20/04/23

The urban heat island (UHI) effect and its sensitivity to large-scale atmospheric flow

Koen De Ridder

20/04/23 2© 2012, VITO NV

The UHI phenomenon

» urban-to-rural temperature excess

» most intense during the evening and early night

» causes:» low albedo» large thermal inertia» limited water availability» poor thermal exchange» anthropogenic heating» …

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Why it is importantHealth

“The evidence that heat waves can result in both increased deaths and illness is substantial, and concern over this issue is rising because of climate change”

Energy

Sailor, D. J. 2002. Urban Heat Islands, Opportunities and Challenges for Mitigation and Adaptation. Sample Electric Load Data for New Orleans, LA (NOPSI, 1995). North American Urban Heat Island Summit. Toronto, Canada. 1-4 May 2002. Data courtesy Entergy Corporation.

Reid CE, O’Neill MS, Gronlund CJ, Brines SJ, Brown DG, Diez-Roux AV, et al. 2009. Mapping Community Determinants of Heat Vulnerability. Environ Health Perspect 117:1730-1736.

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VITO’s urban climate model (UrbClim)

LAICa urbanized surface energy balance model

20/04/23 5© 2012, VITO NV

UrbClim features

» nested in output of global- or regional-scale models in such a way that it stays close to the large-scale atmospheric fields (UrbClim calculates an urban increment)

» employs generic data sets for Europe (CORINE land cover, satellite vegetation index, …)

» operates at a relatively high spatial resolution of 250 m, accounts for urban canopy layer effects

» is very fast – typically a simulation for a 12012020 domain at 250 m resolution takes 48 hours for a Summer season (May-September)

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Mean 22:00 UHI intensity Ghent, August 2012

temperature ranges from 0°C (dark blue) to 3°C (dark red)

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UHI intensity Paris (May-Sep 2003, 22:00 UT)

temperature ranges from 0°C (dark blue) to 9.6°C (dark red)

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UHI versus city size

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UHI intensity Ghent (Aug 2012) RMSE ~ 1.0°CBIAS ~ 0.2°CCORR ~ 0.69

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UHI prediction

CMIP5

UrbClim

socio-economic

health effectsheat stress exposurestratified by population, housing conditions, etc…

city selection

observations

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Service aspects – users

timenow

medium-to-far future (~ 2030-2100)

short-term forecast(~ days)

retrospective(~ 10 years)

seasonal-decadalpredictions

urban administrations(environment, …)

urban plannersclimate adaptation

hospitalscivil protectionenergy providers

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