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Title: Response-Guided Community Detection: Application to Climate Index Discovery

Abstract

Discovering climate indices-time series that summarize spatiotemporal climate patterns-is a key task in the climate science domain. In this work, we approach this task as a problem of response-guided community detection; that is, identifying communities in a graph associated with a response variable of interest. To this end, we propose a general strategy for response-guided community detection that explicitly incorporates information of the response variable during the community detection process, and introduce a graph representation of spatiotemporal data that leverages information from multiple variables. We apply our proposed methodology to the discovery of climate indices associated with seasonal rainfall variability. Our results suggest that our methodology is able to capture the underlying patterns known to be associated with the response variable of interest and to improve its predictability compared to existing methodologies for data-driven climate index discovery and official forecasts.

Authors:
 [1];  [1];  [1];  [1];  [1];  [2];  [3]
  1. North Carolina State University (NCSU), Raleigh
  2. University of Minnesota
  3. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1261480
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Book
Country of Publication:
United States
Language:
English
Subject:
Community detection; Spatiotemporal data; Climate index discovery; Seasonal rainfall prediction; NETWORKS; AFRICA

Citation Formats

Bello, Gonzalo, Angus, Michael, Pedemane, Navya, Harlalka, Jitendra, Semazzi, Fredrick, Kumar, Vipin, and Samatova, Nagiza F. Response-Guided Community Detection: Application to Climate Index Discovery. United States: N. p., 2015. Web.
Bello, Gonzalo, Angus, Michael, Pedemane, Navya, Harlalka, Jitendra, Semazzi, Fredrick, Kumar, Vipin, & Samatova, Nagiza F. Response-Guided Community Detection: Application to Climate Index Discovery. United States.
Bello, Gonzalo, Angus, Michael, Pedemane, Navya, Harlalka, Jitendra, Semazzi, Fredrick, Kumar, Vipin, and Samatova, Nagiza F. Thu . "Response-Guided Community Detection: Application to Climate Index Discovery". United States. doi:.
@article{osti_1261480,
title = {Response-Guided Community Detection: Application to Climate Index Discovery},
author = {Bello, Gonzalo and Angus, Michael and Pedemane, Navya and Harlalka, Jitendra and Semazzi, Fredrick and Kumar, Vipin and Samatova, Nagiza F},
abstractNote = {Discovering climate indices-time series that summarize spatiotemporal climate patterns-is a key task in the climate science domain. In this work, we approach this task as a problem of response-guided community detection; that is, identifying communities in a graph associated with a response variable of interest. To this end, we propose a general strategy for response-guided community detection that explicitly incorporates information of the response variable during the community detection process, and introduce a graph representation of spatiotemporal data that leverages information from multiple variables. We apply our proposed methodology to the discovery of climate indices associated with seasonal rainfall variability. Our results suggest that our methodology is able to capture the underlying patterns known to be associated with the response variable of interest and to improve its predictability compared to existing methodologies for data-driven climate index discovery and official forecasts.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Jan 01 00:00:00 EST 2015},
month = {Thu Jan 01 00:00:00 EST 2015}
}

Book:
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