Abstract

The surface energy balance on an atmosphereless body consists of solar irradiance, subsurface heat conduction, and thermal radiation to space by the Stefan–Boltzmann law. Here we extend the semi-implicit Crank–Nicolson method to this specific nonlinear boundary condition and validate its accuracy. A rapid change in incoming solar flux can cause a numerical instability, and several approaches to dampen this instability are analyzed. A predictor based on the Volterra integral equation formulation for the heat equation is also derived and can be used to improve accuracy and stability. The publicly available implementation provides a fast and robust thermophysical model that has been applied to lunar, Martian, and asteroidal surfaces, on occasion to millions of surface facets or parameter combinations.

Gas exchange between the atmosphere and ocean interior profoundly impacts global climate and biogeochemistry. However, our understanding of the relevant physical processes remains limited by a scarcity of direct observations. Dissolved noble gases in the deep ocean are powerful tracers of physical air-sea interaction due to their chemical and biological inertness, yet their isotope ratios have remained underexplored. Here, we present high-precision noble gas isotope and elemental ratios from the deep North Atlantic (~32°N, 64°W) to evaluate gas exchange parameterizations using an ocean circulation model. The unprecedented precision of these data reveal deep-ocean undersaturation of heavy noble gases and isotopes resulting from cooling-driven air-to-sea gas transport associated with deep convection in the northern high latitudes. Our data also imply an underappreciated and large role for bubble-mediated gas exchange in the global air-sea transfer of sparingly soluble gases, including O ₂ , N ₂ , and SF ₆ . Using noble gases to validate the physical representation of air-sea gas exchange in a model also provides a unique opportunity to distinguish physical from biogeochemical signals. As a case study, we compare dissolved N ₂ /Ar measurements in the deep North Atlantic to physics-only model predictions, revealing excess N ₂ from benthic denitrification in older deep waters (below 2.9 km). These data indicate that the rate of fixed N removal in the deep Northeastern Atlantic is at least three times higher than the global deep-ocean mean, suggesting tight coupling with organic carbon export and raising potential future implications for the marine N cycle.

Abstract

Ocean geochemical tracers such as radiocarbon, protactinium and thorium isotopes, and noble gases are widely used to constrain a range of physical and biogeochemical processes in the ocean. However, their routine simulation in global ocean circulation and climate models is hindered by the computational expense of integrating them to a steady state. Here, a new approach to this long‐standing “spin‐up” problem is introduced to efficiently compute equilibrium distributions of such tracers in seasonally‐forced models. Based on “Anderson Acceleration,” a sequence acceleration technique developed in the 1960s to solve nonlinear integral equations, the new method is entirely “black box” and offers significant speed‐up over conventional direct time integration. Moreover, it requires no preconditioning, ensures tracer conservation and is fully consistent with the numerical time‐stepping scheme of the underlying model. It thus circumvents some of the drawbacks of other schemes such as matrix‐free Newton Krylov that have been proposed to address this problem. An implementation specifically tailored for the batch HPC systems on which ocean and climate models are typically run is described, and the method illustrated by applying it to a variety of geochemical tracer problems. The new method, which provides speed‐ups by over an order of magnitude, should make simulations of such tracers more feasible and enable their inclusion in climate change assessments such as IPCC.

Abstract. Biogeochemical model behaviour for micronutrients istypically hard to constrain because of the sparsity of observational data,the difficulty of determining parameters in situ, and uncertainties inobservations and models. Here, we assess the influence of data distribution,model uncertainty, and the misfit function on objective parameter optimisation ina model of the oceanic cycle of zinc (Zn), an essential micronutrient formarine phytoplankton with a long whole-ocean residence time. We aim toinvestigate whether observational constraints are sufficient forreconstruction of biogeochemical model behaviour, given that the Zn datacoverage provided by the GEOTRACES Intermediate Data Product 2017 is sparse.Furthermore, we aim to assess how optimisation results are affected by thechoice of the misfit function and by confounding factors such as analyticaluncertainty in the data or biases in the model related to either seasonalvariability or the larger-scale circulation. The model framework appliedherein combines a marine Zn cycling model with a state-of-the-art estimationof distribution algorithm (Covariance Matrix Adaption Evolution Strategy,CMA-ES) to optimise the model towards synthetic data in an ensemble of 26optimisations. Provided with a target field that can be perfectly reproducedby the model, optimisation retrieves parameter values perfectly regardlessof data coverage. As differences between the model and the system underlyingthe target field increase, the choice of the misfit function can greatly impactoptimisation results, while limitation of data coverage is in most cases ofsubordinate significance. In cases where optimisation to full or limiteddata coverage produces relatively distinct model behaviours, we find thatapplying a misfit metric that compensates for differences in data coveragebetween ocean basins considerably improves agreement between optimisationresults obtained with the two data situations.

