How well does the local climate zone scheme discern the thermal environment of Toulouse (France)? An analysis using numerical simulation data

Abstract

To build healthy, resilient, and climate‐responsive cities, planners need ways to understand the local complexities of urban thermal climates. To assist in meeting this need, this study employs the simple classification of “local climate zones” (LCZs) to conduct a spatiotemporal thermal climatic analysis of the Toulouse Metropolitan Region (France) under warm and dry summer conditions. Simulations are performed using the mesoscale atmospheric model Méso‐NH. These simulations provide a city‐wide spatial coverage of 2‐m air temperature (T2M), mean radiant temperature (MRT), and Universal Thermal Climate Index (UTCI). Model parameters describing the urban morphology are initialized based on administrative databases and independent of LCZ maps, which allows for an evaluation of whether the distributions of the modelled thermal climatic parameters will differ between LCZs. The results show that different LCZs possess significantly different distributions of T2M and MRT, confirming the suitability of the LCZ scheme for discerning the thermal environment of Toulouse. Compact urban settings (LCZ 1/2/3) show the highest T2M throughout the day and a nocturnal temperature difference of up to 2.8 K compared to rural settings. The MRT of LCZ 1/2/3 in the late afternoon (1700–2000 LST (UTC + 2)) can be as much as 6.3 K lower than it is for LCZs with open settings due to shading by dense urban structures. Additional analysis reveals that the intra‐LCZ variabilities of T2M and MRT may be explained by the distance to the city centre. Finally, the thermal stress in different LCZs is assessed with the modelled UTCI. Among the built LCZs, the probability of strong heat stress is the highest for open high/mid‐rise (LCZ 4/5) and lowest for sparsely built (LCZ 9) and open low‐rise (LCZ 6) settings. For land cover type LCZs, dense trees (LCZ A) are the most favourable for daytime outdoor human thermal comfort.

A Statistical–Dynamical Downscaling for the Urban Heat Island and Building Energy Consumption—Analysis of Its Uncertainties

“…For this reason, they are cooled by advection from the adjacent rural areas. This is captured by Meso-NH and consistent with the findings of Kwok et al (2019). Interestingly, station 15, which is located about 100 m higher than the other stations is not an outlier, probably due to the presence of inversions during the night.…”

“…2a and 2b. For more details on the model configuration, the reader is referred to section 3 of Kwok et al (2019).…”

Assessing the potential and application of crowdsourced urban wind data

“…So far, the framework has mainly been applied in studies investigating air temperature differences (e.g., Alexander and Mills, 2014;Stewart et al, 2014;Leconte et al, 2015;Skarbit et al, 2017;Beck et al, 2018). Others showed that different LCZs also possess different characteristics in terms of humidity (e.g., Unger et al, 2018a;Yang et al, 2020) or human thermal comfort (e.g., Geletič et al, 2018;Unger et al, 2018b;Kwok et al, 2019). To the authors' knowledge, no investigation concerning wind characteristics of LCZs has been carried out so far.…”

The effect of sub-facet scale surface structure on wall brightness temperatures at multiple scales

“…The similarity of the air temperatures suggests that the differences seen in wall temperature distributions between the sites stem from geometries and materials of houses themselves rather than from neighbourhood-scale morphological characteristics. Small daytime differences in air temperature between the sites are also more broadly characteristic of studies that have examined air temperature differences between LCZs (Fenner et al 2017;Beck et al 2018;Kwok et al 2019), likely due to enhanced turbulent processes that provide better mixing of the canopy-layer air by day.…”