Stride search: A general algorithm for storm detection in high-resolution climate data
Abstract
This study discusses the problem of identifying extreme climate events such as intense storms within large climate data sets. The basic storm detection algorithm is reviewed, which splits the problem into two parts: a spatial search followed by a temporal correlation problem. Two specific implementations of the spatial search algorithm are compared: the commonly used grid point search algorithm is reviewed, and a new algorithm called Stride Search is introduced. The Stride Search algorithm is defined independently of the spatial discretization associated with a particular data set. Results from the two algorithms are compared for the application of tropical cyclone detection, and shown to produce similar results for the same set of storm identification criteria. Differences between the two algorithms arise for some storms due to their different definition of search regions in physical space. The physical space associated with each Stride Search region is constant, regardless of data resolution or latitude, and Stride Search is therefore capable of searching all regions of the globe in the same manner. Stride Search's ability to search high latitudes is demonstrated for the case of polar low detection. Wall clock time required for Stride Search is shown to be smaller than a gridmore »
- Authors:
-
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Univ. of California Los Angeles, Los Angeles, CA (United States)
- Publication Date:
- Research Org.:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Org.:
- USDOE National Nuclear Security Administration (NNSA)
- OSTI Identifier:
- 1333537
- Report Number(s):
- SAND-2015-4839J
Journal ID: ISSN 1991-9603; 594917
- Grant/Contract Number:
- AC04-94AL85000
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Geoscientific Model Development (Online)
- Additional Journal Information:
- Journal Name: Geoscientific Model Development (Online); Journal Volume: 9; Journal Issue: 4; Journal ID: ISSN 1991-9603
- Publisher:
- European Geosciences Union
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; 97 MATHEMATICS AND COMPUTING
Citation Formats
Bosler, Peter A., Roesler, Erika L., Taylor, Mark A., and Mundt, Miranda R. Stride search: A general algorithm for storm detection in high-resolution climate data. United States: N. p., 2016.
Web. doi:10.5194/gmd-9-1383-2016.
Bosler, Peter A., Roesler, Erika L., Taylor, Mark A., & Mundt, Miranda R. Stride search: A general algorithm for storm detection in high-resolution climate data. United States. https://doi.org/10.5194/gmd-9-1383-2016
Bosler, Peter A., Roesler, Erika L., Taylor, Mark A., and Mundt, Miranda R. Wed .
"Stride search: A general algorithm for storm detection in high-resolution climate data". United States. https://doi.org/10.5194/gmd-9-1383-2016. https://www.osti.gov/servlets/purl/1333537.
@article{osti_1333537,
title = {Stride search: A general algorithm for storm detection in high-resolution climate data},
author = {Bosler, Peter A. and Roesler, Erika L. and Taylor, Mark A. and Mundt, Miranda R.},
abstractNote = {This study discusses the problem of identifying extreme climate events such as intense storms within large climate data sets. The basic storm detection algorithm is reviewed, which splits the problem into two parts: a spatial search followed by a temporal correlation problem. Two specific implementations of the spatial search algorithm are compared: the commonly used grid point search algorithm is reviewed, and a new algorithm called Stride Search is introduced. The Stride Search algorithm is defined independently of the spatial discretization associated with a particular data set. Results from the two algorithms are compared for the application of tropical cyclone detection, and shown to produce similar results for the same set of storm identification criteria. Differences between the two algorithms arise for some storms due to their different definition of search regions in physical space. The physical space associated with each Stride Search region is constant, regardless of data resolution or latitude, and Stride Search is therefore capable of searching all regions of the globe in the same manner. Stride Search's ability to search high latitudes is demonstrated for the case of polar low detection. Wall clock time required for Stride Search is shown to be smaller than a grid point search of the same data, and the relative speed up associated with Stride Search increases as resolution increases.},
doi = {10.5194/gmd-9-1383-2016},
journal = {Geoscientific Model Development (Online)},
number = 4,
volume = 9,
place = {United States},
year = {Wed Apr 13 00:00:00 EDT 2016},
month = {Wed Apr 13 00:00:00 EDT 2016}
}
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