Search

On 18 September 2020, medicane Ianos hit the western coast of Greece resulting in flooding and severe damage at several coastal locations. In this work, we aim at evaluating its impact on sea conditions and the associated uncertainty through the use of an ensemble of numerical simulations. We applied a coupled wave-current model to an unstructured mesh representing the whole Mediterranean Sea, with a grid resolution increasing in the Ionian Sea along the cyclone path and the landfall area. To investigate the uncertainty of modelling sea levels and waves for such an intense event, we performed a multimodel ensemble of ocean simulations using several coarse (10 km) and high-resolution (2 km) meteorological forcings from different mesoscale models. The performance of the ocean and wave models was evaluated against observations retrieved from fixed monitoring stations and satellites. All model runs emphasized the occurrence of severe sea conditions along the cyclone path and at the coast. Due to the rugged and complex coastline, extreme sea levels are localised at specific coastal sites. However, numerical results show a large spread of the simulated sea conditions for both the sea level and waves highlighting the large uncertainty in simulating this kind of extreme event. The multi-model / multi-physics approach allows us to assess how the uncertainty propagates from meteorological to ocean variables and the subsequent coastal impact. The ensemble mean and standard deviation were combined to prove the hazard scenarios of the potential impact of such an extreme event to be used in a flood risk management plan.

A sequence of dust intrusions occurred from the Sahara Desert to the central Mediterranean in the second half of June 2021. This event was simulated by means of the Weather Research and Forecasting coupled with chemistry (WRF-Chem) regional chemical transport model (CTM). The population exposure to the dust surface PM2.5 was evaluated with the open-source quantum geographical information system (QGIS) by combining the output of the CTM with the resident population map of Italy. WRF-Chem analyses were compared with spaceborne aerosol observations derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and, for the PM2.5 surface dust concentration, with the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis. Considering the full-period (17–24 June) and area-averaged statistics, the WRF-Chem simulations showed a general underestimation for both the aerosol optical depth (AOD) and the PM2.5 surface dust concentration. The comparison of exposure classes calculated for Italy and its macro-regions showed that the dust sequence exposure varies with the location and entity of the resident population amount. The lowest exposure class (up to 5 µg m−3) had the highest percentage (38%) of the population of Italy and most of the population of north Italy, whereas more than a half of the population of central, south and insular Italy had been exposed to dust PM2.5 in the range of 15–25 µg m−3. The coupling of the WRF-Chem model with QGIS is a promising tool for the management of risks posed by extreme pollution and/or severe meteorological events. Specifically, the present methodology can also be applied for operational dust forecasting purposes, to deliver safety alarm messages to areas with the most exposed population.

Tornadoes are among the most extreme hazardous weather phenomena. Several recent studies have assessed their important impact also in mid-latitudes European countries. An update climatology of the EF1+ tornadoes in Italy confirms that the central Tyrrhenian (CT) and the South-Eastern (SE) regions of the Italian peninsula represent two of the areas most affected by tornadoes in the Mediterranean. Two recent works, in particular, analyzed some case studies affecting these two regions: Avolio and Miglietta (2021) studied four tornado-spawning supercells over SE regions, that hit the same (Ionian) areas and that were characterized by similar synoptic conditions; in a more recent work (Avolio and Miglietta, 2022; under review), the same authors performed a synoptic/mesoscale analysis of the main patterns associated to the most intense tornadoes in the CT regions, also analyzing a significant event hitting the surroundings of Rome. Aim of this work is to propose a comparative analysis between these two tornado hotspots: the possible causes that generate these events in relation to the peculiarities of the two areas are analyzed by using upper air observations, radar images, ERA5 reanalysis, and high resolution WRF simulations. While for tornadoes in southeastern Italy the synergy of orographic forcing and air-sea interaction in a strongly sheared environment appears fundamental, in the Tyrrhenian regions the genesis is mainly related to the presence of convergence lines over the sea.

On 20 August 2018 a flash flood affected the Raganello Creek (southern Italy) causing 10 casualties. The rainfall event was so highly localized that the spatial coverage of rain gauges were inadequate to measure it, while radar products showed a storm cell with rain peaks of about 70–100 mm h−1. This scientific report provides a preliminary hydro-meteorological analysis of the event and evaluates the forecasting skills of a system based on the WRF–WRF-Hydro models, using both one-way and fully coupled approaches. The first results show a reasonable simulation of the event in terms of both rainfall and hydrological impact.

In this paper, we study the impact of lightning and radar reflectivity factor data assimilation on the precipitation VSF (very short-term forecast, 3 h in this study) for two severe weather events that occurred in Italy. The first case refers to a moderate and localized rainfall over central Italy that occurred on 16 September 2017. The second case occurred on 9 and 10 September 2017 and was very intense and caused damages in several geographical areas, especially in Livorno (Tuscany) where nine people died. The first case study was missed by several operational forecasts, including that performed by the model used in this paper, while the Livorno case was partially predicted by operational models. We use the RAMS@ISAC model (Regional Atmospheric Modelling System at Institute for Atmospheric Sciences and Climate of the Italian National Research Council), whose 3D-Var extension to the assimilation of radar reflectivity factor is shown in this paper for the first time. Results for the two cases show that the assimilation of lightning and radar reflectivity factor, especially when used together, have a significant and positive impact on the precipitation forecast. For specific time intervals, the data assimilation is of practical importance for civil protection purposes because it changes a missed forecast of intense precipitation (≥40 mm in 3 h) to a correct one. While there is an improvement of the rainfall VSF thanks to the lightning and radar reflectivity factor data assimilation, its usefulness is partially reduced by the increase in false alarms, especially when both datasets are assimilated.

