Articles | Volume 15, issue 4
https://doi.org/10.5194/nhess-15-895-2015
https://doi.org/10.5194/nhess-15-895-2015
Research article
 | 
23 Apr 2015
Research article |  | 23 Apr 2015

Forecast-based financing: an approach for catalyzing humanitarian action based on extreme weather and climate forecasts

E. Coughlan de Perez, B. van den Hurk, M. K. van Aalst, B. Jongman, T. Klose, and P. Suarez

Abstract. Disaster risk reduction efforts traditionally focus on long-term preventative measures or post-disaster response. Outside of these, there are many short-term actions, such as evacuation, that can be implemented in the period of time between a warning and a potential disaster to reduce the risk of impacts. However, this precious window of opportunity is regularly overlooked in the case of climate and weather forecasts, which can indicate heightened risk of disaster but are rarely used to initiate preventative action. Barriers range from the protracted debate over the best strategy for intervention to the inherent uncomfortableness on the part of donors to invest in a situation that will likely arise but is not certain. In general, it is unclear what levels of forecast probability and magnitude are "worth" reacting to. Here, we propose a novel forecast-based financing system to automatically trigger action based on climate forecasts or observations. The system matches threshold forecast probabilities with appropriate actions, disburses required funding when threshold forecasts are issued, and develops standard operating procedures that contain the mandate to act when these threshold forecasts are issued. We detail the methods that can be used to establish such a system, and provide illustrations from several pilot cases. Ultimately, such a system can be scaled up in disaster-prone areas worldwide to improve effectiveness at reducing the risk of disaster.

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Short summary
How can we use weather or climate forecasts to avoid disasters? This article offers a framework for determining when it is "worth" taking action to try to avoid a potential disaster. Considering forecast probabilities, actions, and funding constraints, we propose a novel forecast-based financing system that would automatically trigger action based on forecasts of increased risks.
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