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Phosphorus (P) is essential for life, but most of the global surface ocean is P depleted, which can limit marine productivity and affect ecosystem structure. Over recent decades, a wealth of new knowledge has revolutionized our understanding of the marine P cycle. With a revised residence time (~10–20 kyr) that is similar to nitrate and a growing awareness that P transformations are under tight and elaborate microbial control, the classic textbook version of a tectonically slow and biogeochemically simple marine P cycle has become outdated. P moves throughout the world’s oceans with a higher level of complexity than has ever been appreciated before, including a vast, yet poorly understood, P redox cycle. Here, we illustrate an oceanographically integral view of marine P by reviewing recent advances in the coupled cycles of P with carbon, nitrogen and metals in marine systems. Through this lens, P takes on a more dynamic and connected role in marine biogeochemistry than previously acknowledged, which points to unclear yet profound potential consequences for marine ecosystems, particularly under anthropogenic influence. Phosphorus plays a dynamic and complex role in marine biogeochemistry, which is closely connected to carbon, nitrogen and metal cycling, according to a literature synthesis on recent advances in understandings of the marine phosphorus cycle.

We developed a simple method to refine existing open-ocean maps and extend them towards different coastal seas. Using a multi-linear regression we produced monthly maps of surface ocean fCO2 in the northern European coastal seas (the North Sea, the Baltic Sea, the Norwegian Coast and the Barents Sea) covering a time period from 1998 to 2016. A comparison with gridded Surface Ocean CO2 Atlas (SOCAT) v5 data revealed mean biases and standard deviations of 0 ± 26 µatm in the North Sea, 0 ± 16 µatm along the Norwegian Coast, 0 ± 19 µatm in the Barents Sea and 2 ± 42 µatm in the Baltic Sea. We used these maps to investigate trends in fCO2, pH and air–sea CO2 flux. The surface ocean fCO2 trends are smaller than the atmospheric trend in most of the studied regions. The only exception to this is the western part of the North Sea, where sea surface fCO2 increases by 2 µatm yr−1, which is similar to the atmospheric trend. The Baltic Sea does not show a significant trend. Here, the variability was much larger than the expected trends. Consistently, the pH trends were smaller than expected for an increase in fCO2 in pace with the rise of atmospheric CO2 levels. The calculated air–sea CO2 fluxes revealed that most regions were net sinks for CO2. Only the southern North Sea and the Baltic Sea emitted CO2 to the atmosphere. Especially in the northern regions the sink strength increased during the studied period.

Oceans have remained the least well-researched reservoirs of persistent organic pollutants (POPs) globally, due to their vast scale, difficulty of access, and challenging (trace) analysis. Little data on POPs exists along South America and the effect of different currents and river plumes on aqueous concentrations. Research cruise KN210-04 (R/V Knorr) offered a unique opportunity to determine POP gradients in air, water, and their air-water exchange along South America, covering both hemispheres. Compounds of interest included polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), polybrominated diphenylethers (PBDEs), and polycyclic aromatic hydrocarbons (PAHs). Remote tropical Atlantic Ocean atmospheric concentrations varied little between both hemispheres; for HCB, BDEs 47 and 99, they were ∼5 pg/m3, PCBs were ∼1 pg/m3, α-HCH was ∼0.2 pg/m3, and phenanthrene and other PAHs were in the low 100s pg/m3. Aqueous concentrations were dominated by PCB 52 (mean 4.1 pg/L), HCB (1.6 pg/L), and β-HCH (1.9 pg/L), with other compounds

In this study, we present the first combined open and coastal ocean pCO2 mapped monthly climatology (Landschützer et al. (2020), doi:10.25921/qb25-f418, https://www.nodc.noaa.gov/ocads/oceans/MPI-ULB-SOM_FFN_clim.html) constructed from observations collected between 1998 and 2015 extracted from the Surface Ocean CO2 Atlas (SOCAT) database. We combine two neural network-based pCO2 products, one from the open ocean and the other from the coastal ocean, and investigate their consistency along their common overlap areas. While the difference between open and coastal ocean estimates along the overlap area increases with latitude, it remains close to 0 μatm globally. Stronger discrepancies, however, exist on the regional level resulting in differences that exceed 10 % of the climatological mean pCO2, or an order of magnitude larger than the uncertainty from state of the art measurements. This also illustrates the potential of such analysis to inform the measurement community about the locations where additional measurements are essential to better represent the aquatic continuum and improve our understanding of the carbon exchange at the air water interface. A regional analysis further shows that the seasonal carbon dynamics at the coast-open interface are well represented in our climatology. While our combined product is only a first step towards a true representation of both the open ocean and the coastal ocean air-sea CO2 flux in marine carbon budgets, we show it is a feasible task and the present data product already constitutes a valuable tool to investigate and quantify the dynamics of the air-sea CO2 exchange consistently for oceanic regions regardless of its distance to the coast.

Over the last decade, advanced statistical inference and machine learning have been used to fill the gaps in sparse surface ocean CO2 measurements (Rödenbeck et al., 2015). The estimates from these methods have been used to constrain seasonal, interannual and decadal variability in sea–air CO2 fluxes and the drivers of these changes (Landschützer et al., 2015, 2016; Gregor et al., 2018). However, it is also becoming clear that these methods are converging towards a common bias and root mean square error (RMSE) boundary: “the wall”, which suggests that pCO2 estimates are now limited by both data gaps and scale-sensitive observations. Here, we analyse this problem by introducing a new gap-filling method, an ensemble average of six machine-learning models (CSIR-ML6 version 2019a, Council for Scientific and Industrial Research – Machine Learning ensemble with Six members), where each model is constructed with a two-step clustering-regression approach. The ensemble average is then statistically compared to well-established methods. The ensemble average, CSIR-ML6, has an RMSE of 17.16 µatm and bias of 0.89 µatm when compared to a test dataset kept separate from training procedures. However, when validating our estimates with independent datasets, we find that our method improves only incrementally on other gap-filling methods. We investigate the differences between the methods to understand the extent of the limitations of gap-filling estimates of pCO2. We show that disagreement between methods in the South Atlantic, southeastern Pacific and parts of the Southern Ocean is too large to interpret the interannual variability with confidence. We conclude that improvements in surface ocean pCO2 estimates will likely be incremental with the optimisation of gap-filling methods by (1) the inclusion of additional clustering and regression variables (e.g. eddy kinetic energy), (2) increasing the sampling resolution and (3) successfully incorporating pCO2 estimates from alternate platforms (e.g. floats, gliders) into existing machine-learning approaches.

International audience; The future wide-swath satellite altimeters, such as the upcoming Surface Water Ocean Topography (SWOT) mission, will provide instantaneous 2D measurements of sea level down to the spatial scale of O(10 km) for the first time. However, the validity of the geostrophic assumption for estimating surface currents from these instantaneous maps is not known a priori. In this study, we quantify the accuracy of geostrophy for the estimation of surface currents from a knowledge of instantaneous sea level using the hourly snapshots from a tide- and eddy-resolving global numerical simulation. Geostrophic balance is found to be the leading-order balance in frontal regions characterized by large kinetic energy, such as the western boundary currents and the Antarctic Circumpolar Current. Everywhere else, geostrophic approximation ceases to be a useful predictor of ocean velocity, which may result in significant high-frequency contamination of geostrophically computed velocities by fast variability (e.g., inertial and higher). As expected, the validity of geostrophy is shown to improve at low frequencies (typically urn:x-wiley:21699275:media:jgrc24720:jgrc24720-math-0001 0.5 cpd). Global estimates of the horizontal momentum budget reveal that the tropical and mid-latitude regions where geostrophic balance fails are dominated by fast variability and turbulent stress divergence terms rather than higher-order geostrophic terms. These findings indicate that the estimation of velocity from geostrophy applied on SWOT instantaneous sea level maps may be challenging away from energetic areas.