Abstract. The skill of global ocean biogeochemical models, and the earth system models in which they areembedded, can be improved by systematic calibration of the parameter values against observations.However, such tuning is seldom undertaken as these models are computationally very expensive.Here we investigate the performance of DFO-LS,a local, derivative-free optimisation algorithm which has been designed for computationally expensive models with irregularmodel–data misfit landscapes typical of biogeochemical models. We use DFO-LS to calibrate six parameters of a relatively complexglobal ocean biogeochemical model (MOPS) against synthetic dissolved oxygen, phosphate andnitrate “observations” from a reference run of the same model with a known parameter configuration.The performance of DFO-LS is compared with that of CMA-ES, another derivative-free algorithm thatwas applied in a previous study to the same model in one of the first successful attempts at calibrating aglobal model of this complexity. We find that DFO-LS successfully recovers five of the six parameters in approximately 40evaluations of the misfit function (each one requiring a 3000-year run of MOPS to equilibrium), while CMA-ESneeds over 1200 evaluations. Moreover, DFO-LS reached a “baseline” misfit, defined by observational noise,in just 11–14 evaluations, whereas CMA-ES required approximately 340 evaluations. We also find that the performance of DFO-LS is not significantly affected by observational sparsity, however fewer parameters were successfully optimised in the presence of observational uncertainty. The results presented heresuggest that DFO-LS is sufficiently inexpensive and robust to apply to the calibration of complex, global oceanbiogeochemical models.

Abstract

Computer simulations are invaluable tools for scientific discovery. However, accurate simulations are often slow to execute, which limits their applicability to extensive parameter exploration, large-scale data analysis, and uncertainty quantification. A promising route to accelerate simulations by building fast emulators with machine learning requires large training datasets, which can be prohibitively expensive to obtain with slow simulations. Here we present a method based on neural architecture search to build accurate emulators even with a limited number of training data. The method successfully emulates simulations in 10 scientific cases including astrophysics, climate science, biogeochemistry, high energy density physics, fusion energy, and seismology, using the same super-architecture, algorithm, and hyperparameters. Our approach also inherently provides emulator uncertainty estimation, adding further confidence in their use. We anticipate this work will accelerate research involving expensive simulations, allow more extensive parameters exploration, and enable new, previously unfeasible computational discovery.

Abstract

Emissions of carbon dioxide from fossil fuel combustion are reducing the ratio ¹³C/¹²C, δ¹³C, in atmospheric CO₂ and in the carbon in the ocean and terrestrial biosphere that exchanges with the atmosphere on timescales of decades to centuries. Future changes to fossil fuel emissions vary across different scenarios and may cause decreases of more than 6% in atmospheric δ¹³CO₂ between 1850 and 2100. The effects of these potential changes on the three‐dimensional distribution of δ¹³C in the ocean have not yet been investigated. Here, we use an ocean biogeochemical‐circulation model forced with a range of Shared Socioeconomic Pathway (SSP)‐based scenarios to simulate δ¹³C in ocean dissolved inorganic carbon from 1850 to 2100. In the future, vertical and horizontal δ¹³C gradients characteristic of the biological pump are reduced or reversed, relative to the preindustrial period, with the reversal occurring in higher emission scenarios. For the highest emission scenario, SSP5‐8.5, surface δ¹³C in the center of Pacific subtropical gyres falls from 2.2% in 1850 to −3.5% by 2100. In lower emission scenarios, δ¹³C in the surface ocean decreases but then rebounds. The relationship between anthropogenic carbon (C_ant) and δ¹³C in the ocean shows a larger scatter in all scenarios, suggesting that uncertainties in δ¹³C‐based estimates of C_ant may increase in the future. These simulations were run with fixed physical forcing and ocean circulation, providing a baseline of predicted δ¹³C. Further work is needed to investigate the impact of climate‐carbon cycle feedbacks on ocean δ¹³C changes.

