Identification of Linear and Nonlinear Causal Relationship Among
Low-Frequency Climatic Phenomena in the Last Millennium
Abstract
Considering that the instrumental climate record covers a period of
about a century, it becomes necessary to use paleoclimatic
records/models to explore the stability of the climatic variability and
investigate the robustness of the teleconnections of the past. It is
important to identify if the observed patterns in the current period
persist over the last millennium when the changes in the orbital induced
climate variations are negligible. In several studies on climatic
causality crosscorrelation functions are used and the analysis is based
on the relationship between atmospheric structures in pairs, a procedure
that has several limitations in the elucidation of the network of
possible connections. To mitigate these barriers, this work uses Partial
Directed Coherence (PDC) and kernel nonlinear Partial Directed Coherence
(knPDC) to allow the inference of the linear or nonlinear couplings
between the climatological patterns, respectively. Connections between
the two groups of climatic indicators in the last millennium were
observed from 850 to 1850. The first group comprises the El
Nino-Southern Oscillation (ENSO), Atlantic Multidecadal Oscillation
(AMO) and Atlantic Interhemispheric SST Gradient (GTA) and the second,
Antarctic Oscillation (AAO), El Nino-Southern Oscillation (ENSO),
Pacific-South American (PSA1, EOF2) and QuasiBiennial Oscillation (QBO).
The climate indices were computed from a weighted average set of climate
model simulations of PMIP3, which represent simulations oriented to the
past climate in the climate projection models of CMIP5. For the first
group, no significant results were observed on the low-frequency band,
observing only linear relationships between the Pacific and Atlantic
Oceans. For the second group, the causal analysis point to linear
relationships between ENSO↔AAO, and nonlinear between ENSO↔PSA in the
low and high band and QBO↔AAO, QBO↔ENSO and QBO↔PSA in the low-frequency
band. In summary, the results indicate a higher nonlinear connection
between low-frequency phenomena.