Accurately Measuring the Color of the Ocean on Earth and from Space: Uncertainties Revisited and A Report from the Community-Led Spectral Absorption Workshop to Update and Revise the NASA Inherent Optical Properties Protocol

The color of the ocean (apparent optical properties or AOPs) is determined by the spectral scattering and absorption of light by its dissolved and particulate constituents.The absorption and scattering properties of the water column are the so-called inherent optical properties

Improving Quantitative Laboratory Analysis of Phycobiliproteins to Provide High Quality Validation Data for Ocean Color Remote Sensing Algorithm

Identification and characterization of phytoplankton communities and their physiology is a primary aim of NASA's PACE satellite mission. The concentration and composition of phytoplankton pigments modulate the spectral distribution of light emanating from the ocean, which is measured by ocean color satellites, and thus provide critical information on phytoplankton community composition and physiological parameters. One diagnostic class of pigments not routinely well-characterized is the phycobiliproteins (PBPs), and NASA has a requirement to collect and distribute high quality in situ data in support of data product validation activities for ocean color missions. Phycobiliproteins are light-harvesting proteins that are the predominant photosynthetic pigments in some classes of phytoplankton including cyanobacteria, such as Synechococcus, Trichodesmium, and Microcystis. With the advance of hyperspectral ocean color sensors such as on PACE (expected to launch in late 2022), it is essential that we implement routine analysis of PBPs that satisfies several considerations: reproducible, high extraction efficiency for a variety of environments, and Suitable for large scale analysis. Published techniques for PBP analysis vary in recommendations for: collection, extraction, disruption mode, and analysis; evidence suggests the variation in results may depend at least in part on the species and even strain(s) of interest. Experiments that tested variations in these parameters have drawn very different conclusions regarding extraction efficiency and reproducibility. Cyanobacteria are more difficult to extract than other PBP-containing algae such as cryptophytes, but can be important primary producers. We used a cryptophyte (Rhodomonas salina) and cyanobacterium (Synechococcus sp.) to compare extraction efficiencies of water samples concentrated via centrifugation to filtered samples using two different extraction buffers (phosphate and asolectin-CHAPS). Samples were analyzed on a fluorometer configured for PC and PE detection. The results have important implications for collection and storage of samples for routine analysis; some previous studies (although not all) have suggested that filtered samples have a much lower extraction efficiency than whole water samples

An evaluation of methods for measuring phytoplankton and ecosystem status in the Chukchi Sea

This dissertation represents a three-pronged approach for evaluating ecosystem-level changes in the Chukchi Sea: 1) evaluation of uncertainties in field measurements of absorption 2) direct measurements of phytoplankton taxonomy and the community’s interaction with the environment and 3) apply existing and new remote sensing tools to measure ecosystem-level changes over large spatio-temporal scales. The first and final chapters provide context for the dissertation and conclusions. The second chapter quantifies the magnitude of uncertainty within multiple methods for measuring particle absorption. The light field exiting the surface ocean is measured by satellite instruments as ocean color and is impacted by water column absorption. Biogeochemically-relevant products, such as phytoplankton and particle absorption are derived from the light field using algorithms. Therefore, accurate measurements of absorption are critical to algorithm development and validation. I employed a multi-method approach to estimate the precision of measuring optical density of particles on a filter pad using two common spectrophotometric methods, and assessed the uncertainty of the computational techniques for estimating ap. The uncertainty ranged from 7.48%-119%. Values of ap at 555 nm and 670 nm exhibited the highest values of uncertainty. Poor performance of modeled ap compared to measured ap suggests the uncertainties are propagated into bio-optical algorithms. The third chapter investigates the consequences of earlier seasonal sea ice retreat and a longer sea-ice-free season on phytoplankton community composition. The timing of sea ice retreat, light availability and sea surface stratification largely control the phytoplankton community composition in the Chukchi Sea. This region is experiencing a significant warming trend, decrease in sea ice cover, and a documented decline in annual sea ice persistence and thickness over the past several decades. I applied multivariate statistical techniques to elucidate the mechanisms that relate environmental variables to phytoplankton community composition in the Chukchi Sea using data collected during a single field campaign in the summer of 2011. Three phytoplankton groups emerged that were correlated with sea ice, sea surface temperature, nutrients, salinity and light. The fourth chapter evaluates a new remote sensing tool for its utility to trace trends in ocean color over the summer months, 2003-2018, in the Chukchi Sea. The apparent visible wavelength reduces an ocean color spectrum to one number that represents the apparent color of the water. Median trend analysis of apparent visible wavelength and Chlorophyll a indicated that an ecosystem-level change in phytoplankton and nonalgal particles has occurred, correlated with the loss of sea ice

