Mesoscale eddies stimulate biological production in the ocean, but knowledge of energy transfers to higher trophic levels within eddies remains fragmented and not quantified. Increasing the knowledge base is constrained by the inability of traditional sampling methods to adequately sample biological processes at the spatio-temporal scales at which they occur.By combining satellite and acoustic observations over spatial scales of 10 s of km horizontally and 100 s of m vertically, supported by hydrographical and biological sampling we show that anticyclonic eddies shape distribution and density of marine life from the surface to bathyal depths. Fish feed along density structures of eddies, demonstrating that eddies catalyze energy transfer across trophic levels. Eddies create attractive pelagic habitats, analogous to oases in the desert, for higher trophic level aquatic organisms through enhanced 3-D motion that accumulates and redistributes biomass, contributing to overall bioproduction in the ocean.Integrating multidisciplinary observation methodologies promoted a new understanding of biophysical interaction in mesoscale eddies. Our findings emphasize the impact of eddies on the patchiness of biomass in the sea and demonstrate that they provide rich feeding habitat for higher trophic marine life.

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The Copernicus Marine Environment Monitoring Service (CMEMS) Ocean State Report (OSR) provides an annual report of the state of the global ocean and European regional seas for policy and decision-makers with the additional aim of increasing general public awareness about the status of, and changes in, the marine environment. The CMEMS OSR draws on expert analysis and provides a 3-D view (through reanalysis systems), a view from above (through remote-sensing data) and a direct view of the interior (through in situ measurements) of the global ocean and the European regional seas. The report is based on the unique CMEMS monitoring capabilities of the blue (hydrography, currents), white (sea ice) and green (e.g. Chlorophyll) marine environment. This first issue of the CMEMS OSR provides guidance on Essential Variables, large-scale changes and specific events related to the physical ocean state over the period 1993–2015. Principal findings of this first CMEMS OSR show a significant increase in global and regional sea levels, thermosteric expansion, ocean heat content, sea surface temperature and Antarctic sea ice extent and conversely a decrease in Arctic sea ice extent during the 1993–2015 period. During the year 2015 exceptionally strong large-scale changes were monitored such as, for example, a strong El Niño Southern Oscillation, a high frequency of extreme storms and sea level events in specific regions in addition to areas of high sea level and harmful algae blooms. At the same time, some areas in the Arctic Ocean experienced exceptionally low sea ice extent and temperatures below average were observed in the North Atlantic Ocean

International audienceBuilding the capacity for monitoring and forecasting marine biogeochemistry and ecosystem dynamics is a scientific challenge of strategic importance in the context of rapid environmental change and growing public awareness of its potential impacts on marine ecosystems and resources. National Operational Oceanography centres have started to take up this challenge by integrating biogeochemistry in operational systems. Ongoing activities are illustrated in this paper by presenting examples of (pre-)operational biogeochemical systems active in Europe and North America for global to regional applications. First-order principles underlying biogeochemical modelling are briefly introduced along with the description of biogeochemical components implemented in these systems. Applications are illustrated with examples from the fields of hindcasting and monitoring ocean primary production, the assessment of the ocean carbon cycle and the management of living resources. Despite significant progress over the past 5 years in integrating biogeochemistry into (pre-)operational data-assimilation systems, a sustained research effort is still needed to assess these systems and their products with respect to their usefulness to the management of marine systems

