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We use the method of least squares with Lagrange multipliers to fit an ocean general circulation model to the Multiproxy Approach for the Reconstruction of the Glacial Ocean Surface (MARGO) estimate of near sea surface temperature (NSST) at the Last GlacialMaximum (LGM; circa 23–19 thousand years ago). Compared to a modern simulation, the resulting global, last-glacial ocean state estimate, which fits the MARGO data within uncertainties in a free-running coupled ocean–sea ice simulation, has global-mean NSSTs that are 2°C lower and greater sea ice extent in all seasons in both the Northern and Southern Hemispheres. Increased brine rejection by sea ice formation in the Southern Ocean contributes to a stronger abyssal stratification set principally by salinity, qualitatively consistent with pore fluid measurements. The upper cell of the glacial Atlantic overturning circulation is deeper and stronger. Dye release experiments show similar distributions of Southern Ocean source waters in the glacial and modern western Atlantic, suggesting that LGM NSST data do not require a major reorganization of abyssal water masses. Outstanding challenges in reconstructing LGM ocean conditions include reducing effects from model biases and finding computationally efficient ways to incorporate abyssal tracers in global circulation inversions. Progress will be aided by the development of coupled ocean–atmosphere–ice inverse models, by improving high-latitude model processes that connect the upper and abyssal oceans, and by the collection of additional paleoclimate observations.

This paper investigates the uncertainties related to atmospheric fields from reanalysis products used in forcing ocean models. Four reanalysis products, namely from 1) the interim ECMWF Re-Analysis (ERA-Interim), 2) version 2 of the Common Reference Ocean–Ice Experiments (CORE2), 3) the 25-Year Japanese Reanalysis Project (JRA-25), and 4) NCEP–NCAR, are evaluated against satellite-derived observations for eight different fields (zonal and meridional winds, precipitation, specific humidity, continental discharge, surface air temperature, and downwelling longwave and shortwave radiation fluxes). No single product is found to agree better inallfields with satellite-derived observations. Reanalysis products are mostly comparable to each other because of their similar physical assumptions and assimilation of common observations. Adjusted atmospheric fields from the Estimating the Circulation and Climate of the Ocean (ECCO) optimizations are also in agreement with other reanalysis products. Time-mean and time-variable errors are estimated separately and mapped globally in space, based on 14-day average fields to focus on monthly to interannual periods. Time-variable errors are larger in comparison to the signal than time-mean errors for most fields, thus justifying the need to separate them for studying uncertainties as well as formulating optimization procedures. Precipitation and wind stress fields show significant time-mean and time-variable errors whereas downwelling radiation, air temperature, and humidity fields show small time-mean errors but large time-variable errors, particularly in the tropics. Uncertainties based on evaluating multiple products presented here are considerably larger than uncertainties based on single product pairs.

Ocean–sea ice reanalyses are crucial for assessing the variability and recent trends in the Arctic sea ice cover. This is especially true for sea ice volume, as long-term and large scale sea ice thickness observations are inexistent. Results from the Ocean ReAnalyses Intercomparison Project (ORA-IP) are presented, with a focus on Arctic sea ice fields reconstructed by state-of-the-art global ocean reanalyses. Differences between the various reanalyses are explored in terms of the effects of data assimilation, model physics and atmospheric forcing on properties of the sea ice cover, including concentration, thickness, velocity and snow. Amongst the 14 reanalyses studied here, 9 assimilate sea ice concentration, and none assimilate sea ice thickness data. The comparison reveals an overall agreement in the reconstructed concentration fields, mainly because of the constraints in surface temperature imposed by direct assimilation of ocean observations, prescribed or assimilated atmospheric forcing and assimilation of sea ice concentration. However, some spread still exists amongst the reanalyses, due to a variety of factors. In particular, a large spread in sea ice thickness is found within the ensemble of reanalyses, partially caused by the biases inherited from their sea ice model components. Biases are also affected by the assimilation of sea ice concentration and the treatment of sea ice thickness in the data assimilation process. An important outcome of this study is that the spatial distribution of ice volume varies widely between products, with no reanalysis standing out as clearly superior as compared to altimetry estimates. The ice thickness from systems without assimilation of sea ice concentration is not worse than that from systems constrained with sea ice observations. An evaluation of the sea ice velocity fields reveals that ice drifts too fast in most systems. As an ensemble, the ORA-IP reanalyses capture trends in Arctic sea ice area and extent relatively well. However, the ensemble can not be used to get a robust estimate of recent trends in the Arctic sea ice volume. Biases in the reanalyses certainly impact the simulated air–sea fluxes in the polar regions, and questions the suitability of current sea ice reanalyses to initialize seasonal forecasts.