Abstract

In the subsurface ocean, O₂ depleted because of organic matter remineralization is generally estimated based on apparent oxygen utilization (AOU). However, AOU is an imperfect measure of oxygen utilization because of O₂ air‐sea disequilibrium at the site of deepwater formation. Recent methodological and instrumental advances have paved the way to further deconvolve the processes driving the O₂ signature. Using numerical model simulations of the global ocean, we show that the measurements of the dissolved O₂/Ar ratio, which so far have been confined to the ocean surface, can provide improved estimates of oxygen utilization, especially in regions where the disequilibrium at the site of deepwater formation is associated with physical processes. We discuss applications of this new approach and implications for the current tracers relying on O₂ such as remineralization ratios, respiratory quotients, and preformed nutrients. Finally, we propose a new composite geochemical tracer, combining dissolved O₂/Ar and phosphate concentration. Being insensitive to photosynthesis and respiration, the change in this new tracer reflects gas exchange at the air‐sea interface at the sites of deepwater formation.

Abstract

The climate's response to forcing depends on how efficiently heat is absorbed by the ocean. Much, if not most, of this ocean heat uptake results from the passive transport of warm surface waters into the ocean's interior. Here we examine how geographic patterns of surface warming influence the efficiency of this passive heat uptake process. We show that the average pattern of surface warming in CMIP5 damps passive ocean heat uptake efficiency by nearly 25%, as compared to homogeneous surface warming. This “pattern effect” occurs because strong ventilation and weak surface warming are robustly colocated, particularly in the Southern Ocean. However, variations in warming patterns across CMIP5 do not drive significant ensemble spread in passive ocean heat uptake efficiency. This spread is likely linked to intermodel differences in ocean circulation, which our idealized results suggest may be dominated by differences in Southern Ocean and subtropical ventilation processes.

Temperature and iron fertilization are more important in driving glacial-interglacial CO ₂ cycles than previously thought.

Significance

Since the 19th century, rising greenhouse gas concentrations have caused the ocean to absorb most of the Earth’s excess heat and warm up. Before the 1990s, most ocean temperature measurements were above 700 m and therefore, insufficient for an accurate global estimate of ocean warming. We present a method to reconstruct ocean temperature changes with global, full-depth ocean coverage, revealing warming of 436J since 1871. Our reconstruction, which agrees with other estimates for the well-observed period, demonstrates that the ocean absorbed as much heat during 1921–1946 as during 1990–2015. Since the 1950s, up to one-half of excess heat in the Atlantic Ocean at midlatitudes has come from other regions via circulation-related changes in heat transport.

Abstract

We investigate the spatiotemporal evolution of radiocarbon (Δ¹⁴C) in the ocean over the 21st century under different scenarios for anthropogenic CO₂ emissions and atmospheric CO₂ and radiocarbon changes using a 3‐D ocean carbon cycle model. Strong decreases in atmospheric Δ¹⁴C in the high‐emission scenario result in strong outgassing of ¹⁴C over 2050–2100, causing Δ¹⁴C spatial gradients in the surface ocean and vertical gradients between the surface and intermediate waters to reverse sign. Surface Δ¹⁴C in the subtropical gyres is lower than Δ¹⁴C in Pacific Deep Water and Southern Ocean surface water in 2100. In the low‐emission scenario, ocean Δ¹⁴C remains slightly higher than in 1950 and relatively constant over 2050–2100. Over the next 20 years we find decadal changes in Δ¹⁴C of −30‰ to +5‰ in the upper 2 km of the ocean, which should be detectable with continued hydrographic surveys. Our simulations can help in planning future observations, and they provide a baseline for investigating natural or anthropogenic changes in ocean circulation using ocean Δ¹⁴C observations and models.

Abstract

Previous studies found large biases between individual observational and model estimates of historical ocean anthropogenic carbon uptake. We show that the largest bias between the Coupled Model Intercomparison Project phase 5 (CMIP5) ensemble mean and between two observational estimates of ocean anthropogenic carbon is due to a difference in start date. After adjusting the CMIP5 and observational estimates to the 1791–1995 period, all three carbon uptake estimates agree to within 3 Pg of C, about 4% of the total. The CMIP5 ensemble mean spatial bias compared to the observations is generally smaller than the observational error, apart from a negative bias in the Southern Ocean and a positive bias in the Southern Indian and Pacific Oceans compensating each other in the global mean. This dipole pattern is likely due to an equatorward and weak bias in the position of Southern Hemisphere westerlies and lack of mode and intermediate water ventilation.

