In this work, the results of a sensitivity study based on ICON-LAM simulations at 2.5 km of spatial resolution over the Italian area, driven by ECMWF IFS global data, are presented. The main aim is to provide a contribution to the selection of suitable parameterization schemes that result in more effective for a proper representation of the Italian climate features. Model evaluation was conducted in terms of the air temperature and precipitation for three subregions, comparing a set of 13 simulations against SCIA and E-OBS standard datasets. In addition, evaluation was also conducted against selected data stations scattered over the Italian area. We found that the ICON-LAM model was able to provide a good representation of the temperature over Italy, whereas non-negligible biases were observed for precipitation in certain regions. The model proved to be sensitive to changes in physical parameterization schemes. In particular, we found that the explicit treatment of deep convection and the “clouds as in turbulence” scheme for cloud cover allowed for a better representation of precipitation in the summer over the Alpine region. The single moment scheme is currently the best option for cloud microphysics.

This work represents a first step in the definition of a framework aimed at finding, by means of efficient global optimization based on metamodels, an optimal configuration of physical parameters for the ICON (ICOsahedral Nonhydrostatic) Limited Area Mode at high resolution (about 1.1 km) over Southern Italy, to be used for operational runs. The objective of the optimization is to reduce the distance between observed meteorological variables and modeled data. This distance is measured by an opportunely designed objective function. This work represents a preparatory step, since the input parameters considered are only a reduced number with respect to the huge amount of parameters potentially involved. First, domain size sensitivity was performed to choose the optimal domain. Then, the optimization was conducted by means of an Efficient Global Optimization algorithm relying on a Gaussian-based metamodel. The four parameters considered control the heat transfer in the turbulent layer, the laminar resistance and the snow vertical velocity. They were optimized over a week in November 2018, a period characterized by extreme events in the region considered. The results demonstrated the effectiveness of the proposed approach, reducing the distance from observed data, and the method can be considered promising from the perspective taking into account a larger set of physical parameters, and validation over a wider time-window.

In recent years, the scientific community has paid particular attention to the analysis of extreme events, such as heat waves, droughts, and intense rain events that have caused loss of human life and significant economic damage. Climate-related extremes generally produce large impact on infrastructures, especially on those with insufficient design, while some infrastructures may become inadequate under the effects of severe extremes. In the particular case of airports, the increase in frequency and severity of extreme weather events will worsen their deterioration rate. This work presents an analysis of the expected climate variability over Napoli Capodichino Airport, using climate projections generated by the Regional Climate Model COSMO-CLM. Simulations were performed over Italy, employing a spatial resolution of approximately 8 km. The time period simulated was 1979–2100, and, in particular, the CMIP5 historical experiment (based on historical greenhouse gas concentrations) was used for the period 1979–2005, while, for the period 2006–2100, two different simulations were performed, employing the Representative Concentration Pathways IPCC RCP4.5 and RCP8.5 greenhouse gas concentrations. The meteorological situations over the airport have been analyzed, along with the identification of conditions that could cause relevant impact on airport environment. In particular, extreme summer temperatures may exceed design standards, leading to heat damage to surfaces, while runways or aprons may have trouble due to the surface melting during peak heat periods. Long term changes in the directions of wind can adversely affect the usability of runways, while changes in wind shear could modify strength and frequency of clear-air turbulence. Analyses have been performed considering suitable Extreme Events Indicators (EWI), both on past trends and on numerical projections over future periods, with the aim of contributing to the definition of a risk assessment methodology based on the combination of the frequency and of the severity of meteorological hazards.

Aviation operations are increasingly impacted by clear-air turbulence (CAT) encounters, a growing concern in both media and academic circles. Research into CAT focuses on the generation, prediction, detection, and monitoring of the occurring events (thanks to weather-related methodologies and instruments) along with technologies and operational aspects to mitigate their effects, from the perspective of both the flight segment (aircraft and pilot and related onboard systems) and the ground segment (ATM and ATC and related tools). Climate changes have led to more frequent and severe CAT events, highlighting the need for sustainable aviation solutions, aiming to achieve improved theoretical knowledge and technological and operational management advancements. This paper addresses the CAT topic under two main perspectives: the scientific understanding of the phenomena, and the technological management of such occurrence in aviation operations. With reference to the first addressed domain, the paper provides a comprehensive review of the currently used and perspective proposed methodologies and tools for understanding, detecting, and predicting CAT phenomena. With reference to the second addressed domain, then, this paper aimed to analyze the state of the art and trends in the technological and operational management and mitigation of the CAT occurrences at a tactical level (i.e., while in flight) by the aviation, covering the technologies and procedures implemented onboard and in the ground segment. Overall, therefore, this paper assesses the state of the art and identifies the most promising innovations that promote safer, more sustainable future aviation operations, by bridging weather and climate science with aviation engineering, in the presence of CAT events.

Weather conditions and Air Traffic Management (ATM) operations are strongly related, due to the relevant influence that the observed and forecasted weather conditions into assigned airspace have on the operational conditions that are therefore possible for such airspace. In the framework of the SESAR JU funded project CREATE (Innovative operations and climate and weather models to improve ATM resilience and reduce impacts), therefore, a dedicated study has been carried out in order to investigate the relation between weather and ATM. Such study both investigated the consequences that adverse weather conditions can have on ATM and, on the other side, addressed the currently and future available tools that can support ATM in the prediction and management of weather conditions from the aeronautical operations point of view. In this paper, the results of such literature study are outlined. More in details, in the paper first the main outcomes of the study are summarized, in terms of identification of the most relevant weather phenomena that affect the ATM operations, indication of their main impacts on them in terms of operational disruptions and, finally, identification of the associated level of severity. In particular, the above indicated aspects are addressed by taking into specific consideration the enroute and the TMA (Terminal Manoeuvring Area) flight phases and, for each of them, the main affecting weather phenomena and the main affected operations are identified. Then, in the paper the results of the study are summarized about the identification of the most relevant meteo tools that are expressed by state-of-the-art technologies to support the ATM operations in order to properly take into account the weather conditions in a precise and timely manner. This study addresses both the review of available and perspective tools for weather reporting and of the available and perspective numerical models supporting ATM in terms of weather models and air quality models.

The present work is focused on the validation of the urban canopy scheme TERRA-URB, implemented in ICON weather forecast model. TERRA-URB is used to capture the behavior of urbanized areas as sources of heat fluxes, mainly due to anthropogenic activities that can influence temperature, humidity, and other atmospheric variables of the surrounding areas. Heat fluxes occur especially during the nighttime in large urbanized areas, characterized by poor vegetation, and are responsible for the formation of Urban Heat and Dry Island, i.e., higher temperatures and lower humidity compared to rural areas. They can be exacerbated under severe conditions, with dangerous consequences for people living in these urban areas. For these reasons, the need of accurately forecasting these phenomena is particularly felt. The present work represents one of the first attempts of using a very high resolution (about 600 m) in a Numerical Weather Prediction model. Performances of this advanced version of ICON have been investigated over a domain located in southern Italy, including the urban metropolitan area of Naples, considering a week characterized by extremely high temperatures. Results highlight that the activation of TERRA-URB scheme entails a better representation of temperature, relative humidity, and wind speed in urban areas, especially during nighttime, also allowing a proper reproduction of Urban Heat and Dry Island effects. Over rural areas, instead, no significant differences are found in model results when the urban canopy scheme is used.