Heat redistribution is one of the main mechanisms by which oceans regulate Earth’s climate. Analyses of ocean heat transport tend to emphasize global-scale seawater pathways and concepts such as the great ocean conveyor belt. However, it is the divergence or convergence of heat transport within an oceanic region, rather than the origin or destination of seawater transiting through that region, that is most immediately relevant to Earth’s heat budget. Here we use a recent gridded estimate of ocean heat transport to reveal the net effect on Earth’s heat budget, the ‘effective’ ocean heat transport, by removing internal ocean heat loops that have obscured the interpretation of measurements. The result demonstrates the overwhelming predominance of the tropical Pacific, which exports four times as much heat as is imported in the Atlantic and Arctic. It also highlights the unique ability of the Atlantic and Indian oceans to transport heat across the Equator—Northward and Southward, respectively. However, effective inter-ocean heat transports are smaller than expected, suggesting that global-scale seawater pathways play only a minor role in Earth’s heat budget.Effective heat transport in the global ocean is dominated by heat export from the tropical Pacific, whereas seawater transport pathways play only a minor role, according to an analysis of a gridded ocean data product.

The Ship Of Opportunity Expendable BathyThermograph (SOOP-XBT) Network has been measuring upper ocean temperature aboard volunteer vessels over multiple decades in key locations of the global ocean. Through international collaboration, these data are systematically collected, quality-controlled and made available to the scientific and operational communities. The network’s strengths: its low cost, high spatial resolution, and long-term repeatability, have made it a key asset for advancing ocean state estimation and climate studies. Here, we introduce a synthesis of formatted XBT data from selected transects across the global ocean, and provide a high-quality gridded product of temperature and derived salinity and absolute geostrophic velocity across five major boundary currents: the Gulf Stream, Kuroshio, East Australian Current, Brazil Current and the Antarctic Circumpolar Current. The Gridded Observations of XBT transects (GOXBT) product offers a unique temporal coverage and spatial resolution, providing a critical resource for ocean model and reanalysis validation, and supporting future studies on the variability and dynamics of major ocean currents.

The Southern Ocean features ventilation pathways that transport surface waters into the subsurface thermocline on time scales from decades to centuries, sequestering anomalies of heat and carbon away from the atmosphere and thereby regulating the rate of surface warming. Despite its importance for climate sensitivity, the factors that control the distribution of heat along these pathways are not well understood. In this study, we use an observationally constrained, physically consistent global ocean model to examine the sensitivity of heat distribution in the recently ventilated subsurface Pacific (RVP) sector of the Southern Ocean to changes in ocean temperature and salinity. First, we define the RVP using numerical passive tracer release experiments that highlight the ventilation pathways. Next, we use an ensemble of adjoint sensitivity experiments to quantify the sensitivity of the RVP heat content to changes in ocean temperature and salinity. In terms of sensitivities to surface ocean properties, we find that RVP heat content is most sensitive to anomalies along the Antarctic Circumpolar Current (ACC), upstream of the subduction hotspots. In terms of sensitivities to subsurface ocean properties, we find that RVP heat content is most sensitive to basin-scale changes in the subtropical Pacific Ocean, around the same latitudes as the RVP. Despite the localized nature of mode water subduction hotspots, changes in basin-scale density gradients are an important controlling factor on heat distribution in the southeast Pacific.

