameters in humanitarian challenges
      • Basics of system dynamics modeling
      • Key trade-offs, feedbacks, thresholds, delays and incentives
  • Integrating knowledge and action
    • A system dynamics approach to forecasts for humanitarian logistics
      • Anatomy of a science-based prediction
      • Anatomy of a humanitarian decision
      • Linking predictions and decisions through playable dynamic models
    • Design of a participatory activity on forecast-based decisions
      • Selection of key climate-sensitive decisions