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Inferring interactions between processes promises deeper insight intomechanisms underlying network phenomena. Renormalised partial directedcoherence (rPDC) is a frequency-domain representation of the concept of Grangercausality while directed partial correlation (DPC) is an alternative approachfor quantifying Granger causality in the time domain. Both methodologies havebeen successfully applied to neurophysiological signals for detecting directedrelationships. This paper introduces their application to climatological timeseries. We first discuss the application to ENSO -- Monsoon interaction, andthen apply the methodologies to the more challenging air-sea interaction in theSouth Atlantic Convergence Zone (SACZ). While in the first case the resultsobtained are fully consistent with present knowledge in climate modeling, inthe second case the results are, as expected, less clear, and to fullyelucidate the SACZ air-sea interaction, further investigations on thespecificity and sensitivity of these methodologies are needed.

Inferring directed climatic interactions with renormalized partial directed coherence and directed partial correlation