Ocean color remote sensing has long been utilized as a fundamental research tool in the oceanographic investigations of coupled biological-physical processes. Despite numerous technical advances in the application of space borne ocean-viewing radiometers, host satellite platforms in a polar-orbiting configuration often render the temporal frequency of sensor data acquisition insufficient for studies of ocean processes that occur within increasingly smaller space-time scales. Whereas geostationary ocean color missions are presently the exception (GOCI) rather than the rule, this paper presents a method to convolve ocean reflectance data obtained from contemporary ocean-viewing multispectral radiometers (VIIRS, OLCI) with spectrally-limited Advanced Baseline Imager (ABI) data obtained from the GOES-R meteorological satellites. The method, Chromatic Domain Mapping (CDM), employs a colorimetry approach to visible range ocean reflectance data. The true color space is used as a frame-of-reference that is mapped by the dedicated yet temporally sparse ocean color sensors; coincident and spectrally coarse information from ABI is then used to estimate the evolution of the true color scene. The procedure results in very high resolution (~5 min) true color image sequences. Herein, example CDM applications of rapid frontal boundary evolution and feature displacement in the Gulf of Mexico are presented and future applications of this technique are discussed.

An increasing number of commercial nanosatellite-based Earth-observing sensors are providing high-resolution images for much of the coastal ocean region. Traditionally, to improve the accuracy of normalized water-leaving radiance ($n{L}_w$) estimates, sensor gains are computed using in-orbit vicarious calibration methods. The initial series of Planet nanosatellite sensors were primarily designed for land applications and are missing a second near-infrared band, which is typically used in selecting aerosol models for atmospheric correction over oceanographic regions. This study focuses on the vicarious calibration of Planet sensors and the duplication of its red band for use in both the aerosol model selection process and as input to bio-optical ocean product algorithms. Error measurements show the calibration performed well at the Marine Optical Buoy location near Lanai, Hawaii. Further validation was performed using in situ data from the Aerosol Robotic Network—Ocean Color platform in the northern Adriatic Sea. Bio-optical ocean color products were generated and compared with products from the Visual Infrared Imaging Radiometric Suite sensor. This approach for sensor gain generation and usage proved effective in increasing the accuracy of $n{L}_w$ measurements for bio-optical ocean product algorithms.

Oceanographic observations in the northern Gulf of Mexico captured an unusual combination of atmospheric forcing and shelf frontal dynamics that brought about the surface ventilation of sediment‐laden bottom waters. Colorimetric analysis of in situ optical data indicates a specific turquoise‐white color signature for turbid and low‐oxygen bottom waters that match a coincident shelf‐wide feature detected in MODIS satellite true color images. The physical processes leading to this ventilation event are simulated using the Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS), which includes an integrated surface wave model. The combined model‐data analysis suggests that low‐oxygen, bottom water ventilation may occur episodically during boreal spring and summer in the northern Gulf of Mexico following the passage of high‐energy atmospheric systems, and these events may be identified in the historical satellite record based on the unique bottom water optical characteristics.

Tropical cyclone induced phytoplankton productivity is examined using a tropical cyclone version of the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS®). A four-component Nutrient–Phytoplankton–Detritus biological model is integrated into COAMPS to create a fully integrated air-ocean-wave-biology model. This study investigates the upper ocean physical and biological states before and after Hurricane Ivan traversed the central Gulf of Mexico, in mid-September 2004. Elevated concentrations of surface chlorophyll-a appear in the simulation two days after the passage of the tropical cyclone, and these results are spatially and temporally coherent with Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data for this time period. Model results reveal enhancement of chlorophyll-a in submesoscale filaments on the periphery of a warm-core eddy that are dominated by large values of lateral strain and relative vorticity at the surface. The vertical circulation of the filament, with its associated upward vertical motion, permits surface ventilation of cold, nitrogen-rich water and subsequent stimulation of primary biological production. Here, we show for the first time that coupled biological-physical submesoscale processes may be simulated via a fully integrated air-sea-wave-biology tropical cyclone model that provides a mechanistic explanation of the conspicuous features revealed in satellite ocean color imagery following Ivan.