Simple Summary Metabolic rewiring fuels cancer proliferation by enhanced glycolysis and the increased NADH/NAD+ ratio. In this study, we highlight the critical role of NADH in the epigenetic landscape mediated by CtBP2 (C-terminal binding protein 2) activation, linking metabolism to epigenetic transcriptional reprogramming. Moreover, using metabolomics and transcriptomics integration, we show that genetic and pharmacological down-regulation of CtBP2 strongly reduces cell proliferation by modulating the redox balance, nucleotide synthesis, reactive oxygen species (ROS) generation, and scavenging. Therefore, we provide evidence that metabolic rewiring plasticity regulates the crosstalk between metabolism and the transcriptional program that sustains energetic and anabolic demands in cancer cells. Abstract Rewiring glucose metabolism toward aerobic glycolysis provides cancer cells with a rapid generation of pyruvate, ATP, and NADH, while pyruvate oxidation to lactate guarantees refueling of oxidized NAD+ to sustain glycolysis. CtPB2, an NADH-dependent transcriptional co-regulator, has been proposed to work as an NADH sensor, linking metabolism to epigenetic transcriptional reprogramming. By integrating metabolomics and transcriptomics in a triple-negative human breast cancer cell line, we show that genetic and pharmacological down-regulation of CtBP2 strongly reduces cell proliferation by modulating the redox balance, nucleotide synthesis, ROS generation, and scavenging. Our data highlight the critical role of NADH in controlling the oncogene-dependent crosstalk between metabolism and the epigenetically mediated transcriptional program that sustains energetic and anabolic demands in cancer cells.

In the months of November 2012, 2014 and 2018, four tornadic events affected southern Italy (Calabria and Apulia regions). Tornado-spawning supercells hit the same regions, had similar trajectories, and were characterized by common synoptic conditions. The events are analysed through the use of multiple observational tools; large-scale and mesoscale analysis are performed, in addition to high-resolution numerical simulations and sensitivity tests with the WRF model. In particular, the effect of changes in Sea Surface Temperature on the intensity and tracking of tornadic supercells in the Mediterranean is investigated, finding that small variations of SST may cause significant changes on instability parameters, consequently on the supercell intensity. Numerical simulations show that the structure and the track of the convective cells can be correctly reproduced, as well as the triggering of convection due to interaction of the flow with the topographic features, such as the land-sea interface and orography, within a relatively small temporal delay. The mesoscale analysis also reveals, in all cases, an environment highly favourable for tornado formation, with most simulated instability parameters/indices exceeding their critical thresholds.

An in-depth analysis of historical heavy rainfall fields clearly constitutes an important aspect in many related topics: as examples, mesoscale models for early warning systems and the definition of design event scenarios can be improved, with the consequent upgrading in the prediction of induced phenomena (mainly floods and landslides) into specific areas of interest. With this goal, in this work the authors focused on Calabria region (southern Italy) and classified the main precipitation systems through the analysis of selected heavy rainfall events from high resolution rain gauge network time series. Moreover, the authors investigated the relationships among the selected events and the main synoptic atmospheric patterns derived by the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 Reanalysis dataset, in order to assess the possible large-scale scenarios which can induce heavy rainfall events in the study area. The obtained results highlighted: (i) the importance of areal reduction factors, rainfall intensities and amounts in order to discriminate the investigated precipitations systems for the study area, (ii) the crucial role played by the position of the averaged low-pressure areas over the Mediterranean for the synoptic systems, and by low-level temperature for the convective systems.

The Mediterranean area is a climate-change hotspot because of the natural and anthropogenic pollution pressure. The presence of natural aerosols, such as dust, influences solar radiation and contributes to the detection, in storm episodes, of significant concentrations of PM10 in Southern Italy, where generally fresh and clean air is due to local circulation, and particulate matter concentrations are very low. We present the results of medium-term observations (2015&ndash, 2019) at Lamezia Terme GAW (Global Atmospheric Watch) Regional Observatory, with the purpose of identifying the dust incursion events by studying the aerosol properties in the site. To achieve this goal, the experimental data, collected by several instruments, have been also correlated with the large-scale atmospheric patterns derived by the ERA5 reanalysis dataset, in order to study the meteorological conditions that strongly influence dust outbreaks and their spatio-temporal behavior. An intense dust-outbreak episode, which occurred on 23&ndash, 27 April 2019, was chosen as a case study, a detailed analysis was carried out considering surface and column optical properties, chemical properties, large-scale pattern circulation, air-quality modeling/satellite products, and back-trajectory analysis, to confirm the capability of the modeled large-scale atmospheric fields to correctly simulate the conditions mainly related to the desert dust-outbreak events.

Coastal areas are more and more exposed to the effects of climatic change. Intense local rainfalls increases the frequency of flash floods and/or flow-like subaerial and afterward submarine landslides. The overall phenomenon of flash flood is complex and involves different phases strongly connected: heavy precipitations in a short period of time, soil erosion, fan deltas forming at mouth and hyperpycnal flows and/or landslides occurrence. Such interrelated phases were separately modelled for simulation purposes by different computational models: Partial Differential Equations methods for weather forecasts and sediment production estimation and Cellular Automata for soil erosion by rainfall and subaerial sediment transport and deposit. Our aim is to complete the model for the last phase of final sediment outcome. This research starts from the results of the previous models and introduces the processes concerning the demolition of fan deltas by sea waves during a sea-storm and the subsequent transport of and sediments in suspension by current at the sea-storm end and their deposition and eventual flowing on the sea bed. A first reduced implementation of the new model SCIDDICA-ss2/w&c1 was applied on the partial reconstruction of the 2016 Bagnara case regarding the meteorological conditions and the flattening of Sfalassa’s fan delta.

