Journal of Geodesy

, Volume 83, Issue 5, pp 469–476 | Cite as

Forecasting sea level anomalies from TOPEX/Poseidon and Jason-1 satellite altimetry

Original Article

Abstract

This paper aims at the prediction of both global mean sea level anomalies (SLAs) and gridded SLA data in the east equatorial Pacific obtained from TOPEX/Poseidon and Jason-1 altimetric measurements. The first prediction technique (denoted as LS) is based on the extrapolation of a polynomial-harmonic deterministic least-squares model describing a linear trend, annual and semi-annual oscillations. The second prediction method (denoted as LS + AR) is a combination of the extrapolation of a polynomial-harmonic model with the autoregressive forecast of LS residuals. In the case of forecasting global mean SLA data, both techniques allow one to compute the predictions of comparable accuracy (root mean square error for 1-month in the future is of 0.5 cm). In the case of predicting gridded SLA data, the LS + AR prediction method gains significantly better prediction accuracy than the accuracy obtained by the LS technique during El Niño 1997/1998, La Niña 1998/1999 and during normal conditions.

Keywords

Sea level anomaly Satellite altimetry Prediction Autoregressive process Time series 

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Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  1. 1.Space Research CentrePolish Academy of SciencesWarsawPoland
  2. 2.Department of Geomorphology, Institute of Geography and Regional DevelopmentUniversity of WrocławWrocławPoland

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