Decision making and long term planning in government, the private sector, and civil society can benefit from local estimates of the future probabilities of domain-specific climate event frequencies. This note describes methods for selecting and calibrating downscaled global climate models and using the modeled projections to generate probability models of complex climate hazard indicators. Information from the resulting probability distributions can inform decision-making in numerous domains, including public health, infrastructure planning, agriculture, risk management, and climate adaptation. The note provides the methods and two detailed examples.

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