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Located in a highly sensitive climate area, according to the IPCC reports, Lake Kinneret is exposed to extreme changes in the next few decades. Lake Kinneret is a warm monomictic lake, located between subtropical and arid climatic belts. It is thermally stratified throughout most of the year and mixes thoroughly each winter when the epilimnion water temperature reaches equilibrium with the hypolimnion water temperature by surface cooling and turbulence. Using high-resolution atmospheric projections obtained from COSMO-CLM simulation to force a 3D hydrodynamical model, we show significant changes in the stratification and circulation of the lake over the next five decades. As air temperature is expected to rise by up to 2.5oC in winter and autumn by 2070, the water column full mixing is expected to be suppressed. Unmixed years are expected to appear more often and full mixing will be re-activated just when cold enough winter conditions allow a full water column turnover. The lack of mixing between the epilimnion and the hypolimnion may create an environment that is oxygen depleted in which very few organisms can live, hence, might strongly affect the lake's present ecological system, its sustainability, and its water quality. Stratification Index analysis results show that Lake Kinneret will remain stratified throughout the year 20%-30% of the time in 2030-2070 under the moderate climate change scenario RCP4.5. However, abrupt cooling of the lake surface due to enhanced latent heat loss is identified, around the year 2065, in the model results, and is expected to restrain the dramatic change in the lake stratification.

In 2021, a group of seven Italian institutions decided to bring together their know-how, experience, and instruments for measuring the drop size distribution (DSD) of atmospheric precipitation, giving birth to the Italian Group of Disdrometry (in Italian named Gruppo Italiano Disdrometria, GID, https://www.gid-net.it/, last access: 16 May 2023). GID has made freely available a database of 1 min records of DSD collected by the disdrometer network along the Italian peninsula. At the time of writing, the disdrometer network was composed of eight laser disdrometers belonging to six different Italian institutions (including research centres, universities, and environmental regional agencies). This work aims to document the technical aspects of the Italian DSD database consisting of 1 min sampling data from 2012 to 2021 in a uniform standard format defined within GID. Although not all the disdrometers have the same data record length, the DSD data collection effort is the first of its kind in Italy, and from here onwards, it opens up new opportunities in the surface characterization of microphysical properties of precipitation in the perspective of climate records and beyond. The Version 01 GID database can be downloaded at https://doi.org/10.5281/zenodo.6875801 (Adirosi et al., 2022), while Version 02 can be downloaded at https://doi.org/10.5281/zenodo.7708563 (Adirosi et al., 2023). The difference among the two versions is the diameter–fall velocity relation used for the DSD computation.

In the last few decades there has been increasing interest in the commercial usage of the stratosphere, especially for Earth observation systems. Stratospheric platforms allow Earth monitoring at a regional scale with persistency toward a limited area. For this reason, accurate meteorological forecasts are needed in order to guarantee stationarity. The main aim of this work is to provide a review of wind prediction techniques in the stratosphere, achieved by the most popular global models, such as ECMWF IFS, NCEP GFS and ICON. Then, the capabilities of the COSMO limited area model to reproduce the wind speed in the stratosphere are evaluated considering a model configuration with very high resolution (about 1 km) over a domain located in Southern Italy, assuming the radio sounding data at Pratica di Mare airport as the reference. Vertical profiles were analyzed for selected days, highlighting good performances, though improvements can be achieved by adopting a fifth-order interpolation of the model data. Finally, monthly wind speed time series for selected heights were post-processed by means of fast Fourier transform, revealing the existence of main frequencies and the presence of a scaling regime and a power law of the form f−β over a broad range of time scales, in the Fourier space. The exponent spectral β is close to the exact 5/3 Kolmogorov value for all the datasets.

A new urban canopy scheme for the ICON atmospheric model is presented. Increasing the resolution of atmospheric models for numerical weather prediction (NWP) or climate simulations allows, among others, for a more realistic description of the processes at the land surface. Here, one field of growing interest are the processes in urban areas. Beside their relevance for the meteorological modelling, there is a general trend in most countries that the number of people living in towns is significantly increasing. During the recent years, an urban canopy parameterization was developed for the multi-layer land surface scheme TERRA of the Consortium for Small-scale Modeling (COSMO) mesoscale atmospheric model. This parameterisation, TERRA_URB, originally developed for the climate version of COSMO and then ported to the NWP version, was shown to be able to reproduce the key urban meteorological features for different European cities. In the framework of the transition of the COSMO Consortium to the ICON model, TERRA_URB needs to be implemented in ICON. Furthermore, an updated set of urban canopy parameters needs to be provided, for describing the urban characteristics down to a mesh size of 1 km, and below. For these purposes, the COSMO Consortium organises the dedicated Priority Project CITTA’. First results are presented for TERRA_URB in the ICON limited-area model ICON-LAM for different cities of interest of the CITTA’ partners. The preliminary results indicate already that urban features like the urban heat island effect are well represented. This is in agreement with the experiences with TERRA_URB in the COSMO model, both the climate as well as the NWP version.

