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The ability to generate chlorophyll a (Chl a) assessments from ocean color orbital sensors, such as VIIRS and MODIS, that satisfy the requirements to be climate-quality data record (CDR) quality is contingent in part on the quality of the in situ ground or sea truth observations that serve as datasets for vicarious calibration and algorithm validation activities. NASA has a mandate to collect, analyze, and distribute in situ data of the highest possible quality with documented uncertainties and in keeping with established performance metrics. Using a dataset of over 18,000 HPLC phytoplankton pigment samples representing water collected in all major ocean basins analyzed a central laboratory (Field Support Group (FSG) of the Ocean Ecology Laboratory (OEL) at NASA Goddard Space Flight Center (GSFC)), we performed an assessment of the global precision among sample replicates of Chl a as well as major accessory pigments. We investigated the impacts of filtration volume, water basin, collection technique, pigment concentration, and different filtration volumes for replicate filters on replicate filter precision, as well as investigating any pigment-specific differences. Our results quantify sample variability with the goal of understanding any systemic biases or biogeographic influences.

The types and abundance of phytoplankton is largely controlled by availability of sunlight and bioavailable nutrients. Phytoplankton require essential nutrients including nitrate, phosphate, and silicate to grow, so understanding the role of these macronutrients in limiting the growth phytoplankton communities—and the way this may differ depending on community composition—is key to understanding the controls on phytoplankton biomass and community structure. We aimed to explore how the availability of these nutrients affects the health and composition of phytoplankton communities by conducting a series of nutrient amendment experiments (NAEs) with samples from the Western Tropical North Atlantic, which is heavily influenced by the nutrient-rich, low salinity waters of the Amazon River Plume. These experiments, conducted at five locations in and around the plume, provide greater resolution and further our understanding about the ways nutrients affect communities in dynamic coastal regions.

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.

Ten international laboratories specializing in the determination of marine pigment concentrations using high performance liquid chromatography (HPLC) were intercompared using in situ samples and a mixed pigment sample. Although prior Sea-viewing Wide Field-of-view Sensor (SeaWiFS) High Performance Liquid Chromatography (HPLC) Round-Robin Experiment (SeaHARRE) activities conducted in open-ocean waters covered a wide dynamic range in productivity, and some of the samples were collected in the coastal zone, none of the activities involved exclusively coastal samples. Consequently, SeaHARRE-4 was organized and executed as a strictly coastal activity and the field samples were collected from primarily eutrophic waters within the coastal zone of Denmark. The more restrictive perspective limited the dynamic range in chlorophyll concentration to approximately one and a half orders of magnitude (previous activities covered more than two orders of magnitude). The method intercomparisons were used for the following objectives: a) estimate the uncertainties in quantitating individual pigments and higher-order variables formed from sums and ratios; b) confirm if the chlorophyll a accuracy requirements for ocean color validation activities (approximately 25%, although 15% would allow for algorithm refinement) can be met in coastal waters; c) establish the reduction in uncertainties as a result of applying QA procedures; d) show the importance of establishing a properly defined referencing system in the computation of uncertainties; e) quantify the analytical benefits of performance metrics, and f) demonstrate the utility of a laboratory mix in understanding method performance. In addition, the remote sensing requirements for the in situ determination of total chlorophyll a were investigated to determine whether or not the average uncertainty for this measurement is being satisfied.

Seven international laboratories specializing in the determination of marine pigment concentrations using high performance liquid chromatography (HPLC) were intercompared using in situ samples and a mixed pigment sample. The field samples were collected primarily from oligotrophic waters, although mesotrophic and eutrophic waters were also sampled to create a dynamic range in chlorophyll concentration spanning approximately two orders of magnitude (0.020 1.366 mg m^{-3}) The intercomparisons were used to establish the following: a) the uncertainties in quantitating individual pigments and higher-order variables (sums, ratios, and indices); b) the reduction in uncertainties as a result of applying quality assurance (QA) procedures; c) the importance of establishing a properly defined referencing system in the computation of uncertainties; d) the analytical benefits of performance metrics, and e) the utility of a laboratory mix in understanding method performance. In addition, the remote sensing requirements for the in situ determination of total chlorophyll a were investigated to determine whether or not the average uncertainty for this measurement is being satisfied.

The purpose of this technical report is to provide current documentation of the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project activities, NASA Research Announcement (NRA) research status, satellite data processing, data product validation, and field calibration. This documentation is necessary to ensure that critical information is related to the scientific community and NASA management. This critical information includes the technical difficulties and challenges of validating and combining ocean color data from an array of independent satellite systems to form consistent and accurate global bio-optical time series products. This technical report is not meant as a substitute for scientific literature. Instead, it will provide a ready and responsive vehicle for the multitude of technical reports issued by an operational project. This particular document focus on the variability in chlorophyll pigment measurements resulting from differences in methodologies and laboratories conducting the pigment analysis.

The need for accurate determination of chlorophyll a (chl a) is of interest for numerous reasons. From the need for ground-truth data for remote sensing to pigment detection for laboratory experimentation, it is essential to know the accuracy of the analyses and the factors potentially contributing to variability and error. Numerous methods and instrument techniques are currently employed in the analyses of chl a. These methods range from spectrophotometric quantification, to fluorometric analysis and determination by high performance liquid chromatography. Even within the application of HPLC techniques, methods vary. Here we provide the results of a comparison among methods and provide some guidance for improving the accuracy of these analyses. These results are based on a round-robin conducted among numerous investigators, including several in the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) and HyCODE Programs. Our purpose here is not to present the full results of the laboratory intercalibration; those results will be presented elsewhere. Rather, here we highlight some of the major factors that may contribute to the variability observed. Specifically, we aim to assess the comparability of chl a analyses performed by fluorometry and HPLC, and we identify several factors in the analyses which may contribute disproportionately to this variability.