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Abstract. The Norwegian Climate Prediction Model version 1 (NorCPM1) is a new research tool for performing climate reanalyses and seasonal-to-decadal climate predictions. It combines the Norwegian Earth System Model version 1 (NorESM1) – which features interactive aerosol–cloud schemes and an isopycnic-coordinate ocean component with biogeochemistry – with anomaly assimilation of sea surface temperature (SST) and T/S-profile observations using the ensemble Kalman filter (EnKF). We describe the Earth system component and the data assimilation (DA) scheme, highlighting implementation of new forcings, bug fixes, retuning and DA innovations. Notably, NorCPM1 uses two anomaly assimilation variants to assess the impact of sea ice initialization and climatological reference period: the first (i1) uses a 1980–2010 reference climatology for computing anomalies and the DA only updates the physical ocean state; the second (i2) uses a 1950–2010 reference climatology and additionally updates the sea ice state via strongly coupled DA of ocean observations. We assess the baseline, reanalysis and prediction performance with output contributed to the Decadal Climate Prediction Project (DCPP) as part of the sixth Coupled Model Intercomparison Project (CMIP6). The NorESM1 simulations exhibit a moderate historical global surface temperature evolution and tropical climate variability characteristics that compare favourably with observations. The climate biases of NorESM1 using CMIP6 external forcings are comparable to, or slightly larger than those of, the original NorESM1 CMIP5 model, with positive biases in Atlantic meridional overturning circulation (AMOC) strength and Arctic sea ice thickness, too-cold subtropical oceans and northern continents, and a too-warm North Atlantic and Southern Ocean. The biases in the assimilation experiments are mostly unchanged, except for a reduced sea ice thickness bias in i2 caused by the assimilation update of sea ice, generally confirming that the anomaly assimilation synchronizes variability without changing the climatology. The i1 and i2 reanalysis/hindcast products overall show comparable performance. The benefits of DA-assisted initialization are seen globally in the first year of the prediction over a range of variables, also in the atmosphere and over land. External forcings are the primary source of multiyear skills, while added benefit from initialization is demonstrated for the subpolar North Atlantic (SPNA) and its extension to the Arctic, and also for temperature over land if the forced signal is removed. Both products show limited success in constraining and predicting unforced surface ocean biogeochemistry variability. However, observational uncertainties and short temporal coverage make biogeochemistry evaluation uncertain, and potential predictability is found to be high. For physical climate prediction, i2 performs marginally better than i1 for a range of variables, especially in the SPNA and in the vicinity of sea ice, with notably improved sea level variability of the Southern Ocean. Despite similar skills, i1 and i2 feature very different drift behaviours, mainly due to their use of different climatologies in DA; i2 exhibits an anomalously strong AMOC that leads to forecast drift with unrealistic warming in the SPNA, whereas i1 exhibits a weaker AMOC that leads to unrealistic cooling. In polar regions, the reduction in climatological ice thickness in i2 causes additional forecast drift as the ice grows back. Posteriori lead-dependent drift correction removes most hindcast differences; applications should therefore benefit from combining the two products. The results confirm that the large-scale ocean circulation exerts strong control on North Atlantic temperature variability, implying predictive potential from better synchronization of circulation variability. Future development will therefore focus on improving the representation of mean state and variability of AMOC and its initialization, in addition to upgrades of the atmospheric component. Other efforts will be directed to refining the anomaly assimilation scheme – to better separate internal and forced signals, to include land and atmosphere initialization and new observational types – and improving biogeochemistry prediction capability. Combined with other systems, NorCPM1 may already contribute to skilful multiyear climate prediction that benefits society.

Water masses are bodies of water with distinctive physical and biogeochemical properties. They impart vertical structure to the deep ocean, participate in circulation, and can be traced over great distances, potentially influencing the distributions of deep-sea fauna. The classic potential temperature-salinity (θ-s) diagram was used to investigate deep-sea sponge (demosponge genus Geodia) association with water masses over the North Atlantic Ocean and Nordic Seas. A novel analysis was conducted, based on sampling the curvature of climatological mean θ-s curves at sponge locations. Sponges were particularly associated with turning points in the θ-s curves, indicative of intermediate and deep water masses. Arctic geodiid species (G. hentscheli and G. parva) were associated with Arctic intermediate and deep waters in the Nordic Seas, and with dense overflows into the northern North Atlantic. Boreal species (G. atlantica, G. barretti, G. macandrewii, and G. phlegraei) were associated with upper and intermediate water masses in the Northeast Atlantic and with upper, Atlantic-derived waters in the Nordic Seas. Taken together with distributional patterns, a link with thermohaline currents was also inferred. We conclude that water masses and major current pathways structure the distribution of a key deep-sea benthic faunal group on an ocean basin scale. This is most likely because of a combination of the physical constraints they place on the dispersal of early life-history stages, ecophysiological adaptation (evolved tolerances) to specific water masses, and the benefits to filter-feeders of certain phenomena linked to water column structure (e.g. nepheloid layers, internal waves/tides, density-driven currents).