Playing the long game: Anticipatory action based on seasonal forecasts
Acting in advance of floods, drought and cyclones often requires decision-makers to work with weather forecasts. The inherently probabilistic nature of these forecasts can be problematic when deciding whether to act or not. Cost-loss analysis has previously been employed to support forecast based de...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Elsevier
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/362e937f49294bc7b3852ef396055c63 |
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| Sumario: | Acting in advance of floods, drought and cyclones often requires decision-makers to work with weather forecasts. The inherently probabilistic nature of these forecasts can be problematic when deciding whether to act or not. Cost-loss analysis has previously been employed to support forecast based decision-making such as Forecast-based Financing (FbF), providing insight to when an FbF system has ‘potential economic value’ relative to a no-forecast alternative. One well-known limitation of cost-loss analysis is the difficulty of estimating losses (which vary with hazard magnitude and extent, and with the dynamics of population vulnerability and exposure). A less-explored limitation is ignorance of the temporal dynamics (sequencing) of costs and losses. That is, even if the potential economic value of a forecast system is high, the stochastic nature of the atmosphere and the probabilistic nature of forecasts could conspire over the first few forecasts to increase the expense of using the system over the no-forecast alternative. Thus, for a forecast-based action system to demonstrate value, it often needs to be used over a prolonged length of time. However, knowing exactly how long it must be used to guarantee value is unquantified. This presents difficulties to institutions mandated to protect those at risk, who must justify the use of limited funds to act in advance of a potential, but not definite disaster, whilst planning multi-year strategies. Here we show how to determine the period over which decision makers must use forecasts in order to be confident of achieving ‘value’ over a no-forecast alternative. Results show that in the context of seasonal forecasting it is plausible that more than a decade may pass before a FbF system will have some certainty of showing value, and that if a particular user requires an almost-certain guarantee that using a forecast will be better than a no-forecast strategy, they must hold out until a near-perfect forecast system is available. The implication: there is potential value in seasonal forecasts, but to exploit it one must be prepared to play the long game. |
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