Coastal areas are more and more exposed to the effects of climatic change. Intense local rainfalls increases the frequency of flash floods and/or flow-like subaerial and afterward submarine landslides. The overall phenomenon of flash flood is complex and involves different phases strongly connected: heavy precipitations in a short period of time, soil erosion, fan deltas forming at mouth and hyperpycnal flows and/or landslides occurrence. Such interrelated phases were separately modelled for simulation purposes by different computational models: Partial Differential Equations methods for weather forecasts and sediment production estimation and Cellular Automata for soil erosion by rainfall and subaerial sediment transport and deposit. Our aim is to complete the model for the last phase of final sediment outcome. This research starts from the results of the previous models and introduces the processes concerning the demolition of fan deltas by sea waves during a sea-storm and the subsequent transport of and sediments in suspension by current at the sea-storm end and their deposition and eventual flowing on the sea bed. A first reduced implementation of the new model SCIDDICA-ss2/w&c1 was applied on the partial reconstruction of the 2016 Bagnara case regarding the meteorological conditions and the flattening of Sfalassà's fan delta.

In this paper we study the sensitivity of the quantitative precipitation forecast (QPF) to different physical parameterization schemes and configuration settings of WRF (Weather Research and Forecasting) model for a catastrophic event occurred in Calabria, Southern Italy. The event lasted four days, from 30 October 2015 to 2 November 2015, and affected mostly the eastern side of the peninsula. Several raingauges measured >500 mm for the whole event, with the maximum recorded in Chiaravalle (739 mm for the whole event, which is about half of the yearly rainfall). Damages to railway, roads and properties were extensive. To show the sensitivity of the QPF to the model settings and physical parameterization schemes, twelve configurations of WRF are considered, in addition to the control run ( CC ), which is the configuration used for the operational forecast at ISAC-CNR in Lamezia Terme. In particular, we tested the sensitivity of the QPF to four different microphysical schemes, three Planetary Boundary Layer (PBL) schemes (non-local and local), two cumulus parameterization schemes, two different horizontal resolutions (1 km vs 3 km), and different initial and boundary conditions. The QPF is verified both by quantitative measures and qualitative scores, using the observations of 156 raingauges quite uniformly distributed over Calabria. The analysis refers to 12 h and 24 h rainfall, but some details are given also for shorter time scales. Results show that most of the WRF configurations are able to predict most of the features of the precipitation field. However, there are differences at the local scale (few tens of kilometers) that are important for several purposes, including civil protection. In particular, using a non-local PBL closure scheme was fundamental to correctly simulate the heavy precipitation close to the sea for this case, while other configurations predicted the rainfall more anchored to mountain peaks. The good performance of non-local PBL scheme confirms the findings of a previous study over Calabria. The results of this paper show the sensitivity of the QPF at the local scale for different WRF configurations and an ensemble approach is envisaged to improve the prediction of such catastrophic events.

The sensitivity of boundary layer variables to five (two non-local and three local) planetary boundary-layer (PBL) parameterization schemes, available in the Weather Research and Forecasting (WRF) mesoscale meteorological model, is evaluated in an experimental site in Calabria region (southern Italy), in an area characterized by a complex orography near the sea. Results of 1 km × 1 km grid spacing simulations are compared with the data collected during a measurement campaign in summer 2009, considering hourly model outputs. Measurements from several instruments are taken into account for the performance evaluation: near surface variables (2 m temperature and relative humidity, downward shortwave radiation, 10 m wind speed and direction) from a surface station and a meteorological mast; vertical wind profiles from Lidar and Sodar; also, the aerosol backscattering from a ceilometer to estimate the PBL height. Results covering the whole measurement campaign show a cold and moist bias near the surface, mostly during daytime, for all schemes, as well as an overestimation of the downward shortwave radiation and wind speed. Wind speed and direction are also verified at vertical levels above the surface, where the model uncertainties are, usually, smaller than at the surface. A general anticlockwise rotation of the simulated flow with height is found at all levels. The mixing height is overestimated by all schemes and a possible role of the simulated sensible heat fluxes for this mismatching is investigated. On a single-case basis, significantly better results are obtained when the atmospheric conditions near the measurement site are dominated by synoptic forcing rather than by local circulations. From this study, it follows that the two first order non-local schemes, ACM2 and YSU, are the schemes with the best performance in representing parameters near the surface and in the boundary layer during the analyzed campaign.

