Wednesday, 15 January 2020
Hall B1 (Boston Convention and Exhibition Center)
The introduction of polarimetric capabilities to the WSR-88D network has allowed for the implementation of a Hail Size Discrimination Algorithm (HSDA) and the exploration of more precise hail sizing capabilities using integrations of reflectivity weighted by differential reflectivity below the melting level. Currently, CIMMS/NSSL is exploring the best options for merging polarimetric data on the MRMS three-dimensional grid. The availability of polarimetric moments on the MRMS grid would allow for implementation of polarimetric hail sizing algorithms, like the HSDA into the MRMS system. This presentation will explore such an implementation and using vertical profiles of MRMS polarimetric data to develop machine learning algorithms for hail sizing and classification. Further, the presentation will investigate the differences between single-radar outputs (such as HSDA) that are then merged to the MRMS grid and outputs derived directly from polarimetric moments merged on the MRMS grid. The algorithms will be evaluated against hail reports from the Severe Hazards Analysis and Verification Experiment (SHAVE), which is a high-resolution report database with spacing between reports on the same scale as the MRMS horizontal grid spacing. Comparisons of algorithm performance and vertical profiles of the polarimetric MRMS products to the polarimetric single-radar products will be produced.
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