During severe thunderstorms, cold outflows can eject pollen and dust particles from the surface, releasing allergens and causing thunderstorm asthma epidemics in sensitive populations. We report the first case in Israel that occurred on 25 October 2015. The emergency room presentation records from three hospitals in central Israel showed a clear increase in patients with respiratory complaints immediately after the passage of a massive super-cell thunderstorm in the area.

This study shows the possibility to improve the weather forecast at the very short range (0–3 h) using lightning and/or radar reflectivity observations. We consider two challenging events that occurred over Italy, named Serrano and Livorno, characterized by moderate and exceptional rainfall, respectively. The improvement given to the forecast by using the lightning and/or radar reflectivity observations is considerable. The best performance is obtained when using both data.

The estimation of precipitable water vapour (W) content is of great interest in both meteorological and climatological studies. Sun photometers allowed the development of W automatic estimations with high temporal resolution. A new methodology, based on the hypothesis that the calibration parameters characterizing the atmospheric transmittance are dependent on vertical profiles of temperature, air pressure and moisture typical of each measurement site, has been presented providing good results.

This study investigates the impact of using lightning data on the precipitation forecast at different forecast ranges (3–24 h). Twenty case studies, occurred over Italy in fall 2012, are selected to show the impact. Results show the important and positive impact of using lightning data to improve the precipitation forecast. The time range, however, is very important because the performance decreases steadily and substantially with forecasting time.

In this paper we evaluate the performance of two estimates of the global horizontal irradiance (GHI), one derived from the Meteosat Second Generation and one from a meteorological model (Regional Atmospheric Modeling System) forecast. The focus area is Italy, and the performance is evaluated for 12 pyranometers spanning a range of climate conditions, from Mediterranean maritime to Alpine.

The motivation of this study is to use lightning observations to improve the precipitation forecast at the short range (3 h). For this purpose 20 case studies, occurring in fall 2012, were analyzed using a meteorological model, whose set-up is applicable in real-time weather forecasting. Lightning observations were provided by the LINET network. Results show a systematic improvement of the 3 h precipitation forecast when lightning observations are used.

The cloud radar on board the NASA CloudSat mission provides information on the vertical structure of the cloud that, in the present study, is matched to ground-based measurements of lightning occurrences. The aim of this research was to study the relationship between the ice content of the cloud and its capability to produce lightning. Results show the importance of high ice content, especially close to the cloud top, for producing lightning.

The objective of this paper is to describe the development and evaluate the performance of a totally new version of the Passive microwave Neural network Precipitation Retrieval (PNPR v2), an algorithm based on a neural network approach, designed to retrieve the instantaneous surface precipitation rate using the cross-track ATMS radiometer measurements.

This study examines various microphysical properties of liquid and solid hydrometeors to investigate their relationship with lightning activity. Measurements were collected from the Polar 55C dual-polarization radar, a 2-DVD, and LINET. From the analysis of three significant case studies, linear relations between the total mass of graupel and the number of strokes were found. Results point out the key role of ice mass in determining the electrical charging of convective clouds.

The CCA algorithm is applicable to any modern passive microwave radiometer on board polar orbiting satellites; it has been developed using a data set of co-located SSMIS and TRMM-PR measurements and AMSU-MHS and TRMM-PR measurements. The algorithm shows a small rate of false alarms and superior detection capability and can efficiently detect (POD between 0.55 and 0.71) minimum rain rate varying from 0.14 mm/h (AMSU over ocean) to 0.41 (SSMIS over coast).

The aim of this work is to show that the CloudSat Cloud Profiling Radar (CPR) can be a valuable source of snowfall rate data in Antarctica that can be used at different temporal scales. Two years of CloudSat data over Antarctica are analyzed and two different approaches for precipitation estimates are considered. The results show that CPR can provide valuable support to the sparse network of ground-based instruments both for numerical model validation and climatological studies.

This paper shows the implementation of a simple model for simulating lightning into the RAMS model. The methodology is applied to six case studies that occurred in central Italy and the results are verified against LINET observations. Advantages and weaknesses of the methodology are discussed.