Extreme Heat Decision-Making: Perspectives on Data used by Emergency Managers

Excessive heat events are increasing around the world. Preparation for and response to excessive heat events can be informed by real-time environmental monitoring and assessment of societal vulnerabilities. This is key for decision-making that can save lives. The type of information necessary can vary between events, requiring emergency managers to understand meteorological variables, environmental conditions, and vulnerable populations at different scales and time periods. Variables may include atmosphere measures of temperature, humidity, pressure, wind, etc.; data about conditions in the built environment that exacerbate heat corridors such as green spaces and access to shade; and demographic information such as population density, housing type, and resident characteristics.

The kind of information used by decision-makers may also be affected by their ability to access it, how it is presented (e.g., static or dynamic), at what timeframe and how useful it is perceived to be. Furthermore, depending on their prior training, knowledge, and experiences, emergency managers may choose to access and make use of data for decision-making in different ways. Importantly, products and tools that are created for decision makers to monitor excessive heat forecasts can increase their capacity to respond in a timely and effective manner, especially if their decision-making needs are considered. This warrants understanding what they do want to use for decision-making, how they use that information, and why.

In this talk, we present findings from interviews with ten emergency managers across the U.S. about decision-making and extreme heat events with a focus on the data that is most useful to them. Using an interactive exercise, emergency managers identified the vulnerabilities they are most concerned about (e.g., societal, infrastructure, or other), the types of data they need (e.g., atmospheric, population, housing), and the sources from which they obtain data over the course of an extreme heat event. Participants then discussed how each datapoint is useful for specific decisions that are made to initiate resource deployment or issue risk messaging. The results of these interviews will inform the design of a dashboard useful for decision-making in the context of excessive heat.