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Temperature is the most used meteorological variable for a large number of applications in urban resilience planning, but direct measurements using traditional sensors are not affordable at the usually required spatial density. On the other hand, spaceborne remote sensing provides surface temperatures at medium to high spatial resolutions, almost compatible with the needed requirements. However, in this case, limitations are represented by cloud conditions and passing times together with the fact that surface temperature is not directly comparable to air temperature. Various methodologies are possible to take benefits from both measurements and analysis methods, such as direct assimilation in numerical models, multivariate analysis, or statistical interpolation. High-resolution thermal fields in the urban environment are also obtained by numerical modelling. Several codes have been developed to resolve at some level or to parameterize the complex urban boundary layer and are used for research and applications. Downscaling techniques from global or regional models offer another possibility. In the Milan metropolitan area, given the availability of both a high-quality urban meteorological network and spaceborne land surface temperatures, and also modelling and downscaling products, these methods can be directly compared. In this paper, the comparison is performed using: the ClimaMi Project high-quality data set with the accurately selected measurements in the Milan urban canopy layer, interpolated by a cokriging technique with remote-sensed land surface temperatures to enhance spatial resolution; the UrbClim downscaled data from the reanalysis data set ERA5; a set of near-surface temperatures produced by some WRF outputs with the building environment parameterization urban scheme. The comparison with UrbClim and WRF of the cokriging interpolated data set, mainly based on the urban canopy layer measurements and covering several years, is presented and discussed in this article. This comparison emphasizes the primary relevance of surface urban measurements and highlights discrepancies with the urban modelling data sets.

The study of urban climate change has to take into account two components: global warming and microclimate variability due to urban growth. The present article tries to quantify the global and local components in six Italian towns over the last fifty years: Milano, Bologna, Roma, Napoli, Bari and Palermo. Historical temperature series measured in the city centre and in the suburbs of the towns have been investigated: the Climatological Normals 1961-1990 and 1971-2000 have been compared with the mean data of the last 15 years (2001-2015). Everywhere the mean temperatures have been higher in the city centre than in the suburbs and both have progressively raised over time. Conversely, the differences between city centre temperatures and suburban ones have decreased. Mean temperature differences between the two kinds of monitoring sites can be considered as a first rough estimate of the urban contribution to local warming up. To better analyse the local effects of urban warming and their relation with health and welfare of urban residents, a quantitative spatial analysis of hot extreme events in Milano has been performed, as Milano is subject to stable atmospheric conditions in more than 60% of days per year. Such conditions contribute to the accumulation of waste heat generated by urban energy usage. Dry and moist heatwaves have been treated, resulting in quite different spatial distribution of such events, as a strict effect of built and green areas in urban texture. [ABSTRACT FROM AUTHOR]