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In order to minimize the economic and social impact of hazardous weather in the Alps, three X‐band dual‐polarization radars were deployed in the southeast of France during the RHYTMME project in 2011–2013 and more recently have been incorporated formally into the conventional radar network already operating S‐ and C‐band radars. In this mountainous region, the radars' beam shielding by the complex terrain, the very different altitudes of the radars, the significant attenuation at X‐band and the low density of rain‐gauges have made the integration of these radars into the operational service a challenging exercise. In this article, the framework used to evaluate the corrections applied to the volume data produced by the radars is presented and the residual errors related to the partial beam blockages, the attenuation by rain, the wet radome, and the melting layer are carefully studied and disentangled. The results of the analysis suggest that: (a) the beam blockage correction requires the use of a much higher resolution digital elevation model (DEM) in mountainous regions than the 250 m resolution DEM currently uses, (b) the dual‐pol reflectivity (Zh) attenuation correction used at Météo‐France performs well in the rain but the differential attenuation on Zdr is overestimated, (c) the attenuation of wet snow is underestimated and a mean error of 2 dB is induced by the melting layer in spring and autumn, (d) the wet radome, as well as producing significant attenuation on Zh, induces differential attenuation on Zdr. The attenuation in the melting layer is further investigated taking advantage of the height difference between the radar sites. A new specific attenuation coefficient for wet snow is suggested and it is shown to reduce the seasonal bias on three particular events observed in spring and autumn. Dual polarimetric X‐band radars have been considered as a promising solution to fill gaps in radar networks over mountainous regions. The quantitative estimation of precipitation from these radars is subject to various error sources. Based on comparisons of co‐located radars observations, this study presents a quantitative error assessment of (a) the beam‐blockage correction, (b) the attenuation correction in the rain layer, (c) the wet radome attenuation correction and (d) the attenuation correction in the melting layer. [ABSTRACT FROM AUTHOR]

A new fuzzy logic hydrometeor classification algorithm is proposed that takes into account data-based membership functions, measurement conditions, and three-dimensional temperature information provided by a high-resolution nonhydrostatic numerical weather prediction model [the Application of Research to Operations at Mesoscale model (AROME)]. The formulation of the algorithm is unique for X-, C-, and S-band radars and employs wavelength-adapted bivariate membership functions for ( ZH, ZDR), ( ZH, KDP), and ( ZH, ρHV) that were established by using real data collected by the French polarimetric radars and T-matrix simulations. The distortion of membership functions caused by deteriorating measurement conditions (e.g., precipitation-induced attenuation, signal-to-clutter ratio, signal-to-noise ratio, partial beam blocking, and distance) is documented empirically and subsequently parameterized in the algorithm. The result is an increase in the amount of overlapping between the membership functions of the different hydrometeor types. The relative difference between the probability function values of the first and second choice of the hydrometeor classification algorithm is analyzed as a measure of the quality of identification. Semiobjective scores are calculated using an expert-built validation dataset to assess the respective improvements brought by using 'richer' temperature information and by using more realistic membership functions. These scores show a significant improvement in the detection of wet snow. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of a hail event that occurred 27 May 2012 over Brignoles, located in southeastern France. The event was observed by an X-band polarimetric radar located in Mont Maurel, 75 km northeast of the hailstorm. Lightning data from the French national network (owned and operated by Météorage) are also used in the study. The analysis highlights that the lightning and radar data provide complementary information that may allow a better microphysical interpretation of the hailstorm and potentially increase the probability of its detection. [ABSTRACT FROM AUTHOR]

The effect of wet radome attenuation is estimated on a French operational X-band weather radar deployed in the Maritime Alps of southeastern France. As the radar is deployed in a remote location, the reflectivity factor in the immediate vicinity of the radar is used as a proxy for rain rate at the radar and by extension, to the radome wetting. By means of intercomparison with a neighboring radar that lacks a radome, a wet radome correction is deduced. The correction is reasonably consistent with theoretical expectations and with other evaluations done, for example, via disdrometer. The improvement is evaluated by comparison to a Micro Rain Radar located under the point of comparison, and the impact on quantitative precipitation estimation (QPE) retrievals is positive. The intercomparison of such observations permits a routine means of monitoring radome attenuation. [ABSTRACT FROM AUTHOR]