Abstract. Conventional integration of Earth system and ocean models can accrue considerable computational expenses, particularly for marine biogeochemical applications. Offline numerical schemes in which only the biogeochemical tracers are time stepped and transported using a pre-computed circulation field can substantially reduce the burden and are thus an attractive alternative. One such scheme is the transport matrix method (TMM), which represents tracer transport as a sequence of sparse matrix–vector products that can be performed efficiently on distributed-memory computers. While the TMM has been used for a variety of geochemical and biogeochemical studies, to date the resulting solutions have not been comprehensively assessed against their online counterparts. Here, we present a detailed comparison of the two. It is based on simulations of the state-of-the-art biogeochemical sub-model embedded within the widely used coarse-resolution University of Victoria Earth System Climate Model (UVic ESCM). The default, non-linear advection scheme was first replaced with a linear, third-order upwind-biased advection scheme to satisfy the linearity requirement of the TMM. Transport matrices were extracted from an equilibrium run of the physical model and subsequently used to integrate the biogeochemical model offline to equilibrium. The identical biogeochemical model was also run online. Our simulations show that offline integration introduces some bias to biogeochemical quantities through the omission of the polar filtering used in UVic ESCM and in the offline application of time-dependent forcing fields, with high latitudes showing the largest differences with respect to the online model. Differences in other regions and in the seasonality of nutrients and phytoplankton distributions are found to be relatively minor, giving confidence that the TMM is a reliable tool for offline integration of complex biogeochemical models. Moreover, while UVic ESCM is a serial code, the TMM can be run on a parallel machine with no change to the underlying biogeochemical code, thus providing orders of magnitude speed-up over the online model.

Abstract. Global biogeochemical ocean models contain a variety of different biogeochemical components and often much simplified representations of complex dynamical interactions, which are described by many ( ≈ 10 to  ≈ 100) parameters. The values of many of these parameters are empirically difficult to constrain, due to the fact that in the models they represent processes for a range of different groups of organisms at the same time, while even for single species parameter values are often difficult to determine in situ. Therefore, these models are subject to a high level of parametric uncertainty. This may be of consequence for their skill with respect to accurately describing the relevant features of the present ocean, as well as their sensitivity to possible environmental changes. We here present a framework for the calibration of global biogeochemical ocean models on short and long timescales. The framework combines an offline approach for transport of biogeochemical tracers with an estimation of distribution algorithm (Covariance Matrix Adaption Evolution Strategy, CMA-ES). We explore the performance and capability of this framework by five different optimizations of six biogeochemical parameters of a global biogeochemical model, simulated over 3000 years. First, a twin experiment explores the feasibility of this approach. Four optimizations against a climatology of observations of annual mean dissolved nutrients and oxygen determine the extent to which different setups of the optimization influence model fit and parameter estimates. Because the misfit function applied focuses on the large-scale distribution of inorganic biogeochemical tracers, parameters that act on large spatial and temporal scales are determined earliest, and with the least spread. Parameters more closely tied to surface biology, which act on shorter timescales, are more difficult to determine. In particular, the search for optimum zooplankton parameters can benefit from a sound knowledge of maximum and minimum parameter values, leading to a more efficient optimization. It is encouraging that, although the misfit function does not contain any direct information about biogeochemical turnover, the optimized models nevertheless provide a better fit to observed global biogeochemical fluxes.

Abstract

The respective contributions of saline (Atlantic and Pacific water) and freshwater (sea ice melt, meteoric water) components in the surface Labrador Current are quantified using salinity, δ¹⁸O, and nutrient data collected between 2012 and 2015 east of Newfoundland to investigate the seasonal variability of salinity in relation with the different freshwater contributions. Nutrient data indicate that the surface saline water is composed on average over 2012–2015 of roughly 62% Atlantic Water and 38% Pacific Water. A large salinity seasonal cycle of ≈ 1.5 peak‐to‐peak amplitude is found over the middle continental shelf, which is explained by the freshwater input seasonal variability: 2/3 of the amplitude of the salinity seasonal cycle can be explained by meteoric water input and 1/3 by the sea ice melt. A smaller seasonal salinity cycle (≈1.3) is observed over the inner shelf compared to the middle shelf, because of smaller variability in the large meteoric water inputs. Furthermore, the data reveal that sea ice melt (SIM) input was particularly important during July 2014, following a larger extension of sea ice over the Labrador shelf during the 2013/2014 winter season, compared to both previous winter seasons. Some patches of large SIM contribution observed during July 2014 and April 2015 were located on the continental slope or further offshore. The comparison of 2012–2015 data with data collected in 1994–1995 shows that the surface water over the Newfoundland shelf and slope is strongly affected by sea ice processes in both periods and suggests a larger contribution of brines over the slope during 1994–1995.

