Impact of urban form on heat index spatial and temporal
distribution based on WRF-BEP/BEM
Background:Urban heat islands exacerbate heat waves, leading to a high incidence of heat stroke.
WBGT index has been published by Japan’s Minister of the Environment to warn the risk inadvance, but there are still shortcomings:▪ Sparse monitors can hardly reflect the detailed distribution of WBGT across the city;▪ Most stations are located in open areas, without taking into account the impact of dense buildings
on wind, radiation, etc.
What should we do: Widespread deployment and maintenance of monitors is unrealistic, but aweather-urban canopy coupling model WRF-BEP/BEM can be used instead to reproduce thespatio-temporal distribution of WBGT within cities and explore it's relationship with urban form.

How to calculate WBGT? -- Measurement-based and simulation-basedStandard calculation formula from ISO

Fig. 1. WBGT measuring equipment

WBGT = 0.7 × Twb + 0.2 × Tg + 0.1 × Ta

Measurement-based method

Mesoscale simulation-based method▪The measurement system includes 3 types ofthermometers, placed in an open area.
▪Ta , Twb , Tg are measured by dry bulb thermometer,
wet bulb thermometer and black bulb thermometer,respectively.
▪Thermometers are located 1.5m above the ground▪ Twb can be calculated iteratively by air temperature,pressure and humidity.
▪ Tg can be approximated by air temperature, global
solar radiation and wind speed:

SR − 38.5
Tg = Ta +0.217SR + 4.5U + 23.5

Methodology: WRF-BEP/BEM with Gridded Urban Canopy Parameters (UCPs) imported▪ High temperature days from 2018-2022 were selected for simulation, 85 days in total.
▪The gridded Urban Canopy Parameters (UCPs) were calculated based on the Tokyo GIS
building information to provide an accurate input for the WRF-BEP/BEM. Fig. 2 c.
▪ Case 1CAT was created as a controlled experiment, taking the geometric parameters of allurban grids as an average of 23 wards. Fig. 2 b.
▪The gridded UCPs gave each computational grid independent geometric parameters, which
are key factors in reproducing the impact of urban form on microclimate. Fig. 3.

WRF
Domain setting(c)(b)(a)Fig. 2. Simulation area (a) and urban canopy parameters input settings. (b) 1CAT, (c) UCPs

Fig. 3. Comparison ofsimulation results with and without gridded UCPs.

Result and conclusion
Impact of urban form on the spatio-temporal distribution characteristics of WBGT
landform with the following formula:∗

WBGT = (WBGTUCPs /WBGT1CAT ) × WBGTave▪An equivalent WBGT (WBGT*) can intuitively
reflect the influence of urban form on the spatial
distribution of WBGT, and the influence is greater inthe afternoon than at midday.
Fig. 4. WBGT in 23 wards at different time, box plot. (a) case
UCPs, (b) difference between cases (UCPs-1CAT)

Temporal characteristics – Fig.4 and Fig. 5▪WBGT difference between regions peakedaround 12:00 noon, then narrowed slightly andremained broadly unchanged in the afternoon.
▪Differences in WBGT due to urban form weresignificant throughout the afternoon until rapidly
decreasing around sunset.
Spatial characteristics – Fig. 6

Fig 5. WBGT probability density
distribution in 23 wards at different times(width of bins is 0.25°C)▪The pronounced temperature gradient causedby the ocean confuses the the effect caused by
the urban form. However, the control experiment1CAT can be used to eliminate the influence of

Impact of urban form on heat index spatial andtemporal distribution based on WRF-BEP/BEM

Fig. 6. Spatial distribution of normalized
WBGT at 12:00 and 15:00.

Ooka・Kikumoto Laboratory
大岡・菊本研究室