A human body–clothing–atmosphere environment system energy balance model is constructed to evaluate individual human thermal climates in the Carpathian Basin. The analysis is performed in terms of clothing resistance and operative temperature for the period 1971–2000. The model's main strength is that it simulates the metabolic activity rate M as simply as possible taking into account interpersonal variations. Non‐sweating, walking humans are considered in natural outdoor conditions at a walking speed of 4 km⋅h⁻¹. Atmospheric data are used from the CarpatClim dataset; human data are taken from a Hungarian human dataset. The dataset reveals that the interpersonal variations of M of walking humans can reach 40–50 W⋅m⁻². According to the results, the variability of individual human thermal climates can be significant. This variability increases towards cold climates and is less in the comfortable thermal zone, when the operative temperature is between 23 and 28°C. It should be mentioned that summer is thermally neutral in the Little Hungarian Plain, the Great Hungarian Plain and in larger parts of the Transylvanian Plateau, irrespective of the person considered. The warmest areas in the Carpathian Basin can be found in Bačka and Banat. In terms of thermal sensation, the results obtained agree well with the results referring to the human considered in the Physiological Equivalent Temperature index model.

The Carpathian Basin climate in the time period 1971–2000 is analyzed in terms of the results obtained by the Köppen method and a clothing resistance scheme. A clothing resistance scheme is based on human body energy balance considerations taking into account human interperson variations as simply as possible. Interperson variations are considered by estimating human body somatotypes using the Heath-Carter somatotype classification method. Non-sweating, walking humans in outdoor conditions are treated. Environmental and human data are taken from the CarpatClim dataset and a Hungarian human dataset, respectively. Though the biophysical bases of the methods are completely different, the spatial structure of thermal climates expressed in terms of Köppen climate types and the clothing resistance parameter r_cl are basically similar. A clothing resistance scheme creates more information than the Köppen method not only in mountain, plateau areas but also in lowlands. It is shown that more human thermal climate categories can refer to one Köppen climate formula irrespective of which Köppen formulae are considered. The magnitude and area heterogeneity of r_cl is strongly sensitive to human somatotype changes. A clothing resistance scheme cannot be used in classroom applications; it needs to be drastically simplified while maintaining its sensitivity to somatotype changes in order to be competitive with the Köppen method.

The Köppen method, the Worldwide Bioclimatic Classification System (WBCS), and Feddema's descriptive climate classification method are used to analyse the Larger Carpathian Region (LCR) climate. Minimum, maximum and average temperature, precipitation and latitude and elevation data as input data are taken from the CarpatClim dataset. It refers to the period 1961–2010 with a 1‐day temporal resolution and a spatial resolution of 0.1° × 0.1°. The methods are compared in terms of their capability to represent climate heterogeneity and thermal and moisture characteristics on the annual and seasonal time scales. The region's climate is analysed separately for lowland, hill, mountain and high mountain regions using the results of the Köppen method as reference. The WBCS gave the highest spatial climate heterogeneity, followed by Feddema's method, and then the Köppen method in all three region types. However, the WBCS has the largest data input requirement. The rarest climate type according to the Köppen method is ET. This climate type is registered according to the Feddema and WBCS methods by three different climate types. The most frequent climate type according to the Köppen method is Cfb. This climate type is represented by 19 and 14 climate types according to the Feddema and the WBCS methods, respectively. The most frequent climate type according to Feddema's method is cool and dry with extreme seasonality of T and according to WBCS it is temperate continental steppic supratemperate sub‐humid. The coldest climate is produced by Feddema, the warmest by the WBCS. The Feddema method treats seasonality in the most comprehensive way. The Feddema and the WBCS methods reproduced the large climate heterogeneity of the LCR. The results can also be used as basic information in the PannEx project, as well as in future environmental and regional climate change‐related investigations for estimating thermal and moisture stresses.

Human thermal climate in the Hungarian lowland is investigated by using a clothing resistance‐operative temperature model performing individual, local, and long‐term concurrent observations of weather and human thermal perception. Human thermal load is characterized in terms of clothing resistance r_cl and operative temperature T_o. The model is also used as a tool to analyse the relationship between r_cl and the structural parameters of the body (relative fat mass index (fatBMI) and relative muscle mass index (muscleBMI)). This analysis works with data collected on more than 1,000 occasions of weather and thermal perception observation and uses body structure data of more than 3,000 adults and children. By analysing the data, the following human thermal climate characteristics have been established. (a) T_o of about 80°C can be considered as the upper limit of heat stress in the Hungarian lowland, similarly, T_o of about −35 to −37°C can be taken as the lower limit of cold stress. (b) Interpersonal thermal load variations increase with increasing of cold stress; these variations are the smallest within the “thermoneutral” zone. (c) In cold stress situations, there is a significant sexual dimorphism in the relationship between r_cl and fatBMI. (d) In night time period of the day, T_o can vary between 25°C and the lower limit of cold stress. In this range of T_o, thermal perception types “neutral,” “cool,” “cold,” and “very cold” occurred. Based on the results, it can be seen that interpersonal thermal load variations cannot be neglected in extreme cold weather conditions, and that interpersonal variations of fatBMI index are determinant in the formation of individual clothing resistance.