Abstract

The omnipresence of chromophoric dissolved organic matter (CDOM) in the open ocean enables its use as a tracer for biochemical processes throughout the global overturning circulation. We made an inventory of CDOM optical properties, ideal water age (τ), and apparent oxygen utilization (AOU) along the Atlantic, Indian, and Pacific Ocean waters sampled during the Malaspina 2010 expedition. A water mass analysis was applied to obtain intrinsic, hereinafter archetypal, values of τ, AOU, oxygen utilization rate (OUR), and CDOM absorption coefficients, spectral slopes and quantum yield for each one of the 22 water types intercepted during this circumnavigation. Archetypal values of AOU and OUR have been used to trace the differential influence of water mass aging and aging rates, respectively, on CDOM variables. Whereas the absorption coefficient at 325 nm (a₃₂₅) and the fluorescence quantum yield at 340 nm (Φ₃₄₀) increased, the spectral slope over the wavelength range 275–295 nm (S_275–295) and the ratio of spectral slopes over the ranges 275–295 nm and 350–400 nm (S_R) decreased significantly with water mass aging (AOU). Combination of the slope of the linear regression between archetypal AOU and a₃₂₅ with the estimated global OUR allowed us to obtain a CDOM turnover time of 634 ± 120 years, which exceeds the flushing time of the dark ocean (>200 m) by 46%. This positive relationship supports the assumption of in situ production and accumulation of CDOM as a by‐product of microbial metabolism as water masses turn older. Furthermore, our data evidence that global‐scale CDOM quantity (a₃₂₅) is more dependent on aging (AOU), whereas CDOM quality (S_275–295, S_R, Φ₃₄₀) is more dependent on aging rate (OUR).

The strength of feedbacks between a changing climate and future CO₂ concentrations is uncertain and difficult to predict using Earth System Models (ESMs). We analyzed emission‐driven simulations—in which atmospheric CO₂levels were computed prognostically—for historical (1850–2005) and future periods (Representative Concentration Pathway (RCP) 8.5 for 2006–2100) produced by 15 ESMs for the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5). Comparison of ESM prognostic atmospheric CO₂ over the historical period with observations indicated that ESMs, on average, had a small positive bias in predictions of contemporary atmospheric CO₂. Weak ocean carbon uptake in many ESMs contributed to this bias, based on comparisons with observations of ocean and atmospheric anthropogenic carbon inventories. We found a significant linear relationship between contemporary atmospheric CO₂ biases and future CO₂levels for the multimodel ensemble. We used this relationship to create a contemporary CO₂ tuned model (CCTM) estimate of the atmospheric CO₂ trajectory for the 21st century. The CCTM yielded CO₂estimates of 600±14 ppm at 2060 and 947±35 ppm at 2100, which were 21 ppm and 32 ppm below the multimodel mean during these two time periods. Using this emergent constraint approach, the likely ranges of future atmospheric CO₂, CO₂‐induced radiative forcing, and CO₂‐induced temperature increases for the RCP 8.5 scenario were considerably narrowed compared to estimates from the full ESM ensemble. Our analysis provided evidence that much of the model‐to‐model variation in projected CO₂ during the 21st century was tied to biases that existed during the observational era and that model differences in the representation of concentration‐carbon feedbacks and other slowly changing carbon cycle processes appear to be the primary driver of this variability. By improving models to more closely match the long‐term time series of CO₂from Mauna Loa, our analysis suggests that uncertainties in future climate projections can be reduced.

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Abstract. The global ocean is a significant sink for anthropogenic carbon (Cant), absorbing roughly a third of human CO2 emitted over the industrial period. Robust estimates of the magnitude and variability of the storage and distribution of Cant in the ocean are therefore important for understanding the human impact on climate. In this synthesis we review observational and model-based estimates of the storage and transport of Cant in the ocean. We pay particular attention to the uncertainties and potential biases inherent in different inference schemes. On a global scale, three data-based estimates of the distribution and inventory of Cant are now available. While the inventories are found to agree within their uncertainty, there are considerable differences in the spatial distribution. We also present a review of the progress made in the application of inverse and data assimilation techniques which combine ocean interior estimates of Cant with numerical ocean circulation models. Such methods are especially useful for estimating the air–sea flux and interior transport of Cant, quantities that are otherwise difficult to observe directly. However, the results are found to be highly dependent on modeled circulation, with the spread due to different ocean models at least as large as that from the different observational methods used to estimate Cant. Our review also highlights the importance of repeat measurements of hydrographic and biogeochemical parameters to estimate the storage of Cant on decadal timescales in the presence of the variability in circulation that is neglected by other approaches. Data-based Cant estimates provide important constraints on forward ocean models, which exhibit both broad similarities and regional errors relative to the observational fields. A compilation of inventories of Cant gives us a "best" estimate of the global ocean inventory of anthropogenic carbon in 2010 of 155 ± 31 PgC (±20% uncertainty). This estimate includes a broad range of values, suggesting that a combination of approaches is necessary in order to achieve a robust quantification of the ocean sink of anthropogenic CO2.

