Contextualizing the Human Health Impact of Extreme Temperature Events using Intensity-Duration-Frequency Curves (AMS 2024)
Citation:
Tierney, G., M. Mallard, T. Spero, G. Gray, A. Jalowska, J. Willison, AND J. Bowden. Contextualizing the Human Health Impact of Extreme Temperature Events using Intensity-Duration-Frequency Curves (AMS 2024). 104th Annual Meeting of the American Meteorological Society, Baltimore, MD, January 28 - February 01, 2024.
Impact/Purpose:
Heat is the leading weather-related cause of fatalities in the United States, disproportionately affecting underserved communities. As heat waves are projected to increase in intensity and duration, providing decisionmakers with tools for effective action and communication around these events can mitigate their impact. This presentation summarizes the human health aspects of a framework based around intensity-duration-frequency (IDF) curves that can provide valuable context for extreme temperature events in real time. This framework utilizes an objective fitting algorithm covering a wide range of durations and return periods, making it extraordinarily flexible and customizable to the needs of the user. Such information can help stakeholders, such as emergency managers and government partners, to more effectively deploy heat adaptation measures and heat interventions in a timely manner to reduce the otherwise potentially devastating impacts of these events.
Description:
While dry-bulb temperature remains a familiar method for communicating heat hazards, metrics tailored to human health concerns – such as heat index and wet bulb globe temperature – are more holistic assessments of extreme temperature events’ potential for heat-related illness and death. With heat waves projected to increase in duration and intensity in the future, understanding and effectively communicating heat hazards to the public and stakeholders becomes even more crucial. Contextualizing these events in real-time can serve as additional near-term risk guidance for stakeholders, allowing them to draw on previous experience to enact the appropriate level of heat intervention and deploy mitigating measures. Long used in hydrology for quantifying flood risk, intensity-duration-frequency (IDF) curves can be utilized similarly in temperature applications, providing the expected return period of an event given its intensity and duration. By not imposing specific event definitions, IDF curves enable a single compact framework to inform a variety of human health applications, a few of which are highlighted in this presentation. We first demonstrate the construction of climatological IDF curves using an objective fitting algorithm applied to ASOS hourly observations (one of many potential options for input data). These climatological IDFs can then be combined with NWS forecasts and recent observational data within the framework to provide context for extreme events in real-time. Further distilling this product results in a tool with similar functionality for several stations simultaneously, covering scales from statewide to CONUS-wide, based on the needs of stakeholders. Potential customization of the IDF framework is subsequently demonstrated, including a focus on seasonal IDF curves, elevated overnight minimum temperatures, and applications beyond human health – exhibiting the far-reaching potential of this unified framework.
