Abstract
Abstract. 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. 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.
Highlights
The climate system is inherently complex, due to the existence of nonlinear interactions, or couplings, between its subsystems, global-scale temperature anomalies (e.g., El Niño–Southern Oscillation), and other climate behaviors
The results obtained enabled the formulation of the North Atlantic Oscillation (NAO)-driven hypothesis, among others, which theorizes that the NAO modulates the drivers of West African climate, the Atlantic dipole and the EATL, via the low-level westerly (LLW) jet
We extended this work by developing coupled heterogeneous association rule mining (CHARM), which allowed us to mine higher-order couplings of climate relationships and to capture the anomaly phases with which each climate factor is related to each other (Gonzalez et al, 2013) (Sect. 2.1)
Summary
The climate system is inherently complex, due to the existence of nonlinear interactions, or couplings, between its subsystems (e.g., the ocean and the atmosphere), global-scale temperature anomalies (e.g., El Niño–Southern Oscillation), and other climate behaviors. Comprehending these mechanisms is important due to the influence of rainfall variability in the region. Dry conditions (low rainfall anomaly) lead to the spread of meningitis as, under wet conditions, higher humidity during both the spring and summer seasons strongly reduces disease risk by decreasing the transmission capacity of the bacteria (Sultan et al, 2005) These issues make the Sahel vulnerable to fluctuations in rainfall, and provide motivation to improve domain scientists’ knowledge of the contributing factors (Tetteh, 2012). The identification and characterization of more comprehensive and predictive models of the physical phenomenon under study
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