To derive an optimal observation system for surface ocean pCO2 in the Atlantic Ocean and the Atlantic sector of the Southern Ocean eleven Observation System Simulation Experiments (OSSEs) were completed. Each OSSE is a Feed-Forward Neural Network (FFNN) that is based on a different data distribution and provides ocean surface pCO2 for the period 2008–2010 with a 5 day time interval. Based on the geographical and time positions from three observational platforms, volunteering observing ships (VOS), Argo floats and OceanSITES moorings, pseudo-observations were constructed using the outputs from an online-coupled physical-biogeochemical global ocean model with 0.25° nominal resolution. The aim of this work was to find an optimal spatial distribution of observations to supplement the widely used Surface Ocean CO2 Atlas (SOCAT) and to improve the accuracy of ocean surface pCO2 reconstructions. OSSEs showed that the additional data from mooring stations and an improved coverage of the Southern Hemisphere with biogeochemical ARGO floats corresponding to least 25 % of the density of active floats (2008–2010) (OSSE 10) would significantly improve the pCO2 reconstruction and reduce the bias of derived estimates of sea-air CO2 fluxes by 74 % compared to ocean model outputs.

19 pages, 7 tables, 11 figures.-- Open access, Global climatologies of the seawater CO2 chemistry variables are necessary to assess the marine carbon cycle in depth. The climatologies should adequately capture seasonal variability to properly address ocean acidification and similar issues related to the carbon cycle. Total alkalinity (AT) is one variable of the seawater CO2 chemistry system involved in ocean acidification and frequently measured.We used the Global Ocean Data Analysis Project version 2.2019 (GLODAPv2) to extract relationships among the drivers of the AT variability and AT concentration using a neural network (NNGv2) to generate a monthly climatology. The GLODAPv2 qualitycontrolled dataset used was modeled by the NNGv2 with a root-mean-squared error (RMSE) of 5.3 μmol kg1. Validation tests with independent datasets revealed the good generalization of the network. Data from five ocean time-series stations showed an acceptable RMSE range of 3–6.2 μmol kg1. Successful modeling of the monthly AT variability in the time series suggests that the NNGv2 is a good candidate to generate a monthly climatology. The climatological fields of AT were obtained passing through the NNGv2 the World Ocean Atlas 2013 (WOA13) monthly climatologies of temperature, salinity, and oxygen and the computed climatologies of nutrients from the previous ones with a neural network. The spatiotemporal resolution is set by WOA13: 1 1 in the horizontal, 102 depth levels (0–5500 m) in the vertical and monthly (0–1500 m) to annual (1550–5500 m) temporal resolution. The product is distributed through the data repository of the Spanish National Research Council (CSIC; https://doi.org/10.20350/digitalCSIC/8644, Broullón et al., 2019), This research has been supported by the H2020 Food (AtlantOS, grant no. 633211); the Ministerio de Educación, Cultura y Deporte (grant no. FPU15/06026); the Ministerio de Economía y Competitividad, Consejo Superior de Investigaciones Científicas (grant no. CTM2016-76146-C3-1-R); and the Ministerio de Economía y Competitividad, Salvador de Madariaga (grant no. PRX18/00312)

Previous work has not led to a clear understanding of the causes of spatial pattern in global surface ocean dissolved inorganic carbon (DIC), which generally increases polewards. Here, we revisit this question by investigating the drivers of observed latitudinal gradients in surface salinity-normalized DIC (nDIC) using the Global Ocean Data Analysis Project version 2 (GLODAPv2) database. We used the database to test three different hypotheses for the driver producing the observed increase in surface nDIC from low to high latitudes. These are (1) sea surface temperature, through its effect on the CO2 system equilibrium constants, (2) salinity-related total alkalinity (TA), and (3) high-latitude upwelling of DIC- and TA-rich deep waters. We find that temperature and upwelling are the two major drivers. TA effects generally oppose the observed gradient, except where higher values are introduced in upwelled waters. Temperature-driven effects explain the majority of the surface nDIC latitudinal gradient (182 of the 223 µmol kg−1 increase from the tropics to the high-latitude Southern Ocean). Upwelling, which has not previously been considered as a major driver, additionally drives a substantial latitudinal gradient. Its immediate impact, prior to any induced air–sea CO2 exchange, is to raise Southern Ocean nDIC by 220 µmol kg−1 above the average low-latitude value. However, this immediate effect is transitory. The long-term impact of upwelling (brought about by increasing TA), which would persist even if gas exchange were to return the surface ocean to the same CO2 as without upwelling, is to increase nDIC by 74 µmol kg−1 above the low-latitude average.

A new feed-forward neural network (FFNN) model is presented to reconstruct surface ocean partial pressure of carbon dioxide ( pCO2 ) over the global ocean. The model consists of two steps: (1) the reconstruction of pCO2 climatology, and (2) the reconstruction of pCO2 anomalies with respect to the climatology. For the first step, a gridded climatology was used as the target, along with sea surface salinity (SSS), sea surface temperature (SST), sea surface height (SSH), chlorophyll a (Chl a ), mixed layer depth (MLD), as well as latitude and longitude as predictors. For the second step, data from the Surface Ocean CO2 Atlas (SOCAT) provided the target. The same set of predictors was used during step (2) augmented by their anomalies. During each step, the FFNN model reconstructs the nonlinear relationships between pCO2 and the ocean predictors. It provides monthly surface ocean pCO2 distributions on a 1 ∘ × 1 ∘ grid for the period from 2001 to 2016. Global ocean pCO2 was reconstructed with satisfying accuracy compared with independent observational data from SOCAT. However, errors were larger in regions with poor data coverage (e.g., the Indian Ocean, the Southern Ocean and the subpolar Pacific). The model captured the strong interannual variability of surface ocean pCO2 with reasonable skill over the equatorial Pacific associated with ENSO (the El Nino–Southern Oscillation). Our model was compared to three pCO2 mapping methods that participated in the Surface Ocean pCO2 Mapping intercomparison (SOCOM) initiative. We found a good agreement in seasonal and interannual variability between the models over the global ocean. However, important differences still exist at the regional scale, especially in the Southern Hemisphere and, in particular, in the southern Pacific and the Indian Ocean, as these regions suffer from poor data coverage. Large regional uncertainties in reconstructed surface ocean pCO2 and sea–air CO2 fluxes have a strong influence on global estimates of CO2 fluxes and trends.

Purpose of Review We summarize recent progress on autonomous observations of ocean carbonate chemistry and the development of a network of sensors capable of observing carbonate processes at multiple temporal and spatial scales. Recent Findings The development of versatile pH sensors suitable for both deployment on autonomous vehicles and in compact, fixed ecosystem observatories has been a major development in the field. The initial large-scale deployment of profiling floats equipped with these new pH sensors in the Southern Ocean has demonstrated the feasibility of a global autonomous open-ocean carbonate observing system. Summary Our developing network of autonomous carbonate observations is currently targeted at surface ocean CO2 fluxes and compact ecosystem observatories. New integration of developed sensors on gliders and surface vehicles will increase our coastal and regional observational capability. Most autonomous platforms observe a single carbonate parameter, which leaves us reliant on the use of empirical relationships to constrain the rest of the carbonate system. Sensors now in development promise the ability to observe multiple carbonate system parameters from a range of vehicles in the near future.

