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 kmÁh −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 WÁm −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 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.

ABSTRACT. In Madagascar, soil erosion is significant even when it is compared to world averages. A resulting special geomorphic feature is a form of gully erosion known as lavaka that appears in the highlands of the country. Lavakization (the generation and development of these features) is due to rather unique multifactorial environmental conditions. Among many factors (geology, soil composition, human activities, etc.)

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.

Clothing resistance parameter rcl and potential evapotranspiration (PET), a major component of Thornthwaite type climate classifications, are used as thermal climate indicators for characterizing the thermal climate of the Carpathian region. rcl is simulated by a model based on clothed human body energy balance considerations. rcl refers to a walking human in outdoor conditions, whose somatotype can differ. Somatotype shapes are determined by applying the Heath–Carter somatotype method. PET is estimated using only air temperature and latitude as inputs. In addition rcl is linked to PET. The annual mean of rcl is statistically interconnected with annual sum of PET, and the annual fluctuation of rcl (drcl = rclmax − rclmin) with the annual fluctuation of PET (dPET = PETmax − PETmin). The Carpathian region's thermal climate is analysed by comparing PET results with rcl model results and rcl results obtained by statistical link. We showed that rcl model results are strongly sensitive to human body somatotype variations. It is also shown that the spatial heterogeneity of thermal climates is the lowest in the lowlands and the highest in the mountains. The spatial heterogeneity of rcl and drcl values obtained by statistical link is comparable to the spatial heterogeneity of PET, but is lower than that obtained from the rcl model. Similarly to rcl model results, rcl results obtained by statistical link are also sensitive to human body somatotype variations. All these results suggest that statistical connections between rcl and PET and drcl and dPET can be used as subunits in Thornthwaite type climate classifications to obtain human thermal climate information. Lastly, areas with the largest thermal contrast are reproduced in terms of both the annual sum of PET and the rcl, which is obtained by both the model and the statistical link.