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Reconstructing the Subsurface Temperature Field by Using Sea Surface Data Through Self-Organizing Map Method
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DOI：10.1109/LGRS.2018.2866237.png)
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Abstract
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Self-organizing map (SOM) method combined with the empirical orthogonal function was used to reconstruct the subsurface temperature field by using sea surface data in the Northwestern Pacific Ocean. In contrast to the traditional method, SOM method can extract nonlinear relations from the data and is more suitable for nonlinear dynamics in the ocean. Error statistics show that SOM method provides reconstructions of the subsurface temperature field with the majority of relative errors below 20% at 0-1000-m depth.
Keywords:
Empirical orthogonal function (EOF)
sea surface data
self-organizing map (SOM)
subsurface temperature reconstruction
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