Storm Identification and Tracking Algorithm for Modeling of Rainfall Fields Using 1-h NEXRAD Rainfall Data in Texas
Publication: Journal of Hydrologic Engineering
Volume 14, Issue 7
Abstract
A method to identify and track rainfall structures using accumulated NEXt generation RADar (NEXRAD) rainfall data is presented and used to analyze the dynamics of storm features over an area in Texas. Storm features are identified from a Gaussian mixture model using the expectation maximization algorithm. The method assigns NEXRAD pixels to storm features, simultaneously producing a smooth fitted function to the rainfall intensity distribution. Once the storm features are identified, they are tracked using inverse cost functions and using the fact that continuous features overlap each other from frame to frame in the accumulated data. The inverse cost functions also account for storm feature merging, splitting, birth, and death. Application of this storm identification and tracking algorithm for Brazos County in southeastern Texas distinguishes several characteristics of the storm feature dynamics. From September through April, storm features are predominantly of a frontal nature, with storm features following geostrophic flow along low pressure fronts moving in from the north. In summer (May–August), storm features are convective in nature following random track directions. Both types of storm features have durations of in Brazos County due to the county’s relatively small size compared to the measured average storm speed of and due to the fact that most storms only intersect the county over part of their area.
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Published In
Journal of Hydrologic Engineering
Volume 14 • Issue 7 • July 2009
Pages: 721 - 730
Copyright
© 2009 ASCE.
History
Received: Sep 15, 2006
Accepted: Feb 17, 2009
Published online: Jun 15, 2009
Published in print: Jul 2009
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