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Abstract The abundance and productivity of phytoplankton constrain energy transfer through marine food webs and the export of organic carbon to the deep ocean. Bio‐optical measurements correlate well with phytoplankton carbon (Cphyto), but the effect of taxonomic variability on this relationship is still uncertain. Here, we explore how changes in phytoplankton community composition influence the relationship between the particulate backscatter coefficient (bbp) and Cphyto and present a new approach to estimate phytoplankton biomass more accurately using bbp. We found that using a fixed scaling factor for the conversion of bbp to Cphyto could lead to the underestimation or overestimation of biomass, depending on the dominant taxonomic group in the phytoplankton community. In addition, we demonstrate how a simple ratio of absorption at two wavelengths can be used to provide a coarse approximation of phytoplankton community composition when scaling bbp to Cphyto, thereby improving the estimation of net primary production.

The role of phytoplankton as ocean primary producers and their influence on global biogeochemical cycles makes them arguably the most important living organisms in the sea. Like plants on land, phytoplankton exhibit seasonal cycles that are controlled by physical, chemical, and biological processes. Nearshore coastal waters often contain the highest levels of phytoplankton biomass. Yet, owing to difficulties in sampling this dynamic region, less is known about the seasonality of phytoplankton in the nearshore (e.g., surf zone) compared to offshore coastal, shelf and open ocean waters. Here, we analyse an annual dataset of chlorophyll-a concentration—a proxy of phytoplankton biomass—and sea surface temperature (SST) collected by a surfer at Bovisand Beach in Plymouth, UK on a near weekly basis between September 2017 and September 2018. By comparing this dataset with a complementary in-situ dataset collected 7 km offshore from the coastline (11 km from Bovisand Beach) at Station L4 of the Western Channel Observatory, and guided by satellite observations of light availability, we investigated differences in phytoplankton seasonal cycles between nearshore and offshore coastal waters. Whereas similarities in phytoplankton biomass were observed in autumn, winter and spring, we observed significant differences between sites during the summer months of July and August. Offshore (Station L4) chlorophyll-a concentrations dropped dramatically, whereas chlorophyll-a concentrations in the nearshore (Bovsiand Beach) remained high. We found chlorophyll-a in the nearshore to be significantly positively correlated with SST and PAR over the seasonal cycle, but no significant correlations were observed at the offshore location. However, offshore correlation coefficients were found to be more consistent with those observed in the nearshore when summer data (June–August 2018) were removed. Analysis of physical (temperature and density) and chemical variables (nutrients) suggest that the offshore site (Station L4) becomes stratified and nutrient limited at the surface during the summer, in contrast to the nearshore. However, we acknowledge that additional experiments are needed to verify this hypothesis. Considering predicted changes in ocean stratification, our findings may help understand how the spatial distribution of phytoplankton phenology within temperate coastal seas could be impacted by climate change. Additionally, this study emphasises the potential for using marine citizen science as a platform for acquiring environmental data in otherwise challenging regions of the ocean, for understanding ecological indicators such as phytoplankton abundance and phenology. We discuss the limitations of our study and future work needed to explore nearshore phytoplankton dynamics.

Plankton is one of the most basic components in the marine ecosystem. The community structure and population change of plankton are the important ecological information to reflect the environmental situation. As the fundamental parameter of the plankton community structure, size spectrum is very useful for the evaluation of the marine ecosystem. In this paper, we propose a real-time and adaptive algorithm to calculate the size spectrum of underwater plankton video, which is captured by the high-resolution and high-speed optical camera. First, this algorithm screens the high-resolution plankton images to ensure that every plankton is counted once with the clearest frame. Second, edge detection and morphological methods are performed to get plankton areas. Furthermore, we perform several simplifications that each particle is handled as ellipses shape to calculate the volume to obtain the size spectrum. Moreover, in order to facilitate the biologists to research plankton deeply, we record a region of the clear area containing each plankton to build a plankton database.

