Predicting impacts of weather-driven urban disasters in the current and future climate

Effective city operations depend on local weather conditions at the scale of critical urban infrastructure such as power and water distribution systems. This includes both routine and severe weather events. For example, with precipitation events, local topography and weather influence water runoff and infiltration, which directly affect flooding as well as drinking water quality and availability. The impact of such events creates issues of public safety. Thus, the availability of highly localized weather model predictions focused on public safety and operations of infrastructure can mitigate the impact of severe weather. This is especially true if the lead time for the availability of such predictions enables proactive allocation and deployment of resources to minimize recovery time from severe events. Typically, information at such a scale is simply not available. Hence, the ability of municipalities to proactively respond to these events is limited. Available continental- or regional-scale weather models are not appropriately matched to the temporal or spatial scale of such operations. While near-real-time assessment of observations of current weather conditions may have the appropriate geographic locality, by its very nature it is only directly suitable for reactive response. To address this gap, we use state-of-the-art physical weather models at the spatial scale of the city's infrastructure to avoid this mismatch in predictability. Model results are coupled to data-driven stochastic models to represent the actionable prediction of weather (business) impacts. In some cases, an intermediate physical model may be required to translate predicted weather into the phenomena that lead to such impacts. We have applied these ideas to several cities with a diversity of impacts and weather concerns and show how this coupled model methodology enables prediction of storm impacts on local infrastructure. We also discuss how this concept can be extended to a climate scale in order to evaluate the potential localized impacts of a warming planet and the effectiveness of strategies being used to mitigate such impacts.