High-Resolution Gridded Air Temperature Data for the Urban Environment: The Milan Data Set

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 usually required spatial density. On other hand, spaceborne remote sensing provides surface temperatures medium to high resolutions, almost compatible with needed requirements. However, this case, limitations represented by cloud conditions and passing times together fact that temperature directly comparable air temperature. Various methodologies possible take benefits from both analysis methods, such as assimilation numerical models, multivariate analysis, or statistical interpolation. High-resolution thermal fields environment also obtained modelling. Several codes have been developed resolve some level parameterize complex boundary layer research applications. Downscaling techniques global regional models offer another possibility. In Milan metropolitan area, given availability high-quality network land temperatures, modelling downscaling products, these methods can be compared. paper, comparison performed using: ClimaMi Project data set accurately selected canopy layer, interpolated cokriging technique remote-sensed enhance resolution; UrbClim downscaled reanalysis ERA5; near-surface produced WRF outputs building parameterization scheme. The set, mainly based on covering several years, presented discussed article. This emphasizes primary relevance highlights discrepancies sets.