Il progetto SMoRI (Smart Monitoring per il controllo di bacini ad elevato Rischio Idrogeologico), cofinanziato nell'ambito del POR CALABRIA FESR-FSE 2014- 2020, si prefigge di realizzare un sistema integrato di monitoraggio dei diversi fenomeni che possono determinare il rischio idrogeologico, attraverso un approccio multidisciplinare, coniugando know-how specialistico e le nuove tecnologie inerenti il Cloud Computing e l'IoT (Internet of Things). Al fine di realizzare un sistema prototipale integrato di monitoraggio del rischio idrogeologico, il progetto ha previsto lo sviluppo di una metodologia multicomponente innovativa di monitoraggio ambientale, applicabile su scala di bacino idrografico e nel relativo tratto costiero alimentato. SMoRI integra, infatti, i dati provenienti da "sensori a terra" con gli output di modelli previsionali atmosferici (Modulo Meteo), di modelli idrologici (Modulo Idraulica fluviale e costiera) e di analisi geologiche e morfologiche (Modulo Suolo), in modo da riprodurre scenari storici di franosità dei versanti, fenomeni di tipo idraulico, con conseguenti esondazioni dei corsi d'acqua ed elevata produzione/trasporto di materiale solido, fenomeni di tipo marittimo. I Moduli Meteo e Suolo si basano sull'utilizzo di centraline meteorologiche di superficie e sulla ricostruzione microclimatica, mediante modellistica atmosferica riferita a periodi passati, ed effettuano una analisi comparata fra caratteristiche pluviometriche e microclimatiche e i quantitativi mobilizzati in passato sui versanti, in occasione di eventi pluviometrici particolarmente intensi e/o prolungati, visualizzando scenari storici di franosità dei versanti e effettuando stime delle quantità di sedimenti prodotti, sia per processi erosivi sia per instabilità superficiali. Il Modulo Suolo, inoltre, permette di calcolare produzione/trasporto di sedimento a scala di bacino (celle 250m x 250m), 361 mediante l'utilizzo del plug-in YES. YES utilizza dati vettorializzati meteoclimatici, resistenza geolitologica, di uso del suolo e dei processi geomorfologici, acquisiti sul terreno ed in laboratorio e tarati attraverso misure di ridistribuzione del suolo (erosione/accumulo), lungo i versanti, mediante isotopi da fall-out e calcoli idraulici. Il Modulo Suolo consente così di definire indici di produzione di sedimenti, in relazione a parametri meteoclimatici, litologici, d'uso del suolo, di pendenza dei versanti, ecc. Il Modulo di Idraulica fluviale e costiera si basa sull'applicazione di procedure automatizzate di trasformazione afflussi-deflussi (HEC-HMS), e di formule empiriche per il trasporto solido, opportunamente tarate in laboratorio, anche per il tramite di un sistema embedded costituito da una piccola rete di sensori idrofonici. Il modulo permette la stima delle portate, liquida e solida, dei corsi d'acqua, con particolare attenzione a quelle sezioni più vicine ad aree antropizzate. L'utilizzo di traccianti artificiali e naturali può consentire anche la ricostruzione dei percorsi di trasporto del materiale solido. Inoltre, partendo dalla ricostruzione del clima meteomarino estremo al largo e sottocosta, legato a eventi di mareggiata, marea e pressione atmosferica sul mare, e dalla propagazione del moto ondoso tramite il modello spettrale SWAN, il Modulo permette la stima dell'evoluzione a breve termine del profilo di spiaggia attiva, attraverso il modello idromorfodinamico XBeach, e la stima del trasporto solido costiero a livello trasversale. La variazione della linea di riva, a lungo termine, viene stimata attraverso il modello ad una linea GENCADE. Il sistema SMORI permette anche di implementare moduli per il monitoraggio dei movimenti di versante (tempi, profondità, velocità), in stretta correlazione con le piogge registrate, e tramite sensori di tipo geotecnico, collegati al Cloud in real time. La metodologia multicomponente è stata quindi implementata all'interno di un sistema software complesso multisensore IoT con metodologia OMT. L'infrastruttura tecnologica prevede: protocolli di comunicazione e di sicurezza per reti di sensori ambientali e geo-idrologici; modellazione delle componenti software di un sistema complesso multi sensore IoT; sistemi Cloud in modalità Smart Objects; protocollo di fruizione di un sistema di stazioni IoT multicomponenti da Cloud in modalità multicanale; protocollo di comunicazione tra Cloud Multi-Federato e Smart Objects; protocollo di sicurezza e affidabilità per lo storage su Cloud "Multi-Federato" per lo scenario di riferimento. E' stato anche realizzato un GIS in grado sia di gestire la diversità di informazioni presenti (geometriche, topologiche, informative), sia di implementare funzionalità di analisi spaziale e basi di dati. Un sistema di business intelligence, inoltre, implementa i moduli di analisi dei dati raccolti. Per tarare, calibrare e validare l'intero sistema, è stato selezionato, sulla base delle caratteristiche geomorfologiche, idrologiche, idrauliche, e delle implicazioni sulle dinamiche costiere, il bacino del Fiume Aron, ubicato nel territorio di Cetraro (CS). Si tratta di un'area rappresentativa dell'intero settore nordoccidentale della Calabria, dove la presenza di numerosi insediamenti antropici e di infrastrutture, può determinare, in caso di eventi pluviometrici intensi e/o prolungati, scenari complessi di rischio (rischio frana, esondazione, costiero). SMoRI, nato da una efficace sinergia fra mondo aziendale e comunità scientifica, potrà essere applicato, con una adeguata taratura, su altri bacini ed essere di grande utilità nella prevenzione e previsione del rischio idrogeologico.

The improvement of the Solar and Wind short-term forecasting represents a critical goal for the weather prediction community and is of great importance for a better estimation of power production from solar and wind farms. In this work we analyze the performance of two deterministic models operational at ISAC-CNR for the prediction of short-wave irradiance and wind speed, at two experimental sites in southern Italy. A post-processing technique, i.e the multi-model, is adopted to improve the performance of the two mesoscale models. The results show that the multi-model approach produces a significant error reduction with respect to the forecast of each model. The error is reduced up to 20 % of the model errors, depending on the parameter and forecasting time.

