Estimation of thermal comfort felt by human exposed to extreme heat wave in a complex urban area using a WRF-MENEX model

Hwang, Mi-Kyoung; Bang, Jin-Hee; Kim, Sangil; Kim, Y.-K.; Oh, Inbo

doi:10.1007/s00484-019-01705-1

Cited by 15 publications

(5 citation statements)

References 34 publications

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“…The increasing frequency, intensity and duration of HWs in different world regions seem to follow the observed global warming in recent decades [3,4]. The impact of HWs on human health has been investigated in terms of mortality, morbidity and hospital admissions as well as in terms of heat stress and human body's energy balance [5][6][7][8][9][10][11][12]. The populations in low and middle income countries are more affected from HWs as compared to high income countries and as global warming progresses, they will still be more affected [13].…”

Section: Introductionmentioning

confidence: 99%

Response of Urban Heat Stress to Heat Waves in Athens (1960–2017)

Katavoutas

Founda

2019

Atmosphere

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The increasing frequency, intensity and duration of heat waves seem to follow the observed global warming in recent decades. Vulnerability to heat waves is expected to increase in urban environments mainly due to population density and the effect of the urban heat island that make cities hotter than surrounding non-urban areas. The present study focuses on a vulnerable area of the eastern Mediterranean, already characterized as a ‘hot spot’ with respect to heat-related risk and investigates the change in heat stress levels during heat wave compared to non-heat wave conditions as well as the way that heat stress levels respond to heat waves in urban, compared to non-urban, environments. The adoption of a metric accounting for both the intensity and duration of the hot event yielded a total of 46 heat wave episodes over a nearly 60-year period, but with very rare occurrence until the late 1990s and a profound increased frequency thereafter. The results reveal a difference of at least one thermal stress category between heat wave and non-heat wave periods, which is apparent across the entire range of the thermal stress distribution. The analysis demonstrates a robust intensification of nighttime heat stress conditions in urban, compared to non-urban, sites during severe heat waves. Nevertheless, severe heat waves almost equalize heat stress conditions between urban and non-urban sites during midday.

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Section: Introductionmentioning

confidence: 99%

Response of Urban Heat Stress to Heat Waves in Athens (1960–2017)

Katavoutas

Founda

2019

Atmosphere

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“…The observation data at 10 weather stations (Figure 3, Table 2) over Hong Kong were collected and compared against WRF-WUDAPT simulation results. The root-mean-square errors (RMSEs) of 2-m air temperature (T2), 2-m relative humidity (RH2), 2-m specific humidity (q2), and 10-m wind speed (W10) at all 10 stations (Table 2) were within acceptable ranges [33,[43][44][45][46], showing reasonable accuracy of model simulations. Specifically, for air temperature, RMSEs at all stations (1.1-1.8 C) were comparable with previous WRF studies [33,43,44].…”

Section: Model Evaluationmentioning

confidence: 99%

“…The root-mean-square errors (RMSEs) of 2-m air temperature (T2), 2-m relative humidity (RH2), 2-m specific humidity (q2), and 10-m wind speed (W10) at all 10 stations (Table 2) were within acceptable ranges [33,[43][44][45][46], showing reasonable accuracy of model simulations. Specifically, for air temperature, RMSEs at all stations (1.1-1.8 C) were comparable with previous WRF studies [33,43,44]. For relative humidity and specific humidity, average RMSEs at urban stations were slightly larger than those at most suburban and rural stations, which are all in similar ranges (RH2: 7.2-11.9 %, q2: 1.3-2.3 g/kg) with previous WRF studies covering over 10 cities in China [33,44,45].…”

Section: Model Evaluationmentioning

confidence: 99%

High-resolution regional modeling of urban moisture island: mechanisms and implications on thermal comfort

Jooho

Huang

et al. 2022

Building and Environment

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“…The WRF model, which was developed by NCAR/NCEP, the Forecast Systems Laboratory, and other university scientists, is widely used in weather forecast or prediction and long-term research [20,45,46]. The WRF model is also widely used to research extreme weather, especially during heatwaves or hot weather [9,[47][48][49][50].…”

Section: Model Setupmentioning

confidence: 99%

Integrating Remote-Sensing and Assimilation Data to Improve Air Temperature on Hot Weather in East China

Liu

Pan

et al. 2021

Remote Sensing

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Land-surface characteristics (LSCs) and land-soil moisture conditions can modulate energy partition at the land surface, impact near-surface atmosphere conditions, and further affect land–atmosphere interactions. This study investigates the effect of land-surface-characteristic parameters (LSCPs) including albedo, leaf-area index (LAI), and soil moisture (SM) on hot weather by in East China using the numerical model. Simulations using the Weather Research and Forecasting (WRF) Model were conducted for a hot weather event with a high spatial resolution of 1 km in domain 3 by using ERA-Interim forcing fields on 20 July 2017 until 16:00 UTC on 25 July 2017. The satellite-based albedo and LAI, and assimilation-based soil-moisture data of high temporal–spatial resolution, which are more accurate to match fine weather forecasts and high-resolution simulations, were used to update the default LSCPs. A control simulation with the default LSCPs (WRF_CTL), a main sensitivity simulation with the updated LSCP albedo, LAI and SM (WRF_CHAR), and a series of other sensitivity simulations with one or two updated LSCPs were performed. Results show that WRF_CTL could reproduce the spatial distribution of hot weather, but overestimated air temperature (Ta) and maximal air temperature (Tamax) with a warming bias of 1.05 and 1.32 °C, respectively. However, the WRF_CHAR simulation reduced the warming bias, and improved the simulated Ta and Tamax with reducing relative biases of 33.08% and 29.24%, respectively. Compared to the WRF_CTL, WRF_CHAR presented a negative sensible heat-flux difference, positive latent heat flux, and net radiation difference of the area average. LSCPs modulated the partition of available land-surface energy and then changed the air temperature. On the basis of statistical-correlation analysis, the soil moisture of the top 10 cm is the main factor to improve warming bias on hot weather in East China.

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Estimation of thermal comfort felt by human exposed to extreme heat wave in a complex urban area using a WRF-MENEX model

Cited by 15 publications

References 34 publications

Response of Urban Heat Stress to Heat Waves in Athens (1960–2017)

Response of Urban Heat Stress to Heat Waves in Athens (1960–2017)

High-resolution regional modeling of urban moisture island: mechanisms and implications on thermal comfort

Integrating Remote-Sensing and Assimilation Data to Improve Air Temperature on Hot Weather in East China

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