Modeling Ocean Chlorophyll Distributions by Penalizing the Blending Technique

Mathias A. Onabid, Simon Wood

Department of Mathematical Sciences, University of Bath, Bath, UK.
Department of Maths-Computer Science, Faculty of Sciences, University of Dschang, Dschang, Cameroon.

DOI: 10.4236/ojms.2014.41004                

Abstract

Disparities between the in situ and satellite values at the positions where in situ values are obtained have been the main handicap to the smooth modeling of the distribution of ocean chlorophyll. The blending technique and the thin plate regression spline have so far been the main methods used in an attempt to calibrate ocean chlorophyll at positions where the in situ field could not provide value. In this paper, a combination of the two techniques has been used in order to provide improved and reliable estimates from the satellite field. The thin plate regression spline is applied to the blending technique by imposing a penalty on the differences between the satellite and in situ fields at positions where they both have observations. The objective of maximizing the use of the satellite field for prediction was outstanding in a validation study where the penalized blending method showed a remarkable improvement in its estimation potentials. It is hoped that most analysis on primary productivity and management in the ocean environment will be greatly affected by this result, since chlorophyll is one of the most important components in the formation of the ocean life cycle.

Keywords

In Situ, Satellite; Ship and Buoy; Penalized Regression Spline; Penalty; Penalized Blending

Conflicts of Interest

The authors declare no conflicts of interest.

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