Two methods for the mapping of ocean surface currents from satellite measurements of sea level and future current vectors are presented and contrasted. Both methods rely on the linear and Gaussian analysis framework with different levels of covariance definitions. The first method separately maps sea level and currents with single‐scale covariance functions and leads to estimates of the geostrophic and ageostrophic circulations. The second maps both measurements simultaneously and projects the circulation onto 4 contributions: geostrophic, ageostrophic rotary, ageostrophic divergent and inertial. When compared to the first method, the second mapping moderately improves the resolution of geostrophic currents but significantly improves estimates of the ageostrophic circulation, in particular near‐inertial oscillations. This method offers promising perspectives for reconstructions of the ocean surface circulation. Even the hourly dynamics can be reconstructed from measurements made locally every few days because nearby measurements are coherent enough to help fill the gaps. Based on numerical simulation of ocean surface currents, the proposed SKIM mission that combines a nadir altimeter and a Doppler scatterometer with a 300 km wide swath (with a mean revisit time of 3 days) would allow the reconstruction of 50% of the near‐inertial variance around an 18 hour period of oscillation. Plain Language Summary Ocean surface currents are caused by a variety of phenomena that varies at different space and time scales. Here we mainly consider the two dominant contributions. The first is the current resulting from the quasi‐equilibrium between the sloping sea level and the Coriolis force, slowly evolving over a few days. The second is also associated with the Coriolis force, but out of equilibrium: oscillating currents caused by rapid changes of the wind with a narrow range of periods around a natural period of oscillation that increase with latitude from 12 hours at the poles. For many applications it is desirable to separate these two contributions, for example to compute transports associated to the slowly evolving component and to evaluate the amount of kinetic energy pumped by the wind, mostly in the fast oscillations. This separation is easy with hourly sampled in situ measurements, but few are available. Here we show that we can perform this separation using satellite passes with measurements of sea level and a swath of surface current vectors, as can be measured by proposed future satellites. The fast oscillations can be reproduced even if data is available every few days, thanks to their spatial patterns and temporal coherence.

205 pages, 12 figures, 1 table, 3 appendixes.-- Data Availability Statement: All data are accessible from https://apps.ecmwf.int/datasets/data/interim-full-daily/levtype=sfc/, https://www.cpc.ncep.noaa.gov/data/teledoc/telecontents.shtml and from https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=SEALEVEL_MED_PHY_L4_REP_OBSERVATIONS_008_051, Effects of wind and waves on the surface dynamics of the Mediterranean Sea are assessed using a modified Ekman model including a Stokes-Coriolis force in the momentum equation. Using 25 years of observations, we documented intermittent but recurrent episodes during which Ekman and Stokes currents substantially modulate the total mesoscale dynamics by two nonexclusive mechanisms: (a) by providing a vigorous input of momentum (e.g., where regional winds are stronger) and/or (b) by opposing forces to the main direction of the geostrophic component. To properly characterize the occurrence and variability of these dynamical regimes, we perform an objective classification combining self-organizing maps and wavelet coherence analyses. It allows proposing a new regional classification of the Mediterranean Sea based on the respective contributions of wind, wave, and geostrophic components to the total mesoscale surface dynamics. We found that the effects of wind and waves are more prominent in the northwestern Mediterranean, while the southwestern and eastern basins are mainly dominated by the geostrophic component. The resulting temporal variability patterns show a strong seasonal signal and cycles of 5–6 years in the total kinetic energy arising from both geostrophic and ageostrophic components. Moreover, the whole basin, specially the regions characterized by strong wind- and wave-induced currents, shows a characteristic period of variability at 5 years. This can be related to climate modes of variability. Regional trends in the geostrophic and ageostrophic currents show an intensification of 0.058 ± 1.43 · 10−5 cm/s per year, Authors acknowledge financial support from MINECO/FEDER through projects MOCCA (RTI2018-093941-B-C31) and from the Balearic Islands Goverment Project ADAPTA. V. Morales-Márquez is supported by an FPI grant from the Ministerio de Ciencia, Innovación y Universidades. I. Hernandez-Carrasco acknowledges the Vicenç Mut contract funded by the Government of the Balearic Island and the European Social Fund (ESF) Operational Programme and the financial support from the Fundacion Universidad Empresa de las Islas Baleares, Spain, through project ALERTA (REF-190121). V. Rossi acknowledges financial support from the European project SEAMoBB, funded by ERA-Net Mar-TERA and managed by ANR (number ANR_17_MART-0001_01, P.I.: A.C.). This work was partially performed while V. Morales-Márquez was staying in MIO (Marseille, France) with the support of FPI grant from the Ministerio de Ciencia, Innovación y Universidades. In addition, this work was carried out in part when A. Orfila was a visiting scientist at the Earth, Environmental and Planetary Sciences Department at Brown University through a Ministerio de Ciencia, Innovación y Universidades fellowship (PRX18/00218), With the institutional support of the ‘Severo OchoaCentre of Excellence’ accreditation (CEX2019-000928-S)

International audience; The China France Oceanography Satellite (CFOSAT) launched in 2018 now routinely provides directional ocean wave spectra at the global scale. It consists of analyzing the normalized radar cross-section measured by the near-nadir pointing Ku-Band real-aperture scanning radar SWIM (Surface Waves Investigation and Monitoring). The significant wave height, dominant wavelength and direction are provided as the main parameters, but here we analyze additional parameters, namely the frequency width of the omni-directional spectra, the directional spread of the dominant waves, and the related Benjamin-Feir index. This latter was proposed in the literature to estimate the probability of extreme waves. We discuss the geographical distributions of these parameters, their relation with sea-state conditions, and their similarities and diferences with respect to the same parameters obtained from the MFWAM numerical wave model and buoy data. Wef ind that the SWIM omni-directional spectra are narrower and more peaked than the model spectra and that these differences are more obvious in the high sea-state conditions encoun31tered in the Southern Ocean. We nd that under the intense conditions of the Southern Ocean, the SWIM directional spread at the peak is the smallest for swell, the largest for young wind seas, and takes intermediate values for mature wind seas. The directional Benjamin-Feir index is similar for SWIM and MFWAM, but this is mainly due to compensating effects in the parameters contributing to this index. The results indicate that these shape parameters may be used in the future to better describe the wave space-time evolution.

The ocean is a sink for ~25% of the atmospheric CO2 emitted by human activities, an amount in excess of 2 petagrams of carbon per year (PgC yr−1). Time-resolved estimates of global ocean-atmosphere CO2 flux provide an important constraint on the global carbon budget. However, previous estimates of this flux, derived from surface ocean CO2 concentrations, have not corrected the data for temperature gradients between the surface and sampling at a few meters depth, or for the effect of the cool ocean surface skin. Here we calculate a time history of ocean-atmosphere CO2 fluxes from 1992 to 2018, corrected for these effects. These increase the calculated net flux into the oceans by 0.8–0.9 PgC yr−1, at times doubling uncorrected values. We estimate uncertainties using multiple interpolation methods, finding convergent results for fluxes globally after 2000, or over the Northern Hemisphere throughout the period. Our corrections reconcile surface uptake with independent estimates of the increase in ocean CO2 inventory, and suggest most ocean models underestimate uptake., Ocean uptake of carbon dioxide impacts the climate, but flux estimates from surface measurements have not been corrected for temperature differences between surface and water sampling depth. Making that correction, the authors find previous estimates for ocean uptake have been substantially underestimated.

