An improved version of the exponential cell (EXCELL) rain attenuation model is presented here. Analogously to the original one, it predicts attenuation through a cellular representation of precipitation, but, in addition, is able to discriminate between stratiform and convective rain by means of an embedded algorithm. Accordingly, two separate physical rain heights, derived from the ERA-15 database, are used to calculate stratiform and convective rain attenuation and, when considering stratiform precipitation, the melting layer contribution to attenuation is added. Eventually, the predicted cumulative distribution function (CDF) of excess attenuation is the combination of the contributions due to stratiform and convective precipitation types. Some input parameters of the prediction model, such as those defining the melting layer process or the rain plateau embedding rain cells, can be modified in order to account for the local meteorological characteristics.

MultiEXCELL, a new rainfall model oriented to the analysis of radio propagation impairments which was developed on the basis of a comprehensive rain field database collected by the weather radar sited in Spino d'Adda (Italy), is presented. Single rain cells are modeled by an analytical exponential profile which best represents real single-peaked rain structures. The rain cells' probability of occurrence is analytically derived from the local rainfall statistics. The spatial features of the rain field at mid- and large-scale are investigated through their natural aggregative process. The clusters (aggregates) of cells are studied in terms of distance between individual cells, number of cells per aggregate, and distance between aggregates. Finally, the fractional area covered by rain, which the rainfall spatial correlation strongly depends on, is derived from radar data through the comparison with the same quantity provided by global long-term numerical weather products. The MultiEXCELL procedure for the generation of spatially correlated synthetic rain fields is duly presented and the model's accurateness is preliminary assessed against the available radar dataset. Although MultiEXCELL is mainly oriented to propagation-related applications, its cellular approach may reveal useful also in hydrology, for the prediction/management of water resources, and in meteorology, for the nowcasting of the temporal evolution of rain structures.

The Mediterranean region is frequently struck by severe rainfall events causing numerous casualties and several million euros of damages every year. Thus, improving the forecast accuracy is a fundamental goal to limit social and economic damages. Numerical Weather Prediction (NWP) models are currently able to produce forecasts at the km scale grid spacing but unreliable surface information and a poor knowledge of the initial state of the atmosphere may produce inaccurate simulations of weather phenomena. The STEAM (SaTellite Earth observation for Atmospheric Modelling) project aims to investigate whether Sentinel satellites constellation weather observation data, in combination with Global Navigation Satellite System (GNSS) observations, can be used to better understand and predict with a higher spatio-temporal resolution the atmospheric phenomena resulting in severe weather events. Two heavy rainfall events that occurred in Italy in the autumn of 2017 are studied—a localized and short-lived event and a long-lived one. By assimilating a wide range of Sentinel and GNSS observations in a state-of-the-art NWP model, it is found that the forecasts benefit the most when the model is provided with information on the wind field and/or the water vapor content.

This letter investigates rain attenuation in Kuala Lumpur, Malaysia, by exploiting local drop size distribution (DSD) measurements. Coefficients for the well-established power-law model relating rain rate and specific attenuation are derived for frequencies in the Ku-, Ka-, and Q/V-bands based on three years of disdrometer data. We analyze the diurnal variation of rainfall rate for four time intervals and, moreover, we present statistics of rain attenuation for slant-path Earth-space links estimated by means of a new model (Stratiform-Convective SST) that combines the advantages of the Dual-Layer Synthetic Storm Technique (SST) and the SC EXCELL model. The predicted statistics are in good agreement with those obtained from beacon measurements (MEASAT-1 satellite at 12 GHz). Finally, the diurnal variation of the slant-path rain attenuation is presented to provide system operators and radio communication engineers with useful information on the quality of service (QoS) that can be achieved during a typical day on an Earth-space link.

The results from 1 year of data collected during an electromagnetic wave propagation experiment at ${E}$ -band are presented. The research activity originates from the collaboration between Politecnico di Milano, Milan, Italy, and the Huawei European Microwave Centre in Milan, which installed short (325 m) terrestrial links operating at 73 and 83 GHz, connecting two buildings in the university main campus. The received power data are processed, using a novel approach, to identify rain events and to remove the wet antenna effect, with the aim of accurately quantifying the fade induced by precipitation, $A_{R}$ . Moreover, $A_{R}$ is estimated by taking advantage of the ancillary data collected by the laser-based disdrometer collocated with the link transceivers. The results definitely point out the higher prediction accuracy achieved by exploiting the information on the rain drop size. A full year of data are used as reference to test the accuracy of the statistical prediction model for terrestrial links currently recommended by the ITU-R, which reveals a large overestimation. Finally, alternative models providing a higher accuracy are proposed and their accuracy assessed.