Abstract

Abstract This paper describes the subjective interpolation method (SIM) for generating three-dimensional temperature distributions from remotely sensed sea surface temperature (SST) fields. SIM incorporates MATLAB-based cloud removal software and a method of generating synthetic temperature profiles based on observations. This approach depends on the human facility for recognizing patterns in complex images. Three-dimensional temperature fields produced by SIM are compared to analogous fields based on optimal interpolation (OI) methods by using temperature fields interpolated by the two methods to initialize a baroclinic coastal ocean circulation model. The initial SST surface fields from both methods have a bias of less than −0.5°C and rms errors of less than 1.5°C. After running for 48 h, the bias and rms errors for the OI simulations are 0.3° and 1.2°C, respectively, whereas the same errors for the SIM run are 0.7° and 0.9°C. The OI and SIM approaches can be combined to allow preprocessing of SST data ...

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