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首页> 外文期刊>Journal of Geodesy >Forecasting sea level anomalies from TOPEX/Poseidon and Jason-1 satellite altimetry
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Forecasting sea level anomalies from TOPEX/Poseidon and Jason-1 satellite altimetry

机译：通过TOPEX / Poseidon和Jason-1卫星测高仪预测海平面异常

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摘要

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 Nino 1997/1998, La Nina 1998/1999 and during normal conditions.
机译：本文旨在预测从TOPEX / Poseidon和Jason-1高空测量获得的赤道东太平洋全球平均海平面异常（SLA）和网格化SLA数据。第一种预测技术（表示为LS）是基于多项式谐波确定性最小二乘模型的外推法，该模型描述了线性趋势，年度和半年度振荡。第二种预测方法（表示为LS + AR）是多项式谐波模型的外推与LS残差的自回归预测的组合。在预测全球平均SLA数据的情况下，两种技术都允许一种计算可比较精度的预测（未来1个月的均方根误差为0.5 cm）。在预测网格化SLA数据的情况下，LS + AR预测方法比El Nino 1997/1998，La Nina 1998/1999和正常条件下通过LS技术获得的精度要好得多。

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