Is There a Need to Integrate Human Thermal Models with Weather Forecasts to Predict Thermal Stress?

Int J Environ Res Public Health. 2019 Nov 19;16(22):4586. doi: 10.3390/ijerph16224586.


More and more people will experience thermal stress in the future as the global temperature is increasing at an alarming rate and the risk for extreme weather events is growing. The increased exposure to extreme weather events poses a challenge for societies around the world. This literature review investigates the feasibility of making advanced human thermal models in connection with meteorological data publicly available for more versatile practices and a wider population. By providing society and individuals with personalized heat and cold stress warnings, coping advice and educational purposes, the risks of thermal stress can effectively be reduced. One interesting approach is to use weather station data as input for the wet bulb globe temperature heat stress index, human heat balance models, and wind chill index to assess heat and cold stress. This review explores the advantages and challenges of this approach for the ongoing EU project ClimApp where more advanced models may provide society with warnings on an individual basis for different thermal environments such as tropical heat or polar cold. The biggest challenges identified are properly assessing mean radiant temperature, microclimate weather data availability, integration and continuity of different thermal models, and further model validation for vulnerable groups.

Keywords: cold spell; cold stress; heat stress; heat wave; human thermal models; meteorological forecast; thermal stress warning.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Cold Temperature*
  • Female
  • Forecasting
  • Heat Stress Disorders / epidemiology*
  • Heat Stress Disorders / physiopathology*
  • Heat-Shock Response / physiology*
  • Hot Temperature*
  • Humans
  • Male
  • Middle Aged
  • Models, Biological*
  • Sex Factors
  • Weather*