Individual local human thermal climates in the Hungarian lowland: Estimations by a simple clothing resistance‐operative temperature model

Ács, Ferenc; Kristóf, Erzsébet; Zsákai, Annamária

doi:10.1002/joc.7910

Cited by 4 publications

(3 citation statements)

References 50 publications

(93 reference statements)

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“…Biases in the estimation of rcl index can be predominantly attributed to biases in temperature, but biases in wind speed and atmospheric downward radiation appear to be important factors as well. These results agree with the findings of Ács et al (2021a, 2023), considering that atmospheric radiation is more important than solar radiation in winter, owing to the increased cloud cover and shorter daylight hours.…”

Section: Discussionsupporting

confidence: 93%

Comparison of CMIP6 model performance in estimating human thermal load in Europe in the winter season

Szalkai,

Kristóf,

Zsákai

et al. 2024

Intl Journal of Climatology

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In this work, historical simulations of CMIP6 GCMs are evaluated with respect to the ERA5 reanalysis dataset, in order to examine their ability to assess human thermal load in Europe in the winter season. The period of 1981–2010 is chosen for the analysis, and thermal load is expressed via the clothing resistance index (rcl index; expressed in clo). It is found that the GCMs are able to reproduce the areal differences of thermal load satisfactorily, the spatial correlation with the reanalysis is greater than 0.95 in all cases. The effects of the main geographical constraints (latitude, continentality and elevation) are shown by all GCM simulations, as rcl index values are greater at higher latitudes, away from the ocean and in mountainous areas, although GCMs only capture major mountains (the Caucasus, the Armenian Highlands, the Scandinavian Mountains, the Alps). The root‐mean‐square error (RMSE) is around 0.2 clo in all cases, GCMs generally perform better in homogenous lowland areas, while results are less accurate in highlands and mountains owing to the coarse horizontal resolution of GCMs (~1°). The smallest errors occur over central and western Europe and the Mediterranean region, while results tend to be less accurate over the northeastern part of Europe. Biases in the estimation of heat deficit can mainly be attributed to biases in temperature, but biases in wind speed and atmospheric downward radiation seem to be important factors as well.

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Section: Discussionsupporting

confidence: 93%

Comparison of CMIP6 model performance in estimating human thermal load in Europe in the winter season

Szalkai,

Kristóf,

Zsákai

et al. 2024

Intl Journal of Climatology

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“…It should be mentioned that we did not perform thermal perception observations during the fog events. But we can also give an estimate based on [30]. In the case of the smallest heat deficit (r cl around 0-0.8 clo), the thermal perception type is "cool" or even "neutral".…”

Section: Discussionmentioning

confidence: 99%

“…However, in some recent model applications [28], the concept of "reference human" is not applied; instead, anthropometric data of real persons were used. The main result of these investigations [29,30] is that human thermal load is significantly sensitive to the interpersonal variations in the anthropometric data in the case of a large environmental heat deficit.…”

Section: Introductionmentioning

confidence: 99%

On the Human Thermal Load in Fog

Kristóf,

Ács,

Zsákai

2024

Meteorology

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We characterized the thermal load of a person walking and/or standing in the fog by analyzing the thermal resistance of clothing, rcl, and operative temperature, To. The rcl–To model applies to individuals using weather data. The body mass index and basal metabolic flux density values of the person analyzed in this study are 25 kg m−2 and 40 W m−2, respectively. Weather data are taken from the nearest automatic weather station. We observed 146 fog events in the period 2017–2024 in Martonvásár (Hungary’s Great Plain region, Central Europe). The main results are as follows: (1) The rcl and To values were mostly between 2 and 0.5 clo and −4 and 16 °C during fog events, respectively. (2) The largest and smallest rcl and To values were around 2.5 and 0 clo and −7 and 22 °C, respectively. (3) The rcl differences resulting from interpersonal and wind speed variability are comparable, with a maximum value of around 0.5–0.7 clo. (4) Finally, rcl values are significantly different for standing and walking persons. At the very end, we can emphasize that the thermal load of the fog depends noticeably on the person’s activity and anthropometric characteristics.

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New statistical deterministic method for estimating human thermal load and sensation — application in the Carpathian region

Ács

Kristóf

Szabó

et al. 2022

Theor Appl Climatol

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A new statistical deterministic model is presented for estimating human thermal load and sensation. Human thermal load is simulated in terms of clothing resistance (rcl) and operative temperature (To). The model’s input data are wind speed, air temperature, mass of the human body, body length, sex, age, and the latitude of the site. To is statistically linked to potential evapotranspiration, whilst human thermal perception to rcl. The model has been validated in the Carpathian Mountains region for the period 1971–2000 comparing it with the original deterministic rcl model. Thermal perceptions of the representative Hungarian male and female are estimated by using individual thermal perception–rcl point clouds. Metabolic heat flux density differences between persons are less than 15 Wm−2. Human thermal perception area distribution has a topography-based configuration. The prevailing annual perception of Hungarians (for both men and women) in lowland and hilly areas is “cool,” although “neutral” may also occur; in mountains, perception is mostly “cool” or “cold,” with “very cold” being also possible. In the month of July, the perception type in mountains is “neutral” or “cool” depending on the person. In lowland areas, the methodology cannot be applied since the energy balance is not met. The model can also be applied in other heat-deficient regions if the region-specific operative temperature–potential evapotranspiration and the human-specific thermal perception-rcl statistical relationships are determined for the new region.

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Individual local human thermal climates in the Hungarian lowland: Estimations by a simple clothing resistance‐operative temperature model

Cited by 4 publications

References 50 publications

Comparison of CMIP6 model performance in estimating human thermal load in Europe in the winter season

Comparison of CMIP6 model performance in estimating human thermal load in Europe in the winter season

On the Human Thermal Load in Fog

New statistical deterministic method for estimating human thermal load and sensation — application in the Carpathian region

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