Search

Atmospheric microbursts are low‐level meteorological events that can produce significant damage on the surface and pose a major risk to aircraft flying close to the ground. Studies and ad hoc numerical models have been developed to understand the origin and dynamics of the microburst; nevertheless, there are few researches of the phenomenon using global and mesoscale models. This is mainly due to the limitations in resolution, as microbursts normally span for less than 4 km and 20 min. In this paper, the Weather Research and Forecasting model is used at resolutions of 400 m and 3 min to test if it can properly capture the variables and dynamics of high‐reflectivity microbursts. Several microphysics and planetary boundary layer parametrizations are tested to find the best model configuration for the simulation of this kind of episodes. General conditions are evaluated by using thermodynamic diagrams. Surface and vertical wind speed, reflectivity, precipitation, and other variables for each simulated event are compared with observations, and the model's sensitivity to the variables is assessed. The dynamics and evolution of the microburst is evaluated using different plots of a chosen event. The results show that the model is able to reproduce high‐reflectivity microbursts in accordance with observations, although there is a tendency to underestimate the intensity of variables, most markedly on the wind vertical velocity. Regarding the microphysics schemes, the Morrison parametrization performs better than the WRF single‐moment 6‐class scheme. No major differences are found between the Mellor‐Yamada‐Janjic and the Mellor‐Yamada‐Nakanishi‐Niino planetary boundary layer parametrizations. Key Points: The Weather Research and Forecasting numerical model is able to reproduce high‐reflectivity microburstsThe characteristic variables of the microburst are properly simulated, although some intensities are lower than observationsDifferences are observed between different microphysics and planetary boundary layer parametrizations [ABSTRACT FROM AUTHOR]

Hailstorms are meteorological phenomena of great interest to the scientific community, owing to their socioeconomic impact, which is mainly on agricultural production. With its global coverage and high spatial and temporal resolution, satellite remote sensing can contribute to monitoring of such events through the development of appropriate techniques. This paper presents an extensive validation in the south of France of a hail detection tool (HDT) developed for the Middle Ebro Valley (MEV). The HDT is based on consecutive application of two filters, a convection mask (CM) and hail mask (HM), using spectral channels of the Meteosat Second Generation (MSG) satellite. The south of France is an ideal area for studying hailstorms, because there is a robust database of hail falls recorded by an extensive network of hailpads managed by the Association Nationale d'Etude et de Lutte contre les Fleáux Atmosphériques (ANELFA). The results show noticeably poorer performance of the HDT in France relative to that in the MEV, with probability of detection (POD) 60.4% and false alarm rate (FAR) 26.6%. For this reason, a new tool to suit the characteristics of hailstorms in France has been developed. The France Hail Detection Tool (FHDT) was developed using logistic regression from channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor of the MSG. The FHDT was validated, resulting in POD 69.3% and FAR 15.4%, thus improving hail detection in the study area as compared with the previous tool. The new tool was tested in a case study with satisfactory results, supporting its future practical application. [ABSTRACT FROM AUTHOR]

Abstract: The characterization of atmospheric conditions at different scales and their relationships to meteorological phenomena is a basic tool for improving the understanding and prediction of severe atmospheric events. Hailstorms are relatively common in southern Europe during summer, causing significant adverse impacts to property and infrastructure. This paper provides a spatiotemporal characterization of hail falls in southwestern France between 2000 and 2010, using the hail pad network operated there by the Association Nationale d'Etude et de Lutte contre les Fléaux Atmosphériques (ANELFA). This area is greatly affected by hailstorms. It was observed that the greatest incidence and severity of hail was in the central Pyrenees during May and July, with decreasing frequency and intensity toward the Atlantic coast. We selected 100 events in which severe hailstorms were reported, to study atmospheric parameters responsible for their occurrence. We performed mesoscale simulations with the WRF model, using parameterizations and fields reported in previous studies. By applying principal component analysis (PCA) and cluster analysis, we obtained three configurations to help establish relationships with the spatiotemporal incidence of hailstorms. The method and results obtained improve knowledge of the conditions favorable for hailstorms in southwestern France. This allows better hail prediction by relating atmospheric conditions with characteristics of hail precipitation on the ground. [Copyright &y& Elsevier]