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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]

In 2012 the Météo France metropolitan operational radar network consists of 24 radars operating at C and S bands. In addition, a network of four X-band gap-filler radars is being deployed in the French Alps. The network combines polarimetric and nonpolarimetric radars. Consequently, the operational radar rainfall algorithm has been adapted to process both polarimetric and nonpolarimetric data. The polarimetric processing chain is available in two versions. In the first version, now operational, polarimetry is only used to correct for attenuation and filter out clear-air echoes. In the second version there is a more extensive use of polarimetry. In particular, the specific differential phase Kdp is used to estimate rainfall rate in intense rain. The performance of the three versions of radar rainfall algorithms (conventional, polarimetric V1, and polarimetric V2) at different frequency bands (S, C, and X) is evaluated by processing radar data of significant events offline and comparing hourly radar rainfall accumulations with hourly rain gauge data. The results clearly show a superior performance of the polarimetric products with respect to the nonpolarimetric ones at all frequency bands, but particularly at higher frequency. The second version of the polarimetric product, which makes a broader use of polarimetry, provides the best overall results. [ABSTRACT FROM AUTHOR]

The differential phase (ΦDP) measured by polarimetric radars is recognized to be a very good indicator of the path integrated by rain. Moreover, if a linear relationship is assumed between the specific differential phase (KDP) and the specific attenuation (AH) and specific differential attenuation (ADP), then attenuation can easily be corrected. The coefficients of proportionality, γH and γDP, are, however, known to be dependent in rain upon drop temperature, drop shapes, drop size distribution, and the presence of large drops causing Mie scattering. In this paper, the authors extensively apply a physically based method, often referred to as the “Smyth and Illingworth constraint,” which uses the constraint that the value of the differential reflectivity ZDR on the far side of the storm should be low to retrieve the γDP coefficient. More than 30 convective episodes observed by the French operational C-band polarimetric Trappes radar during two summers (2005 and 2006) are used to document the variability of γDP with respect to the intrinsic three-dimensional characteristics of the attenuating cells. The Smyth and Illingworth constraint could be applied to only 20% of all attenuated rays of the 2-yr dataset so it cannot be considered the unique solution for attenuation correction in an operational setting but is useful for characterizing the properties of the strongly attenuating cells. The range of variation of γDP is shown to be extremely large, with minimal, maximal, and mean values being, respectively, equal to 0.01, 0.11, and 0.025 dB °-1. Coefficient γDP appears to be almost linearly correlated with the horizontal reflectivity (ZH), differential reflectivity (ZDR), and specific differential phase (KDP) and correlation coefficient (ρHV) of the attenuating cells. The temperature effect is negligible with respect to that of the microphysical properties of the attenuating cells. Unusually large values of γDP, above 0.06 dB °-1, often referred to as “hot spots,” are reported for 15%—a nonnegligible figure—of the rays presenting a significant total differential phase shift (ΔφDP > 30°). The corresponding strongly attenuating cells are shown to have extremely high ZDR (above 4 dB) and ZH (above 55 dBZ), very low ρHV (below 0.94), and high KDP (above 4° km-1). Analysis of 4 yr of observed raindrop spectra does not reproduce such low values of ρHV, suggesting that (wet) ice is likely to be present in the precipitation medium and responsible for the attenuation and high phase shifts. Furthermore, if melting ice is responsible for the high phase shifts, this suggests that KDP may not be uniquely related to rainfall rate but can result from the presence of wet ice. This hypothesis is supported by the analysis of the vertical profiles of horizontal reflectivity and the values of conventional probability of hail indexes. [ABSTRACT FROM AUTHOR]

The recent deployment of an innovative triple pulse rise time (PRT) scheme within the French operational radar network allows for the simultaneous collection of reflectivity and radial velocity measurements up to a range of 250 km with no ambiguity. This achievement brings new perspectives in terms of operational exploitation of Doppler measurements including the capability to consistently perform multiple-Doppler wind synthesis in a fully operational framework. Using real and simulated Doppler observations, the authors show that the 3D wind fields retrieved in that framework can definitely be relied upon to achieve a consistent and detailed mapping of the airflow structure in various precipitation regimes despite radar baselines averaging ∼180 km and very limited scanning strategies. This achievement could be easily transposed to other operational networks and represents a remarkable opportunity to add further value to operational Doppler velocity measurements. [ABSTRACT FROM AUTHOR]

A polarimetric method is devised to correct for attenuation effects at C band on reflectivity ZH and differential reflectivity ZDR measurements. An operational cross-correlation analysis is used to derive advection vectors and to displace echoes over a 5-min time step. These advected echoes are then compared with observations valid at the same time. The method assumes that the mean change in the intrinsic ZH and ZDR over a 5-min period when considering 1–2 h of observations over the entire radar umbrella is approximately zero. Correction coefficients are retrieved through the minimization of a cost function that links observed decreases in ZH and ZDR due to attenuation effects with increases in differential phase shift (ΦDP). The retrieved coefficients are consistent with published values for the typical ranges of temperatures and drop sizes encountered at midlatitudes, even when Mie scattering effects are present. Measurements of ZH and ZDR corrected using retrieved coefficients are compared with raw measurements and to measurements adjusted by mean coefficients found in the literature. The empirical retrieval method shows improvement over using mean correction coefficients based on comparisons of ZH from neighboring, unattenuated radars, disdrometer measurements, and analysis of ZH and ZDR as a function of ΦDP. [ABSTRACT FROM AUTHOR]