Revising upper-ocean sulfur dynamics near Bermuda : new lessons from 3 years of concentration and rate measurements

© The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Environmental Chemistry 13 (2016): 302-313, doi:10.1071/EN15045.Oceanic biogeochemical cycling of dimethylsulfide (DMS), and its precursor dimethylsulfoniopropionate (DMSP), has gained considerable attention over the past three decades because of the potential role of DMS in climate mediation. Here we report 3 years of monthly vertical profiles of organic sulfur cycle concentrations (DMS, particulate DMSP (DMSPp) and dissolved DMSP (DMSPd)) and rates (DMSPd consumption, biological DMS consumption and DMS photolysis) from the Bermuda Atlantic Time-series Study (BATS) site taken between 2005 and 2008. Concentrations confirm the summer paradox with mixed layer DMS peaking ~90 days after peak DMSPp and ~50 days after peak DMSPp : Chl. A small decline in mixed layer DMS was observed relative to those measured during a previous study at BATS (1992–1994), potentially driven by long-term climate shifts at the site. On average, DMS cycling occurred on longer timescales than DMSPd (0.43 ± 0.35 v. 1.39 ± 0.76 day–1) with DMSPd consumption rates remaining elevated throughout the year despite significant seasonal variability in the bacterial DMSP degrader community. DMSPp was estimated to account for 4–5 % of mixed layer primary production and turned over at a significantly slower rate (~0.2 day–1). Photolysis drove DMS loss in the mixed layer during the summer, whereas biological consumption of DMS was the dominant loss process in the winter and at depth. These findings offer new insight into the underlying mechanisms driving DMS(P) cycling in the oligotrophic ocean, provide an extended dataset for future model evaluation and hypothesis testing and highlight the need for a reexamination of past modelling results and conclusions drawn from data collected with old methodologies.The authors acknowledge funding from the National Science Foundation (NSF) (OCE-0425166) and the Center for Microbial Oceanography Research and Education (CMORE) a NSF Science and Technology Center (EF-0424599)

Assessment of holographic microscopy for quantifying marine particle size and concentration

Holographic microscopy has emerged as a tool for in situ imaging of microscopic organisms and other particles in the marine environment: appealing because of the relatively larger sampling volume and simpler optical configuration compared to other imaging systems. However, its quantitative capabilities have so far remained uncertain, in part because hologram reconstruction and image recognition have required manual operation. Here, we assess the quantitative skill of our automated hologram processing pipeline (CCV Pipeline), to evaluate the size and concentration measurements of environmental and cultured assemblages of marine plankton particles, and microspheres. Over 1 million particles, ranging from 10 to 200 μm in equivalent spherical diameter, imaged by the 4‐Deep HoloSea digital inline holographic microscope (DIHM) are analyzed. These measurements were collected in parallel with a FlowCam (FC), Imaging FlowCytobot (IFCB), and manual microscope identification. Once corrections for particle location and nonuniform illumination were developed and applied, the DIHM showed an underestimate in ESD of about 3% to 10%, but successfully reproduced the size spectral slope from environmental samples, and the size distribution of cultures (Dunaliella tertiolecta, Heterosigma akashiwo, and Prorocentrum micans) and microspheres. DIHM concentrations (order 1 to 1000 particles ml−1) showed a linear agreement (r2 = 0.73) with the other instruments, but individual comparisons at times had large uncertainty. Overall, we found the DIHM and the CCV Pipeline required extensive manual correction, but once corrected, provided concentration and size estimates comparable to the other imaging systems assessed in this study. Holographic cameras are mechanically simple, autonomous, can operate at very high pressures, and provide a larger sampling volume than comparable lens‐based tools. Thus, we anticipate that these characterization efforts will be rewarded with novel discovery in new oceanic environments

Standards and practices for reporting plankton and other particle observations from images

