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Urbanized environments are of greater relevance because of the high and still rapidly increasing percentage of the world population living in and around cities and as the preferred location of human activities of every type. For this reason, much attention is paid to the urban climate worldwide. Among the UN 2030 17 Sustainable Development Goals, at least one concerns resilient cities and climate action. The WMO supports these goals promoting safe, healthy, and resilient cities by developing specially tailored integrated urban weather, climate, and environmental services. An unavoidable basis for that is an improved observational capability of urban weather and climate, as well as high-resolution modeling. For both the former and the latter, and of primary importance for the latter, urban meteorological surface networks are undoubtedly a very useful basis. Nevertheless, they are often unfit for detailed urban climatological studies and they are generally unable to describe the air temperature field in the urban canopy layer (UCL) with a spatial resolution which is sufficient to satisfy the requirements set by several professional activities and especially for local adaptation measures to climate change. On the other hand, remote sensing data from space offer a much higher spatial resolution of the surface characteristics, although the frequency is still relatively lower. A useful climatological variable from space is, for instance, the land surface temperature (LST), one of the WMO Essential Climate Variables (ECV). So often used to describe the Surface Urban Heat Islands (S-UHI), LST has no simple correlation with UCL air temperature, which is the most crucial variable for planning and management purposes in cities. In this work, after a review of correlation and interpolation methods and some experimentation, the cokriging methodology to obtain surface air temperature is proposed. The implemented methodology uses high quality but under-sampled in situ measurements of air temperature at the top of UCL, obtained by using a dedicated urban network, and satellite-derived LST. The satellite data used are taken at medium (1 × 1 km2) resolution from Copernicus Sentinel 3 and at high resolution (30 × 30 m2) from NASA-USGS Landsat 8. This fully exportable cokriging-based methodology, which also provides a quantitative measure of the related uncertainties, was tested and used to obtain medium to high spatial resolution air temperature maps of Milan (Italy) and the larger, much populated, but also partly rural, surrounding area of about 6000 km2. Instantaneous as well as long period mean fields of fine spatially resolved air temperature obtained by this method for selected weather types and different Urban Heat Island configurations represent an important knowledge improvement for the climatology of the urban and peri-urban area of Milan. It finds application not only in more detailed urban climate studies but also in monitoring the effects of urban activities and for the assessment of adaptation and mitigation measures in the urban environment. Finally, the first set of interactive maps of medium–high resolution UCL air temperature was produced in the framework of the locally funded ClimaMi project and made freely available to urban authorities and professionals as an improved climatological basis for present and future plans and projects to be developed in the framework of the national and international adaptation and mitigation measures.

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.

Resilience plans to cope with climate change are of particular relevance in cities, because of the large and still increasing percentage of population living in urbanized environments. Urban adaptation implies general planning, but reflects also in single and limited urbanistic, engineering and architectural projects, in which local authorities as well as professionals and practitioners are directly involved.The basic concept of ClimaMi (www.progettoclimami.it), a locally funded but easily replicable project for the city of Milan and immediate neighborhood (a densely populated and industrial area in the western-central part of Po valley in northern Italy), relies on the need to provide, bottom-up, updated and useful climatological information to agencies and personnel directly involved in public and private enterprises and management practices, which have immediate impact in present and future urban climate and citizens wellness. The 3 years Project was therefore developed as an interdisciplinary activity, directly involving not only climatologists but also local professional organizations, and producing as a first result a common basis of knowledge and technical language among different disciplines.A second fundamental task has been the creation of an as much as possible complete database of 7 essential climatic variables and relevant derived indexes (94 in total) for specific applications, representing an updated and detailed description of the urban environment in the most recent climate. Relating mainly on a high-quality and metrologically managed climate network of urban automatic weather stations (CN by OMD), and integrating data from stations of third-party networks according to accurate selection criteria for homogeneity and reliability, a 6 years DB for 19 selected points and 6 different time windows is now openly available to professionals for direct and immediate use in their activities.A further development has been the production of interactive GIS-based maps of air temperature distribution at medium-high resolution (100 m) in the Project area: a climatological and geostatistical methodology has been in this case applied to optimally integrate near surface measurements and space-borne observations of land skin temperature. The result is an Atlas of mean thermal fields in selected typical weather situations of specific relevance for resilience applications, for instance in case of enhanced Urban Heat Island and Heat Wave episodes. In the third and last Project year (2021), a DB and Atlas update is planned, while similar methodologies are specifically applied to precipitation.In order to make the Project results as effective as possible with real impacts on planning and project activities, numerous capacity building courses have also been planned and activated, involving hundreds of officials and professionals. Furthermore, practical laboratories and case studies were performed in order to evaluate the real effects in the aware and informed use of updated climatological information in adaptation projects.

