Near-Real-Time Multi-Sensor Global Ocean Color Data and Applications

In this paper, we provide an overview of the progress on producing accurate global ocean color products from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) and NOAA-20 satellites. VIIRS global ocean color products include normalized water-leaving radiance spectra nL_w(λ), chlorophyll-a (Chl-a) concentration, water diffuse attenuation coefficients at 490 nm, K_d(490), and at the domain of photosynthetically available radiation (PAR), K_d(PAR). However, satellite-derived daily ocean color images on either SNPP or NOAA-20 have significant data gaps due to some limitations, e.g., sensor swath width, data over high sensor-zenith angle, high sun glint, heavy dust contamination, clouds, etc. Merging VIIRS ocean color products derived from the SNPP and NOAA-20 significantly improves the spatial coverage of daily data images. The two VIIRS sensors on SNPP and NOAA-20 have similar sensor characteristics, and ocean color products are derived using the same Multi-Sensor Level-1 to Level-2 (MSL12) ocean color data processing system. Therefore, the directly merged VIIRS global Chl-a data from the two sensors have high data quality with consistent statistical property and accuracy. In addition, near-real-time global gap-free Chl-a data are being generated using the Data Interpolating Empirical Orthogonal Functions (DINEOF) method. We describe in detail an approach to remove data gaps of missing pixels from the merged SNPP and NOAA-20 ocean color data. Some applications using the global daily gap-free ocean color product are also presented and discussed. Ocean color data merging examples from an additional sensor of the Ocean and Land Colour Instrument (OLCI) on Sentinel-3A (three sensors) are also provided.