This technical manual guides the user through the process of creating a data table for the submission of taxonomic and morphological information for plankton and other particles from images to a repository. Guidance is provided to produce documentation that should accompany the submission of plankton and other particle data to a repository, describes data collection and processing techniques, and outlines the creation of a data file. Field names include scientificName that represents the lowest level taxonomic classification (e.g., genus if not certain of species, family if not certain of genus) and scientificNameID, the unique identifier from a reference database such as the World Register of Marine Species or AlgaeBase. The data table described here includes the field names associatedMedia, scientificName/ scientificNameID for both automated and manual identification, biovolume, area_cross_section, length_representation and width_representation. Additional steps that instruct the user on how to format their data for a submission to the Ocean Biodiversity Information System (OBIS) are also included. Examples of documentation and data files are provided for the user to follow. The documentation requirements and data table format are approved by both NASA’s SeaWiFS Bio-optical Archive and Storage System (SeaBASS) and the National Science Foundation’s Biological and Chemical Oceanography Data Management Office (BCO-DMO).This report was an outcome of a working group supported by the Ocean Carbon and Biogeochemistry (OCB) project office, which is funded by the US National Science Foundation (OCE1558412) and the National Aeronautics and Space Administration (NNX17AB17G). AN, SB, and CP conceived and drafted the document. IC, IST, JF and HS contributed to the main body of the document as well as the example files. All members of the working group contributed to the content of the document, including the conceptualization of the data table and metadata format. We would also like thank the external reviewers Cecile Rousseaux (NASA GSFC), Susanne Menden-Deuer (URI) Frank Muller-Karger (USF), and Abigail Benson (USGS) for their valuable feedback

Effects of increased pCO2 and temperature on the North Atlantic spring bloom. III. Dimethylsulfoniopropionate

The CLAW hypothesis argues that a negative feedback mechanism involving phytoplankton- derived dimethylsulfoniopropionate (DMSP) could mitigate increasing sea surface temperatures that result from global warming. DMSP is converted to the climatically active dimethylsulfide (DMS), which is transferred to the atmosphere and photochemically oxidized to sulfate aerosols, leading to increases in planetary albedo and cooling of the Earth’s atmosphere. A shipboard incubation experiment was conducted to investigate the effects of increased temperature and pCO2 on the algal community structure of the North Atlantic spring bloom and their subsequent impact on particulate and dissolved DMSP concentrations (DMSPp and DMSPd). Under ‘greenhouse’ conditions (elevated pCO2; 690 ppm) and elevated temperature (ambient + 4°C), coccolithophorid and pelagophyte abundances were significantly higher than under control conditions (390 ppm CO2 and ambient temperature). This shift in phytoplankton community structure also resulted in an increase in DMSPp concentrations and DMSPp:chl a ratios. There were also increases in DMSP-lyase activity and biomass-normalized DMSP-lyase activity under ‘greenhouse’ conditions. Concentrations of DMSPd decreased in the ‘greenhouse’ treatment relative to the control. This decline is thought to be partly due to changes in the microzooplankton community structure and decreased grazing pressure under ‘greenhouse’ conditions. The increases in DMSPp in the high temperature and greenhouse treatments support the CLAW hypothesis; the declines in DMSPd do not

Ocean carbon from space: Current status and priorities for the next decade

The ocean plays a central role in modulating the Earth\u27s carbon cycle. Monitoring how the ocean carbon cycle is changing is fundamental to managing climate change. Satellite remote sensing is currently our best tool for viewing the ocean surface globally and systematically, at high spatial and temporal resolutions, and the past few decades have seen an exponential growth in studies utilising satellite data for ocean carbon research. Satellite-based observations must be combined with in-situ observations and models, to obtain a comprehensive view of ocean carbon pools and fluxes. To help prioritise future research in this area, a workshop was organised that assembled leading experts working on the topic, from around the world, including remote-sensing scientists, field scientists and modellers, with the goal to articulate a collective view of the current status of ocean carbon research, identify gaps in knowledge, and formulate a scientific roadmap for the next decade, with an emphasis on evaluating where satellite remote sensing may contribute. A total of 449 scientists and stakeholders participated (with balanced gender representation), from North and South America, Europe, Asia, Africa, and Oceania. Sessions targeted both inorganic and organic pools of carbon in the ocean, in both dissolved and particulate form, as well as major fluxes of carbon between reservoirs (e.g., primary production) and at interfaces (e.g., air-sea and land–ocean). Extreme events, blue carbon and carbon budgeting were also key topics discussed. Emerging priorities identified include: expanding the networks and quality of in-situ observations; improved satellite retrievals; improved uncertainty quantification; improved understanding of vertical distributions; integration with models; improved techniques to bridge spatial and temporal scales of the different data sources; and improved fundamental understanding of the ocean carbon cycle, and of the interactions among pools of carbon and light. We also report on priorities for the specific pools and fluxes studied, and highlight issues and concerns that arose during discussions, such as the need to consider the environmental impact of satellites or space activities; the role satellites can play in monitoring ocean carbon dioxide removal approaches; economic valuation of the satellite based information; to consider how satellites can contribute to monitoring cycles of other important climatically-relevant compounds and elements; to promote diversity and inclusivity in ocean carbon research; to bring together communities working on different aspects of planetary carbon; maximising use of international bodies; to follow an open science approach; to explore new and innovative ways to remotely monitor ocean carbon; and to harness quantum computing. Overall, this paper provides a comprehensive scientific roadmap for the next decade on how satellite remote sensing could help monitor the ocean carbon cycle, and its links to the other domains, such as terrestrial and atmosphere

