A Satellite Covariance-Based Method to Support AERONET Ocean Color Validation Activities

Abstract

The objective is to determine the location(s) in any given oceanic area during different temporal periods where in situ sampling for Calibration/Validation (Cal/Val) provides the greatest improvement in retrieving accurate radiometric and derived product data (lowest uncertainties). A method is presented to merge satellite imagery with in situ samples and to determine the best in situ sampling strategy suitable for satellite Cal/Val efforts. This methodology uses satellite acquisitions to build a covariance matrix encoding the spatio-temporal variability of the area of interest. The covariance matrix is used in a Bayesian framework to merge satellite and in situ data providing a product with lower uncertainty. The best in situ location for Cal/Val efforts is retrieved using a design principle (A-optimum design) that looks for minimizing the estimated variance of the merged product.