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International audience; A dynamical-system approach is proposed to describe the relationship between precipitation and a chosen predictor. This is done by constructing a two dimensional phase space spanned by predictor and predictant. This study uses two sounding data sets from the Tropical Western Pacific and Friuli Venezia Giulia (FVG) over NorthEast Italy as representatives of the tropics and midlatitudes, in addition to a basin-scale average over the winter-period North Atlantic from global re-analysis data. In contrast to conventional correlationbased approaches, the proposed approach depicts periodic cycles, as well as discharge-recharge cycles as its nonlinear extension. Discharge-recharge cycles for tropical convection are identified by using both the convective available potential energy (CAPE) and the column-integrated water vapor (CIW) as predictors, as well as the baroclinicity for the winter-period North-Atlantic rain. On the other hand, the midlatitude rain, as seen over FVG as well as the winter-period North Atlantic, does not constitute a well-defined periodic cycle either with CAPE or CIW as a predictor. The inferred phase-space trajectories are more deterministic at peripheries of dense data areas rather than at a middle in the phase space. Data-dense areas in phase space, where traditional approaches primarily focus, are associated with more prediction uncertainties in our analysis due to more phase-velocity fluctuations.

A bstract Friuli Venezia Giulia (FVG, NE Italy) is an area of maximum rainfall in the whole Alpine chain territory, reaching more than 3200 mm of mean annual rain in the Julian Prealps. According to recent climatological studies, the same area is also one of the European spot in recent lightning climatologies, meaning that convective rain plays an important role in the total rainfall. A network of 104 raingauges placed around the FVG territory is used to extract the absolute maximum rain accumulated every 6 hours in four subareas of FVG. In an attempt to improve the original ECMWF maximum rain, these data have been targeted to develop 32 statistical downscaling models, according to the period of the day, of the year and specific sub-area. ECMWF 6-hour rain forecasts available for all the gridpoints encompassed in the FVG territory and some derived variables (absolute values, anomalies, standardized values, plus mean, max and SD in time and/or space) have been used as predictors. With respect to a previous version of this work, here also the instability pseudo-indices (derived from the vertical profile with the maximum vertical resolution available in the ECMWF hybrid levels) are used as candidate predictors. Moreover, also non-linear methods, namely neural networks, are implemented, together with exhaustive multiregression models. Results show that the 32 models improve -on average- R2 of 12% on the validation sample and of 5% on the 2017 test sample, with respect to the ECMWF rain forecast, but the improvement is particularly notable during the convective season (18%).

This work evaluates numerous thunderstorm predictors and investigates the use of artificial neural networks (ANNs) for identifying occurrences of thunderstorms in reanalysis data. Environmental conditions favorable for deep, moist convection are derived from 6-hourly ERA-Interim reanalyses, while thunderstorm occurrence in the following 6 h over Finland is derived from lightning location data. By taking advantage of the consistency and large sample size (14 summers) provided by the reanalysis, complex multivariate models can be trained for a robust estimation of convective weather events from model data. This and other methods are used to yield information on the most effective convective predictors in a multivariate setting, which can also benefit the forecasting community. The best ANN found uses 15 inputs and received a Heidke skill score (HSS) of 0.51 on an independent test sample. This is a substantial improvement over the best predictor when used alone, the most unstable lifted index (MULI) with HSS = 0.40, the multivariate model having fewer false alarms in particular. After MULI, the most important ANN input was relative humidity near 700 hPa. Dry air aloft was associated with significantly lower thunderstorm probability and flash density regardless of convective available potential energy (CAPE). Other important parameters for thunderstorm development were vertical velocity and low-level θe advection. Finally, the Peirce skill score indicates a clear meridional gradient in skill for categorical forecasts, with higher skill in northern Finland. This analysis suggests that the difference in skill is real and associated with a steeper thunderstorm probability curve in the north, but further studies are needed for a physical explanation.

During the first HyMeX Special Observation Period (SOP1) field campaign, the target site of north‐eastern Italy (NEI) experienced a large amount of precipitation, locally exceeding the climatological values and distributed among several heavy‐rainfall episodes. In particular, two events that occurred during the last period of the campaign drew our attention. These events had common large‐scale patterns and a similar mesoscale setting, characterised by southerly low‐level flow interacting with the Alpine orography, but the precipitation distribution was very different. During Intensive Observing Period IOP18 (31 October–1 November 2012), convective systems were responsible for intense rainfall mainly located over a flat area of the eastern Po Valley, well upstream of the orography. Conversely, during IOP19 (4/5 November 2012), heavy precipitation affected only the Alpine area. In addition to IOP18 and IOP19, the present study analyses other heavy‐precipitation episodes that display similar characteristics and which occurred over NEI during the autumn of recent years. A high‐resolution (2 km grid spacing) non‐hydrostatic NWP model and available observations are used for this purpose. The two different observed precipitation patterns are explained in terms of interaction between the impinging flow and the Alps. Depending on the thermodynamic profile, convection can be triggered when the impinging flow is forced to rise over a pre‐existing cold‐air layer at the base of the orography. In this situation a persistent blocked‐flow condition and upstream convergence are responsible for heavy rain localized over the plain. Conversely, if convection does not develop, flow‐over conditions are established and heavy rain affects the Alps. Numerical parameters proposed in the literature are used to support the analysis. Finally, the role of evaporative cooling beneath the convective systems is evaluated. It turns out that the stationarity of the systems upstream of the Alps is mainly attributable to persistent blocked‐flow conditions, while convective outflow slightly modifies the location of precipitation.