Dedicated JPSS VIIRS Ocean Color Calibration/Validation Cruise

The NOAA/STAR ocean color team is focused on “end-to-end” production of high quality satellite ocean color products. In situ validation of satellite data is essential to produce the high quality, “fit for purpose” remotely sensed ocean color products that are required and expected by all NOAA line offices, as well as by external (both applied and research) users. In addition to serving the needs of its diverse users within the U.S., NOAA has an ever increasing role in supporting the international ocean color community and is actively engaged in the International Ocean-Colour Coordinating Group (IOCCG). The IOCCG, along with the Committee on Earth Observation Satellites (CEOS) Ocean Colour Radiometry Virtual Constellation (OCR-VC), is developing the International Network for Sensor Inter-comparison and Uncertainty assessment for Ocean Color Radiometry (INSITU-OCR). The INSITU-OCR has identified, amongst other issues, the crucial need for sustained in situ observations for product validation, with longterm measurement programs established and maintained beyond any individual mission. Recently, the NOAA/STAR Ocean Color Team has been making in situ validation measurements continually since the launch in fall 2011 of the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (SNPP) platform, part of the U.S. Joint Polar Satellite System (JPSS) program. NOAA ship time for the purpose of ocean color validation, however, had never been allocated until the cruise described herein. As the institutional lead for this cruise, NOAA/STAR invited external collaborators based on scientific objectives and existing institutional collaborations. The invited collaborators are all acknowledged professionals in the ocean color remote sensing community. Most of the cruise principal investigators (PIs) are also PIs of the VIIRS Ocean Color Calibration and Validation (Cal/Val) team, including groups from Stennis Space Center/Naval Research Laboratory (SSC/NRL) and the University of Southern Mississippi (USM); City College of New York (CCNY); University of Massachusetts Boston (UMB); University of South Florida (USF); University of Miami (U. Miami); and, the National Institute of Standards and Technology (NIST). These Cal/Val PIs participated directly, sent qualified researchers from their labs/groups, or else contributed specific instruments or equipment. Some of the cruise PIs are not part of the NOAA VIIRS Ocean Color Cal/Val team but were chosen to complement and augment the strengths of the Cal/Val team participants. Outside investigator groups included NASA Goddard Space Flight Center (NASA/GSFC), Lamont-Doherty Earth Observatory at Columbia University (LDEO), and the Joint Research Centre of the European Commission (JRC). This report documents the November 2014 cruise off the U.S. East Coast aboard the NOAA Ship Nancy Foster. This cruise was the first dedicated ocean color validation cruise to be supported by the NOAA Office of Marine and Air Operations (OMAO). A second OMAO-supported cruise aboard the Nancy Foster is being planned for late 2015. We at NOAA/STAR are looking forward to continuing dedicated ocean color validation cruises, supported by OMAO on NOAA vessels, on an annual basis in support of JPSS VIIRS on SNPP, J-1, J-2 and other forthcoming satellite ocean color missions from the U.S as well as other countries. We also look forward to working with the U.S. and the international ocean community for improving our understanding of global ocean optical, biological, and biogeochemical properties.JRC.H.1-Water Resource

PACE Technical Report Series, Volume 7: Ocean Color Instrument (OCI) Concept Design Studies

Extending OCI hyperspectral radiance measurements in the ultraviolet to 320 nm on the blue spectrograph enables quantitation of atmospheric total column ozone (O3) for use in ocean color atmospheric correction algorithms. The strong absorption by atmospheric ozone below 340 nm enables the quantification of total column ozone. Other applications are possible but were not investigated due to their exploratory nature and lower priority.The first step in the atmospheric correction processing, which converts top-of-the-atmosphere radiances to water-leaving radiances, is removal of the absorbance by atmospheric trace gases such as water vapor, oxygen, ozone and nitrogen dioxide. Details of the atmospheric correction process currently used by the Ocean Biology Processing Group (OBPG) and will be employed for PACE with appropriate modifications, are described by Mobley et al. [2016]. Atmospheric ozone absorbs within the visible to near-infrared spectrum between ~450 nm and 800nm and most appreciably between 530 nm and 650 nm, a spectral region critical for maintaining NASA's chlorophyll-a climate data record and for PACE algorithms planned to characterize phytoplankton community composition and other ocean color products.While satellite-based observations will likely be available during PACE's mission lifetime, the difference in acquisition time with PACE, the coarseness in their spatial resolution, and differences in viewing geometries will introduce significant levels of uncertainties in PACE ocean color data products