Understanding how climate change will affect oceanic fluid transport is crucial for environmental applications and human activities. However, a synoptic characterization of the influence of climate change on mesoscale stirring and transport in the surface ocean is missing. To bridge this gap, we exploit a high-resolution, fully coupled climate model of the Mediterranean basin using a Network Theory approach. We project significant increases of horizontal stirring and kinetic energies in the next century, likely due to increments of available potential energy. The future evolution of basin-scale transport patterns hints at a rearrangement of the main hydrodynamic provinces, defined as regions of the surface ocean that are well mixed internally but with minimal cross-flow across their boundaries. This results in increased heterogeneity of province sizes and stronger mixing in their interiors. Our approach can be readily applied to other oceanic regions, providing information for the present and future marine spatial planning., SI

International audience; Based on the 2019 assessment of the Global Carbon Project, the ocean took up on average, 2.5 ± 0.6 PgC yr−1 or 23 ± 5% of the total anthropogenic CO2 emissions over the decade 2009–2018. This sink estimate is based on simulation results from global ocean biogeochemical models (GOBMs) and is compared to data-products based on observations of surface ocean pCO2 (partial pressure of CO2) accounting for the outgassing of river-derived CO2. Here we evaluate the GOBM simulations by comparing the simulated surface ocean pCO2 to observations. Based on this comparison, the simulations are well-suited for quantifying the global ocean carbon sink on the time-scale of the annual mean and its multi-decadal trend (RMSE

The ability to routinely quantify global carbon dioxide (CO2) absorption by the oceans has become crucial: it provides a powerful constraint for establishing global and regional carbon (C) budgets, and enables identification of the ecological impacts and risks of this uptake on the marine environment. Advances in understanding, technology, and international coordination have made it possible to measure CO2 absorption by the oceans to a greater degree of accuracy than is possible in terrestrial landscapes. These advances, combined with new satellite‐based Earth observation capabilities, increasing public availability of data, and cloud computing, provide important opportunities for addressing critical knowledge gaps. Furthermore, Earth observation in synergy with in‐situ monitoring can provide the large‐scale ocean monitoring that is necessary to support policies to protect ocean ecosystems at risk, and motivate societal shifts toward meeting C emissions targets; however, sustained effort will be needed. In a nutshell: The oceans cover >70% of the Earth's surface and are critical for food supply and maintaining global climate Increasing carbon dioxide (CO2) absorption alters ocean chemistry and ecology, affecting marine ecosystems over both the short and long term Accurate estimates of CO2 absorption by the world's oceans provide a powerful constraint on carbon (C) budgets, and are needed to inform policies to motivate societal shifts toward reducing C emissions We review recent and foreseeable advances for studying oceanic CO2 absorption, explain why satellite‐based Earth observation is key to addressing existing knowledge gaps, and discuss how global monitoring is now both possible and necessary to support policy and conservation

It has become clear that anthropogenic carbon invasion into the surface ocean drives changes in the seasonal cycles of carbon dioxide partial pressure (pCO(2)) and pH. However, it is not yet known whether the resulting sea-air CO2 fluxes are symmetric in their seasonal expression. Here we consider a novel application of observational constraints and modeling inferences to test the hypothesis that changes in the ocean's Revelle factor facilitate a seasonally asymmetric response in pCO(2) and the sea-air CO2 flux. We use an analytical framework that builds on observed sea surface pCO(2) variability for the modern era and incorporates transient dissolved inorganic carbon concentrations from an Earth system model. Our findings reveal asymmetric amplification of pCO(2) and pH seasonal cycles by a factor of two (or more) above preindustrial levels under Representative Concentration Pathway 8.5. These changes are significantly larger than observed modes of interannual variability and are relevant to climate feedbacks associated with Revelle factor perturbations. Notably, this response occurs in the absence of changes to the seasonal cycle amplitudes of dissolved inorganic carbon, total alkalinity, salinity, and temperature, indicating that significant alteration of surface pCO(2) can occur without modifying the physical or biological ocean state. This result challenges the historical paradigm that if the same amount of carbon and nutrients is entrained and subsequently exported, there is no impact on anthropogenic carbon uptake. Anticipation of seasonal asymmetries in the sea surface pCO(2) and CO2 flux response to ocean carbon uptake over the 21st century may have important implications for carbon cycle feedbacks. Plain Language Summary The ocean uptake of human released carbon dioxide (CO2) is causing the natural seasonal swings in seawater CO2 to grow over time. Using observations and numerical models, we conduct a theoretical experiment to see how the surface ocean may respond to continued carbon additions under business-as-usual future atmospheric CO2 concentrations. We find that between 1861 and 2100, the chemical properties of CO2 in seawater cause the seasonal CO2 maximum to grow by more than the seasonal CO2 minimum. As a result, the rate of summer surface ocean CO2 growth is different than winter, requiring year-round observations to accurately measure the overall annual ocean carbon absorption. Additionally, these seasonal CO2 changes affect how much carbon is lost from the ocean during high-CO2 periods relative to how much carbon is gained from the atmosphere during low-CO2 periods, creating a trend in the average ocean carbon absorption over years to decades that must be considered in the interpretation of marine carbon cycle observations and numerical models. These findings are important as they have implications for future rates of climate change and ocean acidification.

Highlights • Elevated concentrations of surface DPb near South Georgia in the Southern Ocean originated from glacial flour • DPb in the open ocean North Atlantic and Southern Ocean originate from dust particles delivered from Patagonia and Northern Hemisphere • Scavenging of DPb onto biogenic particles formed during spatially confined phytoplankton blooms leads to dissolved Pb removal Abstract Today, four decades past peak anthropogenic lead emissions in the 1970s, dissolved lead (DPb) concentrations in the surface ocean remain elevated. To constrain contemporary sources and sinks of DPb, we studied high latitude surface waters of the North Atlantic and the Southern Ocean. We observed high concentrations of surface DPb (46 pmol kg-1) near South Georgia in the Southern Ocean, sourced from glacial flour, while offshore DPb concentrations of 3–9 pmol kg-1 were attributable to aeolian Pb inputs mainly from Patagonia. Dissolved Pb in the North Atlantic (4–29 pmol kg-1) originated from aeolian particles from Northern Hemisphere sources. Extremely low DPb concentrations of

The Southern Ocean is highly under-sampled for the purpose of assessing total carbon uptake and its variability. Since this region dominates the mean global ocean sink for anthropogenic carbon, understanding temporal change is critical. Underway measurements of pCO2 collected as part of the Drake Passage Time-series (DPT) program that began in 2002 inform our understanding of seasonally changing air–sea gradients in pCO2, and by inference the carbon flux in this region. Here, we utilize available pCO2 observations to evaluate how the seasonal cycle, interannual variability, and long-term trends in surface ocean pCO2 in the Drake Passage region compare to that of the broader subpolar Southern Ocean. Our results indicate that the Drake Passage is representative of the broader region in both seasonality and long-term pCO2 trends, as evident through the agreement of timing and amplitude of seasonal cycles as well as trend magnitudes both seasonally and annually. The high temporal density of sampling by the DPT is critical to constraining estimates of the seasonal cycle of surface pCO2 in this region, as winter data remain sparse in areas outside of the Drake Passage. An increase in winter data would aid in reduction of uncertainty levels. On average over the period 2002–2016, data show that carbon uptake has strengthened with annual surface ocean pCO2 trends in the Drake Passage and the broader subpolar Southern Ocean less than the global atmospheric trend. Analysis of spatial correlation shows Drake Passage pCO2 to be representative of pCO2 and its variability up to several hundred kilometers away from the region. We also compare DPT data from 2016 and 2017 to contemporaneous pCO2 estimates from autonomous biogeochemical floats deployed as part of the Southern Ocean Carbon and Climate Observations and Modeling project (SOCCOM) so as to highlight the opportunity for evaluating data collected on autonomous observational platforms. Though SOCCOM floats sparsely sample the Drake Passage region for 2016–2017 compared to the Drake Passage Time-series, their pCO2 estimates fall within the range of underway observations given the uncertainty on the estimates. Going forward, continuation of the Drake Passage Time-series will reduce uncertainties in Southern Ocean carbon uptake seasonality, variability, and trends, and provide an invaluable independent dataset for post-deployment assessment of sensors on autonomous floats. Together, these datasets will vastly increase our ability to monitor change in the ocean carbon sink.

