Open AccessA Method for Extracting Postevent Storm Tracks
Author(s) -
Valliappa Lakshmanan,
Benjamin S. Herzog,
Darrel M. Kingfield
Publication year - 2015
Publication title -
journal of applied meteorology and climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.079
H-Index - 134
eISSN - 1558-8432
pISSN - 1558-8424
DOI - 10.1175/jamc-d-14-0132.1
Subject(s) - storm , computer science , set (abstract data type) , data set , tracking (education) , algorithm , statistical analysis , real time computing , data mining , meteorology , statistics , artificial intelligence , mathematics , psychology , pedagogy , programming language , physics
Although existing algorithms for storm tracking have been designed to operate in real time, they are also commonly used to do postevent data analysis and research. Real-time algorithms cannot use information on the subsequent positions of a storm because it is not available at the time that associations between frames are made, but postevent analysis is not similarly constrained. Therefore, it should be possible to obtain better tracks for postevent analysis than those that a real-time algorithm is capable of producing. In this paper, a statistical procedure for determining storm tracks from a set of identified storm cells over time is described. It is found that this procedure results in fewer, longer-lived tracks at the potential cost of a small increase in positional error.