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Abstract The Echo Classification from COnvectivity (ECCO) algorithm identifies convective and stratiform types of radar echo in three dimensions. It is based on the calculation of reflectivity texture—a combination of the intensity and the heterogeneity of the radar echoes on each horizontal plane in a 3D Cartesian volume. Reflectivity texture is translated into convectivity, which is designed to be a quantitative measure of the convective nature of each 3D radar grid point. It ranges from 0 (100% stratiform) to 1 (100% convective). By thresholding convectivity, a more traditional qualitative categorization is obtained, which classifies radar echoes as convective, mixed, or stratiform. In contrast to previous algorithms, these echo-type classifications are provided on the full 3D grid of the reflectivity field. The vertically resolved classifications, in combination with temperature data, allow for subclassifications into shallow, mid-, deep, and elevated convective features, and low, mid-, and high stratiform regions—again in three dimensions. The algorithm was validated using datasets collected over the U.S. Great Plains during the PECAN field campaign. An analysis of lightning counts shows ∼90% of lightning occurring in regions classified as convective by ECCO. A statistical comparison of ECCO echo types with the well-established GPM radar precipitation-type categories show 84% (88%) of GPM stratiform (convective) echo being classified as stratiform (convective) or mixed by ECCO. ECCO was applied to radar grids for the continental United States, the United Arab Emirates, Australia, and Europe, illustrating its robustness and adaptability to different radar grid characteristics and climatic regions. 

Abstract Using data from the airborne HIAPER Cloud Radar (HCR), a partitioning algorithm (ECCO-V) that provides vertically resolved convectivity and convective versus stratiform radar-echo classification is developed for vertically pointing radars. The algorithm is based on the calculation of reflectivity and radial velocity texture fields that measure the horizontal homogeneity of cloud and precipitation features. The texture fields are translated into convectivity, a numerical measure of the convective or stratiform nature of each data point. The convective–stratiform classification is obtained by thresholding the convectivity field. Subcategories of low, mid-, and high stratiform, shallow, mid-, deep, and elevated convective, and mixed echoes are introduced, which are based on the melting-layer and divergence-level altitudes. As the algorithm provides vertically resolved classifications, it is capable of identifying different types of vertically layered echoes, and convective features that are embedded in stratiform cloud layers. Its robustness was tested on data from four HCR field campaigns that took place in different meteorological and climatological regimes. The algorithm was adapted for use in spaceborne and ground-based radars, proving its versatility, as it is adaptable not only to different radar types and wavelengths, but also different research applications. 

Abstract The bulk microphysical properties and number distribution functions (N(D)) of supercooled liquid water (SLW) and ice inside and between ubiquitous generating cells (GCs) observed over the Southern Ocean (SO) during the Southern Ocean Clouds Radiation Aerosol Transport Experimental Study (SOCRATES) measured by in situ cloud probes onboard the NCAR/NSF G‐V aircraft are compared. SLW was detected inside all GCs with an average liquid water content of 0.31 ± 0.19 g m⁻³, 11% larger than values between GCs. TheN(D)of droplets (maximum dimensionD < 50 μm) inside and between GCs had only slight differences. For ice particles, on the other hand, the mean concentration (median mass diameter) withD > 200 μm inside GCs was 2.0 ± 3.3 L⁻¹(323 ± 263 μm), 65% (37%) larger than values outside GCs. AsDincreases, the percentage differences became larger (up to ~500%). The more and larger ice particles inside GCs suggest the GC updrafts provide a favorable environment for particle growth by deposition and riming and that mixing processes are less efficient at redistributing larger particles. The horizontal scale of observed GCs ranged from 200 to 600 m with a mean of 395 ± 162 m, smaller than GC widths observed in previous studies. This study expands knowledge of the microphysical properties and processes acting in GCs over a wider range of conditions than previously available.