Spatially detailed urban climatology for temperature and precipitation.

With the growing relevance of urbanized environments in the framework of adaptation and mitigation plans, improvements in monitoring the urban weather, and specially in the knowledge of the urban climatology and its evolution, are urgently needed. A basic difficulty arises from the fact that dedicated surface observational networks with the desired characteristics of measurement quality and continuity are often lacking in cities, while remote sensing data are mainly used for specific aspects, as for instance the Surface Urban Heat Island, while air temperature is more important for applications. After the experience gained, and the methodologies developed in Milan during a locally co-funded project (ClimaMi: https://www.progettoclimami.it/), the possibility was investigated of a medium- to high-resolution urban climatology mainly derived from observed air temperature and precipitation data.

The urban specialized surface network (by Fondazione Osservatorio Meteorologico Milano Duomo: FOMD), in operation since 2011 and “metrologically” tested during MeteoMet Project (Merlone et al., 2015), was considered as a reliable basis for a new and more detailed analysis of the most recent urban climate in Milan. To complement the necessarily limited number of high quality measurements by this urban Climate Network (CN),  other  automatic weather stations  (as homogenous as possible to CN) were accurately selected from third-party networks, in particular from the regional (ARPA Lombardy) meso-synoptic one, and from a private citizens association (MeteoNetwork): this helped in setting up a database of reliable hourly observational data (and metadata) in urban and peri-urban environments, dense enough for a mesoscale description of the city main statistical characteristics and for an already significative time span of 5 years.

Nevertheless, resilience plans by local authorities and professionals often require a spatial resolution of the order of tens of meters: to significantly improve the spatial resolution, space-borne sensors are an obvious and nowadays practical possibility. Furthermore, to make the best use of the quality of (under sampled) surface measurements, and of the high spatial resolution offered by remote sensed data, a cokriging-based methodology (Goovaerts, 1999) was developed and tested for air temperature. While direct correlation methods between Land Surface Temperature (LST) and the (more interesting and required) near-surface air temperature are not straightforward and generally unreliable, the encouraging results obtained in reconstructing air temperature fields by cokriging allowed an analysis of the recent climate of the cities and neighborhoods at medium to high spatial resolution for selected weather types of particular relevance in the definition of resilience measures.

The same methodology is now under test for precipitation measurements by different sensors and networks, and first results will be presented together with the unprecedented climatological description of temperature in the greater Milan, and analysis of micro-scale urban climate variations in consideration of (present and future) climate monitoring and assessment needs.