CORRIGENDUM

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An EF3 Multivortex Tornado over the Ionian Region: Is It Time for a Dedicated Warning System over Italy?

Abstract The possibility offered by the Internet to share pictures of tornadoes, and the storm-report archiving in the European Storm Weather Database, have made it apparent that the occurrence of tornadoes over Europe has been underestimated. Together with weak waterspouts and tornadoes, large and intense vortices are occasionally observed. Among these, an EF3 multivortex tornado with a path width of some hundreds of meters affected southeastern Italy on 28 November 2012, causing one casualty and estimated damage of €60M to the largest steel plant in Europe. A tide gauge positioned near the location of tornado landfall and a vertical atmospheric profile available a few hours later near the affected region represent unique sources of information for these events in the Mediterranean. During its transit across the port of Taranto, a waterspout, which was to become the tornado, was observed to have induced a sea level rise of about 30 cm. The supercell responsible for the tornado developed from convective cells triggered by orographic uplift over the Apennines. The 0–1-km wind shear was exceptional in comparison with other Italian tornadoes, and was remarkable in comparison with U.S. events as well. Other indices for severe convection diagnosis also showed extremely high values. The occasional occurrence of events with similar or stronger intensities over Italy emphasizes the need for the Distributed National Weather Service—which will integrate Italian meteorological institutions under one agency and is currently under development—to devise a warning system dedicated to the monitoring and prediction of severe convective events

FURTHER RESULTS ON MOIST NEARLY NEUTRAL FLOW PAST A RIDGE

A systematic numerical study has been performed in the case of moist neutral flows past a twodimensional ridge. The experiments considered here describe the effect of the Coriolis force and of wider mountains on the flow features

Cambiamento climatico e protezione delle coste

Le aree costiere sono particolarmente sensibili al cambiamento climatico perché, oltre alle conseguenze legate alle variazioni di temperatura e precipitazioni, subiscono direttamente anche quelle dovute agli aumenti del livello medio del mare e dell'altezza delle onde. Le proiezioni dei modelli climatici prevedono che, entro la fine del XXI secolo, il livello medio del Mediterraneo potrebbe essere più alto di oltre mezzo metro rispetto all'attuale. Un altro effetto del riscaldamento dell'atmosfera terrestre nel Mediterraneo, ossia l'aumento dell'intensità e/o della frequenza di fenomeni meteorologici estremi, come i cicloni con caratteristiche tropicali (noti come medicane), potrebbe inoltre accelerare alcuni processi di erosione costiera. Tutto ciò comporterebbe notevoli impatti ambientali ed economici. Verranno qui illustrati alcuni esempi e discusse le conseguenze sulle opere e sulle attività dell'uomo

Ensemble using different Planetary Boundary Layer schemes in WRF model for wind speed and direction prediction over Apulia region

Abstract. The Weather Research and Forecasting mesoscale model (WRF) was used to simulate hourly 10 m wind speed and direction over the city of Taranto, Apulia region (south-eastern Italy). This area is characterized by a large industrial complex including the largest European steel plant and is subject to a Regional Air Quality Recovery Plan. This plan constrains industries in the area to reduce by 10 % the mean daily emissions by diffuse and point sources during specific meteorological conditions named wind days. According to the Recovery Plan, the Regional Environmental Agency ARPA-PUGLIA is responsible for forecasting these specific meteorological conditions with 72 h in advance and possibly issue the early warning. In particular, an accurate wind simulation is required. Unfortunately, numerical weather prediction models suffer from errors, especially for what concerns near-surface fields. These errors depend primarily on uncertainties in the initial and boundary conditions provided by global models and secondly on the model formulation, in particular the physical parametrizations used to represent processes such as turbulence, radiation exchange, cumulus and microphysics. In our work, we tried to compensate for the latter limitation by using different Planetary Boundary Layer (PBL) parameterization schemes. Five combinations of PBL and Surface Layer (SL) schemes were considered. Simulations are implemented in a real-time configuration since our intention is to analyze the same configuration implemented by ARPA-PUGLIA for operational runs; the validation is focused over a time range extending from 49 to 72 h with hourly time resolution. The assessment of the performance was computed by comparing the WRF model output with ground data measured at a weather monitoring station in Taranto, near the steel plant. After the analysis of the simulations performed with different PBL schemes, both simple (e.g. average) and more complex post-processing methods (e.g. weighted average, linear and nonlinear regression, and artificial neural network) are adopted to improve the performances with respect to the output of each single setup. The neural network approach comes out as the most promising method

Dynamical and statistical downscaling of precipitation and temperature in a Mediterranean area

