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Several typologies of urban surface properties have been proposed, in recent years, for urban heat island studies and climate modeling. Some were specifically developed for cities and urban climate issues, like the Urban Climate Zones, and the more recent Local Climate Zones. The initial objective of this paper is to evaluate the capacity of these two typologies to identify thermal environments in and around cities, and to determine which typology best captures the daily spatio-temporal patterns of surface and urban canopy heat islands. To simulate urban climate with a model, LULC data based on a given typology are required. To avoid circularity, we combined the Corine Land Cover database, with data for the whole of Europe, and the BD TOPO database, for France, to form a new tool, CLC_USGS, which we used as input for the WRF limitedarea model, with a 150-m grid resolution. The capacity of each typology to identify coherent thermal zones was estimated for Dijon, a medium-sized French city, during a three-week heat wave, over a 24-hour period, in conditions favorable to urban heat island development. The comparison was based on hourly air temperatures directly output from the WRF model, those obtained from the purpose-built MUSTARDijon 47-sensor meteorological network, and NDVI values and land surface temperatures estimated from Landsat images for 11 July 2015 at 1030 UTC. Typical diurnal variations and spatial contrasts of surface and air temperatures were identified in both simulations and observations. As both typologies show significant capacity for identifying thermally coherent intra-urban areas, this study suggests that they could both be useful for urban climate applications. The typology that is most generally applicable in worldwide contexts is Local Climate Zones. 1. Introduction Urbanization and urban expansion linked to demographic growth produce diverse mosaics of built and non-built surfaces. This diversity results in very different surface energy budgets and Urban Heat Island (UHI) effects, induced by impermeable, heat-storing

The small heat shock protein (smHsp) Lo18 from lactic acid bacteria Oenococcus oeni reduces in vitro thermal aggregation of proteins and modulates the membrane fluidity of native liposomes. An absence of information relating to the way in which the smHsp demonstrates a stabilizing effect for both proteins and membranes prompted this study. We expressed three Lo18 proteins with amino acid substitutions in Escherichia coli to investigate their ability to prevent E. coli protein aggregation and their capacity to stabilize E. coli whole-cell membranes. Our results showed that the alanine 123 to serine substitution induces a decrease in chaperone activity in denaturated proteins, and that the tyrosine 107 is required for membrane stabilization. Moreover, this study revealed that the oligomeric structures of proteins with amino acid substitutions do not appear to be modified. Our data strongly suggest that different amino acids are involved in the thermostabilization of proteins and in membrane fluidity regulation and are localized in the alpha-crystallin domain.

High-resolution maps of the urban heat island (UHI) and building energy consumption are relevant for urban planning in the context of climate change mitigation and adaptation. A statistical-dynamical downscaling for these parameters is proposed in the present study. It combines a statistical local weather type approach with dynamical simulations using the mesoscale atmospheric model Meso-NH coupled to the urban canopy model Town Energy Balance. The downscaling is subject to uncertainties related to the weather type approach (statistical uncertainty) and to the numerical models (dynamical uncertainty). These uncertainties are quantified for two French cities (Toulouse and Dijon) for which long-term dense high-quality observations are available. The seasonal average nocturnal UHI intensity is simulated with less than 0.2 K bias for Dijon, but it is overestimated by up to 0.8 K for Toulouse. The sensitivity of the UHI intensity to weather type is, on average, captured by Meso-NH. The statistical uncertainty is as large as the dynamical uncertainty if only one day is simulated for each weather type. It can be considerably reduced if 3-6 days are taken instead. The UHI reduces the building energy consumption by 10% in the center of Toulouse; it should therefore be taken into account in the production of building energy consumption maps.