Summary: Two so-called “integrated” polarimetric rate estimation techniques, ZPHI () and ZZDR (), are evaluated using 12 episodes of the year 2005 observed by the French C-band operational Trappes radar, located near Paris. The term “integrated” means that the concentration parameter of the drop size distribution is assumed to be constant over some area and the algorithms retrieve it using the polarimetric variables in that area. The evaluation is carried out in ideal conditions (no partial beam blocking, no ground-clutter contamination, no bright band contamination, a posteriori calibration of the radar variables Z H and Z DR) using hourly rain gauges located at distances less than 60km from the radar. Also included in the comparison, for the sake of benchmarking, is a conventional Z =282R 1.66 estimator, with and without attenuation correction and with and without adjustment by rain gauges as currently done operationally at Météo France. Under those ideal conditions, the two polarimetric algorithms, which rely solely on radar data, appear to perform as well if not better, pending on the measurements conditions (attenuation, rain rates, …), than the conventional algorithms, even when the latter take into account rain gauges through the adjustment scheme. ZZDR with attenuation correction is the best estimator for hourly rain gauge accumulations lower than 5mmh−1 and ZPHI is the best one above that threshold. A perturbation analysis has been conducted to assess the sensitivity of the various estimators with respect to biases on Z H and Z DR, taking into account the typical accuracy and stability that can be reasonably achieved with modern operational radars these days (1dB on Z H and 0.2dB on Z DR). A +1dB positive bias on ZH (radar too hot) results in a +14% overestimation of the rain rate with the conventional estimator used in this study (Z=282R1.66), a -19% underestimation with ZPHI and a +23% overestimation with ZZDR. Additionally, a +0.2dB positive bias on ZDR results in a typical rain rate under- estimation of 15% by ZZDR. [Copyright &y& Elsevier]

The influence of ground clutter contamination on the estimation of polarimetric radar parameters, horizontal reflectivity (Zh), differential reflectivity (Zdr), correlation coefficient (ρhν), and differential propagation phase (φdp) was examined. This study aims to derive the critical level of ground clutter contamination for Zh, Zdr, ρhν, and φdp at which ground clutter influence exceeds predefined precision thresholds. Reference data with minimal ground clutter contamination consist of eight precipitation fields measured during three rain events characterized by stratiform and convective precipitation. Data were collected at an elevation angle of 0.8° by the Météo-France operational, polarimetric Doppler C-band weather radar located in Trappes, France, ∼30 km southwest of Paris. Nine different ground clutter signatures, ranging from point targets to more complex signatures typical for mountain ranges or urban obstacles, were added to the precipitation fields. This is done at the level of raw in-phase and quadrature component data in the two polarimetric channels. For each ground clutter signature, 30 simulations were conducted in which the mean reflectivity of ground clutter within the resolution volume varied between being 30 dB higher to 30 dB lower than the mean reflectivity of precipitation. Differences in Zh, Zdr, ρν, and φdp between simulation and reference were shown as a function of ratio between ground clutter and precipitation intensities. As a result of this study, horizontal reflectivity showed the lowest sensitivity to ground clutter contamination. Furthermore, a precision of 1.7 dBZ in Zh is achieved on average when the precipitation and ground clutter intensities are equal. Requiring a precision of 0.2 dB in Zdr and 3° in φdp, the reflectivity of precipitation needs to be on average ∼5.5 and ∼6 dB, respectively, higher compared to the reflectivity of ground clutter. The analysis also indicates that the highest sensitivity to the nine clutter signatures was derived for ρhν. To meet a predefined precision threshold of 0.02, reflectivity of precipitation needs to be ∼13.5 dB higher than the reflectivity of ground clutter. [ABSTRACT FROM AUTHOR]

Radar reflectivity (Zh), differential reflectivity (Zdr), and specific differential phase (Kdp) measured from the operational, polarimetric weather radar located in Trappes, France, were used to examine the effects of radar beam shielding on rainfall estimation. The objective of this study is to investigate the degree of immunity of Kdp-based rainfall estimates to beam shielding for C-band radar data during four typical rain events encountered in Europe. The rain events include two cold frontal rainbands with average rainfall rates of 7 and 17 mm h-1, respectively, and two summertime convective rain events with average rainfall rates of 11 and 22 mm h-1. The large effects of beam shielding on rainfall accumulation were observed for algorithms using Zh and Zdr with differences of up to ∼2 dB (40%) compared to a Kdp-based algorithm over a power loss range of 0–8 dB. This analysis reveals that Zdr and Kdp are not affected by partial beam shielding. Standard reflectivity corrections based on the degree of beam shielding would have overestimated rainfall rates by up to 1.5 dB for less than 40% beam shielding and up to 3 dB for beam shielding less than 75%. The investigation also examined the sensitivity of beam shielding effects on rainfall rate estimation to (i) axis–ratio parameterization and drop size distribution, (ii) methods used to smooth profiles of differential propagation phase (φdp) and estimate Kdp, and (iii) event-to-event variability. Although rainfall estimates were sensitive to drop size distribution and axis–ratio parameterization, differences between Zh- and Kdp-based rainfall rates increased independently from those parameters with amount of shielding. Different approaches to smoothing φdp profiles and estimating Kdp were examined and showed little impact on results. [ABSTRACT FROM AUTHOR]

A fuzzy logic algorithm has been developed for the purpose of segregating precipitating from nonprecipitating echoes using polarimetric radar observations at C band. Adequate polarimetric descriptions for each type of scatterer are required for the algorithm to be effective. An observations-based approach is presented in this study to derive membership functions and objectively weight them so that they apply directly to conditions experienced at the radar site and to the radar wavelength. Three case studies are examined and show that the algorithm successfully removes nonprecipitating echoes from rainfall accumulation maps. [ABSTRACT FROM AUTHOR]