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|Title: ||On the data-driven inference of modulatory networks in climate science: an application to West African rainfall|
|Authors: ||González II, D. L.|
Angus, M. P.
Tetteh, I. K.
Bello, G. A.
Pendse1, S. V.
|Issue Date: ||13-Jan-2015|
|Publisher: ||Nonlin. Processes Geophys., 22, 33–46, 2015|
|Citation: ||Received: 1 February 2014 – Published in Nonlin. Processes Geophys. Discuss.: 4 April 2014 Revised: 10 July 2014 – Accepted: 21 November 2014 – Published: 13 January 2015|
|Abstract: ||. Decades of hypothesis-driven and/or firstprinciples 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. 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
|Description: ||An article published by Nonlin. Processes Geophys. Discuss.: 4 April 2014
Revised: 10 July 2014 – Accepted: 21 November 2014 – Published: 13 January 2015 and available at doi:10.5194/npg-22-33-2015|
|Appears in Collections:||College of Science|
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