In this paper we present and discuss a comparison between statistical and regional climate modeling techniques for downscaling GCM prediction. The comparison is carried out over the Capitanata region, an area of agricultural interest in south-eastern Italy, for current (1961-1990) and future (2071-2100) climate. The statistical model is based on Canonical Correlation Analysis (CCA), associated with a data pre-filtering obtained by a Principal Component Analysis (PCA), whereas the Regional Climate Model REGCM3 was used for dynamical downscaling. Downscaling techniques were applied to estimate rainfall, maximum and minimum temperatures and average number of consecutive wet and dry days. Both methods have comparable skills in estimating stations data. They show good results for spring, the most important season for agriculture. Both statistical and dynamical models well reproduce the statistical properties of precipitation, the crucial variable for the growth of crops

Bayesian Exploration of Multivariate Orographic Precipitation Sensitivity for Moist Stable and Neutral Flows

Abstract Recent idealized studies examined the sensitivity of topographically forced rain and snowfall to changes in mountain geometry and upwind sounding in moist stable and neutral environments. These studies were restricted by necessity to small ensembles of carefully chosen simulations. Research presented here extends earlier studies by utilizing a Bayesian Markov chain Monte Carlo (MCMC) algorithm to create a large ensemble of simulations, all of which produce precipitation concentrated on the upwind slope of an idealized Gaussian bell-shaped mountain. MCMC-based probabilistic analysis yields information about the combinations of sounding and mountain geometry favorable for upslope rain, as well as the sensitivity of orographic precipitation to changes in mountain geometry and upwind sounding. Exploration of the multivariate sensitivity of rainfall to changes in parameters also reveals a nonunique solution: multiple combinations of flow, topography, and environment produce similar surface rainfall amount and distribution. Finally, the results also divulge that the nonunique solutions have different sensitivity profiles, and that changes in observation uncertainty also alter model sensitivity to input parameters

Meteorological drought analysis using copula theory and drought indicators under climate change scenarios (RCP)

AbstractThe study was carried out to assess meteorological drought on the basis of the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) evaluated in future climate scenarios. Yazd province, located in an arid region in the centre of Iran, was chosen for analysis. The study area has just one synoptic station with a long‐term record (56 years). The impact of climate change on future drought was examined by using the CanESM2 of the CMIP5 model under three scenarios, that is, representative concentration pathways RCP2.6, RCP4.5 and RCP8.5. Given that a drought is defined by several dependent variables, the evaluation of this phenomenon should be based on a multivariate analysis. For this purpose, two main characteristics of drought (severity and duration) were extracted by run theory in a past (1961–2016) and future (2017–2100) period based on the SPI and SPEI, and studied using copula theory. Three functions, that is, Frank, Gaussian and Gumbel copula, were selected to fit with drought severity and duration. The results of the bivariate analysis using copula showed that, according to both indicators, the study area will experience droughts with greater severity and duration in future as compared with the historical period, and the drought represented by the SPEI is more severe than that associated with the SPI. Also, drought simulated using the RCP8.5 scenario was more severe than when using the other two scenarios. Finally, droughts with a longer return period will become more frequent in future

Investigation With Large-eddy Simulation of the Sea Breeze Regimes

Neste trabalho, investigam-se as interações entre a brisa marítima e a turbulência sobre a Terra empregando uma simulação dos grandes turbilhões (LES). Os resultados mostram que o modelo LES é capaz de similar um regime de brisa Mar-Terra-Mar

Analysis of waterspout environmental conditions and of parent-storm behaviour based on satellite data over the southern Aegean Sea of Greece

ABSTRACTA frequent area of waterspout formation is identified over the southern Aegean Sea. The objectives of this study are threefold: (1) to investigate the temporal evolution of Cloud Top Temperature (CTT) of cloud lines (waterspouts' parent clouds) that triggered the formation of single or multiple waterspout events, by using Meteorological Satellite Second Generation infrared satellite data, cloud base height data and weather observations from the closest Hellenic National Meteorological Service meteorological station; (2) to synthesize a detailed climatology of the thermodynamic environment during waterspout activity and (3) to explore the sea‐surface temperature (SST) seasonal distribution and its possible relationships with the temperature of the middle and lower troposphere during waterspout days over the southern Aegean Sea.It was found that the CTT of waterspout parent clouds decreases close to waterspout formation time, which is consistent with growing clouds. The Severe Weather Threat Index (SWEAT), the Bulk Richardson Number (BRN) and the Convective Potential Available Energy during the autumn season were consistent with a shallow‐convection environment. The instability parameter ΔT1000 (difference in the air temperature between 1000 hPa and that at other pressure levels) exhibited a symmetric distribution about the median during both seasons and at all levels. More than 75% of autumn waterspout activity over the southern Aegean Sea developed with SST values varying from 22 to 24.5 °C, while the instability parameter ΔTSST (the temperature difference between the SST and the temperature at various pressure levels) exhibited a symmetrical distribution about the median for both seasons and for all pressure levels, consistent with the ΔT1000 seasonal distribution. A statistical analysis showed that the means of SWEAT, BRN, convective inhibition, SST, ΔTSST and ΔT1000 from air temperature at 700 hPa differ statistically significant (p < 0.001) between waterspout and non‐waterspout days in autumn, over the southern Aegean Sea, during 2005–2012