This study analyzes the spatial distribution and temporal characteristics of cloud-to-ground lightnings (C2G) in the North East of Italy and the neighboring areas of Austria, Slovenia and Croatia. The dataset consists of about 6.5 millions C2G flash records, both positive and negative, observed between January 1995 and December 2011 by the "Centro Elettrotecnico Sperimentale Italiano-Sistema Italiano Rilevamento Fulmini'' (CESI/SIRF), part of the European Cooperation for Lightning Detection (EUCLID) Network. The results show that C2G lightnings concentrate in the foothill regions on the southern flank of the Eastern Alps with a maximum of discharge frequency of 10 lightnings per km2 per year. The number of C2G strokes varies with the period of the year: the most active period for lightning starts in April and lasts through November with the highest number of C2G strokes happening during the summer months of July and August, with maximum spatial density slightly moving from the mountain to the coastal area. The least frequency of C2G strokes is observed during wintertime. The mean diurnal C2G lightning activity for the whole domain shows a peak around 16:00–17:00 UTC and reaches a minimum around 07:00–09:00 UTC; the mean spatial distribution follows different patterns depending on the period of the day.

On 12 September 2012 a sequence of convective events hit the northeastern part of Italy and in particular the eastern part of Veneto and the plain of Friuli Venezia Giulia regions. During the day at least two events could be classified as supercells, the first one being also associated with a heavy hailfall. After a few hours, a third storm system, resembling a squall-line, although of limited dimensions, swept over the area.This event occurred during the first Special Observing Period (SOP1) of the HyMeX project as IOP2 (Intense Observing Period) and - also for this reason - many observations managed by different institutions were collected, including Doppler radar, extra-soundings, sodar and surface stations. Moreover, EUMETSAT was conducting its first experimental 2.5-minute rapid scan with the MSG-3 satellite, with data available from early morning until 0900 UTC of the IOP2 day.Several mesoscale models were run during the HyMeX SOP to support the field operations. A comparison between simulations of two high-resolution models (MOLOCH and WRF) is presented here and shows the capability in forecasting the intense convective activity in the area, although the exact temporal evolution of the systems was missed. Model simulations also provide useful insights concerning the mesoscale conditions conducive to the development of the convective systems.Finally, a diagnostic tool (Corfidi and Bunkers vectors) is applied using the model wind field, in order to infer further information on the temporal evolution of the convective cells. © 2014 Elsevier B.V.

The main object of this work is to study the lightning climatology in the Po Valley in Italy and how it varies in time (interannual, annual, weekly, and daily time scales) and space (sea coast, plains, and mountain areas) and how that is related to topographic characteristics and anthropogenic emissions. Cloud-to-ground (CG) lightning in the target area is analyzed for 18 yr of data (about 7 million records). It is found that the Julian Prealps of the Friuli Venezia Giulia region are one of the areas of maximum CG lightning activity across all of Europe. During spring lightning activity is more confined toward the mountainous regions, whereas during summer and even more during autumn the lightning activity involves also the coastal region and the Adriatic Sea. This is due to different triggering mechanisms acting in different topographic zones and during different periods of the year and times of the day. In analogy to previous studies of lightning done in the United States, a weekly cycle is also identified in the area of interest, showing that on Friday the probability of thunderstorms reaches its maximum. After conducting a parallel analysis with monitoring stations of atmospheric particulates (diameter ≤ 10 μm: PM10) and sounding-derived potential instability, the results presented herein seem to support the hypothesis that the weekly cycle in the thunderstorm activity may be due to anthropogenic emissions.

In this work the hailpad data collected during the April–September period of the years 1992–2009 by a network of approximately 360 stations on the plain of the Friuli Venezia Giulia region (northeast Italy) were analyzed. The frequency distribution of the hail cases is studied for the different years, for the yearday, and for the time of day, considering four 6-h-long periods of the day. Hail is found to be more frequent during the 1100–2300 UTC time interval and in the months of June and July even though during the 18 years analyzed there does not seem to be a defined trend in hail probability. The spatial distribution shows a maximum of probability along the foothills in particular in the northwest. In the middle of this area there is also the Udine–Campoformido radiosounding station, which performed four soundings per day. Each case (6-h-long period) is then associated with the 52 indices derived from the sounding launched at the beginning of that period. These sounding-derived indices are not all statistically independent, as found by looking at their correlation matrix and aggregating the most-correlated indices in three groups. A diagnostic bivariate analysis between each index and the hit hailpads in 6 h was done as a preliminary attempt to evaluate the utility of these indices for forecasting hail. It is found that some measures of instability (like updraft, hail diameter, and lifted index) seem to have more skill than the other indices when classifying the hail-event occurrence. When estimating the number of hit hailpads, the best correlation is obtained by the indices belonging to the “lifted index family.”