Reconstructing surface ocean CO2 from scarce measurements plays an important role in estimating oceanic CO2 uptake. There are varying degrees of differences among the 14 models included in the Surface Ocean CO2 Mapping (SOCOM) inter-comparison initiative, in which five models used neural networks. This investigation evaluates two neural networks used in SOCOM, self-organization map and feedforward neural network, and introduces a machine learning model called support vector machine for ocean CO2 mapping. The technique note provides a practical guide to selecting the models.

The Surface Ocean CO2 NETwork (SOCONET) and atmospheric Marine Boundary Layer (MBL) CO2 measurements from ships and buoys focus on the operational aspects of measurements of CO2 in both the ocean surface and atmospheric MBLs. The goal is to provide accurate pCO2 data to within 2 micro atmosphere (μatm) for surface ocean and 0.2 parts per million (ppm) for MBL measurements following rigorous best practices, calibration and intercomparison procedures. Platforms and data will be tracked in near real-time and final quality-controlled data will be provided to the community within a year. The network, involving partners worldwide, will aid in production of important products such as maps of monthly resolved surface ocean CO2 and air-sea CO2 flux measurements. These products and other derivatives using surface ocean and MBL CO2 data, such as surface ocean pH maps and MBL CO2 maps, will be of high value for policy assessments and socio-economic decisions regarding the role of the ocean in sequestering anthropogenic CO2 and how this uptake is impacting ocean health by ocean acidification. SOCONET has an open ocean emphasis but will work with regional (coastal) networks. It will liaise with intergovernmental science organizations such as Global Atmosphere Watch (GAW), and the joint committee for and ocean and marine meteorology (JCOMM). Here we describe the details of this emerging network and its proposed operations and practices RW, AS, LB, DP, JT, NB, TT, RF, KO’B, and KT were supported by the NOAA office of Oceanic and Atmospheric Research, including the Ocean Observations and Monitoring Division (OOMD), funding reference #100007298 and PMEL contribution #4893. AO and SL were supported by the Norwegian Research Council (ICOS-Norway 245927). MT acknowledges support from the United States National Science Foundation grant OCE-1840868 to the Scientific Committee on Oceanic Research (SCOR, United States). US was supported by the European AtlantOS project (Grant Agreement #633211), RINGO project (Grant Agreement #730944), the United Kingdom NERC SONATA project (Grant No. NE/P021417/1), and RAGNARoCC project (Grant No. NE/K002473/1). PP was supported by the NERC SONATA project. MH was partly supported by the German Federal Ministry of Education and Research (grant no. 01LK1224I; ICOS-D). BT was supported by the Australia’s Integrated Marine Observing System. NCAR was sponsored by the United States National Science Foundation SI

International audience; Key Points: 6 • Weakly varying climatological winds reduce upper ocean vertical mixing, affect-7 ing the redistribution of air-sea fluxes 8 • Coupled to an atmospheric boundary layer, the modeled ocean response to clima-9 tological winds is to warm up considerably at the surface 10 • Results illustrate the pivotal improvements in air-sea interactions achieved by driv-11 ing an ocean model with an atmospheric boundary layer 12 Abstract 13 We examine various strategies for forcing ocean-only models, including an atmospheric 14 boundary layer model. This surface forcing allows air-sea exchanges to affect atmospheric 15 temperature and relative humidity, thus removing the assumption of an infinite atmo-16 spheric heat capacity associated with the prescription of these variables. When exposed 17 to climatological winds, the simulated North Atlantic oceanic temperature warms con-18 siderably at the surface as compared to a model with full atmospheric variability. This 19 warming is mainly explained by a weakened upper ocean vertical mixing in response to 20 the weakly varying climatological winds. Specifying the atmospheric temperatures in-21 hibits this warming, but depends on the unrealistic large atmospheric heat capacity. We 22 thus interpret the simulated warmer ocean as a more physically consistent ocean response. 23 We conclude the use of an atmospheric boundary layer model provides many benefits 24 for ocean only modeling, although a 'normal' year strategy is required for maintaining 25 high frequency winds. 26

We use a neural network-based estimate of the sea surface partial pressure of CO2 (pCO(2)) derived from measurements assembled within the Surface Ocean CO2 Atlas to investigate the dominant modes of pCO(2) variability from 1982 through 2015. Our analysis shows that detrended and deseasonalized sea surface pCO(2) varies substantially by region and the respective frequencies match those from the major modes of climate variability (Atlantic Multidecadal Oscillation, Pacific Decadal Oscillation, multivariate ENSO index, Southern Annular Mode), suggesting a climate modulated air-sea exchange of CO2. We find that most of the regional pCO(2) variability is driven by changes in the ocean circulation and/or changes in biology, whereas the North Atlantic variability is tightly linked to temperature variations in the surface ocean and the resulting changes in solubility. Despite the 34-year time series, our analysis reveals that we can currently only detect one to two periods of slow frequency oscillations, challenging our ability to robustly link pCO(2) variations to climate variability. Plain Language Summary In our study we show that there is a link between the amount of carbon in the surface ocean and natural climate variability. We find that this variability is very different between different oceanic regions, but most of the observed variability is on decadal timescales and longer. Current data products therefore do not extend long enough in time to robustly detect long-term oscillations of the surface ocean carbon content.

Winter data of surface ocean temperature (SST), salinity (SSS) and CO2 fugacity (fCO(2)) collected on the VOS M/V Nuka Arctica in the subpolar North Atlantic between 2004 and 2017 are used to establish trends, drivers, and interannual variability. Over the period, waters cooled and freshened, and the fCO(2) increased at a rate similar to the atmospheric CO2 growth rate. When accounting for the freshening, the inferred increase in dissolved inorganic carbon (DIC) was found to be approximately twice that expected from atmospheric CO2 alone. This is attributed to the cooling. In the Irminger Sea, fCO(2) exhibited additional interannual variations driven by atmospheric forcing through winter mixing. As winter fCO(2) in the region is close to the atmospheric, the subpolar North Atlantic has varied between being slightly supersaturated and slightly undersaturated over the investigated period.

Spatio-temporal variability of surface geostrophic mesoscale currents in the Balearic Sea (western Mediterranean) is characterized from satellite altimetry in combination with in-situ velocity measurements collected, among others, by drifting buoys, gliders and high-frequency radar. Here, we explore the use of tracking data from living organisms in the Balearic Sea as an alternative way to acquire in-situ velocity measurements. Specifically, we use GPS-tracks of resting Scopoli¿s shearwaters Calonectris diomedea, that act as passive drifters, and compare them with satellite-derived velocity patterns. Results suggest that animal-borne GPS data can be used to identify rafting behaviour outside of the breeding colonies and, furthermore, as a proxy to describe local sea surface currents. Four rafting patterns were identified according to the prevailing driving forces responsible for the observed trajectories. We find that 76% of the bird trajectories are associated with the combined effects of slippage and Ekman drift and/or surface drag; 59% are directly driven by the sea surface currents. Shearwaters are therefore likely to be passively transported by these driving forces while resting. The tracks are generally consistent with the mesoscale features observed in satellite data and identified with eddy-tracking software., The study was conducted in the framework of the CMEMS Sea Level Thematic Assembly Centre (SL-TAC) and partially supported by CNES (grant OSTST-MANATEE).

