This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1175/JTECH-D-22-0019.1. This is version 1 of this Preprint.
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Abstract
Using data from the airborne HIAPER Cloud Radar (HCR), a partitioning algorithm (ECCO-V) that provides vertically resolved convectivity and convective vs 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 which took place in different meteorological and climatological regimes. The algorithm was adapted for use in space borne and ground based radars, proving its versatility, as it is adaptable not only to different radar types and wavelengths, but also different research applications.
DOI
https://doi.org/10.31223/X54S77
Subjects
Atmospheric Sciences, Meteorology, Oceanography and Atmospheric Sciences and Meteorology
Keywords
radar, Convective, Stratiform, Airborne, cloud
Dates
Published: 2022-01-27 08:35
License
CC BY Attribution 4.0 International
Additional Metadata
Data Availability (Reason not available):
Data availability is described in the Data Availability Statement in the manuscript.
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