By 31 December 2018, 39 537 quality-controlled reports of large hail had been submitted to the European Severe Weather Database (ESWD) by volunteers and ESSL. This dataset and the NatCatSERVICE Database of Munich RE jointly allowed us to study the hail hazard and its impacts across Europe over a period spanning multiple decades. We present a spatiotemporal climatology of the ESWD reports, diurnal and annual cycles of large hail, and indicate where and how they may be affected by reporting biases across Europe. We also discuss which hailstorms caused the most injuries and present the only case with hail fatalities in recent times. Additionally, we address our findings on the relation between hail size to the type of impacts that were reported. For instance, the probability of reported hail damage to roofs, windows, and vehicles strongly increases as hail size exceeds 5 cm, while damage to crops, trees, and greenhouses is typically reported with hailstone diameters of 2–3 cm. Injuries to humans are usually reported with hail 4 cm in diameter and larger, and number of injuries increases with increasing hail size. Using the NatCatSERVICE data, we studied economic losses associated with hailstorms occurring in central Europe and looked for long-term changes. The trend in hail losses and the annual number of hail loss days since 1990 to 2018 are compared to that of meteorological conditions favorable for large hail as identified by ESSL’s Additive Regression Convective Hazards model. Both hail loss days and favorable environments show an upward trend, in particular since 2000.

Atmospheric aerosols play a crucial role in the Earth's system, but their role is not completely understood, partly because of the large variability in their properties resulting from a large number of possible aerosol sources. Recently developed lidar-based techniques were able to retrieve the height distributions of optical and microphysical properties of fine-mode and coarse-mode particles, providing the types of the aerosols. One such technique is based on artificial neural networks (ANNs). In this article, a Neural Network Aerosol Typing Algorithm Based on Lidar Data (NATALI) was developed to estimate the most probable aerosol type from a set of multispectral lidar data. The algorithm was adjusted to run on the EARLINET 3β + 2α( + 1δ) profiles. The NATALI algorithm is based on the ability of specialized ANNs to resolve the overlapping values of the intensive optical parameters, calculated for each identified layer in the multiwavelength Raman lidar profiles. The ANNs were trained using synthetic data, for which a new aerosol model was developed. Two parallel typing schemes were implemented in order to accommodate data sets containing (or not) the measured linear particle depolarization ratios (LPDRs): (a) identification of 14 aerosol mixtures (high-resolution typing) if the LPDR is available in the input data files, and (b) identification of five predominant aerosol types (low-resolution typing) if the LPDR is not provided. For each scheme, three ANNs were run simultaneously, and a voting procedure selects the most probable aerosol type. The whole algorithm has been integrated into a Python application. The limitation of NATALI is that the results are strongly dependent on the input data, and thus the outputs should be understood accordingly. Additional applications of NATALI are feasible, e.g. testing the quality of the optical data and identifying incorrect calibration or insufficient cloud screening. Blind tests on EARLINET data samples showed the capability of NATALI to retrieve the aerosol type from a large variety of data, with different levels of quality and physical content.

The European Severe Storms Laboratory (ESSL) was founded in 2006 to advance the science and forecasting of severe convective storms in Europe. ESSL was a grassroots effort of individual scientists from various European countries. The purpose of this article is to describe the 10-yr history of ESSL and present a sampling of its successful activities. Specifically, ESSL developed and manages the only multinational database of severe weather reports in Europe: the European Severe Weather Database (ESWD). Despite efforts to eliminate biases, the ESWD still suffers from spatial inhomogeneities in data collection, which motivates ESSL’s research into modeling climatologies by combining ESWD data with reanalysis data. ESSL also established its ESSL Testbed to evaluate developmental forecast products and to provide training to forecasters. The testbed is organized in close collaboration with several of Europe’s national weather services. In addition, ESSL serves a central role among the European scientific and forecast communities for convective storms, specifically through its training activities and the series of European Conferences on Severe Storms. Finally, ESSL conducts wind and tornado damage assessments, highlighted by its recent survey of a violent tornado in northern Italy.

The social and economic impact of tornadoes in Europe is analyzed using tornado reports from the European Severe Weather Database between 1950 and 2015. Despite what is often assumed by the general public and even by meteorologists and researchers, tornadoes do occur in Europe and they are associated with injuries, fatalities, and damages, although their reported frequencies and intensities are lower compared with the United States. Currently, the threat of tornadoes to Europe is underestimated. Few European meteorological services have developed and maintained tornado databases and even fewer have issued tornado warnings. This article summarizes our current understanding of the tornado threat to Europe by showing the changes in tornado injuries and fatalities since the 1950s and by estimating for the first time the damages associated with European tornadoes. To increase awareness of tornadoes and their threat to Europe, we propose a strategy that includes 1) collaboration between meteorological services, researchers, and the general public toward a pan-European database; 2) development of national forecasting and warning systems and of pan-European convective outlooks; and 3) development by decision-makers and emergency managers of policies and strategies that include tornadoes.

A synthesis of tornado observations across Europe between 1800 and 2014 is used to produce a pan-European climatology. Based on regional tornado-occurrence datasets and articles published in peer-reviewed journals, the evolution and the major contributions to tornado databases for 30 European countries were analyzed. Between 1800 and 2014, 9563 tornadoes were reported in Europe with an increase from 8 tornadoes per year between 1800 and 1850 to 242 tornadoes per year between 2000 and 2014. The majority of the reports came from northern, western, and southern Europe, and to a lesser extent from eastern Europe where tornado databases were developed after the 1990s. Tornadoes occur throughout the year with a maximum in June–August for most of Europe and in August–November for southern Europe. Tornadoes occur more frequently between 1300 and 1500 UTC over most of Europe and between 0900 and 1100 UTC over southern Europe. Where intensity was known, 74.7% of tornadoes were classified as F0 and F1, 24.5% as F2 and F3, and 0.8% as F4 and F5. Comparing this intensity distribution over Europe with the intensity distribution for tornadoes in the United States shows that tornadoes over western and eastern Europe are more likely to be supercellular tornadoes and those over northern and southern Europe are likely to also include nonsupercellular tornadoes.