The Surface Ocean CO2 Atlas (SOCAT) is a synthesis of quality-controlled fCO2 (fugacity of carbon dioxide) values for the global surface oceans and coastal seas with regular updates. Version 3 of SOCAT has 14.7 million fCO2 values from 3646 data sets covering the years 1957 to 2014. This latest version has an additional 4.6 million fCO2 values relative to version 2 and extends the record from 2011 to 2014. Version 3 also significantly increases the data availability for 2005 to 2013. SOCAT has an average of approximately 1.2 million surface water fCO2 values per year for the years 2006 to 2012. Quality and documentation of the data has improved. A new feature is the data set quality control (QC) flag of E for data from alternative sensors and platforms. The accuracy of surface water fCO2 has been defined for all data set QC flags. Automated range checking has been carried out for all data sets during their upload into SOCAT. The upgrade of the interactive Data Set Viewer (previously known as the Cruise Data Viewer) allows better interrogation of the SOCAT data collection and rapid creation of high-quality figures for scientific presentations. Automated data upload has been launched for version 4 and will enable more frequent SOCAT releases in the future. High-profile scientific applications of SOCAT include quantification of the ocean sink for atmospheric carbon dioxide and its long-term variation, detection of ocean acidification, as well as evaluation of coupled-climate and ocean-only biogeochemical models. Users of SOCAT data products are urged to acknowledge the contribution of data providers, as stated in the SOCAT Fair Data Use Statement. This ESSD (Earth System Science Data) "living data" publication documents the methods and data sets used for the assembly of this new version of the SOCAT data collection and compares these with those used for earlier versions of the data collection (Pfeil et al., 2013; Sabine et al., 2013; Bakker et al., 2014). Individual data set files, included in the synthesis product, can be downloaded here: doi:10.1594/PANGAEA.849770. The gridded products are available here: doi:10.3334/CDIAC/OTG.SOCAT_V3_GRID.

The Southern Ocean south of 35°S accounts for approximately half of the annual oceanic carbon uptake, thereby substantially mitigating the effects of anthropogenic carbon dioxide (CO2) emissions. The intensity of this important carbon sink varies considerably on inter-annual to decadal timescales. However, the drivers of this variability are still debated, challenging our ability to accurately predict the future role of the Southern Ocean in absorbing atmospheric carbon. Analysing mapped sea-air CO2 fluxes, estimated from upscaled surface ocean CO2 measurements, we find that the overall Southern Ocean carbon sink has weakened since ~2011, reversing the trend of the reinvigoration period of the 2000s. Although we find significant regional positive and negative responses of the Southern Ocean carbon uptake to changes in the Southern Annular Mode (SAM) over the past 35 years, the net effect of the SAM on the Southern Ocean carbon sink variability is approximately zero, due to the opposing effects of enhanced outgassing in upwelling regions and enhanced carbon uptake elsewhere. Instead, regional shifts in sea level pressure, linked to zonal wavenumber 3 (ZW3) and related changes in surface winds substantially contribute to the inter-annual to decadal variability of the Southern Ocean carbon sink.

We report global long-term trends in surface ocean pH using a new pH data set computed by combining fCO2 observations from the Surface Ocean CO2 Atlas (SOCAT) version 2 with surface alkalinity estimates based on temperature and salinity. Trends were determined over the periods 1981–2011 and 1991–2011 for a set of 17 biomes using a weighted linear least squares method. We observe significant decreases in surface ocean pH in ~70% of all biomes and a mean rate of decrease of 0.0018 ± 0.0004 yr−1 for 1991–2011. We are not able to calculate a global trend for 1981–2011 because too few biomes have enough data for this. In half the biomes, the rate of change is commensurate with the trends expected based on the assumption that the surface ocean pH change is only driven by the surface ocean CO2 chemistry remaining in a transient equilibrium with the increase in atmospheric CO2. In the remaining biomes, deviations from such equilibrium may reflect that the trend of surface ocean fCO2 is not equal to that of the atmosphere, most notably in the equatorial Pacific Ocean, or may reflect changes in the oceanic buffer (Revelle) factor. We conclude that well-planned and long-term sustained observational networks are key to reliably document the ongoing and future changes in ocean carbon chemistry due to anthropogenic forcing.

The proposed strong positive relationship between dimethylsulphide (DMS) concentration and the solar radiation dose (SRD) received into the surface ocean is tested using data from the Atlantic Meridional Transect (AMT) programme. In situ, daily data sampled concurrently with DMS concentrations is used for the component variables of the SRD (mixed layer depth, MLD, surface insolation, I0, and a light attenuation coefficient, k) to calculate SRDinsitu. This is the first time in situ data for all of the components, including k, has been used to test the SRD-DMS relationship over large spatial scales. We find a significant correlation (ρ=0.55 n=65 p−2) is less than previously found at the global (0.019 nM/W m−2) and regional scales (Blanes Bay, Mediterranean, 0.028 nM/W m−2; Sargasso Sea 0.017 nM/W m−2). The correlation is improved (ρ=0.74 n=65 pI0 (which assumes a constant 50% removal of the top of atmosphere value; 0.5×TOA), a MLD climatology and a fixed value for k following previous work. Equally strong, but non-linear relationships are also found between DMS and both in situ MLD (ρ=0.61 n=65 pI0 (ρ=0.73 n=65 pn=54 p

Deep Pacific cooling Earth's climate cooled considerably across the transition from the Medieval Warm Period to the Little Ice Age about 700 years ago. Theoretically, owing to how the ocean circulates, this cooling should be recorded in Pacific deep-ocean temperatures, where water that was on the surface then is found today. Gebbie and Huybers used an ocean circulation model and observations from both the end of the 19th century and the end of the 20th century to detect and quantify this trend. The ongoing deep Pacific is cooling, which revises Earth's overall heat budget since 1750 downward by 35%. Science , this issue p. 70

It has been speculated that the partial pressure of carbon dioxide (pCO2) in shelf waters may lag the rise in atmospheric CO2. Here, we show that this is the case across many shelf regions, implying a tendency for enhanced shelf uptake of atmospheric CO2. This result is based on analysis of long-term trends in the air–sea pCO2 gradient (ΔpCO2) using a global surface ocean pCO2 database spanning a period of up to 35 years. Using wintertime data only, we find that ΔpCO2 increased in 653 of the 825 0.5° cells for which a trend could be calculated, with 325 of these cells showing a significant increase in excess of +0.5 μatm yr−1 (p, 0, SCOPUS: ar.j, info:eu-repo/semantics/published

WOS:000447661300002; International audience; Marine net community production (NCP) tracks uptake of carbon by plankton communities and its potential transport to depth. Relationships between marine microbial community composition and NCP currently remain unclear despite their importance for assessing how different taxa impact carbon export. We conducted 16 and 18S rRNA gene (rDNA) sequencing on samples collected across the Western North Atlantic in parallel with high-resolution O-2/Ar-derived NCP measurements. Using an internal standard technique to estimate in-situ prokaryotic and eukaryotic rDNA abundances per liter, we employed statistical approaches to relate patterns of microbial diversity to NCP. Taxonomic abundances calculated using internal standards provided valuable context to traditional relative abundance metrics. A bloom in the Mid-Atlantic Bight featured high eukaryote abundances with low eukaryotic diversity and was associated with the harmful algal bloom-forming Aureococcusanophagefferens, phagotrophic algae, heterotrophic flagellates, and particle-associated bacteria. These results show that coastal Aureococcus blooms host a distinct community associated with regionally significant peaks in NCP. Meanwhile, weak relationships between taxonomy and NCP in less-productive waters suggest that productivity across much of this region is not linked to specific microplankton taxa.

