Ocean and Polar Research
- 제23권2호
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- Pages.189-194
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- 2001
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- 1598-141X(pISSN)
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- 2234-7313(eISSN)
Prediction of SST for Operational Ocean Prediction System
초록
A practical algorithm for prediction of the sea surface temperatures (SST)from the satellite remote sensing data is presented in this paper. The fluctuations of SST consist of deterministic normals and stochastic anomalies. Due to large thermal inertia of sea water, the SST anomalies can be modelled by autoregressive or Markov process, and its near future values can be predicted provided the recent values of SST are available. The actual SST is predicted by superposing the pre-known SST normals and the predicted SST anomalies. We applied this prediction algorithm to the NOAA AVHRR weekly SST data for 18 years (1981-1998) in the seas adjacent to Korea (115-