Evaluating World Urban Database, Access Portal Tools and Copernicus Global Land Service for Urban Meteorological Simulations: A Case Study in Lyon

Urban Categories Green Categories Evaluating World Urban Database, Access Portal Tools and Copernicus Global Land Service for Urban Meteorological Simulations: A Case Study in Lyon Introduction: Urban Heat Island (UHI) effect is the intensified heat in urban areas with few green spaces, causing much higher temperatures. UHI significantly impacts both humans and the environment: Higher energy consumption. Elevated air pollution. Poor human health. Mitigation solutions include photovoltaic systems, green roofs, and cool roofs – all these subjects require much further research. Accurate Land Use and Land Cover (LULC) data is essential to environmental management & planning, and climate change research. The Weather Research and Forecasting (WRF) model plays an important role in improving weather predictions and urban planning. Objective: To compare the WUDAPT-LCZ and CGLC datasets, both with 10 land use categories, for predicting weather parameters and improving accuracy in PV and cool roof studies. Results: Land Use Land Categories Wudapat-LCZ provides more accurate land use data compared to CGLC, as it is based on the latest data from Google Earth. Data Validation Both datasets capture diurnal variations while maintaining significant statistical reliability. Temperature Difference LCZ -CGLC: Wudapat-LCZ and CGLC provide similar predictions, with an average temperature difference of just 1 degree. Temperature at 2m Both datasets accurately represent temperature at 2 meters, but variations in land use cause slight differences in their results. Albedo Both datasets show significant differences in albedo due to variations in land use. Discussion: The Wudapat-LCZ dataset offers more accurate land use categories but predicts temperatures an average of 1 degree lower than the CGLC dataset compared to actual weather temperatures. For studies on PV integration, cool roofs, green roofs, and especially Urban Heat Island (UHI) effects, the superior land use accuracy of Wudapat-LCZ is more beneficial despite its slight temperature prediction discrepancy, as UHI is a major concern. Methodology: Replaced MODIS urban data with WUDAPT-LCZ / CGLC dataset in WRF WRF simulations with updated LULC data Validation of results against observational data Comparison of Wudapat-LCZ and CGLC City polygons via Google Earth LULC input data generation (via WUDAPT) Global LULC data collection (from CGLC) Hamza Nisar , Christophe Menezo , and Mattheos Santamouris 1,2 1 2 WUDAPAT - LCZ CGLC WUDAPAT - LCZ CGLC WUDAPAT - LCZ CGLC (1,2) Hamza Nisar ([email protected]) (1) Université Savoie Mont Blanc, Chambéry, France (2) University of New South Wales, Sydney, Australia References: [1] Siewert, Jolanta, and Krzysztof Kroszczynski.Remote Sensing 15.9 (2023): 2389. [2] Brousse, Oscar, et al. Urban Climate 17 (2016): 116-134.