The understanding of the atmospheric processes in coastal areas requires the availability of quality datasets describing the vertical and horizontal spatial structure of the Atmospheric Boundary Layer (ABL) on either side of the coastline. High-resolution Numerical Weather Prediction (NWP) models can provide this information and the main ingredients for good simulations are: an accurate description of the coastline and a correct subgrid process parametrization permitting coastline discontinuities to be caught. To provide an as comprehensive as possible dataset on Mediterranean coastal area, an intensive experimental campaign was realized at a near-shore Italian site, using optical and acoustic ground-based remote sensing and surface instruments, under different weather characteristic and stability conditions, the campaign is also fully simulated by a NWP model. Integrating information from instruments responding to different atmospheric properties allowed for an explanation of the development of various patterns in the vertical structure of the atmosphere. Wind LiDAR measurements provided information of the internal boundary layer from the value of maximum height reached by the wind profile, a height between 80 and 130 m is often detected as an interface between two different layers. The NWP model was able to simulate the vertical wind profiles and the eight of the ABL.

The analysis of a severe convective storm, occurred in northwestern Italy during late summer 2012, is presented here. The event was characterized by heavy precipitation, hail and intense wind gusts, causing injuries and damages to trees, buildings and infrastructures. The description of the case study draws upon a wide palette of observational data. Surface and upper-air observations helped characterize the event, emphasizing the rapid changes in the meteorological parameters in the study area; satellite data highlights the presence of deep moist convection, associated with strong updrafts; Doppler radar allows the identification of the main features of the event in terms of storm-motion, hail detection/probability and the possible presence of a mesocyclone. A high-resolution (3 km inner grid spacing) simulation with the WRF (Weather Research and Forecasting) model was performed to study the atmospheric conditions conducive to convection, as well as to estimate the main instability parameters. The main features of the storm were well reproduced with WRF; furthermore, the high values of the simulated instability parameters denote the presence of favourable conditions for severe convection. The analysis of this event shows that supercells can develop also in a pre-alpine environment, characterized by a complex orography, in particular in the sub-regions where the local morphology creates conditions favourable for severe weather development.

In this paper, we study the impact of lightning and radar reflectivity factor data assimilation on the precipitation VSF (Very Short-term Forecast, 3 hours in this study) for two relevant case studies occurred over Italy. The first case refers to a moderate localised rainfall over Central Italy happened on 16 September 2017. The second case, occurred on 09 and 10 September 2017, was very intense and caused damages in several parts of Italy, while nine people died around Livorno, in Tuscany. The first case study was missed by most operational forecasts over Italy, including that performed by the model used in this paper, while the Livorno case was partially predicted by operational models. We use the RAMS@ISAC model (Regional Atmospheric Modelling System at Institute for Atmospheric Sciences and Climate of the Italian National Research Council), whose 3D-Var extension to the assimilation of RADAR reflectivity factor is shown in this paper. Results for the two cases show that the assimilation of lightning and radar reflectivity factor, especially when used together, have a significant and positive impact on the precipitation forecast. The improvement compared to the control model, not assimilating lightning and radar reflectivity factor, is systematic because occurs for all the Very Short-term Forecast (VSF, 3h) of the events considered. For specific time intervals, the data assimilation is of practical importance for Civil Protection purposes because it transforms a missed forecast of intense precipitation (> 40 mm/3h) in a correct forecast. While there is an improvement of the rainfall VSF thanks to the lightning and radar reflectivity factor data assimilation, its impact is reduced by the increase of the false alarms in the forecast assimilating both types of data.

This study investigates the sensitivity of a moderate-intense storm that occurred over Calabria, southern Italy, to upper-tropospheric forcing from a Potential Vorticity (PV) perspective. A prominent mid-troposheric trough can be identified for this event, which occurred between 22–24 May 2002, and serves as the precursor agent for the moderate-intense precipitation recorded. The working hypothesis is that the uncertainty in the representation of the upper-level disturbance has a major impact on the precipitation forecast and we test the hypothesis in a two-step approach. First, we examine the degree of uncertainty by comparing five different scenarios in a Limited area model Ensemble Prediction System (LEPS) framework which utilizes the height of the dynamical tropopause as the discriminating variable. Pseudo water vapour images of different scenarios are compared to the corresponding METEOSAT 7 water vapour image at a specific time, antecedent to the rain occurrence over Calabria, in order to evaluate the reliability of the different precipitation scenarios simulated by the LEPS. Second, we examine the impact of upper tropospheric PV variations on precipitation by comparing model simulations with slightly different initial PV fields. Initial velocity and mass fields in each case are balanced with the chosen PV perturbation using a PV inversion technique. The results of this study support the working hypothesis.