The ICON (ICOsahedral Nonhydrostatic) is a joint project between the Deutscher Wetterdienst (DWD) and the Max-Planck-Institute for Meteorology (MPI-M) for the development of a unified global numerical weather prediction system. In 2018, COSMO (COnsortium for Small-scale Modeling) started the migration from the COSMO-LM to the ICON-LAM (ICON Limited Area Model) as the operational model. The main aim of this work is the presentation of a sensitivity study performed over a domain located in southern Italy (including the northern part of the Campania region and the southern part of Lazio) aimed to provide a contribution to the definition of a model configuration suitable for accurate weather forecasts over this area. Following the work performed by the authors with COSMO on a similar domain, the week 19-25 November 2018 has been selected as test case, when a low-pressure system coming from Western Mediterranean determined intense storms and gusts.A computational grid R2B11, characterized by a very high resolution (about 1.2 km), has been adopted. Initial and boundary conditions are provided by the ECMWF IFS model at a spatial resolution of about 8.5 km. The sensitivity was carried out starting from a model configuration optimized by the authors (in a joint effort with the CMCC Foundation, Italy) over the whole Italian area, employing a grid with different resolution (R2B10, about 2.5 km). The reference configuration assumes that the shallow convection parameterization is active whereas the parts treating deep and mid-level convection are switched off. Moreover, a single moment cloud microphysics scheme and a diagnostic Kohler cloud cover scheme are employed.A first sensitivity was performed with respect to the domain size, considering a reference domain (11.38° – 15.38° E; 40.25° - 42.25° N) and two additional domains respectively larger (in both directions) than 50% and 100% with respect to the original one. Then, a sensitivity to the numerical parameters, which have been shown to play a significant role in determining model response, has been carried out, e.g tkhmin (minimal diffusion coefficient for heat), rlam_heat (factor for laminar resistance for heat) and v0snow (factor for vertical velocity of snow).Model evaluation has been conducted against ground observation data provided by CIRA instrumentation and by the SCIA system developed by ISPRA (Italy). Moreover, a comparison with forecasts provided by the COSMO model at 0.009° (about 1 km resolution) forced by the same driving data has been performed, in order to highlight the differences between the performances of the two models.

Remote sensing measurements provided by satellite-borne radars play a fundamental role in estimating precipitation distribution worldwide. However, they are subjected to a variety of potential errors and need continuous validation with ground-based measurements. Validating satellite products using measurements collected by sensors at the ground has been addressed in the literature, but it is still challenging due to intrinsic differences in the measuring principle and viewing geometries of the instrument being compared each other. To date, the Dual-frequency Precipitation Radar (DPR) aboard the Core Satellite of the Global Precipitation Measurement (GPM) mission is the only active sensor able to provide, at the global scale, vertical profiles of rainfall rate, radar reflectivity, and Drop Size Distribution (DSD) parameters from space. After the launch of the GPM Core Satellite, on February 2014, an extensive Ground Validation (GV) program was established with the aim of evaluating the performance of the retrieval algorithms, over long periods and in different climatic regions across the world. Since the free availability of GPM data, many studies have been conducted to compare and validate the available version of satellite precipitation products with data collected by ground-based instrumentations such as radars and rain gauges, however very few published studies used networked disdrometers data on national scale.For the first time, we used disdrometers to evaluate near surface GPM-DPR products (Version V06A) against long time series of measurements collected by seven laser disdrometers dislocated along the Italian peninsula and networked thanks to a cooperation effort of seven institutions (including research centers, universities and environmental regional agencies). The comparison was made in terms of rainfall and DSD parameters: rainfall rate, radar reflectivity, mass-weighted mean diameter (Dm), and normalized gamma DSD intercept (Nw). The comparison showed limited differences between single- or dual-frequency GPM algorithms, although the former presents better performance in most cases. The conclusions suggest that the agreement was good for rain rate, reflectivity factor, and Dm, while Nw satellite estimates need to be improved. Same method is used for evaluating current V07A of precipitation products.Given the collaborative nature that has allowed the validation analysis presented, this study also represents an opportunity to consolidate cooperation between Institutions managing disdrometers in Italy and set the stage for future plans aimed at improving the use of disdrometer data in Italy.

One of the most severe weather hazards to aviation is in-flight airframe icing, i.e. the accretion of ice on airplane’s surfaces during flight. In order to increase margins of aviation safety, the early detection of regions affected by icing conditions is a challenging and desirable goal. In the framework of the H2020 EU project SENS4ICE (SENSors and certifiable hybrid architectures for safer aviation in ICing Environment), CIRA has developed a remote detection tool of icing conditions based on satellite data. Specifically, high-resolution satellite products, based on Meteosat Second Generation (MSG) data, have been considered, with spatial and temporal resolutions of about 3 km and 15 minutes respectively. The aim of this tool is to identify areas potentially affected by in-flight icing hazard, giving information about the severity of the phenomenon (light, moderate or severe) and an estimate of the altitude at which this hazard can occur. The developed algorithm also takes into account supercooled large droplets (SLD), which pose a serious threat to aviation and have been the cause of tragic accidents over the last decades. The tool relies on satellite data, to remotely infer the properties of clouds, and a set of experimental curves and envelopes that describe the interrelationship of cloud liquid water content, mean effective diameter of the cloud droplets and ambient air temperature. These curves, provided by the Federal Aviation Administration (FAA), define the atmospheric icing conditions and represent the reference legislation in this field. Furthermore, a nowcasting algorithm based on the extrapolation in time of the current icing conditions has been implemented, in order to perform a forecast over a short period ahead, responding to the great need for timely and location-specific forecasts that are relevant for aviation, e.g. for safety reasons or for planning and routing air traffic. This presentation will provide a preliminary analysis of the performance of the implemented tools, which will be evaluated in relevant icing conditions in the framework of SENS4ICE flight campaigns, planned for 2023.Acknowledgment: This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement N° 824253 (SENS4ICE project).

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.