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...

Full description

Bibliographic Details
Published in:Annales Geophysicae
Main Author: Dobrovolski, S. G.
Format: Article in Journal/Newspaper
Language:English
Published: Springer Verlag 1994
Subjects:
article
Verlagsveröffentlichung
Antarctic
Antarc*
Online Access:https://doi.org/10.1007/s00585-994-0903-9
https://noa.gwlb.de/receive/cop_mods_00038087
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.

Similar Items