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This paper presents a model intercomparison study to improve the prediction and understanding of Mediterranean cyclone dynamics. It is based on a collective effort with five mesoscale models to look for a robust response among 10 numerical frameworks used in the community involved in the networking activity of the EU COST Action “MedCyclones”. The obtained multi-model, multi-physics ensemble is applied to the high-impact Medicane Ianos of September 2020 with a focus on the cyclogenesis phase, which was poorly forecast by numerical weather prediction systems. Models systematically perform better when initialised from operational IFS analysis data compared to the widely used ERA5 reanalysis. Reducing horizontal grid spacing from 10 km with parameterised convection to convection-permitting 2 km further improves the cyclone track and intensity. This highlights the critical role of deep convection during the early development stage. Higher resolution enhances convective activity, which improves the phasing of the cyclone with an upper-level jet and its subsequent intensification and evolution. This upscale impact of convection matches a conceptual model of upscale error growth in the midlatitudes, while it emphasises the crucial interplay between convective and baroclinic processes during medicane cyclogenesis. The 10 numerical frameworks show robust agreement but also reveal model specifics that should be taken into consideration, such as the need for a parameterisation of deep convection even at 2 km horizontal grid spacing in some models. While they require generalisation to other cases of Mediterranean cyclones, the results provide guidance for the next generation of global convection-permitting models in weather and climate.

Abstract Leveraging the Copernicus high‐resolution multi‐year Mediterranean Sea Surface Temperature (SST) dataset, 15 selected tropical‐like cyclones (TLCs) are analyzed with the objective of elucidating the anomalies of SST at the time of cyclogenesis and the connection between the change in SST during the cyclone lifetime and its characteristics. The long‐term SST increase associated with climate change is identified by comparing detrended and original anomalies. Detrending removes the effect of the intensification of SST anomaly over time, revealing that no significant anomalies generally emerge in the early stages of the TLC lifetimes. Conversely, winter events exhibit early‐stage positive SST anomalies. Also, high SST values were observed during the intensification of the most intense cyclones. A cold SST anomaly is left after the passage of the cyclones, due to the intense sea surface fluxes extracting heat from the sea.

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 in modelling sea levels and waves for such an intense event, we performed an 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 localized 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 and 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.

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.

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.

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.

This paper shows the results of a tailored version of a previously published methodology, designed to simulate lightning activity, implemented into the Regional Atmospheric Modeling System (RAMS). The method gives the flash density at the resolution of the RAMS grid scale allowing for a detailed analysis of the evolution of simulated lightning activity. The system is applied in detail to two case studies occurred over the Lazio Region, in Central Italy. Simulations are compared with the lightning activity detected by the LINET network. The cases refer to two thunderstorms of different intensity which occurred, respectively, on 20 October 2011 and on 15 October 2012. The number of flashes simulated (observed) over Lazio is 19435 (16231) for the first case and 7012 (4820) for the second case, and the model correctly reproduces the larger number of flashes that characterized the 20 October 2011 event compared to the 15 October 2012 event. There are, however, errors in timing and positioning of the convection, whose magnitude depends on the case study, which mirrors in timing and positioning errors of the lightning distribution. For the 20 October 2011 case study, spatial errors are of the order of a few tens of kilometres and the timing of the event is correctly simulated. For the 15 October 2012 case study, the spatial error in the positioning of the convection is of the order of 100 km and the event has a longer duration in the simulation than in the reality. To assess objectively the performance of the methodology, standard scores are presented for four additional case studies. Scores show the ability of the methodology to simulate the daily lightning activity for different spatial scales and for two different minimum thresholds of flash number density. The performance decreases at finer spatial scales and for higher thresholds. The comparison of simulated and observed lighting activity is an immediate and powerful tool to assess the model ability to reproduce the intensity and the evolution of the convection. This shows the importance of using computationally efficient lightning schemes, such as the one described in this paper, in forecast models.

