Earth science data records derived from ocean color satellite products form an important source of information for studying and monitoring global ocean biogeochemical processes. These products, such as the chlorophyll-a concentration, are generated from the primary ocean color product - spectral water-leaving radiance - through bio-optical algorithms. The validity or accuracy of these derived products has historically been evaluated by comparing them with in situ measurements of the same property at discrete locations. Factors which collectively contribute to the overall uncertainty budget of the products include algorithm errors, radiance errors from atmospheric correction and sensor calibration, and match-up errors resulting from time and space mismatches. These error sources are not constant over space and time, and vary among optical environments in the oceans. We have developed a method based on the concept of optical water types for mapping ocean color product uncertainties, and we have demonstrated its application to estimate the MODIS chlorophyll product uncertainty. We are proposing to adapt this method to other ocean color satellite products with the end result of producing uncertainty maps for a suite of products. The advantage gained with our proposed method is that it can be applied to any ocean color satellite data to map uncertainty at the same scale as the radiance measurements.
Project PI: Timothy Moore/University of New Hampshire
Phone: (603) 862-0690
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