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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/11935

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.
Padmanabhan, K.
Pendse1, S. V.
and Et..al
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 research.
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
URI: http://hdl.handle.net/123456789/11935
Appears in Collections:College of Science

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