Since June 2008, 1-h temperature forecasts for the Calabria region (Southern Italy) are issued at 2.5 km horizontal resolution at CRATI/ISAC-CNR. Forecasts are available online at http://meteo.crati.it/previsioni.html (every 6-h). This paper shows the forecast performance out to three days for one climatological year (from 1 December 2008 to 30 November 2009, 365 run) for minimum, mean and maximum temperature. The forecast is evaluated against gridded analyses at the same horizontal resolution. Gridded analysis is based on Optimal Interpolation (OI) and uses a de-trending technique for computing the background field. Observations from 87 thermometers are used in the analysis system. In this paper cumulative statistics are shown to quantify forecast errors out to three days.

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 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.

This study investigates the atmospheric pattern circulations associated with heavy rainfall (HR) days in Calabria, southern Italy, and contributes to the understanding of the dynamical mechanisms that produce those events. Heavy rainfall days are extracted from the raingauge database of the "Protezione Civile Regionale", which has more than a hundred pluviometric stations for the period 1999–2007 (eight years). To study the synoptic atmospheric circulations associated with HR we use the Regional Atmospheric Modeling System (RAMS) gridded data field of 925 hPa and 500 hPa geopotential height. First the number of variables is reduced by principal component analysis (PCA), then a cluster analysis (CA) is applied on those new atmospheric variables and eleven atmospheric patterns are obtained. Clear associations emerged between each of the circulation types and rainfall patterns over Calabria for HR days. These associations can be explained by the interaction between the complex orography of the region, the sea and the synoptic scale flow.

In this study we conduct a numerical analysis of an intense and destructive storm that occurred over Calabria, southern Italy, on 10–12 December 2003. More than 250 mm of precipitation was recorded over a large area in southern Calabria and one station reported about 660 mm in two days (more than half of the yearly climatological value). Precipitation fell mainly during 11 and 12 December. The storm was characterized by the entrance of an Atlantic upper-level trough associated with a deep surface low that advected humid marine air toward steep Calabrian orography. The steep mountain ridges favoured landslides, which were reported in several villages. Property damage was extensive. We study the storm at the mesoscale by means of the Regional Atmospheric Modeling System (RAMS). The model was successful at representing the observed accumulated rainfall patterns. This justifies our use of RAMS for further analysis of the physical and dynamic factors involved in the storm event. In particular, we use RAMS to evaluate the roles of Calabrian orography, surface latent heat flux, and upper level forcing. The key role of a potential vorticity (PV) streamer, which forced the entire meteorological system from the upper levels is assessed by the PV inversion technique in a Limited Area Model Ensemble Prediction System (LEPS) framework. Results show that the roles of Calabrian orography and surface latent heat flux are important in our simulations. Indeed, humid marine air masses were advected by the synoptic flow toward Calabrian steep coastal mountain ranges determining intense and abundant rainfall.

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.

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.

This paper reports preliminary results for a Limited area model Ensemble Prediction System (LEPS), based on RAMS (Regional Atmospheric Modelling System), 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 an operational implementation of LEPS, we perform a cluster analysis of ECMWF-EPS runs. Starting from the 51 members that form 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. To analyze the impact of enhanced horizontal resolution on quantitative precipitation forecasts, LEPS forecasts are compared to a full Brute Force (BF) ensemble. This ensemble is based on RAMS, has 36 km horizontal resolution and is generated by 51 members, nested in each ECMWF-EPS member. LEPS and BF results are compared subjectively and by objective scores. Subjective analysis is based on precipitation and probability maps of case studies whereas objective analysis is made by deterministic and probabilistic scores. Scores and maps are calculated by comparing ensemble precipitation forecasts against reports from the Calabria regional raingauge network. Results show that LEPS provided better rainfall predictions than BF for all case studies selected. This strongly suggests the importance of the enhanced horizontal resolution, compared to ensemble population, for Calabria for these cases. To further explore the impact of local physiographic features on QPF (Quantitative Precipitation Forecasting), LEPS results are also compared with a 6-km horizontal resolution deterministic forecast. Due to local and mesoscale forcing, the high resolution forecast (Hi-Res) has better performance compared to the ensemble mean for rainfall thresholds larger than 10mm but it tends to overestimate precipitation for lower amounts. This yields larger false alarms that have a detrimental effect on objective scores for lower thresholds. To exploit the advantages of a probabilistic forecast compared to a deterministic one, the relation between the ECMWF-EPS 700 hPa geopotential height spread and LEPS performance is analyzed. Results are promising even if additional studies are required.

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.