Three-Dimensional Convective–Stratiform Echo-Type Classification and Convectivity Retrieval from Radar Reflectivity

Journal Article · Fri Oct 28 04:00:00 EDT 2022 · Journal of Atmospheric and Oceanic Technology (Online)

DOI:https://doi.org/10.1175/JTECH-D-22-0018.1· OSTI ID:1897074

Dixon, Michael ^[1]; Romatschke, Ulrike ^[1]

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1. National Center for Atmospheric Research (NCAR), Boulder, CO (United States)

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.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Atmospheric Radiation Measurement (ARM) Data Center
• Sponsoring Organization: USDOE Office of Science (SC), Biological and Environmental Research (BER); National Science Foundation (NSF)
• Grant/Contract Number: AC05-76RL01830
• OSTI ID: 1897074
• Journal Information: Journal of Atmospheric and Oceanic Technology (Online), Journal Name: Journal of Atmospheric and Oceanic Technology (Online) Journal Issue: 11 Vol. 39; ISSN 1520-0426
• Publisher: American Meteorological Society
• Country of Publication: United States
• Language: English

Related Subjects

Radars/Radar observations
54 ENVIRONMENTAL SCIENCES
Algorithms
Convective clouds
Convective storms
Precipitation
Stratiform clouds