The purpose of the data assimilation is to optimally use all the available information, to determine as accurately as possible the state of the atmosphere. We show the assimilation of the GPS-ZTD (Global Positioning System - Zenith Total Delay) by a 3D-Var data assimilation system that can be used in cycling mode with the Regional Atmospheric Modeling System (RAMS). The water vapour mixing ratio and temperature given by the background are modified according to the assimila- tion of the GPS-ZTD to improve the representation of the humidity and temperature fields and decrease the model spin-up time. To verify the impact of the GPS-ZTD data assimilation on the representation of the humidity field, two numerical experiments are performed: the first refers to the HyMeX-SOP1 period (6 September 2012 - 5 November 2012) over Italy, and the second, focused on the local scale, is performed over the Lazio region, in Central Italy, and refers to summer 2017. For both experiments, the background error matrix is computed by the NMC method and is invariant for the whole period. The observation error is the RMSE of the GPS data and varies form few millimetres to centimetres. For the first experiment, GPS-ZTD values are downloaded from the HyMeX database and analyses are produced every six-hours. The spatial grid for the analysis has 4 km horizontal resolution. To verify the improvement of the representation of the atmospheric humidity given by the analysis, the integrated water vapour column (IWV) is compared with the ECMWF analysis of the same quantity. Results show the im- provement of the IWV analysis compared to the background and the RMSE decrease for all GPS-receivers, with a reduction of the error of about 30%. The absolute value of the bias is also reduced. To evaluate the impact of the GPS-ZTD data assimilation at the local scale, a numerical experiment is performed using a network of 26 dual frequency GPS receivers distributed over the Lazio Region, in Central Italy, from 27 July to 30 September. The ZTD values were obtained by processing the data coming from the Italpos, Netgeo and Rete Lazio databases. Processing was carried out in PPP (Precise Point Positioning) using RTKLIB (http://www.rtklib.com/). Also for this experiment the analysis is performed over a 4 km horizontal resolution grid and the background is given by the RAMS model. The whole dataset is divided in two parts: a set of receivers is used for the data assimilation, while the remaining stations are used for verification. Results show a substantial decrease of the RMSE of the GPS-ZTD and IWV for the stations used for verification and the bias decreases, showing the potential of the assimilation of the GPS-ZTD. The results of this study are promising and will be further developed to evaluate the impact of GPS-ZTD data assimilation on the forecast of the atmospheric water vapour as well as on the rainfall prediction.

Recentemente l'Organizzazione Mondiale della Sanità (OMS) ha confermato gli effetti dannosi sulla salute umana del particolato fine (PM2.5) cui risulta particolarmente esposta la popolazione urbana. In alcuni casi, la presenza del particolato non è dovuta esclusivamente all'impatto antropico locale ma può derivare da trasporto di inquinanti e medio e a lungo raggio. A tal proposito diventa significativo se oltre alle misure in situ si tengono in considerazione le osservazioni da satellite, insieme a strumenti modellistici che permettono di delineare la circolazione atmosferica e quindi la circolazione di inquinanti. Il lavoro in oggetto tratta di alcune casistiche che sono state rilevate presso l'Osservatorio Climatico Ambientale dell'ISAC -CNR di Lamezia Terme in concomitanza di alcuni eventi naturali e non, in cui è stato significativo individuare la provenienza della sorgente con l'ausilio sia delle misure in situ che da remote sensing (wind-lidar, satellite ,...) oltre a strumenti modellistici.

Reliable measurements of vertical profiles of wind speed and direction are needed for testing models and methodologies of use for wind energy assessment. In particular, modelling complex terrain such as coastal areas is challenging due to the coastal discontinuity that is not accurately resolved in mesoscale numerical model. Here, we present a unique database from a coastal site in South Italy (middle of the Mediterranean area) where vertical profiles of wind speed and direction have been collected during a two-year period from a wind-lidar ZEPHIR-300® at a coastal-suburban area. We show an overview analysis on two-year 10-minute averaged wind profiles.

The knowledge of water vapour distribution is a key element in atmospheric modeling and considerable information, also at the local scale, can be derived from the GPS-ZTD (global positioning system-Zenith total delay) data.

Quality of wind prediction is of great importance since a good wind forecast allows the prediction of available wind power, improving the penetration of renewable energies into the energy market. Here, a 1-year (1 December 2012 to 30 November 2013) three-model ensemble (TME) experiment for wind prediction is considered. The models employed, run operationally at National Research Council – Institute of Atmospheric Sciences and Climate (CNR-ISAC), are RAMS (Regional Atmospheric Modelling System), BOLAM (BOlogna Limited Area Model), and MOLOCH (MOdello LOCale in H coordinates). The area considered for the study is southern Italy and the measurements used for the forecast verification are those of the GTS (Global Telecommunication System). Comparison with observations is made every 3 h up to 48 h of forecast lead time. Results show that the three-model ensemble outperforms the forecast of each individual model. The RMSE improvement compared to the best model is between 22 and 30 %, depending on the season. It is also shown that the three-model ensemble outperforms the IFS (Integrated Forecasting System) of the ECMWF (European Centre for Medium-Range Weather Forecast) for the surface wind forecasts. Notably, the three-model ensemble forecast performs better than each unbiased model, showing the added value of the ensemble technique. Finally, the sensitivity of the three-model ensemble RMSE to the length of the training period is analysed.

Phenological investigations that adopt aerobiological monitoring methodologies are frequently used for species that rely on the wind for pollen grain dispersion, such as the olive in the Mediterranean basin. The present study of olive flowering dates was carried out in the Calabria region (southern Italy). These were calculated on the basis of a phenological study of pollen levels in the atmosphere in three typical olive-growing areas over an 11 year study period (1999–2009). This phenological method provides olive flowering maps that are based on temperatures (as the growing degree days: GDDs), which are highly correlated with the release of the pollen grains. According to the model developed, the average GDDs corresponding to the flowering dates were calculated for the baseline period of 1981–2000. Moreover, with the use of meteorological data derived from the Intergovernmental Panel on Climate Change scenarios, the future olive flowering dates are estimated for the 20 year period from 2081 to 2100. The close relationships between the spring temperature trends and the reproductive phenological phases in the olive are highly sensitive to climatic change, which has implications in terms of potential latitude and altitude shifts in the olive cultivation areas. In some cultivation areas in southern Italy, the present particular combination of microclimate, soil status and level of erosion is considered as limiting to regular vegetative plant development. However, the use of olive cultivars that are specifically adapted to extremely stressful environments, in terms of high temperatures and water deficit, might represent the main solution for the mitigation of the consequences of climatic change.

