During the last 15 years, weather extremes caused several disruptions to the Italian electric system. Their increasingly occurrence is mainly due to the exchanges along the meridians of air masses with very different thermal, density and moisture content properties. The Italian transmission system operator and the distribution companies have repeatedly stressed the need to have a reliable and updatable weather dataset with a history of at least 15 years to improve the resilience of the electric system. The aim of this work is to develop a new MEteorological Reanalysis Italian DAtaset (MERIDA) able to respond to the energy stakeholders, who need reliable meteorological data to implement effective adaptation strategies to operate the electric system safely. MERIDA consists of a dynamical downscaling of the new European Centre for Medium‐range Weather Forecasts (ECMWF) global reanalysis ERA5 using the Weather Research and Forecasting (WRF) model, which is configured to describe the typical weather conditions of Italy. Furthermore, the optimal interpolation (OI) technique is applied to the modelled 2 m temperature and precipitation data through the use of meteorological observations of the Regional Agencies for Environmental Protection. MERIDA is verified against COSMO REA6 of the Deutscher Wetterdienst (DWD) and ERA5 itself for the period 2010–2015, showing comparable or better results in the reconstruction of 2 m temperature and precipitation. The best results are obtained with MERIDA post‐processed by the OI. Some severe weather events that determined important electric disruptions are also analysed, showing that MERIDA is able to identify the meteorological conditions leading to significant events of wet snow, heatwaves and floods through their correct spatial and temporal location and through a quantitative assessment of each atmospheric phenomenon.

Recent observation and modeling-based studies have shown how air quality has been positively affected by the containment measures enforced due to the COVID-19 outbreak. This work aims to analyze Lombardy’s NO2 atmospheric concentration during the spring lockdown. The region of Lombardy is known for having the largest number of residents in Italy and high levels of pollution. It is also the region where the first European confinement measures were imposed by the Italian government. The modeling suite composed of CAMx (Comprehensive Air Quality Model with Extensions) and WRF (Weather Research and Forecasting model) provides the setting to compare the atmospheric NO2 concentration from mid-February to the end of March with a business as usual situation. The main interest in this work is to investigate the response of NO2 atmospheric concentration to increasingly reduced road traffic. We can simulate, for the first time, a real circumstance of progressively reduced mobility, as well as validating it with measured air quality data. Focusing on the city of Milan, we found that the decrease in NO2 concentration reflects progressively reduced traffic contraction. In the case of a large traffic abatement (71%), the concentration level is reduced by one third. We also find that industrial activities have a relevant impact on NO2 atmospheric concentration, especially in the provinces of Brescia and Bergamo. This study provides an overview of how incisive policies must be implemented to achieve the set environmental targets and protect human health.

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Soil moisture changes are generally due to external factors (precipitation, evaporation, etc.) and internal forces (gravitational force, capillarity, transpiration, etc.). When soil temperatures remain below 0 °C for a long time (hours or even entire consecutive days), part of the liquid water content of the soil can freeze, thus freezing/thawing effects must be taken into account in those conditions. The present work is devoted to the numerical modeling of the water phase change in the soil. The model used in this study for the land surface processes is UTOPIA (University of TOrino land Process Interaction in Atmosphere) model, which is the updated version of LSPM (Land Surface Process Model). Scientific literature proposes some formulations to account for freezing/thawing processes. Three different parameterizations have been compared using a synthetic dataset in order to assess which one performs best from a physical point of view. Parameterizing freezing/thawing processes creates numerical instability and water overproduction in the UTOPIA model. These problems have been solved and described in the paper by means of synthetic data created to test the new parameterizations. The results show that UTOPIA is able to capture the freezing/thawing physical processes.

Wind energy is one of the key renewable resources contributing to climate change mitigation policies in national and international energy transition strategies. However, climate change itself can affect the availability of wind resources, due to possible future changes in large-scale circulation pattern. This study aims to understand whether how and to what extent current and future climate change is affecting wind producibility in Italy. In this analysis, the 10 m wind speed from Euro-CORDEX regional climate models was bias-corrected using MERIDA meteorological reanalysis and the wind producibility is calculated, using a reference turbine chosen among the most commonly installed in Italian wind farms. The changes in the availability of wind resources from the reference period 1986–2005 for the short (2021–2050), medium (2051–2080), and long term (2071–2100) are analyzed, considering both the RCP 4.5 and RCP 8.5 scenarios. The results show a prevalently weak and not statistically significant climate signal for the RCP 4.5 scenario, while a more pronounced and significant signal is highlighted for the RCP 8.5 scenario in the medium and long term, indicating a decrease in wind producibility. Specifically, the conclusions suggest that future planning of wind producibility should mainly focus in some specific areas of the eastern Italian coast and in the south-east Italian regions, mostly in the off-shore areas. In these regions, indeed, the RCP 8.5 scenario shows the lowest decrease in the overall annual producibility, while, for the RCP 4.5 scenario, the medium and the long term foresee a slight increase in wind producibility at the annual level, while, in the short term, an increasing trend is observed mostly in the spring season.