Vertically resolved convective-stratiform echo-type identification and convectivity retrieval for vertically pointing radars
Romatschke, U., Dixon, M. J.. (2022). Vertically resolved convective-stratiform echo-type identification and convectivity retrieval for vertically pointing radars. Journal of Atmospheric and Oceanic Technology, doi:https://doi.org/10.1175/JTECH-D-22-0019.1
| Title | Vertically resolved convective-stratiform echo-type identification and convectivity retrieval for vertically pointing radars |
|---|---|
| Genre | Article |
| Author(s) | Ulrike Romatschke, Michael J. Dixon |
| 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. |
| Publication Title | Journal of Atmospheric and Oceanic Technology |
| Publication Date | Nov 1, 2022 |
| Publisher's Version of Record | https://doi.org/10.1175/JTECH-D-22-0019.1 |
| OpenSky Citable URL | https://n2t.org/ark:/85065/d7s75m6q |
| OpenSky Listing | View on OpenSky |
| EOL Affiliations | RSF |