Abstract. The globally integrated sea–air anthropogenic carbon dioxide (CO2) flux from 1990 to 2009 is determined from models and data-based approaches as part of the Regional Carbon Cycle Assessment and Processes (RECCAP) project. Numerical methods include ocean inverse models, atmospheric inverse models, and ocean general circulation models with parameterized biogeochemistry (OBGCMs). The median value of different approaches shows good agreement in average uptake. The best estimate of anthropogenic CO2 uptake for the time period based on a compilation of approaches is −2.0 Pg C yr−1. The interannual variability in the sea–air flux is largely driven by large-scale climate re-organizations and is estimated at 0.2 Pg C yr−1 for the two decades with some systematic differences between approaches. The largest differences between approaches are seen in the decadal trends. The trends range from −0.13 (Pg C yr−1) decade−1 to −0.50 (Pg C yr−1) decade−1 for the two decades under investigation. The OBGCMs and the data-based sea–air CO2 flux estimates show appreciably smaller decadal trends than estimates based on changes in carbon inventory suggesting that methods capable of resolving shorter timescales are showing a slowing of the rate of ocean CO2 uptake. RECCAP model outputs for five decades show similar differences in trends between approaches.

The injection of radiocarbon (¹⁴C) into the atmosphere by nuclear weapons testing in the 1950s and 1960s has provided a powerful tracer to investigate ocean physical and chemical processes. While the oceanic uptake of bomb‐derived ¹⁴C was primarily controlled by air‐sea exchange in the early decades after the bomb spike, we demonstrate that changes in oceanic ¹⁴C are now primarily controlled by shallow‐to‐deep ocean exchange, i.e., the same mechanism that governs anthropogenic CO₂ uptake. This is a result of accumulated bomb ¹⁴C uptake that has rapidly decreased the air‐sea gradient of ¹⁴C/C (Δ¹⁴C) and shifted the main reservoir of bomb ¹⁴C from the atmosphere to the upper ocean. The air‐sea Δ¹⁴C gradient, reduced further by fossil fuel dilution, is now weaker than before weapons testing in most regions. Oceanic ¹⁴C, and particularly its temporal change, can now be used to study the oceanic uptake of anthropogenic CO₂. We examine observed changes in oceanic Δ¹⁴C between the WOCE/SAVE (1988–1995) and the CLIVAR (2001–2007) eras and simulations with two ocean general circulation models, the Community Climate System Model (CCSM) and the Estimating the Circulation and Climate of the Ocean Model (ECCO). Observed oceanic Δ¹⁴C and its changes between the 1980s–90s and 2000s indicate that shallow‐to‐deep exchange is too efficient in ECCO and too sluggish in CCSM. These findings suggest that mean global oceanic uptake of anthropogenic CO₂ between 1990 and 2007 is bounded by the ECCO‐based estimate of 2.3 Pg C yr⁻¹ and the CCSM‐based estimate of 1.7 Pg C yr⁻¹.

This study presents results from 46 sensitivity experiments carried out with three structurally simple (2, 3, and 6 biogeochemical state variables, respectively) models of production, export and remineralization of organic phosphorus, coupled to a global ocean circulation model and integrated for 3000 years each. The models' skill is assessed via different misfit functions with respect to the observed global distributions of phosphate and oxygen. Across the different models, the global root‐mean square misfit with respect to observed phosphate and oxygen distributions is found to be particularly sensitive to changes in the remineralization length scale, and also to changes in simulated primary production. For this metric, changes in the production and decay of dissolved organic phosphorus as well as in zooplankton parameters are of lesser importance. For a misfit function accounting for the misfit of upper‐ocean tracers, however, production parameters and organic phosphorus dynamics play a larger role. Regional misfit patterns are investigated as indicators of potential model deficiencies, such as missing iron limitation, or deficiencies in the sinking and remineralization length scales. In particular, the gradient between phosphate concentrations in the northern North Pacific and the northern North Atlantic is controlled predominantly by the biogeochemical model parameters related to particle flux. For the combined 46 sensitivity experiments performed here, the global misfit to observed oxygen and phosphate distributions shows no clear relation to either simulated global primary or export production for either misfit metric employed. However, a relatively tight relationship that is very similar for the different model of different structural complexity is found between the model‐data misfit in oxygen and phosphate distributions to simulated meso‐ and bathypelagic particle flux. Best agreement with the observed tracer distributions is obtained for simulated particle fluxes that agree most closely with sediment trap data for a nominal depth of about 1000 m, or deeper.

