Intense precipitation phenomena occurring over the Tyrrhenian area between Tuscany, Corse Sardinia, and Liguria very
often cause floods with considerable socio-economic damages. The need of monitoring such events has led to the
implementation of an observing weather radar network: it firstly started with an S-band radar in Corse, three C-band
radars in Liguria, Tuscany and Sardinia. Recently, the implementation of an X–band network of three radars in Tuscany
and two further C-band radars in Sardinia completed the network. This work shows how this network can be used for the
characterization of weather events, following their development and dynamics and providing some information about
their possible evolution. Furthermore, the use of meteorological satellites observations can upscale the area of interest to
the mesoscale level and provide an enlarged temporal overview. For instance, the Meteosat Second Generation satellites
provide useful information about the air mass distribution, convective phenomena occurrence and microphysics in the
observed scene, by combining different spectral channels. Finally, ground based observations are meaningful for
assessing the observing capabilities of other instruments and for characterizing the effects on soil surface. For some
selected case studies, the different observing instruments were compared and a methodology to integrate them
synergically is presented and tested. Weather radars correctly detect the rainfall systems and their motion in all the case
studies. Clearly, the higher spatial resolution of X-band radars allows detecting the different precipitation areas with
great spatial details, while C- and S-band radars can detect phenomena at higher distances. Satellites images have lower
spatial resolutions but especially thanks to the RSS (Rapid Scan Service) they can help to detect the growing or
dissipating stage of the whole phenomena. Moreover the ground-based network confirms its relevance in improving the
identification of the precipitation intensity and in reducing the number of false alarms.
The real-time measurement of rainfall is a primary information source for many purposes, such as weather forecasting, flood risk assessment, and landslide prediction and prevention. In this perspective, remote sensing techniques to monitor rainfall fields by means of radar measurements are very useful. In this work, a technique is proposed for the estimation of cumulative rainfall fields averaged over a large area, applied on the Tuscany region using the Italian weather radar network. In order to assess the accuracy of radar-based rainfall estimates, they are compared with coincident spatial rain gauge measurements. Observations are compared with average rainfall over areas as large as a few tens of kilometers. An ordinary block kriging method is applied for rain gauge data spatialization. The comparison between the two types of estimates is used for recalibrating the radar measurements. As a main result, this paper proposes a recalibrated relationship for retrieving precipitation from radar data. The accuracy of the estimate increases when considering larger areas: an area of 900 km2 has a standard deviation of less than few millimeters. This is of interest in particular for extending recalibrated radar relationships over areas where rain gauges are not available. Many applications could benefit from it, from nowcasting for civil protection activities, to hydrogeological risk mitigation or agriculture.
In this work we propose a technique for 15-minutes cumulative rainfall mapping, applied over Tuscany, using Italian weather radar networks together with the regional rain gauge network. In order to assess the accuracy of the radar-based rainfall estimates, we have compared them with spatial coincident rain gauge measurements. Precipitation at ground is our target observable: rain gauge measurements of such parameter have a so small error that we consider it negligible (especially if compared from what retrievable from radars). In order to make comparable the observations given from these two types of sensors, we have collected cumulative rainfall over areas a few tens of kilometres wide. The method used to spatialise rain gauges data has been the Ordinary Block Kriging. In this case the comparison results have shown a good correlation between the cumulative rainfall obtained from the rain gauges and those obtained by the radar measurements. Such results are encouraging in the perspective of using the radar observations for near real time cumulative rainfall nowcasting purposes. In addition the joint use of satellite instruments as SEVIRI sensors on board of MSG-3 satellite can add relevant information on the nature, spatial distribution and temporal evolution of cloudiness over the area under study. For this issue we will analyse several MSG-3 channel images, which are related to cloud physical characteristics or ground features in case of clear sky.
A method is presented for integrating the information available in a limited area (corresponding to Tuscany in Italy) coming from satellite sensors, point measurement stations and ground-based radars. The objective is the exploitation of the complementary information provided by the variety of methods and instruments nowadays existing for measuring precipitation or precipitation-related parameters, in order to upgrade the capability of reconstructing weather phenomena of main interest. Ground- and satellite-based measurements, working locally or remotely, are jointly analyzed to evaluate how heterogeneous data can amplify the effectiveness of the measurements, when synergically analyzed, and this holds also when some of the available instruments essentially give just qualitative information. A way to synthesize the different information provided by various instruments is presented, assessing the quality of all the available observations. Namely, steps are described for the achievement of a mosaic of qualitative weather radars, and it is shown how the joint analysis of satellite, rain gauge and lightning observations can support a correct interpretation of precipitation phenomena. Finally, a logical scheme for data integration is presented and discussed.
In this paper we present a method of optical characterization of solar concentrators based on the use of a laser beam.
The method, even though constrained by lengthy measurements, gives nevertheless interesting information on local
mirror surface defects or manufacturing defects, like internal wall shape inaccuracies. It was applied to 3D-CPC-like
concentrators and the measurements were supported by optical simulations with commercial codes. The method,
simple to apply, requires just a laser to scan the CPC input aperture following a matrix-like path, at a controlled
orientation of the beam. Maps of optical efficiency as function of the laser beam incidence angle are obtained by
matching the CPC exit aperture with a photodetector with an efficient light trapping. The integration of each map gives
the CPC efficiency resolved in angle of incidence, so curves of optical transmission (efficiency) as function of
incidence angle can be drawn and the acceptance angle measured. The analysis of the single maps allows to obtain
interesting information on light collection by the different regions of CPC input area. It reveals, moreover, how the
efficiency of light collection depends on several factors like surface reflectivity, number of reflections of the single
beam, local angle of incidence, local surface defects, and so on. By comparing the theoretical analysis with the
experimental results, it is possible to emphasize the effects directly related to manufacturing defects.
The optical characterization of a CPC concentrator is typically performed by using a solar simulator producing a
collimated light beam impinging on the input aperture and characterized by a solar divergence (± 0.27°). The optical
efficiency is evaluated by measuring the flux collected at the exit aperture of the concentrator, as function of incidence
angle of the beam with respect to the optical axis, from which the acceptance angle can be derived.
In this paper we present an alternative approach, based on the inverse illumination of the concentrator. In
accordance with this method, a Lambertian light source replaces the receiver at the exit aperture, and the light
emerging backwards at the input aperture is analyzed in terms of radiant intensity as function of the angular
orientation. The method has been applied by using a laser to illuminate a Lambertian diffuser and a CCD to record the
irradiance map produced on a screen moved in front of the CPC.
Optical simulations show that, when the entire surface of the diffuser is illuminated, the "inverse" method allows to
derive, from a single irradiance map, the angle resolved efficiency curve, and the corresponding acceptance angle, at
any azimuthal angle. Experimental characterizations performed on CPC-like concentrators confirm these results. It is
also shown how the "inverse" method becomes a powerful tool of investigation of the optical properties of the
concentrator, when the Lambertian source is spatially modulated inside the exit aperture area.