Journal of Geophysical Research Oceans · 2021 · 12 citations · 49 references
Natural SciencesEarth SciencesOceanographyOcean CirculationOcean WavesPhysical OceanographyClimate TeleconnectionsEl Niño-southern OscillationRossby WavesClimate Variability ModesEnso TeleconnectionsEquatorial Pacific Ocean DynamicsInterannual Variability AnalysisOceanic Rossby WavesRossby Wave TelesconnectionsSea Surface Height MappingSea Surface Height Observations
Abstract The latitude of separation of the Brazil Current (LSBC) variability is analyzed with a view to unveiling the physical mechanisms that modulate the turning point of the Brazil Current at low frequencies. The global ocean reanalysis ORAP5.0 spanning the period 1979–2013 is employed for this purpose. Three characteristic periodicities of the LSBC variability are found on the basis of a Singular Spectrum Analysis: 2, 4 and 10 years. Lagged sea surface height (SSH) correlation maps relate these modulations to Rossby wave propagation. According to these maps, the biennial signal might be triggered by the Atlantic Niño and the Indian Ocean Dipole. In the last case, SSH anomalies propagate around the southern tip of Africa, connecting the Indian and Atlantic oceans. Correlation maps suggest that the 4‐year signal is triggered by both the Atlantic Niño and the ENSO in the equatorial Pacific Ocean. The ENSO‐related anomalies travel through the Indonesian Throughflow along the western Australian coast, where Rossby waves are excited. These anomalies propagate to the eastern coast of Madagascar and feed into the Agulhas Current, eventually leaking into the Atlantic basin. Finally, the decadal signal is associated to the leading mode of decadal variability of the South Pacific Ocean. SSH propagating patterns derived from ORAP5.0 data are also obtained with satellite altimetry during the overlapping period (1993–2013), which strengthens confidence in our results. The association of the LSCB modulations to characteristic climate variability modes suggests that the position of the LSCB could be predicted.
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ADVANCED SPECTRAL METHODS FOR CLIMATIC TIME SERIES
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