Apparent optical properties of the Canadian Beaufort Sea – Part 2: The 1% and 1 cm perspective in deriving and validating AOP data products
- 1NASA Goddard Space Flight Center, Ocean Ecology Laboratory, Greenbelt, Maryland 20771, USA
- 2Biospherical Instruments Inc., 5340 Riley Street, San Diego, California 92110, USA
- 3Université Laval, Avenue de la Médecine, Québec City, QC G1V 0A6, Canada
Abstract. A next-generation in-water profiler designed to measure the apparent optical properties (AOPs) of seawater was developed and validated across a wide dynamic range of in-water properties. The new free-falling instrument, the Compact-Optical Profiling System (C-OPS), was based on sensors built with a cluster of 19 state-of-the-art microradiometers spanning 320–780 nm and a novel kite-shaped backplane. The new backplane includes tunable ballast, a hydrobaric buoyancy chamber, plus pitch and roll adjustments, to provide unprecedented stability and vertical resolution in near-surface waters. A unique data set was collected as part of the development activity plus the first major field campaign that used the new instrument, the Malina expedition to the Beaufort Sea in the vicinity of the Mackenzie River outflow. The data were of sufficient resolution and quality to show that errors – more correctly, uncertainties – in the execution of data sampling protocols were measurable at the 1% and 1 cm level with C-OPS. A theoretical sensitivity analysis as a function of three water types established by the peak in the remote sensing reflectance spectrum, Rrs(λ), revealed which water types and which parts of the spectrum were the most sensitive to data acquisition uncertainties. Shallow riverine waters were the most sensitive water type, and the ultraviolet and near-infrared spectral end members, which are critical to next-generation satellite missions, were the most sensitive parts of the spectrum. The sensitivity analysis also showed how the use of data products based on band ratios significantly mitigated the influence of data acquisition uncertainties. The unprecedented vertical resolution provided high-quality data products, which supported an alternative classification capability based on the spectral diffuse attenuation coefficient, Kd(λ). The Kd(320) and Kd(780) data showed how complex coastal systems can be distinguished two-dimensionally and how near-ice water masses are different from the neighboring open ocean. Finally, an algorithm for predicting the spectral absorption due to colored dissolved organic matter (CDOM), denoted aCDOM(λ), was developed using the Kd(320) / Kd(780) ratio, which was based on a linear relationship with respect to aCDOM(440). The robustness of the approach was established by expanding the use of the algorithm to include a geographically different coastal environment, the Southern Mid-Atlantic Bight, with no significant change in accuracy (approximately 98% of the variance explained). Alternative spectral end members reminiscent of next-generation (340 and 710 nm) as well as legacy satellite missions (412 and 670 nm) were also used to accurately derive aCDOM(440) from Kd(λ) ratios.