A four-dimensional data assimilation (FDDA) scheme based on a Newtonian relaxation (or “nudging”) was tested using observational asynoptic data collected at a coastal site in the Central Mediterranean peninsula of Calabria, southern Italy. The study is referred to an experimental campaign carried out in summer 2008. For this period a wind profiler, a sodar and two surface meteorological stations were considered. The collected measurements were used for the FDDA scheme, and the technique was incorporated into a tailored version of the Regional Atmospheric Modeling System (RAMS). All instruments are installed and operated routinely at the experimental field of the CRATI-ISAC/CNR located at 600 m from the Tyrrhenian coastline. Several simulations were performed, and the results show that the assimilation of wind and/or temperature data, both throughout the simulation time (continuous FDDA) and for a 12 h time window (forecasting configuration), produces improvements of the model performance. Considering a whole single day, improvements are sub-stantial in the case of continuous FDDA while they are smaller in the case of forecasting configuration. En-hancements, during the first six hours of each run, are generally higher. The resulting meteorological fields are finalised as input into air quality and agro-meteorological models, for short-term predictions of renew-able energy production forecast, and for atmospheric model initialization.

This brief communication introduces a new quality-controlled precipitation database for Calabria, shows the precipitation trend for the period considered, and correlates daily rainfall with some common teleconnection patterns. The database consists of daily accumulated precipitation collected by 61 rain gauges from 1 January 1970 to 31 December 2006. The 37-year trend in yearly rainfall shows a decrease of 4.7 mm/y, with a 17% reduction in the yearly mean value. The correlation of the daily rainfall with large-scale patterns shows that the Mediterranean Oscillation Index (MOI a/c) is a useful predictor of daily precipitation over Calabria.

We present a study on the characteristics of the sea breeze flow at a coastal site located in the centre of the Mediterranean basin at the southern tip of Italy. This study is finalized to add new data on breeze circulations over a narrow peninsula and present a unique experimental coastal site at about 600 m from the coastline in a flat open area at the foot of a mountain chain located in a region of complex orography. We study the seasonal behaviour of the sea-land breeze circulation by analysing two years of hourly data of wind speed and direction, temperature, radiation and relative humidity from a surface meteorological station, eighteen-months data from a wind profiler, and two-year data from the ECMWF analysis. Results show that breezes dominate the local circulation and play a major role for the local climate. They are modulated by the season, through the sea-land temperature difference and the large-scale flow. The large-scale forcing acts in phase with the diurnal breeze and opposes the nocturnal breeze. In summer, the daytime difference between the land surface temperature and the SST (Sea Surface Temperature) reaches its maximum, while the nigh-time difference has its minimum. This causes a strong, frequent and intense diurnal breeze and a weak nocturnal breeze. In winter and fall the nocturnal difference between the sea and land surface temperature reaches a maximum value, while the diurnal difference is at its minimum value. This causes a strong, frequent and intense nocturnal breeze despite of the large-scale forcing that is usually opposed to local-scale flow.

This paper presents first exploratory results and analyses performed on a 30-year (1978–2007) homogeneous precipitation database that has been created for the Calabria peninsula, southern Italy. The database consists of complete time series of daily values of precipitation from 88 stations distributed over the region. The database temporal resolution is one day while its spatial resolution is about 10 km. Calabria offers an interesting scenario for mesoclimatic studies in spatial and temporal rainfall variability. The region is located in the Central Mediterranean Basin, which has a strong seasonal variability that mirrors in large precipitation differences among seasons. The complex orography of the region leads to different exposures of the territory to the rain-bearing air masses and large differences in rainfall can occur in few tens of kilometers. Different kinds of Mediterranean storms are important for Calabria: a) storms originating in the lee of the Alps; b) storms that enter the Basin or develop in the western Mediterranean (Gulf of Lyon, Rhone valley, Iberia, Gibraltar); c) storms from northern Africa; d) storms moving over the central Mediterranean from Balkans and eastern Europe. Again, their interaction with local orography determines complex rainfall patterns and variability. In this paper, the maps of average values of precipitation, rain frequency, rain rate, persistence of rainfall and length of dry periods are presented. Precipitation spatial structure shows that the orography and the sea have a major role, while the seasonal dependence of rainfall unequivocally reveals the influence of the synoptic scale conditions. A large number of cast-studies of heavy precipitation events have been investigated in the past and several of them refer to the east side of Calabria. The results shown here confirm this issue in a climatological sense: despite the fact that yearly precipitation is larger on the west side of the peninsula, most intense rainstorms affect mainly the east side, which is favorably exposed to these storms. The current database represents a foundation for further investigations.