Global biogeochemical ocean models are invaluable tools to examine how physical, chemical, and biological processes interact in the ocean. Satellite-derived ocean color properties, on the other hand, provide observations of the surface ocean, with unprecedented coverage and resolution. Advances in our understanding of marine ecosystems and biogeochemistry are strengthened by the combined use of these resources, together with sparse in situ data. Recent modeling advances allow the simulation of the spectral properties of phytoplankton and remote sensing reflectances, bringing model outputs closer to the kind of data that ocean color satellites can provide. However, comparisons between model outputs and analogous satellite products (e.g., chlorophyll a) remain problematic. Most evaluations are based on point-by-point comparisons in space and time, where spuriously large errors can occur from small spatial and temporal mismatches, whereas global statistics provide no information on how well a model resolves processes at regional scales. Here, we employ a unique suite of methodologies, the Probability Density Functions to Evaluate Models (PDFEM), which generate a robust comparison of these resources. The probability density functions of physical and biological properties of Longhurst's provinces are compared to evaluate how well a model resolves related processes. Differences in the distributions of chlorophyll a concentration (mg m-3) provide information on matches and mismatches between models and observations. In particular, mismatches help isolate regional sources of discrepancy, which can lead to improving both simulations and satellite algorithms. Furthermore, the use of radiative transfer in the model to mimic remotely sensed products facilitates model–observation comparisons of optical properties of the ocean.

Iron is the limiting factor for biological production over a large fraction of the surface ocean because free iron is rapidly scavenged or precipitated under aerobic conditions. Standing stocks of dissolved iron are maintained by association with organic molecules (ligands) produced by biological processes. We hypothesize a positive feedback between iron cycling, microbial activity, and ligand abundance: External iron input fuels microbial production, creating organic ligands that support more iron in seawater, leading to further macronutrient consumption until other microbial requirements such as macronutrients or light become limiting, and additional iron no longer increases productivity. This feedback emerges in numerical simulations of the coupled marine cycles of macronutrients and iron that resolve the dynamic microbial production and loss of iron-chelating ligands. The model solutions resemble modern nutrient distributions only over a finite range of prescribed ligand source/sink ratios where the model ocean is driven to global-scale colimitation by micronutrients and macronutrients and global production is maximized. We hypothesize that a global-scale selection for microbial ligand cycling may have occurred to maintain “just enough” iron in the ocean.

As the major sink of anthropogenic heat, the Southern Ocean has shown quasi-symmetric, deep-reaching warming since the mid-twentieth century. In comparison, the shorter-term heat storage pattern of the Southern Ocean is more complex and has notable impacts on regional climate and marine ecosystems. By analyzing observational datasets and climate model simulations, this study reveals that the Southern Ocean exhibits prominent decadal (>8 years) variability extending to ∼700-m depth and is characterized by out-of-phase changes in the Pacific and Atlantic–Indian Ocean sectors. Changes in the Pacific sector are larger in magnitude than those in the Atlantic–Indian Ocean sectors and dominate the total heat storage of the Southern Ocean on decadal time scales. Instead of heat uptake through surface heat fluxes, these asymmetric variations arise primarily from wind-driven heat redistribution. Pacemaker and preindustrial simulations of the Community Earth System Model version 1 (CESM1) suggest that these variations in Southern Ocean winds arise primarily from natural variability of the tropical Pacific, as represented by the interdecadal Pacific oscillation (IPO). Through atmospheric teleconnection, the positive phase of the IPO gives rise to higher-than-normal sea level pressure and anticyclonic wind anomalies in the 50°–70°S band of the Pacific sector. These winds lead to warming of 0–700 m by driving the convergence of warm water. The opposite processes, involving cyclonic winds and upper-layer divergence, occur in the Atlantic–Indian Ocean sector. These findings aid our understanding of the time-varying heat storage of the Southern Ocean and provide useful implications on initialized decadal climate prediction.

The Southern Ocean (SO) is a major contributor to global ocean heat uptake, exhibiting deep-reaching warming trends within the 35°S-55°S band. Here, we reveal a notable inter-basin contrast in the SO warming rates. Over the past six decades, the warming of the 0-700 m Atlantic-Indian sector was 40.0 ± 5.7% faster than the Pacific sector, nearly doubling at ~44°S. Ocean-only and coupled model experiments suggest that this basin-scale contrast arises from alterations in wind-driven heat redistribution rather than surface heating. Specifically, the intensification and poleward migration of westerly winds are more prominent in the Atlantic-Indian sector, leading to stronger upper-layer heat convergence. The inter-basin warming contrast is projected to persist and amplify throughout the remainder of the 21 st century. This study highlights the inter-basin contrast in the past and future SO warming, with useful implications for understanding regional changes in the SO climate, ice mass, and marine ecosystems. This work highlights a sharp warming contrast within the Southern Ocean: the Atlantic-Indian sector warms faster than the Pacific due to wind-driven heat transport. The contrast is projected to persist, shaping future climate and ocean change.