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Abstract Phytoplankton respond to physical and hydrographic forcing on time and space scales up to and including those relevant to climate change. Quantifying changes in phytoplankton communities over these scales is essential for predicting ocean food resources, occurrences of harmful algal blooms, and carbon and other elemental cycles, among other predictions. However, one of the best tools for quantifying phytoplankton communities across relevant time and space scales, ocean color sensors, is constrained by its own spectral capabilities and availability of adequately vetted and relevant optical models. To address this later shortcoming, greater than fifty strains of phytoplankton, from a range of taxonomic lineages, geographic locations, and time in culture, alone and in mixtures, were grown to exponential and/or stationary phase for determination of hyperspectral UV-VIS absorption coefficients, multi-angle and multi-spectral backscatter coefficients, volume scattering functions, particle size distributions, pigment content, and fluorescence. The aim of this publication is to share these measurements to expedite their utilization in the development of new optical models for the next generation of ocean color satellites.

Arctic landscapes are warming and becoming wetter due to changes in precipitation and the timing of snowmelt which consequently alters seasonal runoff and river discharge patterns. These changes in hydrology lead to increased mobilization and transport of terrestrial dissolved organic matter (DOM) to Arctic coastal seas where significant impacts on biogeochemical cycling can occur. Here, we present measurements of dissolved organic carbon (DOC) and chromophoric DOM (CDOM) in the Yukon River-to-Bering Sea system and two river plumes on the Alaska North Slope which flow into the Beaufort Sea. Our sampling characterized optical and biogeochemical properties of DOM during high and low river discharge periods for the Yukon River-Bering Sea system. The average DOC concentration at the multiple Yukon River mouths ranged from a high of 10.36 mg C L-1 during the ascending limb of the 2019 freshet (late May), 6.4 mg C L-1 during the descending limb of the 2019 freshet (late June), and a low of 3.86 mg C L-1 during low river discharge in August 2018. CDOM absorption coefficient at 412 nm (aCDOM(412)) averaged 8.23 m-1, 5.07 m-1, and 1.9 m-1, respectively. Several approaches to model DOC concentration based on its relationship with CDOM properties demonstrated cross-system seasonal and spatial robustness for these Arctic coastal systems despite spanning an order of magnitude decrease in DOC concentration from the lower Yukon River to the Northern Bering Sea as well as the North Slope systems. “Snapshot” fluxes of DOC and CDOM across the Yukon River Delta to Norton Sound were calculated from our measurements and modeled water fluxes forced with upstream USGS river gauge data. Our findings suggest that during high river flow, DOM reaches the delta largely unaltered by inputs or physical and biogeochemical processing and that the transformations of Yukon River DOM largely occur in the plume. However, during low summer discharge, multiple processes including local precipitation events, microbial decomposition, photochemistry, and likely others can alter the DOM properties within the lower Yukon River and Delta prior to flowing into Norton Sound.

Arctic Ocean physical and biogeochemical properties are strongly influenced by freshwater input from land and through the Bering Strait, where the mean currents transport water northward from the Bering Sea. The Yukon River is one of the largest rivers in North America and the Arctic, contributing large quantities of freshwater and terrigenous material to the coastal ocean in the northern Bering Sea. However, a detailed analysis of the coastal hydrodynamics at the outflow of the river has not been conducted in this remote but regionally important river. A three-dimensional hydrodynamic model was built to represent the lower Yukon River and coastal ocean for the ice-free months in 7 years. On average, a large anticyclonic eddy persisted at the main outflow of the Yukon that recirculates water back toward the coast where the currents converge to form a mean northward transport along the delta. Interannual spatial variance in salinity was relatively small, while there was substantial variance in u and v current velocity. u velocity spatial variance was correlated to the volume of freshwater discharge across years, while v velocity spatial variance was correlated to the N–S wind velocity. During strong wind events, plume structure was substantially altered: southerly winds deepened the plume and enhanced northward transport, while northerly winds shoaled and strengthened the pycnocline, and reversed the flow toward the south. The variability in plume dispersion on short time scales due to wind forcing has implications for where terrigenous material is processed in and settles out of the water column.

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will include a hyperspectral imaging radiometer to advance ecosystem monitoring beyond heritage retrievals of the concentration of surface chlorophyll and other traditional ocean color variables, offering potential for novel science and applications. PACE is the first NASA ocean color mission to occur under the agency’s new and evolving effort to directly engage practical end users prior to satellite launch to increase adoption of this freely available data toward societal challenges. Here we describe early efforts to engage a community of practice around marine food-related resource management, business decisions, and policy analysis. Obviously one satellite cannot meet diverse end user needs at all scales and locations, but understanding downstream needs helps in the assessment of information gaps and planning how to optimize the unique strengths of PACE data in combination with the strengths of other satellite retrievals, in situ measurements, and models. Higher spectral resolution data from PACE can be fused with information from satellites with higher spatial or temporal resolution, plus other information, to enable identification and tracking of new marine biological indicators to guide sustainable management. Accounting for the needs of applied researchers as well as non-traditional users of satellite data early in the PACE mission process will ultimately serve to broaden the base of informed users and facilitate faster adoption of the most advanced science and technology toward the challenge of mitigating food insecurity.

