Improvement on Masking and Flagging Technique on Reducing SST Residual

Sea surface temperature (SST) retrieval depends greatly on algorithm coefficient estimation. However, the algorithm coefficient estimation is relevant to pixel data chosen for multiple regressions analysis. Therefore the proper masking and flagging procedures will ensure that only the good pixels are only chosen for algorithm coefficient analysis. In this paper, new techniques of masking and flagging test were studied. The techniques were based on the characteristics of sea surface temperature at equatorial regions. Statistical techniques included digital satellite data sampling, normality, symmetrical, and homogeneity tests on small-scale and large-scale extraction of group pixels. The SST algorithm was calibrated by correlating in-situ SST data with thermal bands brightness temperatures and sensor zenith angle. In-situ SST data was acquired by drift buoy data, Research on the SEa and islands of Malaysia (ROSES) project and moored buoy data, Malaysia Meteorology Departments. The validation of algorithm with in-situ data showed that combination of of conventional techniques and improved techniques reduced the SST residuals and increase the correlations coefficients.