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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| Format: | Article |
| Language: | English |
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Copernicus Publications
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| Series: | Annales Geophysicae |
| Online Access: | http://www.ann-geophys.net/12/903/1994/angeo-12-903-1994.html |
| 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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| ISSN: | 0992-7689 1432-0576 |