# On the Use of Bright Scatterers for Monitoring Doppler, Dual-Polarization Weather Radars
## 1 Introduction  
Ground echo is a challenge for operational weather radars, especially as far as hydrological applications and precipitation estimates are concerned. The identification and elimination of ground clutter is a prerequisite for the use of weather radar. Since European radars are often used for the surveillance of complex-orography regions, they are installed out of necessity on the top of a hill or a mountain, where the rejection of clutter is of vital importance, since a clear view from a high site implies a large number of ground clutter pixels. Ground clutter is automatically detected in the operational radar processing chain of meteorological services using certain specific and well-consolidated algorithms and then rejected so that only the radar echoes originating from the weather are retained. In this context, the use of high range resolution (for example, \(\mathrm{cr}/2<100\) m, where \(\tau\) is the pulse length), Doppler velocity and dual-polarization information maximizes the probability of having at least some clutter-free radar bins for each Cartesian pixel of the resampled operational product. The distribution of ground clutter echoes can often be fitted using one of the following distributions: Rayleigh (independent randomly distributed scatterers, e.g., [1]), lognormal (e.g., [2]) and Weibull (e.g., [3]). It has been found that, for these skewed-to-the-right distributions, the Log-transformed ratio between the 90 th percentile and the algebraic average of the radar reflectivity value generally ranges between 3 and 4 dB for most ground clutter radar bin cases. Furthermore, in the case of randomly distributed scatterers, the Log-transformed ratio between the algebraic average and the median is 1.6 dB. Ground-clutter characteristics, as well as their modeling and simulation have been studied extensively, primarily to improve the radar detection of meteorological targets (e.g., [4]). Thanks to the increase in knowledge, together with the exponential increase in computational power formodeling and statistical analysis, a novel point of view regarding ground clutter is emerging; it is no longer considered just a disturbance that needs to be rejected and its spatio-temporal characteristics are instead being investigated so that they can be used to monitor the quality of radar hardware. [PERSON] et al. [5], for instance, proposed a statistical method, based on the probability distribution of a clutter area close to a ground-based radar, to provide near-real-time estimates of the relative calibration of reflectivity data. The original application was to an S-band radar in a tropical oceanic location; later, [PERSON] et al. [6] successfully applied a similar approach to an X-band radar in the more complex terrain of the Western Alps. The study by [PERSON] et al. [7] has shown that the technique is capable of monitoring the reflectivity calibration of other S-band radars, given the proper generation of an areal clutter map. The operational implementation of such techniques obviously takes into account the reflectivity values of all the ground clutter low range resolution radar bins (generally, 1\({}^{\circ}\)\(\times\) 500 m) that are above a given high reflectivity threshold (e.g., 55 dBZ) for more than a given percentage of time. It does not consider any other important spectral or polarimetric information that characterizes the ground clutter bins, or perform a temporal analysis of any individual radar bins, even though these could provide useful information for the monitoring of the quality of modern dual-polarization radars. A guiding principle for a comprehensive radar monitoring is in fact to combine as many independent sources of information as possible.