Olives are one of the largest crops in the Mediterranean and in central and southern Italy. This work investigates the correlation of the Olea europaea L. pollen season in Perugia, the capital city of the region of Umbria in central Italy, with atmospheric parameters. The aim of the study is twofold. First, we study the correlation between the pollen season and the surface air temperature of the spring and late spring in Perugia. Second, the correlation between the pollen season and large-scale atmospheric patterns is investigated. The average surface temperature in the spring and late spring has a clear impact on the pollen season in Perugia. Years with higher average temperatures have an earlier onset of the pollen season. In particular, a 1 degrees C higher (lower) average surface temperature corresponds to an earlier (later) start of the pollen season of about 1 week. The correlation between the pollen season and large-scale atmospheric patterns of sea level pressure and 500-hPa geopotential height shows that the cyclonic activity in the Mediterranean is unequivocally tied to the pollen season in Perugia. A larger than average cyclonic activity in the Mediterranean Basin corresponds to a later than average pollen season. Larger than average cyclonic activity in Northern Europe and Siberia corresponds to an earlier than average pollen season. A possible explanation of this correlation, that needs further investigation to be proven, is given. These results can have a practical application by using the seasonal forecast of atmospheric general circulation models.

In order to establish strategies for the mitigation of global warming, a quantitative understanding of the global budget of the greenhouse gases are required. Greenhouse gases, according to the IPCC (2013), are important components of climate pollutants that contribute both directly and indirectly to the Earth's radiative balance. Carbon dioxide, Atmospheric methane, Carbon monoxide mixed to Water Vapour gas-phase molecules, are measured using a CRDS "cavity ring down spectroscopy" (PICARRO) instrument. NO, NO2, O3 greenhouse gases, are also detected by THERMOtei49i and THERMOtei42i analyzers. We study the temporal evolution of the hourly and daily mean values of the concentrations of the greenhouse gases and a seasonal variability. The influence of meteorological parameters and local circulation, on the concentration of CH4, CO, and CO2, NOx, Ozone and pollutants are also analyzed. Some evidence of forest fire smoke detection are also reported. A further analysis on the correlations with back-trajectories technique based on high resolution atmospheric model outputs are also showed

The solar radiation is a critical input parameter when working with solar energy and radiation dependent surface processes. In this study, we present preliminary results from an inter-comparison between hourly values from a pyranometer, MSG-SEVIRI sensor and two meso-scale models, WRF and RAMS, in clear and cloudy sky conditions. Cloudy sky condition is the most important because the attenuation of solar radiation in the atmosphere is strongly dependent on the cloud variability. Bias and RMSE errors are evaluated at a coastal site in the Mediterranean area. These statistics show the tendency of both models to overestimate short-wave radiation.

L'obiettivo principale del lavoro sperimentale in oggetto è finalizzato allo sviluppo di un approccio metodologico di monitoraggio ambientale da adottare come possibile strategia di conservazione preventiva del patrimonio culturale in ambiente marino-costiero.

This paper reports preliminary results of a Limited area model Ensemble Prediction System (LEPS), based on RAMS, for eight case studies of moderate-intense precipitation over Calabria, the southernmost tip of the Italian peninsula. LEPS aims to transfer the benefits of a probabilistic forecast from global to regional scales in countries where local orographic forcing is a key factor to force convection. To accomplish this task and to limit computational time, in order to implement LEPS operational, we perform a cluster analysis of ECMWF-EPS runs. Starting from the 51 members that forms the ECMWF-EPS we generate five clusters. For each cluster a representative member is selected and used to provide initial and dynamic boundary conditions to RAMS, whose integrations generate LEPS. RAMS runs have 12 km horizontal resolution. Hereafter this ensemble will be referred also as LEPS_12L30. To analyze the impact of enhanced horizontal resolution on quantitative precipitation forecast, LEPS_12L30 forecasts are compared to a lower resolution ensemble, based on RAMS that has 50 km horizontal resolution and 51 members, nested in each ECMWF-EPS member. Hereafter this ensemble will be also referred as LEPS_50L30. LEPS_12L30 and LEPS_50L30 results were compared subjectively for all case studies but, for brevity, results are reported for two "representative" cases only. Subjective analysis is based on ensemble-mean precipitation and probability maps. Moreover, a short summary of objective scores. Maps and scores are evaluated against reports of Calabria regional raingauges network. Results show better LEPS_12L30 performance compared to LEPS_50L30. This is obtained for all case studies selected and strongly suggests the importance of the enhanced horizontal resolution, compared to ensemble population, for Calabria, at least for set-ups and case studies selected in this work.

At Crati Scrl an operational version of RAMS 4.3 (Regional Atmospheric Modeling System) was implemented in January 2001. This paper aims to give a first assessment of model performances for quantitative precipitation forecast (QPF). In essence, the effects of enhanced horizontal grid resolution over Calabria, using a 6km spacing domain nested in a 30km resolution parent grid, is studied. To cope with this problem two integrations sets are discussed using two model resolutions. Integrations are performed daily for six months. ECMWF 12:00UTC forecast cycle is used for initial and dynamic boundary conditions. Performances are evaluated by scores computed from model outputs and raingauge measurements coming from Calabrian regional network.

In the last years, surveying large regions of the atmosphere in an automatic way, for early detection of pollutant sources in urban and industrial areas, has become a strategic objective of various public health organizations. The Lidar/Dial technique has become a well-established laser remote sensing method for atmosphere monitoring. It is often used to probe almost any level of the atmosphere and to acquire information necessary to validate theoretical models about different topics of atmospheric physics. It can also be deployed for environment surveying by monitoring particles, aerosols and molecules. For these reasons, an experimental campaign for evaluating the performances of a Lidar/Dial system in detecting pollutants (particulate and/or chemical compounds) has been carried out in an industrial area in the south of Italy. In this work, a homemade Lidar/Dial system (developed and built by the authors) and the results of the experimental campaign will be presented and discussed.