On March 26, 2001 a tornado was observed on the Friuli plain (Northeastern Italy), close to the foothills. The event took place in the afternoon, 15:45 UTC and it lasted for about 15 min. Fortunately no significant damages and injuries have been recorded since the tornado hit an uninhabited area with little vegetation and cultivation owing to the season. The whole event was observed and photographed by witnesses at a distance of about 1 km from the tornado outset to its end. Radar and mesonetwork data revealed the presence of a supercell mesocyclone having a radius of 4.5 ± 0.5 km that lasted for about half an hour and it was moving 30 ± 8° right to the average tropospheric flow; The event occurred in a synoptic situation dominated by a strong jet in the upper troposphere associated with a well-defined baroclinic zone (front). Mesoscale data revealed modest instability, but unusually high for the early spring period in the area. Vertical wind shear was very close to the 10 -2 s 1 that is significantly high for stormy days in Friuli. The surface conditions reveal that a thermal boundary was present that could have played an important role in the formation of the mesocyclone. The thermal boundary was the result of earlier storms' outflows and their interaction with the complex orography of the region. Comparison between horizontal relative vorticity parallel to the low level thermal boundary and the vertical relative vorticity of the mesocyclone suggests that such a boundary could have been a factor for the onset of the supercell. The lightning activity recorded during the event was characterized by a decrease of negative cloud-to-ground lightning (CG) frequency and an increase of positive (CG) lightning frequency during the observation of the event.

In the previous work, “Evaluating the sounding instability with the Lifted Parcel Theory” (hereafter ESI also published in this issue), we described a program which implements the Lifted Parcel Theory in three different ways. In this work, we build a climatology of the sounding-derived instability indices based on 5050 different soundings, made in Udine (WMO code 16044) from April to September 1995–2001. Every 6 h, we associate a sounding with the presence of cloud-to-ground lightning strikes and also with a continuous variable, CALCA6h, built using lightning strikes number, rain and wind gust, measured in the plain of our region. For each of the about 30 indices, we studied the skill score for forecasting the presence of thunderstorms and the linear cross-correlation for forecasting the thunderstorm “intensity”. We also introduce the use of some relatively new indices: the maximum buoyancy, the cloud precipitable water, the mean horizontal vapour flux and the standard deviation of the sounding vertical velocity. Finally, we discuss which indices and which of the three methods are the best in our region for forecasting convective events.

On the morning of June 4th 1999, a severe weather event took place in San Quirino, a small village of Friuli-Venezia Giulia in the northeast of Italy. This village is located near the piedmont of the Alps, 40 km west from Udine and 60 km north from Venice. Around 0900 UTC (1100 local time), a thunderstorm with an intense hail fall affected the area of San Quirino. A few minutes later (around 0920 UTC, source: a farmer), a funnel cloud from a cumulonimbus touched the ground, producing damages to houses, trees and sheds. The damaged area was quite narrow (about 300 m) and short (less than 10 km). No injuries to people were reported. In spite of the smallness of the area interested by the phenomenon, this storm is studied here starting from the synoptic scale, moving to the mesoscale and finishing with the storm scale, trying to underline its characteristics. These analyses, especially those coming from the Doppler radar images, bring us to the conclusion that the San Quirino episode was produced by a supercell storm.

The Special Observation Period (SOP1), part of the HyMeX campaign (Hydrological cycle in the Mediterranean Experiments, 5 September–6 November 2012), was dedicated to heavy precipitation events and flash floods in the western Mediterranean, and three Italian hydro-meteorological monitoring sites were identified: Liguria–Tuscany, northeastern Italy and central Italy. The extraordinary deployment of advanced instrumentation, including instrumented aircrafts, and the use of several different operational weather forecast models, including hydrological models and marine models, allowed an unprecedented monitoring and analysis of high-impact weather events around the Italian hydro-meteorological sites. This activity has seen strong collaboration between the Italian scientific and operational communities. In this paper an overview of the Italian organization during SOP1 is provided, and selected Intensive Observation Periods (IOPs) are described. A significant event for each Italian target area is chosen for this analysis: IOP2 (12–13 September 2012) in northeastern Italy, IOP13 (15–16 October 2012) in central Italy and IOP19 (3–5 November 2012) in Liguria and Tuscany. For each IOP the meteorological characteristics, together with special observations and weather forecasts, are analyzed with the aim of highlighting strengths and weaknesses of the forecast modeling systems, including the hydrological impacts. The usefulness of having different weather forecast operational chains characterized by different numerical weather prediction models and/or different model set up or initial conditions is finally shown for one of the events (IOP19).