Heat Stress Compensability Classification (HSCC) interactive map: Updating HSCC application for 96 cities in the US

This repository includes the interactive map in the format .html of the very first application of the Heat Stress Compensability Classification (HSCC) in 96 cities in the United States. The HSCC is a new approach that characterizes extreme heat exposure using principles of human heat exchange. It focuses on uncompensable heat stress (UHS) or those conditions where the body is unable to maintain a stable internal temperature.

Original publication: Guzman-Echavarria, G., Middel, A., Vecellio, D.J., Vanos, J.K. (2024).The development of an adaptive heat stress compensability classification applied to the United States, International Journal of Biometeorology. https://doi.org/10.1007/s00484-024-02766-7

Methods updated and discussion in: Guzman-Echavarria, G., Middel, A., Vecellio, D.J., Vanos, J.K. (2025). The Heat Stress Compensability Classification (HSCC) applied to the United States: Update and Code, International Journal of Biometeorology.

Contents:

This repository contains an interactive map that offers the detailed results of the very first application of the classification system, as in the journal article: The Development of an Adaptive Heat Stress Compensability Classification Applied to the United States, published in the 4th SNP special issue in the International Journal of Biometeorology. The results of this visualization were obtained from open-source data and coding packages such as Folium, and the model results were obtained by applying the Python Human Heat Balance (PyHHB) on a freely available weather data.

The interactive map provides a detailed visualization of the results from each city, allowing you to view three tabs when the icon of the pie chart from each location is clicked.

Tab: Statistics: Detail per city of percentage of time in each category as updated Figure 4b of the original publication.

Tab: Histogram 2D: Details per city as update of Figure 6 of the original publication. This histogram displays complementary avenues of human heat exchange in the X-axis and Y-axis to provide an idea of heat flux magnitudes in relation to compensable/uncompensable heat stress (UHS) and how UHS is disaggregated into the HSSC categories.

Tab: How to read the 2D histogram?: Details on how the categories are linked in the HSCC within 2D histogram areas (Figure 1 in the 2025 publication).

Changes in the HSCC interactive map from the previous version:

1. Update the interactive supplemental map labels and subplots to account for the updates made in the commentary paper.

From: Evaporative heat loss (W/m²) - Emax *ωmax + Eres  To: Evaporative heat loss (W/m²) - Min (Emax *ωmax , Emax sweat )+ Eres

2. Fixed an indexing bug on how we selected a single “peak hour” when Tmax values happened for more than one hour in a day. For those hot days that produced multi-hour peak hours, the code was computing averages instead of picking instantaneous values from a single hour. The reason was a pandas SettingWithCopyWarning that produced averaged values. The code was changed and now it selects the first occurrence of the Tmax value and does explicit copy-and-loc assignments. This affects <0.05% of peak days, and we verify there are no changes in overall results, as you may see comparing the current pie charts versus the original publication.

For questions related to this dataset/code, please contact Gisel Guzman-Echavarria (gguzma20@asu.edu).

Guzman-Echavarria, G., & Vanos, J. (2023). PyHHB: Physiological-based estimations of human survivability and liveability to heat in a changing climate (Nature Communications (1.0.0)). Zenodo. https://doi.org/10.5281/zenodo.10020137

This visualization is made available under a Creative Commons Attribution 4.0 International License (CC BY 4.0). You are free to reuse, adapt, and redistribute with proper attribution.