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Title: On the data-driven inference of modulatory networks in climate science: An application to West African rainfall

Decades of hypothesis-driven and/or first-principles research have been applied towards the discovery and explanation of the mechanisms that drive climate phenomena, such as western African Sahel summer rainfall~variability. Although connections between various climate factors have been theorized, not all of the key relationships are fully understood. We propose a data-driven approach to identify candidate players in this climate system, which can help explain underlying mechanisms and/or even suggest new relationships, to facilitate building a more comprehensive and predictive model of the modulatory relationships influencing a climate phenomenon of interest. We applied coupled heterogeneous association rule mining (CHARM), Lasso multivariate regression, and dynamic Bayesian networks to find relationships within a complex system, and explored means with which to obtain a consensus result from the application of such varied methodologies. Using this fusion of approaches, we identified relationships among climate factors that modulate Sahel rainfall. As a result, these relationships fall into two categories: well-known associations from prior climate knowledge, such as the relationship with the El Niño–Southern Oscillation (ENSO) and putative links, such as North Atlantic Oscillation, that invite further research.
Authors:
 [1] ;  [2] ;  [2] ;  [1] ;  [1] ;  [1] ;  [1] ;  [2] ;  [2] ;  [3] ;  [1]
  1. North Carolina State Univ., Raleigh, NC (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  2. North Carolina State Univ., Raleigh, NC (United States)
  3. Univ. of Minnesota, Minneapolis, MN (United States)
Publication Date:
Grant/Contract Number:
AC05-00OR22725
Type:
Accepted Manuscript
Journal Name:
Nonlinear Processes in Geophysics (Online)
Additional Journal Information:
Journal Name: Nonlinear Processes in Geophysics (Online); Journal Volume: 22; Journal Issue: 1; Journal ID: ISSN 1607-7946
Publisher:
European Geosciences Union - Copernicus
Research Org:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES
OSTI Identifier:
1333075