We have developed a statistical gap-filling method adapted to the specific coverage and properties of observed fugacity of surface ocean CO2 (fCO2). We have used this method to interpolate the Surface Ocean CO2 Atlas (SOCAT) v2 database on a 2.5°×2.5° global grid (south of 70°N) for 1985–2011 at monthly resolution. The method combines a spatial interpolation based on a “radius of influence” to determine nearby similar fCO2 values with temporal harmonic and cubic spline curve-fitting, and also fits long-term trends and seasonal cycles. Interannual variability is established using deviations of observations from the fitted trends and seasonal cycles. An uncertainty is computed for all interpolated values based on the spatial and temporal range of the interpolation. Tests of the method using model data show that it performs as well as or better than previous regional interpolation methods, but in addition it provides a near-global and interannual coverage.

Carbon and nutrients are transported out of the surface ocean and sequestered at depth by sinking particles. Sinking particle sizes span many orders of magnitude and the relative influence of small particles on carbon export compared to large particles has not been resolved. To determine the influence of particle size on carbon export, the flux of both small (11–64 μm) and large (> 64 μm) particles in the upper mesopelagic was examined during 5 cruises of the Bermuda Atlantic Time Series (BATS) in the Sargasso Sea using neutrally buoyant sediment traps mounted with tubes containing polyacrylamide gel layers and tubes containing a poisoned brine layer. Particles were also collected in surface-tethered, free-floating traps at higher carbon flux locations in the tropical and subtropical South Atlantic Ocean. Particle sizes spanning three orders of magnitude were resolved in gel samples, included sinking particles as small as 11 μm. At BATS, the number flux of small particles tended to increase with depth, whereas the number flux of large particles tended to decrease with depth. The carbon content of different sized particles could not be modeled by a single set of parameters because the particle composition varied across locations and over time. The modeled carbon flux by small particles at BATS, including all samples and depths, was 39 ± 20% of the modeled total carbon flux, and the percentage increased with depth in 4 out of the 5 months sampled. These results indicate that small particles (

The oceanic uptake of anthropogenic carbon is tightly coupled to carbon subduction, i.e., the physical carbon transfer from the well-ventilated surface ocean to its interior. Despite their importance, pathways of anthropogenic carbon subduction are poorly understood. Here we use an ocean carbon cycle model to quantify the mechanisms controlling this subduction. Over the last decade, 90% of the oceanic anthropogenic carbon is subducted at the base of the seasonally varying mixed layer. Vertical diffusion is the primary mechanism of this subduction (contributing 65% of total subduction), despite very low local fluxes. In contrast, advection drives the spatial patterns of subduction, with high positive and negative local fluxes. Our results suggest that vertical diffusion could have a leading role in anthropogenic carbon subduction, which highlights the need for an accurate estimate of vertical diffusion intensity in the upper ocean to further constrain estimates of the future evolution of carbon uptake.

Due to the covariation between temperature and resource availability in the surface ocean, a correct assessment of resource supply is crucial to determine if temperature has a direct effect on phytoplankton size structure. To remove the effect of resources, Lopez-Urrutia and Moran analyzed data subsets with narrow ranges of variation in Chlorophyll a (Chl a) concentration and found that temperature is correlated with Chl a partitioning among size classes, from which they concluded that temperature is an important variable to explain the variability of phytoplankton size structure. Our analysis, however, shows that resource supply varies widely also within these subsets and, importantly, that it is inversely correlated with temperature. Therefore, the relationship between temperature and size structure reflects instead the effect of resources. When groups of samples with similar resource supply conditions are considered, no correlation between temperature and phytoplankton size structure is observed, which invalidates the conclusion of Lopez-Urrutia and Moran. Even within restricted ranges of variation for phytoplankton biomass and production, changes in resource supply alone are sufficient to explain the variability of phytoplankton size structure in the sea.

This dataset includes the monthly distributions of CO2 fugacity in the world surface oceans reconstructed using a feed-forward neural network model and the CO2 measurements of the Surface Ocean CO2 Atlas version 2.0. It has a spatial resolution of 1 9 1° and spans a period of 22 years, from January 1990 to December 2011. The dataset also includes necessary parameters for the reconstruction and an estimate of the CO2 fluxes between the ocean and the atmosphere. The aim of this work is to provide a dataset for estimating the oceans’ contribution to the global carbon budget.

Ocean carbon monitoring efforts have increased dramatically in the past few decades in response to the need for better marine carbon cycle characterization. Autonomous pH and carbon dioxide (CO2) sensors capable of yearlong deployments are now commercially available; however, due to their strong covariance, this is the least desirable pair of carbonate system parameters to measure for high-quality, in situ, carbon-cycle studies. To expand the number of tools available for autonomous carbonate system observations, we have developed a robust surface ocean dissolved inorganic carbon (DIC) sensor capable of extended (year) field deployments with a laboratory determined uncertainty of ±5 μmol kg(-1). Results from the first two field tests of this prototype sensor indicate that measurements of DIC are ∼90% more accurate than estimates of DIC calculated from contemporaneous and collocated measurements of pH and CO2. The improved accuracy from directly measuring DIC gives rise to new opportunities for quantitative, autonomous carbon-cycle studies.

The diversity and geographical distribution of populations within major marine microbial lineages are largely governed by temperature and its co-variables. However, neither the mechanisms by which genomic heterogeneity emerges within a single population nor how it drives the partitioning of ecological niches are well understood. Here we took advantage of billions of metagenomic reads to study one of the most abundant and widespread microbial populations in the surface ocean. We characterized its substantial amount of genomic heterogeneity using single-amino acid variants (SAAVs), and identified systematic purifying selection and adaptive mechanisms governing non-synonymous variation within this population. Our Deep Learning analysis of SAAVs across metagenomes revealed two main ecological niches that reflect large-scale oceanic current temperatures, as well as six proteotypes demarcating finer-resolved niches. We identified significantly more protein variants in cold currents and an increased number of protein sweeps in warm currents, exposing a global pattern of alternating genomic diversity for this SAR11 population as it drifts along with surface ocean currents. Overall, the geographic partitioning of SAAVs suggests natural selection, rather than neutral evolution, is the main driver of the evolution of SAR11 in surface oceans.

International audience; Planet Earth has entered a new geological era, the Anthropocene, in which geologically significant conditions and processes are profoundly altered by human activities (Waters et al., 2016). Among many impacts, human activities have released excessive amounts of carbon dioxide (CO2) in the atmosphere leading to warming and ocean acidification: a decrease in pH and CO32- concentration and an increase in CO2 and HCO3- concentrations (Gattuso and Hansson, 2011). On average, at the global scale, surface ocean pH has decreased by 0.1 units since the beginning of the industrial era, equivalent to an increased acidity of 26% (Ciais et al., 2013). An additional decrease of pH is expected by 2100, ranging from 0.07 to 0.33, depending on the CO2 emission scenario considered (Gattuso et al., 2015).

While the number of surface ocean CO2 partial pressure (pCO2) measurements has soared the recent decades, the Southern Ocean remains undersampled. Williams et al. (2017) now present pCO2 estimates based on data from pH-sensor equipped Bio-Argo floats, which have been measuring in the Southern Ocean since 2014. The authors demonstrate the utility of these data for understanding the carbon cycle in this region, which has a large influence on the distribution of CO2 between the ocean and atmosphere. Biogeochemical sensors deployed on autonomous platforms hold the potential to shape our view of the ocean carbon cycle in the coming decades.

