Offering a model for estimating black globe temperature according to meteorological measurements

Hajizadeh, Roohalah; Dehghan, Somayeh Farhang; Golbabaei, Farideh; Jafari, Sayed Mohammad; Karajizadeh, Mehrdad

doi:10.1002/met.1631

Cited by 32 publications

(13 citation statements)

References 10 publications

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“…The ambiguous result suggests that caution should be used when applying T g coefficients derived from one environment to another environment, even within the same climate zone and the same general region. The results also might be an indicator of the limits of using a fairly simple equation, like the approach by Hajizadeh et al (2017) that we used here. Methods that apply a full energy balance equation, though more data intensive, might be more robust to changes in environment.…”

Section: Resultsmentioning

confidence: 76%

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Methods for Estimating Wet Bulb Globe Temperature From Remote and Low‐Cost Data: A Comparative Study in Central Alabama

et al. 2020

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Heat stress is a significant health concern that can lead to illness, injury, and mortality. The wet bulb globe temperature (WBGT) index is one method for monitoring environmental heat risk. Generally, WBGT is estimated using a heat stress monitor that includes sensors capable of measuring ambient, wet bulb, and black globe temperature, and these measurements are combined to calculate WBGT. However, this method can be expensive, time consuming, and requires careful attention to ensure accurate and repeatable data. Therefore, researchers have attempted to use standard meteorological measurements, using single data sources as an input (e.g., weather stations) to calculate WBGT. Building on these efforts, we apply data from a variety of sources to calculate WBGT, understand the accuracy of our estimated equation, and compare the performance of different sources of input data. To do this, WBGT measurements were collected from Kestrel 5400 Heat Stress Trackers installed in three locations in Alabama. Data were also drawn from local weather stations, North American Land Data Assimilation System (NLDAS), and low cost iButton hygrometers. We applied previously published equations for estimating natural wet bulb temperature, globe temperature, and WBGT to these diverse data sources. Correlation results showed that WBGT estimates derived from all proxy data sources-weather station, weather station/iButton, NLDAS, NLDAS/iButton-were statistically indistinguishable from each other, or from the Kestrel measurements, at two of the three sites. However, at the same two sites, the addition of iButtons significantly reduced root mean square error and bias compared to other methods.Plain Language Summary Heat stress is a buildup of body heat that can lead to illness, injury, or death. One method for estimating heat stress is an index called wet bulb globe temperature (WBGT). The index is usually measured with a monitor that records three types of temperature measurements and combines them. However, this method can be expensive, time consuming, and requires careful attention. Therefore, researchers have tried to use standard measurements such as wind speed, temperature, humidity, etc., to calculate WBGT. Building on these efforts, we wanted to determine if it was possible to accurately calculate WBGT with a variety of inexpensive data sources in central Alabama. We used previously published equations to estimate WBGT. Results showed that all proxy methods accurately estimated WBGT in two Alabama locations, but that using local measurements did change estimates of the number of potentially dangerous heat episodes relative to estimates that rely on remote sources of weather data. The ability to use easily accessible measurements could be a powerful tool for studies and interventions related to heat stress.

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Section: Resultsmentioning

confidence: 76%

“…To calculate T g , we followed a method similar to Hajizadeh et al (2017) in which a regression was fit based on SR, T a , RH, and known T g . We generated a single, cross‐site equation for T g based on Kestrel monitor data from all three sites.…”

Section: Methodsmentioning

confidence: 99%

Methods for Estimating Wet Bulb Globe Temperature From Remote and Low‐Cost Data: A Comparative Study in Central Alabama

et al. 2020

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“…The aim of the present study was to assess thermal comfort and heat stress indices in outdoor occupations for a 15‐year period by referring to the database of the meteorological stations at Sari. The use of meteorological data in the estimation of heat stress for outdoor jobs has a number of advantages, including the continuous nature of the record and the possibility of providing a comprehensive, cost effective and reliable dataset (Hajizadeh et al , ). Moreover, variables such as dry‐bulb temperature, solar radiation and relative humidity are measured by most weather stations, and these data can be easily used to evaluate heat and cold stress under different environmental conditions (Hajizadeh et al , ).…”

Section: Discussionmentioning

confidence: 99%

Thermal comfort and heat stress indices for outdoor occupations over 15 years: a case study from Iran