A field intercomparison was conducted at the Acqua Alta Oceanographic Tower (AAOT) in the northern Adriatic Sea, from 9 to 19 July 2018 to assess differences in the accuracy of in- and above-water radiometer measurements used for the validation of ocean colour products. Ten measurement systems were compared. Prior to the intercomparison, the absolute radiometric calibration of all sensors was carried out using the same standards and methods at the same reference laboratory. Measurements were performed under clear sky conditions, relatively low sun zenith angles, moderately low sea state and on the same deployment platform and frame (except in-water systems). The weighted average of five above-water measurements was used as baseline reference for comparisons. For downwelling irradiance ( E d ), there was generally good agreement between sensors with differences of L s k y ) the spectrally averaged difference between optical systems was −2 nm−1 sr−1. For total above-water upwelling radiance ( L t ), the difference was −2 nm−1 sr−1. For remote-sensing reflectance ( R r s ), the differences between above-water TriOS RAMSES were E d accounted for the largest fraction of the variance in R r s , which suggests that minimizing the errors arising from this measurement is the most important variable in reducing the inter-group differences in R r s . The differences may also be due, in part, to using five of the above-water systems as a reference. To avoid this, in situ normalized water-leaving radiance ( L w n ) was therefore compared to AERONET-OC SeaPRiSM L w n as an alternative reference measurement. For the TriOS-RAMSES and Seabird-HyperSAS sensors the differences were similar across the visible spectra with 4.7% and 4.9%, respectively. The difference between SeaPRiSM L w n and two in-water systems at blue, green and red bands was 11.8%. This was partly due to temporal and spatial differences in sampling between the in-water and above-water systems and possibly due to uncertainties in instrument self-shading for one of the in-water measurements.

Earth observation data can help us understand and address some of the grand challenges and threats facing us today as a species and as a planet, for example climate change and its impacts and sustainable use of the Earth’s resources. However, in order to have confidence in earth observation data, measurements made at the surface of the Earth, with the intention of providing verification or validation of satellite-mounted sensor measurements, should be trustworthy and at least of the same high quality as those taken with the satellite sensors themselves. Metrology tells us that in order to be trustworthy, measurements should include an unbroken chain of SI-traceable calibrations and comparisons and full uncertainty budgets for each of the in situ sensors. Until now, this has not been the case for most satellite validation measurements. Therefore, within this context, the European Space Agency (ESA) funded a series of Fiducial Reference Measurements (FRM) projects targeting the validation of satellite data products of the atmosphere, land, and ocean, and setting the framework, standards, and protocols for future satellite validation efforts. The FRM4SOC project was structured to provide this support for evaluating and improving the state of the art in ocean colour radiometry (OCR) and satellite ocean colour validation through a series of comparisons under the auspices of the Committee on Earth Observation Satellites (CEOS). This followed the recommendations from the International Ocean Colour Coordinating Group’s white paper and supports the CEOS ocean colour virtual constellation. The main objective was to establish and maintain SI traceable ground-based FRM for satellite ocean colour and thus make a fundamental contribution to the European system for monitoring the Earth (Copernicus). This paper outlines the FRM4SOC project structure, objectives and methodology and highlights the main results and achievements of the project: (1) An international SI-traceable comparison of irradiance and radiance sources used for OCR calibration that set measurement, calibration and uncertainty estimation protocols and indicated good agreement between the participating calibration laboratories from around the world; (2) An international SI-traceable laboratory and outdoor comparison of radiometers used for satellite ocean colour validation that set OCR calibration and comparison protocols; (3) A major review and update to the protocols for taking irradiance and radiance field measurements for satellite ocean colour validation, with particular focus on aspects of data acquisition and processing that must be considered in the estimation of measurement uncertainty and guidelines for good practice; (4) A technical comparison of the main radiometers used globally for satellite ocean colour validation bringing radiometer manufacturers together around the same table for the first time to discuss instrument characterisation and its documentation, as needed for measurement uncertainty estimation; (5) Two major international side-by-side field intercomparisons of multiple ocean colour radiometers, one on the Atlantic Meridional Transect (AMT) oceanographic cruise, and the other on the Acqua Alta oceanographic tower in the Gulf of Venice; (6) Impact and promotion of FRM within the ocean colour community, including a scientific road map for the FRM-based future of satellite ocean colour validation and vicarious calibration (based on the findings of the FRM4SOC project, the consensus from two major international FRM4SOC workshops and previous literature, including the IOCCG white paper on in situ ocean colour radiometry).

