Most of the time, the predicted weather forecasts for a specific location gives little to no indication on whether one feels comfortable in a prevailing climate. Information about the expected air temperature does not necessarily help to decide how people might sense a place’s thermal comfort. Skiing below 0°C on a sunny day will feel pleasant, whereas the same scenario with fog and snow will make you wish to stay in a cozy living room. The other way around: How is it possible to relax in a sauna at 70°C or more and not being able to stay a couple of minutes on a sealed square without shadow at 28°C?
To find the underlying cause of this, thermal comfort indices have been developed to elaborate the subjective temperature sensation in different climate scenarios since the 1970’s. One of the first indices developed, the PMV (Predicted Mean Vote), where a person’s thermal comfort is calculated for indoor situations. To calculated the outdoor thermal comfort, indices like the PET (Physical equivalent temperature) and the UTCI ( Universal Thermal Climate Index) have been developed. They take into account not only a combination of the mean radiant temperature TMRT (received shortwave and longwave radiation), the wind speed (advection), the vapour-pressure deficit and air temperature, but also consider personal characteristics like clothing, sex, age, height and weight. Only by the use of this complex combination, a detailed examination of a person’s thermal comfort is possible.
Microclimate models use these thermal comfort indices to determine architectural disadvantages in highly heterogeneous cities and can help to develop improvement measures for the cities’ microclimate.
A typical application for thermal comfort studies are hot and humid areas, but in recent years, the fields of research have been enhanced to cold climates as well, for examining cold stress on pedestrians in artic regions. Thus, the application possibilities of thermal comfort indices are manifold.