2008 An empirical stochastic model of sea-surface temperature and sea-level wind. Unpublished work
This study employs NASA’s recent satellite measurements of sea-surface temperature (SST) and sea-level wind (SLW) with missing data filled-in by Singular Spectrum Analysis (SSA), to construct empirical models that capture both intrinsic and SST-dependent aspects of SLW variability. The model constru...
Main Authors: | , , , |
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Other Authors: | |
Format: | Text |
Language: | English |
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Online Access: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.151.1232 http://www.atmos.ucla.edu/tcd/PREPRINTS/OceanModelling_Kravtsov_etal2009.pdf |
Summary: | This study employs NASA’s recent satellite measurements of sea-surface temperature (SST) and sea-level wind (SLW) with missing data filled-in by Singular Spectrum Analysis (SSA), to construct empirical models that capture both intrinsic and SST-dependent aspects of SLW variability. The model construction methodology uses a number of algorithmic innovations that are essential in providing stable estimates of model’s propagator. The best model tested herein is able to faithfully represent the time scales and spatial patterns of anomalies associated with a number of distinct processes. These processes range from the daily synoptic variability to interannual signals presumably associated with oceanic or coupled dynamics. Comparing the simulations of an SLW model forced by the observed SST anomalies with the simulations of an SLW-only model provides preliminary evidence for the climatic behavior characterized by the ocean driving the atmosphere in the Southern Ocean region. |
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