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High-Resolution Simulation of the Urban Heat Island Effect in Grenoble During the 2018 Heatwave: Evaluating WRF Model Configurations
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Abstract
This study investigates the Urban Heat Island (UHI) effect in Grenoble, France, during the August 2018 heatwave, using high-resolution Weather Research and Forecasting (WRF) simulations at 111 meters. The objective is to evaluate at this resolution the capac- ity of different WRF urban parameterizations such as the Building Effect Parameterization (BEP) and Building Energy Model (BEM), to simulate the UHI effect and overall temper- ature distribution. The validation approach integrates data from official weather stations, crowdsourced Citizen Weather Stations (CWS), and empirical and modeling studies of the UHI in Grenoble. Results show that configurations with advanced urban parameterizations significantly enhance the ability to capture the spatial structure of UHI in urban areas while maintaining strong performance in non-urban regions. However, a trade-off was identified: models that accurately capture the spatial distribution of UHI often exhibit larger errors in absolute temperature predictions, particularly at individual stations. Additionally, all config- urations struggled to simulate thermal wind reversals, a key process affecting UHI dynamics in Grenoble’s valley. This work highlights the importance of advanced urban parameteriza- tions in improving UHI modeling in complex urban and topographic settings.
DOI
https://doi.org/10.31223/X53N0W
Subjects
Atmospheric Sciences, Climate, Fluid Dynamics, Meteorology, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Physics
Keywords
Urban Climate, Urban parameterization, Building morphology, Land surface model, WRF model, BEP-BEM, Urban Heat Island, Frontal area index, lidar, Building height, Raster processing, Geospatial modeling, Urban adaptation, Remote Sensing, Climate simulations
Dates
Published: 2025-08-21 22:50
Last Updated: 2025-08-21 22:50
License
CC BY Attribution 4.0 International
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Data Availability (Reason not available):
All Data Available Upon Request
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