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 (Z H , Z DR ), (Z H , K DP ), and (Z H , r HV ) 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.

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.

A prototype high-resolution (1 km, 5 min) multiradar 3D gridded reflectivity product, including a suite of derived 2D vertical column products, has been developed for the Single European Skies Air Traffic Management Research program. As part of this, a new method for mapping radar data to grid points is being used, based on the concept of a binary space partitioning (BSP) tree that treats radar data as a set of points in a 3D point cloud. This allows the resulting analysis to be based on a complete picture of the nearby data from overlapping radars and can easily adapt to irregular grid configurations. This method is used with a Barnes successive corrections technique to retrieve finescale features while avoiding problems of undersmoothing in data-sparse regions. This has been tested using 3D domains enclosing the terminal maneuvering areas surrounding Paris, France, and London, United Kingdom, and using reflectivity plan position indicator scan data from the French and U.K. operational networks, encoded using the standard European Operational Programme for the Exchange of Weather Radar Information (OPERA) Data Information Model format. Quantitative intercomparisons between the new method, in various configurations; a high-resolution version of an existing method, in operational use at Météo-France; and a method that was developed by the National Oceanic and Atmospheric Administration for use with the Weather Surveillance Radar-1998 Doppler radar network, have been done using simulated radar scans derived from 3D synthetic radar reflectivity fields in stratiform and convective regimes.

International audienceA fuzzy logic hydrometeor classification algorithm (HCA), allowing discrimination between six microphysical species regardless of the radar wavelength is presented and evaluated. The proposed method is based upon combination sets of dual-polarimetric observables (reflectivity at horizontal polarization ZH, differential reflectivity ZDR, specific differential phase KDP, correlation coefficient ρHV) along with temperature data inferred from a numerical weather prediction model output.The performance of the HCA is evaluated using 20 h of multi-frequency dual-polarimetric radar data collected during the first Special Observation Period (SOP1) of the Hydrological Cycle in the Mediterranean Experiment (HyMeX). A new method based upon intercomparisons of retrieved hydrometeor data deduced from pairs of neighbouring radars (S-band vs. S-band and S-band vs. C-band) over a common sampling area is proposed to evaluate the consistency of hydrometor classification outputs. S-/C-band radar comparisons generally show better consistency than S-/S-band radar comparisons due to issues with the identification of the 0°C isotherm on one of the two S-band radars. Imperfect attenuation correction at C-band may also lead into differences in hydrometeor fields retrieved from the C- and S-band radars in convective situations, but retrieved hydrometeor data are globally very consistent from one radar to another. Comparisons against in situ airborne data also confirm the overall good performance of the HCA.In a second experiment, an original method allowing the production of multi-radar three-dimensional (3D) hydrometeor fields from single-radar 2D hydrometeor data is tested on a bow-echo convective system observed with C- and S-band radars. The resulting 3D hydrometeor fields provide a detailed view of the bow-echo microphysical structure and confirm the good performance of both the HCA and interpolation technique

A new X-band Doppler miniradar, the CURIE radar (Canopy Urban Research on Interactions and Exchanges), mainly adapted to low Atmospheric Boundary Layer ABL sounding has been developed at LATMOS (Laboratoire Atmosphères, Milieux, Observations Spatiales) formerly CETP (Centre d'étude des Environnements Terrestre et Planétaires). After a brief description of the measurement conditions in a turbulent atmosphere, the main characteristics of the new sensor are presented. As an example, we compare CURIE vertical velocity f uctuations with UHF observations to show the vertical velocity measurement validity. As a prospective area of application in clear air, we focus on a f rst observation of vertical velocity variance which is supposed to be related to entrainment across the inversion layer. As our objective is to study low boundary layers during different atmospheric conditions and since the radar works in the presence of precipitation (as all X-band radar do), we also show vertical rain soundings in the lower part of the ABL and illustrate our f ndings with results demonstrating comparable ref ectivity and precipitation rates as estimated with a disdrometer and with a rain gauge. Zusammenfassung Ein neues X-Band-Dopppler-Miniradar, das sog. CURIE-Radar (Canopy Urban Research on Interactions and Exchanges) wurde am LATMOS (Laboratoire Atmospheres, Milieux, Observations Spatiales), früher CETP (Centre d'étude des Environnements Terrestre et Planétaires) entwickelt. Es ist hauptsächlich für die Anwendung in der unteren atmosphärischen Grenzschicht vorgesehen. Nach kurzer Beschreibung der Messbedingungen in der turbulenten Atmosphäre wurden die wesentlichen Charakteristika des neuen Systems päsentiert. Es wurden als Beispiel mit CURIE gemessene Vertikalgeschwindigkeitsf uktuationen mit UHF-Beobachtungen verglichen, um die Qualität der Methode aufzuzeigen. Unter clear-air-Bedingungen konzentrieren wir uns auf die Beobachtung der Varianz der Vertikalgeschwindigkeit, von der angenommen wird, dass sie ein Ausdruck für den Entrainment-Prozess in der Inversionsschicht ist. Bei der Untersuchung der unteren atmosphärischen Grenzschicht während unterschiedlicher atmosphärischer Bedingungen, konnten wir auch vertikale Regenechos im unteren Teil der ABL registrieren, da das CURIE (wie alle Radars) auch bei Niederschlägen arbeitet. Es wurden unseren Ergebnissen vergleichbare Ref exions-und Niederschlagsraten, die mit Disdrometern und Regenmessern erhalten wurden, gegenübergestellt.