Inferring interactions between processes promises deeper insight into mechanisms underlying network phenomena. Renormalised partial directed coherence is a frequency-domain representation of the concept of Granger causality, while directed partial correlation is an alternative approach for quantifying Granger causality in the time domain. Both methodologies have been successfully applied to neurophysiological signals for detecting directed relationships. This paper introduces their application to climatological time series. We first discuss the application to El Niño–Southern Oscillation—Monsoon interaction and then apply the methodologies to the more challenging air-sea interaction in the South Atlantic Convergence Zone (SACZ). In the first case, the results obtained are fully consistent with the present knowledge in climate modeling, while in the second case, the results are, as expected, less clear, and to fully elucidate the SACZ air-sea interaction, further investigations on the specificity and sensitivity of these methodologies are needed.