An Improved Spatial-Temporal Interpolation and Its Application in the Oceanic Observations
An improved spatial-temporal interpolation method, which can eliminate suspicious interpolated values effectively and consider both direction anisotropy and angle-based weight, is proposed to overcome the insufficiency of the traditional spatial-temporal interpolation. By using the traditional and improved spatial-temporal interpolation respectively, different weekly products of ocean temperature fields from surface to 2000 m are reconstructed in the Pacific Ocean for interpolated test based on the Argo observations, and then the reconstructed products are validated in comparison with other gridded product and in-situ observations. The results show that the error of reconstructed data by the improved method is smaller than that of the traditional method apparently, and the improved interpolation can eliminate the suspicious estimated data effectively and improve the interpolated results greatly. The improved interpolation method is very effective to interpolate scattered data onto regular grids for data reconstruction.
KeywordsSpatial-temporal weighted interpolation Argo observation Anisotropy Data reconstruction Angle-based weight
The Argo data used in this paper were collected and made freely available by the International Argo Program. Discussion with Prof. Wang Guihua at Fudan University is appreciated.
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