Statistical analysis and modelling of weather radar beam propagation conditions in the Po Valley (Italy)

Ground clutter caused by anomalous propagation (anaprop) can affect seriously radar rain rate estimates, particularly in fully automatic radar processing systems, and, if not filtered, can produce frequent false alarms. A statistical study of anomalous propagation detected from two operational C-band radars in the northern Italian region of Emilia Romagna is discussed, paying particular attention to its diurnal and seasonal variability. The analysis shows a high incidence of anaprop in summer, mainly in the morning and evening, due to the humid and hot summer climate of the Po Valley, particularly in the coastal zone. Thereafter, a comparison between different techniques and datasets to retrieve the vertical profile of the refractive index gradient in the boundary layer is also presented. In particular, their capability to detect anomalous propagation conditions is compared. Furthermore, beam path trajectories are simulated using a multilayer ray-tracing model and the influence of the propagation conditions on the beam trajectory and shape is examined. High resolution radiosounding data are identified as the best available dataset to reproduce accurately the local propagation conditions, while lower resolution standard TEMP data suffers from interpolation degradation and Numerical Weather Prediction model data (Lokal Model) are able to retrieve a tendency to superrefraction but not to detect ducting conditions. Observing the ray tracing of the centre, lower and upper limits of the radar antenna 3-dB half-power main beam lobe it is concluded that ducting layers produce a change in the measured volume and in the power distribution that can lead to an additional error in the reflectivity estimate and, subsequently, in the estimated rainfall rate

Effects of propagation conditions on radar beam-ground interaction: impact on data quality

International audienceA large part of the research in the radar meteorology is devoted to the evaluation of the radar data quality and to the radar data processing. Even when, a set of absolute quality indexes can be produced (like as ground clutter presence, beam blockage rate, distance from radar, etc.), the final product quality has to be determined as a function of the task and of all the processing steps. In this paper the emphasis lies on the estimate of the rainfall at the ground level taking extra care for the correction for ground clutter and beam blockage, that are two main problems affecting radar reflectivity data in complex orography. In this work a combined algorithm is presented that avoids and/or corrects for these two effects. To achieve this existing methods are modified and integrated with the analysis of radar signal propagation in different atmospheric conditions. The atmospheric refractivity profile is retrieved from the nearest in space and time radiosounding. This measured profile is then used to define the `dynamic map' used as a declutter base-field. Then beam blockage correction is applied to the data at the scan elevations computed from this map. Two case studies are used to illustrate the proposed algorithm. One is a summer event with anomalous propagation conditions and the other one is a winter event. The new algorithm is compared to a previous method of clutter removal based only on static maps of clear air and vertical reflectivity continuity test. The improvement in rain estimate is evaluated applying statistical analysis and using rain gauges data. The better scores are related mostly to the ``optimum" choice of the elevation maps, introduced by the more accurate description of the signal propagation. Finally, a data quality indicator is introduced as an output of this scheme. This indicator has been obtained from the general scheme, which takes into account all radar data processing steps

Clutter and rainfall discrimination by means of doppler-polarimetric measurements and vertical reflectivity profile analysis

International audienceThe estimation of rainfall rate and other parameters from radar scattering volume is heavily affected by the presence of intense sea and ground clutter and echoes which appears in anomalous propagation condition. To deal with these non meteorological echoes we present a new clutter removal algorithm which combines the results of previous works. The algorithm fully exploits both the Doppler and polarimetric capabilities of the radar used and the analysis of vertical reflectivity profile in order to achieve the better identification of the meteorological and non-meteorological targets. The algorithm has been applied to the C-band radar of Monte Settepani (Savona, Italy), which runs in a high-topography environment. Preliminary results are presented

Screening of dietary ingredients against the honey bee parasite Nosema ceranae

Nosema ceranae is a major pathogen in the beekeeping sector, responsible for nosemosis. This disease is hard to manage since its symptomatology is masked until a strong collapse of the colony population occurs. Conversely, no medicaments are available in the market to counteract nosemosis, and only a few feed additives, with claimed antifungal action, are available. New solutions are strongly required, especially based on natural methods alternative to veterinary drugs that might develop resistance or strongly pollute honey bees and the environment. This study aims at investigating the nosemosis antiparasitic potential of some plant extracts, microbial fermentation products, organic acids, food chain waste products, bacteriocins, and fungi. Honey bees were singularly infected with 5 × 104 freshly prepared N. ceranae spores, reared in cages and fed ad libitum with sugar syrup solution containing the active ingredient. N. ceranae in the gut of honey bees was estimated using qPCR. The results showed that some of the ingredients administered, such as acetic acid at high concentration, p-coumaric acid, and Saccharomyces sp. strain KIA1, were effective in the control of nosemosis. On the other hand, wine acetic acid strongly increased the N. ceranae amount. This study investigates the possibility of using compounds such as organic acids or biological agents including those at the base of the circular economy, i.e., wine waste production, in order to improve honeybee health

Reflectivity and velocity radar data assimilation for two flash flood events in central Italy: A comparison between 3D and 4D variational methods

The aim of this study is to provide an evaluation of the impact of two largely used data assimilation techniques, namely three- and four-dimensional variational data assimilation systems (3D-Var and 4D-Var), on the forecasting of heavy precipitation events using the Weather Research and Forecasting (WRF) model. For this purpose, two flash flood events in central Italy are analysed. The first occurred on September 14, 2012 during an Intensive Observation Period of the Hydrological cycle in the Mediterranean experiment (HyMeX) campaign, while the other occurred on May 3, 2018. Radial velocity and reflectivity acquired by C-band weather radars at Mt. Midia (central Italy) and San Pietro Capofiume (northern Italy), as well as conventional observations (SYNOP and TEMP), are assimilated into the WRF model to simulate these damaging flash flood events. In order to evaluate the impact of the 3D-Var and 4D-Var assimilation systems on the estimation of short-term quantitative precipitation forecasts, several experiments are carried out using conventional observations with and without radar data. Rainfall evaluation is performed by means of point-by-point and filtering methodologies. The results point to a positive impact of the 4D-Var technique compared to results without assimilation and with 3D-Var experiments. More specifically, the 4D-Var system produces an increase of up to 22% in terms of the Fractions Skill Score compared to 3D-Var for the first flash flood event, while an increase of about 5% is achieved for the second event. The use of a warm start initialization results in a considerable reduction in the spin-up time and a significant improvement in the rainfall forecast, suggesting that the initial precipitation spin-up problem still occurs when using 4D-Var

Clutter and rainfall discrimination by means of doppler-polarimetric measurements and vertical reflectivity profile analysis

The estimation of rainfall rate and other parameters from radar scattering volume is heavily affected by the presence of intense sea and ground clutter and echoes which appears in anomalous propagation condition. To deal with these non meteorological echoes we present a new clutter removal algorithm which combines the results of previous works. The algorithm fully exploits both the Doppler and polarimetric capabilities of the radar used and the analysis of vertical reflectivity profile in order to achieve the better identification of the meteorological and non-meteorological targets. The algorithm has been applied to the C-band radar of Monte Settepani (Savona, Italy), which runs in a high-topography environment. Preliminary results are presented