Ghalhari

Dehghan

Shakeri

et al. 2019

Weather

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The present study aims to assess seasonal trends in thermal comfort and heat stress indices for outdoor occupations over a 15‐year period using the Iranian Meteorological Organization's database for Sari, Iran. Hourly and daily meteorological data including temperature, wind speed, cloudiness, relative humidity and vapor pressure measurements for Sari city from 2000 to 2014 are used. The wet‐bulb globe temperature (WBGT) and universal thermal climate index (UTCI) are calculated, along with thermal comfort indices including physiological equivalent temperature (PET), standard effective temperature (SET) and predicted mean vote (PMV). The highest and lowest mean monthly air temperature values for the 15‐year period were recorded for August (27.55 ± 0.57°C) and January (7.9 ± 0.68°C), respectively. The highest and lowest mean monthly relative humidity values were observed for December (81.2 ± 2.6%) and August (73.7 ± 1.94%), respectively. The strongest correlations were found between all of the thermal comfort and heat stress indices under study and air temperature (r = 0.97–0.99; P < 0.001), as well as all indices and mean radiant temperature (r = 0.96–0.98; P < 0.001). Strong significant correlations were observed between all heat stress and thermal comfort indices (r > 0.93; P < 0.001). The use of meteorological data can enable the prediction of physiologically stressful conditions via knowledge of the strong positive correlation between heat stress and certain physiological indices, as highlighted in this study.

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“…For outdoor conditions, the WBGT is calculated as follows (Epstein and Moran, ):

WBGT = 0.7 T_{w} + 0.2 T_{g} + 0.1 T_{d},

where T w is the wet‐bulb temperature, T g is the globe temperature and T d is the dry bulb temperature. T g was calculated using the following formula (Hajizadeh et al ., ):

T_{g} = 0.01498 S + 1.184 T_{d} - 0.0789 RH - 2.739,

where S is the solar radiation (W/m 2 ) and RH is the relative humidity (%). T w was calculated using the Davies‐Jones () equation, as calculated using the HumanIndexMod developed by Buzan et al .…”

Section: Methodsmentioning

confidence: 97%

“…where T w is the wet-bulb temperature, T g is the globe temperature and T d is the dry bulb temperature. T g was calculated using the following formula (Hajizadeh et al, 2017):…”

Section: Heat Stress Calculationmentioning

confidence: 99%

The impact of climate change and urban growth on urban climate and heat stress in a subtropical city

Chapman

Thatcher

Salazar

et al. 2019

Intl Journal of Climatology

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Urban residents face increasing risk of heat stress due to the combined impact of climate change and intensification of the urban heat island (UHI) associated with urban growth. Considering the combined effect of urban growth and climate change is vital to understanding how temperatures in urban areas will change in the future. This study investigated the impact of urban growth and climate change on the UHI and heat stress in a subtropical city (Brisbane, Australia) in the present day (1991–2000) and medium term (2041–2050; RCP8.5) during summer. A control and urban growth scenario was used to compare the temperature increase from climate change alone with the temperature increase from climate change and urban growth. Average and minimum temperatures increased more with climate change and urban growth combined than with climate change alone, indicating that if urban growth is ignored, future urban temperatures could be underestimated. Under climate change alone, rural temperatures increased more than urban temperatures, decreasing the effect of the UHI by 0.4 °C at night and increasing the urban cool island by 0.8 °C during the day. With climate change, the number of hot days and nights doubled in urban and rural areas in 2041–2050 as compared to 1991–2000. The number of hot nights was higher in urban areas and with urban growth. Dangerous heat stress, defined as apparent temperature above 40 °C, increased with climate change and occurred on average 1–2 days every summer during 2041–2050, even in shaded conditions. There was higher temperature increases with urban growth and climate change than with climate change alone, indicating that reducing the effect of the UHI is vital to ensuring urban growth does not increase the heat stress risks that urban residents will face in the future.

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Offering a model for estimating black globe temperature according to meteorological measurements

Cited by 32 publications

References 10 publications

Methods for Estimating Wet Bulb Globe Temperature From Remote and Low‐Cost Data: A Comparative Study in Central Alabama

Methods for Estimating Wet Bulb Globe Temperature From Remote and Low‐Cost Data: A Comparative Study in Central Alabama

Thermal comfort and heat stress indices for outdoor occupations over 15 years: a case study from Iran

The impact of climate change and urban growth on urban climate and heat stress in a subtropical city

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