319 Best Track: Object-Based Path Identification and Analysis

Monday, 23 January 2017
4E (Washington State Convention Center )
David Harrison, CIMMS/University of Oklahoma/NOAA/NSSL, Norman, OK; and A. McGovern, C. Karstens, and R. A. Lagerquist

Handout (877.6 kB)

Best Track is a newly developed open-source Python package and algorithm designed to identify and optimize geotemporal paths from user-provided coordinate objects (cells) or collections of coordinate objects (tracks).  Based on the Warning Decision Support System - Integrated Information’s (WDSS-II) w2besttrack algorithm, Best Track uses a three-step process to determine the most realistic storm tracks from the provided data.  First, the algorithm breaks cells into estimated track groups.  Second, it joins nearby tracks that meet certain spatial and temporal criteria.  Third, it removes any temporally conflicting storm cells from each track.  Although the algorithm is initially intended to be used with data produced by WDSS-II’s w2segmotionll function, the expandable design has made it possible to run the package on a variety of datasets and formats that provide geotemporal coordinates, including objects generated by the National Oceanic and Atmospheric Administration (NOAA) / Cooperative Institute for Meteorological Satellite Studies (CIMSS) probSevere model.  Best Track is expected to be released on GitHub and the Python Packaging Index at the 97th Annual Meeting of the American Meteorological Society.
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