Abstract. The global ocean has taken up a large fraction of the CO2 released by human activities since the industrial revolution. Quantifying the oceanic anthropogenic carbon (Cant) inventory and its variability is important for predicting the future global carbon cycle. The detailed comparison of data-based and model-based estimates is essential for the validation and continued improvement of our prediction capabilities. So far, three global estimates of oceanic Cant inventory that are "data-based" and independent of global ocean circulation models have been produced: one based on the Δ C* method, and two that are based on constraining surface-to-interior transport of tracers, the TTD method and a maximum entropy inversion method (GF). The GF method, in particular, is capable of reconstructing the history of Cant inventory through the industrial era. In the present study we use forward model simulations of the Community Climate System Model (CCSM3.1) to estimate the Cant inventory and compare the results with the data-based estimates. We also use the simulations to test several assumptions of the GF method, including the assumption of constant climate and circulation, which is common to all the data-based estimates. Though the integrated estimates of global Cant inventories are consistent with each other, the regional estimates show discrepancies up to 50 %. The CCSM3 model underestimates the total Cant inventory, in part due to weak mixing and ventilation in the North Atlantic and Southern Ocean. Analyses of different simulation results suggest that key assumptions about ocean circulation and air-sea disequilibrium in the GF method are generally valid on the global scale, but may introduce errors in Cant estimates on regional scales. The GF method should also be used with caution when predicting future oceanic anthropogenic carbon uptake.

Several large-scale climate patterns influenced climate conditions and weather patterns across the globe during 2010. The transition from a warm El Niño phase at the beginning of the year to a cool La Niña phase by July contributed to many notable events, ranging from record wetness across much of Australia to historically low Eastern Pacific basin and near-record high North Atlantic basin hurricane activity. The remaining five main hurricane basins experienced below- to well-below-normal tropical cyclone activity. The negative phase of the Arctic Oscillation was a major driver of Northern Hemisphere temperature patterns during 2009/10 winter and again in late 2010. It contributed to record snowfall and unusually low temperatures over much of northern Eurasia and parts of the United States, while bringing above-normal temperatures to the high northern latitudes. The February Arctic Oscillation Index value was the most negative since records began in 1950.

The 2010 average global land and ocean surface temperature was among the two warmest years on record. The Arctic continued to warm at about twice the rate of lower latitudes. The eastern and tropical Pacific Ocean cooled about 1°C from 2009 to 2010, reflecting the transition from the 2009/10 El Niño to the 2010/11 La Niña. Ocean heat fluxes contributed to warm sea surface temperature anomalies in the North Atlantic and the tropical Indian and western Pacific Oceans. Global integrals of upper ocean heat content for the past several years have reached values consistently higher than for all prior times in the record, demonstrating the dominant role of the ocean in the Earth's energy budget. Deep and abyssal waters of Antarctic origin have also trended warmer on average since the early 1990s. Lower tropospheric temperatures typically lag ENSO surface fluctuations by two to four months, thus the 2010 temperature was dominated by the warm phase El Niño conditions that occurred during the latter half of 2009 and early 2010 and was second warmest on record. The stratosphere continued to be anomalously cool.

Annual global precipitation over land areas was about five percent above normal. Precipitation over the ocean was drier than normal after a wet year in 2009. Overall, saltier (higher evaporation) regions of the ocean surface continue to be anomalously salty, and fresher (higher precipitation) regions continue to be anomalously fresh. This salinity pattern, which has held since at least 2004, suggests an increase in the hydrological cycle.

Sea ice conditions in the Arctic were significantly different than those in the Antarctic during the year. The annual minimum ice extent in the Arctic—reached in September—was the third lowest on record since 1979. In the Antarctic, zonally averaged sea ice extent reached an all-time record maximum from mid-June through late August and again from mid-November through early December. Corresponding record positive Southern Hemisphere Annular Mode Indices influenced the Antarctic sea ice extents.