Space-based observations offer unique capabilities for studying spatial and temporal dynamics of the upper ocean inorganic carbon cycle and, in turn, supporting research tied to ocean acidification (OA). Satellite sensors measuring sea surface temperature, color, salinity, wind, waves, currents, and sea level enable a fuller understanding of a range of physical, chemical, and biological phenomena that drive regional OA dynamics as well as the potentially varied impacts of carbon cycle change on a broad range of ecosystems. Here, we update and expand on previous work that addresses the benefits of space-based assets for OA and carbonate system studies. Carbonate chemistry and the key processes controlling surface ocean OA variability are reviewed. Synthesis of present satellite data streams and their utility in this arena are discussed, as are opportunities on the horizon for using new satellite sensors with increased spectral, temporal, and/or spatial resolution. We outline applications that include the ability to track the biochemically dynamic nature of water masses, to map coral reefs at higher resolution, to discern functional phytoplankton groups and their relationships to acid perturbations, and to track processes that contribute to acid variation near the land-ocean interface.

Short-term (sub-diurnal) biological and biogeochemical processes cannot be fully captured by the current suite of polar-orbiting satellite ocean color sensors, as their temporal resolution is limited to potentially one clear image per day. Geostationary sensors, such as the Geostationary Ocean Color Imager (GOCI) from the Republic of Korea, allow the study of these short-term processes because their orbit permit the collection of multiple images throughout each day for any area within the sensor’s field of regard. Assessing the capability to detect sub-diurnal changes in in-water properties caused by physical and biogeochemical processes characteristic of open ocean and coastal ocean ecosystems, however, requires an understanding of the uncertainties introduced by the instrument and/or geophysical retrieval algorithms. This work presents a study of the uncertainties during the daytime period for an ocean region with characteristically low-productivity with the assumption that only small and undetectable changes occur in the in-water properties due to biogeochemical processes during the daytime period. The complete GOCI mission data were processed using NASA’s SeaDAS/l2gen package. The assumption of homogeneity of the study region was tested using three-day sequences and diurnal statistics. This assumption was found to hold based on the minimal diurnal and day-to-day variability in GOCI data products. Relative differences with respect to the midday value were calculated for each hourly observation of the day in order to investigate what time of the day the variability is greater. Also, the influence of the solar zenith angle in the retrieval of remote sensing reflectances and derived products was examined. Finally, we determined that the uncertainties in water-leaving “remote-sensing„ reflectance (Rrs) for the 412, 443, 490, 555, 660 and 680 nm bands on GOCI are 8.05 × 10−4, 5.49 × 10−4, 4.48 × 10−4, 2.51 × 10−4, 8.83 × 10−5, and 1.36 × 10−4 sr−1, respectively, and 1.09 × 10−2 mg m−3 for the chlorophyll-a concentration (Chl-a), 2.09 × 10−3 m−1 for the absorption coefficient of chromophoric dissolved organic matter at 412 nm (ag (412)), and 3.7 mg m−3 for particulate organic carbon (POC). These Rrs values can be considered the threshold values for detectable changes of the in-water properties due to biological, physical or biogeochemical processes from GOCI.

A Global Ocean Carbon Algorithm Database (GOCAD) has been developed from over 500 oceanographic field campaigns conducted worldwide over the past 30 years including in situ reflectances and coincident satellite imagery, multi- and hyperspectral Chromophoric Dissolved Organic Matter (CDOM) absorption coefficients from 245⁻715 nm, CDOM spectral slopes in eight visible and ultraviolet wavebands, dissolved and particulate organic carbon (DOC and POC, respectively), and inherent optical, physical, and biogeochemical properties. From field optical and radiometric data and satellite measurements, several semi-analytical, empirical, and machine learning algorithms for retrieving global DOC, CDOM, and CDOM slope were developed, optimized for global retrieval, and validated. Global climatologies of satellite-retrieved CDOM absorption coefficient and spectral slope based on the most robust of these algorithms lag seasonal patterns of phytoplankton biomass belying Case 1 assumptions, and track terrestrial runoff on ocean basin scales. Variability in satellite retrievals of CDOM absorption and spectral slope anomalies are tightly coupled to changes in atmospheric and oceanographic conditions associated with El Niño Southern Oscillation (ENSO), strongly covary with the multivariate ENSO index in a large region of the tropical Pacific, and provide insights into the potential evolution and feedbacks related to sea surface dissolved carbon in a warming climate. Further validation of the DOC algorithm developed here is warranted to better characterize its limitations, particularly in mid-ocean gyres and the southern oceans.