U.S. National Science Foundation's Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) project under the NSF [PLR-1425989]; NASA [NNX14AP49G]; U.S. Argo through NOAA/JISAO grant [NA17RJ1232]; Ocean Observations and Monitoring Division, Climate Program Office, National Oceanic and Atmospheric Administration, U.S. Department of Commerce; David and Lucile Packard Foundation; NOAA Climate and Global Change postdoctoral fellowship; ARCS Foundation Oregon Chapter

The biological carbon pump (BCP) transfers carbon from the surface ocean into the oceans' interior, mainly in the form of sinking particles with an organic component, and thereby keeps atmospheric CO2 at significantly lower levels than if the oceans were abiotic. The depth at which these sinking particles are remineralized is a key control over atmospheric CO2. Particle sinking speed is likely to be a critical parameter over remineralization depth. Carbon export is usually controlled by large, rapidly sinking particles (>150 m·d−1); however, under some circumstances sinking velocity distributions are strongly bimodal with a significant fraction of total flux being carried by slowly (

About 30% of the anthropogenically released CO2 is taken up by the oceans, which causes surface ocean pH to decrease and is commonly referred to as Ocean Acidification (OA). Foraminifera are one of the most abundant groups of marine calcifiers, estimated to precipitate ca. 50% of biogenic calcium carbonate in the open oceans. We have compiled the state of the art of OA effects on foraminifera, because the majority of OA research on this group was published within the last 3 yr. Disparate responses of this important group of marine calcifiers to OA were reported, highlighting the importance of a process based understanding of OA effects on foraminifera. The benthic foraminifer Ammonia sp. was cultured using two carbonate chemistry manipulation approaches: While pH and carbonate ions where varied in one, pH was kept constant in the other while carbonate ion concentration varied. This allows the identification of teh parameter of the parameter of the carbonate system causing observed effects. This parameter identification is the first step towards a process based understanding. We argue that [CO32−] is the parameter affecting foraminiferal size normalized weights (SNW) and growth rates and based on the presented data we can confirm the strong potential of foraminiferal SNW as a [CO32−] proxy.

International audience; The ability of pelagic copepods to remotely detect and encounter potential sexual partners is a critical issue in zooplankton ecology. In calanoid copepods, mate-finding behaviour involves either chemical or hydromechanical cues. Here, I first provide a detailed description of the three-dimensional swimming behaviour of Eurytemora affinis, males, non-ovigerous females and ovigerous females swimming freely in the absence of chemical and hydromechanical cues and discuss potential reasons for the discrepancies observed in the literature. I further demonstrate that E. affinis males modify their swimming behaviour in response to a diffuse background of pheromone concentrations, which can be thought of as an adaptation to increase the encounter rate and follow trail mimics containing female scent. I finally describe the mate-seeking behaviour of E. affinis and show how males swimming freely in a three-dimensional environment modify their direction of motion upon encountering the pheromone trails of females and subsequently follow female trails over distance and duration of nearly 15 cm and 36 s until they hydromechanically sense the female and lunge at her. The relevance of these results is discussed in the general framework of search pattern strategies and the relative contribution of chemical versus hydromechanical cues in relation to the turbulent nature of the surface ocean.

Sabine, C. L. et al., As a response to public demand for a well-documented, quality controlled, publically available, global surface ocean carbon dioxide (CO2) data set, the international marine carbon science community developed the Surface Ocean CO2 Atlas (SOCAT). The first SOCAT product is a collection of 6.3 million quality controlled surface CO2 data from the global oceans and coastal seas, spanning four decades (1968–2007). The SOCAT gridded data presented here is the second data product to come from the SOCAT project. Recognizing that some groups may have trouble working with millions of measurements, the SOCAT gridded product was generated to provide a robust, regularly spaced CO2 fugacity (fCO2) product with minimal spatial and temporal interpolation, which should be easier to work with for many applications. Gridded SOCAT is rich with information that has not been fully explored yet (e.g., regional differences in the seasonal cycles), but also contains biases and limitations that the user needs to recognize and address (e.g., local influences on values in some coastal regions)., SOCAT is promoted by IOCCP, the Sur- face Ocean Lower Atmosphere Study, and the Integrated Marine Biogeochemistry and Ecosystem Research program. Douglas Wallace (Dalhousie University, Canada and former SOLAS chair) has strongly encouraged SOCAT. Support has been received from the University of Bergen (Norway), the Bjerknes Centre for Cli- mate Research (Norway), the National Oceanic and Atmospheric Administration (United States), the University of Washington (United States), Oak Ridge National Laboratory (United States), the University of East Anglia (United Kingdom), PANGAEA – Data Publisher for Earth & Environmental data (Germany), the Alfred Wegener Institute for Polar and Marine Research (Ger- many), the Centre National de la Recherche Scientifique (France), the CarboOcean (Norway, GOCE 511176-1) and CarboChange (Norway, FP7 264879) projects of the European Union, the US National Science Foundation (United States, OCE-1068958), the international Scientific Committee on Oceanic Research (SCOR, United States, OCE-0938349), and the UK Ocean Acidification Research Programme (NE / H017046 / 1; funded by the Natural Environment Research Council, the Department for Energy and Climate Change and the Department for Environment, Food and Rural A ff airs). Support for SOCAT meetings has been received from IOCCP, IMBER, the European Cooperation in Science and Technology (COST) Action 735 (United Kingdom), Geomar (Germany), the National Institute for Environmental Studies (Japan), and the Commonwealth Scientific and Industrial Research Organisation (Australia).

The main objective of this study was to model the contribution of shelf sediments in the Arctic Ocean to the total mass of neutral organic contaminants accumulated in the Arctic environment using a standardized emission scenario for sets of hypothetical chemicals and realistic emission estimates (1930-2100) for polychlorinated biphenyl congener 153 (PCB-153). Shelf sediments in the Arctic Ocean are shown to be important reservoirs for neutral organic chemicals across a wide range of partitioning properties, increasing the total mass in the surface compartments of the Arctic environment by up to 3.5-fold compared to simulations excluding this compartment. The relative change in total mass for hydrophobic organic chemicals with log air-water partition coefficients ≥0 was greater than for chemicals with properties similar to typical POPs. The long-term simulation of PCB-153 generated modeled concentrations in shelf sediments in reasonable agreement with available monitoring data and illustrate that the relative importance of shelf sediments in the Arctic Ocean for influencing surface ocean concentrations (and therefore exposure via the pelagic food web) is most pronounced once primary emissions are exhausted and secondary sources dominate. Additional monitoring and modeling work to better characterize the role of shelf sediments for contaminant fate is recommended.

We use isoprene and related field measurements from three different ocean data sets together with remotely sensed satellite data to model global marine isoprene emissions. We show that using monthly mean satellite-derived chl a concentrations to parameterize isoprene with a constant chl a normalized isoprene production rate underpredicts the measured oceanic isoprene concentration by a mean factor of 19 ± 12. Improving the model by using phytoplankton functional type dependent production values and by decreasing the bacterial degradation rate of isoprene in the water column results in only a slight underestimation (factor 1.7 ± 1.2). We calculate global isoprene emissions of 0.21 Tg C for 2014 using this improved model, which is twice the value calculated using the original model. Nonetheless, the sea-to-air fluxes have to be at least 1 order of magnitude higher to account for measured atmospheric isoprene mixing ratios. These findings suggest that there is at least one missing oceanic source of isoprene and, possibly, other unknown factors in the ocean or atmosphere influencing the atmospheric values. The discrepancy between calculated fluxes and atmospheric observations must be reconciled in order to fully understand the importance of marine-derived isoprene as a precursor to remote marine boundary layer particle formation.