Project Overview
While overall National Weather Service forecast capabilities have improved, the relative lack of observational data on heat and a gap in warning service are particularly significant for historically underserved and socially vulnerable communities (HUSVCs). In these areas there is an especially high prevalence of health concerns that increase susceptibility to heat risks, less access to medical care, and local geography and land cover can lead to higher heat values than currently captured by observational systems and forecast thresholds for warnings. This project addresses three priorities of the CSTAR program: 1) improving weather, water, and climate services to historically underserved and socially vulnerable communities (HUSVCs); 2) enhancing NWS services for HUSVCs at greater risk to negative impacts of heat; and 3) developing new messages and innovating communication processes to deliver forecasts and protective messages. A University of South Carolina–based team will work with the NWS CAE (Columbia, SC) forecast office and the SC Department of Health and Environmental Control’s Public Health Preparedness Office, in advancing heat warnings to underserved populations.
There are five project tasks:
1. Characterize variability of Wet Bulb Globe Temperatures (WBGT) across different
land cover areas.
2. Evaluate WBGT estimation methods and different inputs to compare WBGT against the
standard NWS heat index-based advisories and experimental products.
3. Identify the pre-existing attitudes and behaviors of underserved populations including
awareness of heat-health risks, sources of information about heat-weather, and frequency
in accessing such information.
4. Develop a NWS message on heat forecasts and preparedness designed to meet the needs
of members in the Midlands Public Health Preparedness Coalition.
5. Identify populations with greater susceptibility to heat based on geographic variability
and pre-existing conditions.
Funding: NOAA, Collaborative Science Technology and Applied Research (CSTAR) Program