South Atlantic sea surface temperature anomalies and air-sea interactions: stochastic models

Data on the South Atlantic monthly sea surface temperature anomalies (SSTA) are analysed using the maximum-entropy method. It is shown that the Markov first-order process can describe, to a first approximation, SSTA series. The region of maximum SSTA values coincides with the zone of maximum residua...

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Bibliographic Details
Published in:Annales Geophysicae
Main Author: S. G. Dobrovolski
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 1994
Subjects:
Science
Q
Physics
QC1-999
Geophysics. Cosmic physics
QC801-809
Antarctic
Antarc*
Online Access:https://doi.org/10.1007/s00585-994-0903-9
https://doaj.org/article/b03e8e27b45f4a65a66c460d0f3abe18
Description
Summary:Data on the South Atlantic monthly sea surface temperature anomalies (SSTA) are analysed using the maximum-entropy method. It is shown that the Markov first-order process can describe, to a first approximation, SSTA series. The region of maximum SSTA values coincides with the zone of maximum residual white noise values (sub-Antarctic hydrological front). The theory of dynamic-stochastic climate models is applied to estimate the variability of South Atlantic SSTA and air-sea interactions. The Adem model is used as a deterministic block of the dynamic-stochastic model. Experiments show satisfactorily the SSTA intensification in the sub-Antarctic front zone, with appropriate standard deviations, and demonstrate the leading role of the abnormal drift currents in these processes.

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