An intercomparison of radiance and irradiance ocean color radiometers (The Second Laboratory Comparison Exercise—LCE-2) was organized within the frame of the European Space Agency funded project Fiducial Reference Measurements for Satellite Ocean Color (FRM4SOC) May 8−13, 2017 at Tartu Observatory, Estonia. LCE-2 consisted of three sub-tasks: 1) SI-traceable radiometric calibration of all the participating radiance and irradiance radiometers at the Tartu Observatory just before the comparisons; 2) Indoor intercomparison using stable radiance and irradiance sources in controlled environment; and 3) Outdoor intercomparison of natural radiation sources over terrestrial water surface. The aim of the experiment was to provide one link in the chain of traceability from field measurements of water reflectance to the uniform SI-traceable calibration, and after calibration to verify whether different instruments measuring the same object provide results consistent within the expected uncertainty limits. This paper describes the activities and results of the first two phases of LCE-2: the SI-traceable radiometric calibration and indoor intercomparison, the results of outdoor experiment are presented in a related paper of the same journal issue. The indoor experiment of the LCE-2 has proven that uniform calibration just before the use of radiometers is highly effective. Distinct radiometers from different manufacturers operated by different scientists can yield quite close radiance and irradiance results (standard deviation s < 1%) under defined conditions. This holds when measuring stable lamp-based targets under stationary laboratory conditions with all the radiometers uniformly calibrated against the same standards just prior to the experiment. In addition, some unification of measurement and data processing must be settled. Uncertainty of radiance and irradiance measurement under these conditions largely consists of the sensor’s calibration uncertainty and of the spread of results obtained by individual sensors measuring the same object.

An intercomparison of radiance and irradiance ocean color radiometers (the second laboratory comparison exercise—LCE-2) was organized within the frame of the European Space Agency funded project Fiducial Reference Measurements for Satellite Ocean Color (FRM4SOC) May 8–13, 2017 at Tartu Observatory, Estonia. LCE-2 consisted of three sub-tasks: (1) SI-traceable radiometric calibration of all the participating radiance and irradiance radiometers at the Tartu Observatory just before the comparisons; (2) indoor, laboratory intercomparison using stable radiance and irradiance sources in a controlled environment; (3) outdoor, field intercomparison of natural radiation sources over a natural water surface. The aim of the experiment was to provide a link in the chain of traceability from field measurements of water reflectance to the uniform SI-traceable calibration, and after calibration to verify whether different instruments measuring the same object provide results consistent within the expected uncertainty limits. This paper describes the third phase of LCE-2: The results of the field experiment. The calibration of radiometers and laboratory comparison experiment are presented in a related paper of the same journal issue. Compared to the laboratory comparison, the field intercomparison has demonstrated substantially larger variability between freshly calibrated sensors, because the targets and environmental conditions during radiometric calibration were different, both spectrally and spatially. Major differences were found for radiance sensors measuring a sunlit water target at viewing zenith angle of 139° because of the different fields of view. Major differences were found for irradiance sensors because of imperfect cosine response of diffusers. Variability between individual radiometers did depend significantly also on the type of the sensor and on the specific measurement target. Uniform SI traceable radiometric calibration ensuring fairly good consistency for indoor, laboratory measurements is insufficient for outdoor, field measurements, mainly due to the different angular variability of illumination. More stringent specifications and individual testing of radiometers for all relevant systematic effects (temperature, nonlinearity, spectral stray light, etc.) are needed to reduce biases between instruments and better quantify measurement uncertainties.