Existence of more or less dense urban meteorological networks is nowadays relatively common, even if often heterogenous in scopes, hardware and management. Those networks are undoubtedly useful tools for a variety of practical purposes. Nevertheless, they are generally unfit to climatological studies, and unable to describe Air Temperature in the Urban Canopy Layer (UCL) with sufficient spatial resolution: for example, as required by several professional activities and for local adaptation measures to climate change. On the other hand, remote sensing data from space has become more and more frequent and easily available, offering a higher spatial resolution (but a still very low frequency) of surface characteristics as the Land Surface Temperature (LST). Often used to describe Urban Heat Islands (UHI), LST has not a simple correlation with canopy layer Air Temperature, which on the contrary is the most required variable for planning and management purposes in cities. Using both high quality in situ measurements of Air Temperature at top of UCL obtained by a dedicated urban network as a primary variable, and satellite derived LSTs as the secondary one, a Co-Kriging based methodology has been developed and tested to obtain medium to high spatial resolution Air Temperature maps. Instantaneous as well as long period mean fields of fine spatially resolved Air Temperature find relevant application not only in monitoring and assessing activities of adaptation and mitigation measures in the urban environment, but also in urban climate studies. In this paper the methodology is shortly described, and results for the metropolitan area of Milan and the neighbourhoods, obtained in the framework of the first 2 years of ClimaMi Project (https://www.progettoclimami.it/), are presented and discussed together with error estimations.

Distributed Monitoring Systems (DMS) are essential to implement global policies and daily practices to preserve and improve the energy efficiency of an organization. The Level of Coverage (LoC) is a primary aspect in design, evaluation and implementation/extension of a DMS. The LoC is a numeric indicator representing the ability of a DMS to properly monitor the energy consumption/production in specific Zones and for particular Uses. It allows comparison and choice among several DMS implementations, differing for number and positioning of the measuring instruments. This paper presents a new method for LoC computation. It can be easily implemented in SW and allows to directly calculate not only the LoC of the whole DMS and its subsections but also semi-aggregated LoCs referred to specific Uses or specific Zones. The latter aspect is very useful for assessing the energy monitoring plan adopted in mandatory or voluntary energy audits.

This paper analyzes the requirements for implementing an Energy Management Information System (EMIS) and proposes some methodology criteria and tools for its design, deployment and management. An EMIS combines software, hardware, and data modelling and processing to support people in their efforts to daily manage energy at any level (process, system, facility, and enterprise) year after year. An EMIS has to be designed and operated to fulfill national and international standards and to support improvements of energy performance within the organization. The distributed metering system (DMS) represents just a subset (in terms of signal collection and management) of the EMIS that monitor the energy parameters and the factors that influence energy use in monitored systems. In the paper two main point will be addressed; the first one provides an overview, in the field of energy efficiency measurement and monitoring; the second one of the technical standards that can be considered as essential, furnishes architectural criteria for the design and the implementation of an EMIS. The paper introduces a procedure to assess the DMS introducing the Level of Coverage.

The standards related to energy management emphasize the role of the measurement activity but no exhaustive guidelines have been published for outlining requirements and architecture of a comprehensive energy efficiency monitoring system that goes beyond a simple measuring system. A Monitoring System for Energy Efficiency should transform several kinds of energetic and context data into actionable pieces of information for controlling energy performance, improving operations and maintenance as well as verifying the effectiveness and the continuity of corrective actions. Eventually the energy efficiency monitoring system should be modular to be upgraded over the time and to fit the needs of any organization. This paper aims at contributing to the work of CEN-CENELEC JWG9 "Energy measurement plan for organizations" by providing background information for the development of its standards and for future work.

Energy Efficiency is one of the cornerstones of European and International energy policy. Technical standardization can contribute to promote energy efficient technologies and solutions and ultimately to reach the targets of energy efficiency improvement and CO 2 reduction. This paper provides an overview of the main existing technical standards in the domain of energy efficiency measurement and monitoring. This paper maps these standards against a taxonomy to identify useful references to support the process of designing, implementing, operating and maintaining an "energy efficiency measurement and monitoring system" and eventually to identify gaps that may be covered by future standardization activity. ISO, IEC, CEN and CLC standards published before 28 February 2016 will be analyzed. This paper aims at contributing to the work of CEN-CENELEC JWG9 "Energy measurement plan for organizations" by providing background information for the development of its standards and eventually a tool for identifying gaps for future work.

It is well known that the control of energy consumptions in a building or in an organization enables to improve the energy performance (EP). The measurement plan defines the procedure for the design, deployment, utilization, maintenance and improvement of a distributed measurement and monitoring system (DMS). A DMS is able to measure and analyze the EP of the organization according to factors that influence the operation of the site. The paper suggests a method of assessment of a DMS based on different criteria. The paper focused on the criterion of the Level of Coverage. The authors suggest the definition of a Level of Coverage Numeric Indicator (LoCNI) that evaluates the capacity of the DMS to track consumptions by zones and by uses.