Greenland glaciers lost more mass than any other year in the decade-long record. The Greenland Ice Sheet lost a record amount of mass, as the melt rate was the highest since at least 1958, and the area and duration of the melting was greater than any year since at least 1978. High summer air temperatures and a longer melt season also caused a continued increase in the rate of ice mass loss from small glaciers and ice caps in the Canadian Arctic. Coastal sites in Alaska show continuous permafrost warming and sites in Alaska, Canada, and Russia indicate more significant warming in relatively cold permafrost than in warm permafrost in the same geographical area. With regional differences, permafrost temperatures are now up to 2°C warmer than they were 20 to 30 years ago. Preliminary data indicate there is a high probability that 2010 will be the 20th consecutive year that alpine glaciers have lost mass.

Atmospheric greenhouse gas concentrations continued to rise and ozone depleting substances continued to decrease. Carbon dioxide increased by 2.60 ppm in 2010, a rate above both the 2009 and the 1980–2010 average rates. The global ocean carbon dioxide uptake for the 2009 transition period from La Niña to El Niño conditions, the most recent period for which analyzed data are available, is estimated to be similar to the long-term average. The 2010 Antarctic ozone hole was among the lowest 20% compared with other years since 1990, a result of warmer-than-average temperatures in the Antarctic stratosphere during austral winter between mid-July and early September.

A maximum entropy (ME) method is used to deconvolve tracer data for the joint distribution of locations and times since last ventilation. The deconvolutions utilize World Ocean Circulation Experiment line A20 repeat hydrography for CFC‐11, potential temperature, salinity, oxygen, and phosphate, as well as Global Ocean Data Analysis Project (GLODAP) radiocarbon data, combined with surface boundary conditions derived from the atmospheric history of CFC‐11 and the World Ocean Atlas 2005 and GLODAP databases. Because of the limited number of available tracers the deconvolutions are highly underdetermined, leading to large entropic uncertainties, which are quantified using the information entropy of relative to a prior distribution. Additional uncertainties resulting from data sparsity are estimated using a Monte Carlo approach and found to be of secondary importance. The ME deconvolutions objectively identify key water mass formation regions and quantify the local fraction of water of age τ or older last ventilated in each region. Ideal mean age and radiocarbon age are also estimated but found to have large entropic uncertainties that can be attributed to uncertainties in the partitioning of a given water parcel according to where it was last ventilated. Labrador/Irminger seawater (L water) is determined to be mostly less than ∼40 a old in the vicinity of the deep western boundary current (DWBC) at the northern end of A20 but several decades older where the DWBC recrosses the section further south, pointing to the importance of mixing via a multitude of eddy‐diffusive paths. Overflow water lies primarily below L water with young waters (τ ≲ 40 a) at middepth in the northern part of A20 and waters as old as ∼600 a below ∼3500 m.

A novel computational framework is introduced for the efficient simulation of chemical and biological tracers in ocean models. The framework is based on the “transport matrix” formulation, a scheme for capturing the complex three‐dimensional transport of tracers in a general circulation model (GCM) as a sparse matrix, thus reducing the task of simulating tracers to a sequence of simple matrix‐vector products. The principal advantages of this formulation are efficiency and convenience. It is many orders of magnitude more efficient than GCMs, allowing us to address problems that are currently either difficult or unaffordable with GCMs. The scheme also allows us to quickly “prototype” new biogeochemical parameterizations or “plug in” existing ones. This paper describes the key features and advantages of the transport matrix method, and illustrates its application to a series of realistic problems in chemical and biological oceanography. The examples range from simulation of a transient tracer (SF₆) to adjoint sensitivity of a complex coupled biogeochemical model. Finally, the paper describes an efficient, portable, and freely available implementation of this computational scheme that provides the necessary framework for simulating any biogeochemical tracer.

We apply to Classical Labrador Sea Water (CLSW) the transit‐time distribution (TTD) method to estimate the inventory and uptake of anthropogenic carbon dioxide (C_ant). A model of TTDs representing bulk‐advection and diffusive mixing is constrained with CFC11 data. The constrained TTDs are used to propagate C_ant into CLSW, allowing the air‐sea disequilibrium to evolve consistently. C_ant in the Labrador Sea (LS) surface waters cannot keep pace with increasing atmospheric CO₂ and is highly undersaturated. Our best estimate for 2001 is an anthropogenic inventory of 1.0 Gt C and an uptake of 0.02 Gt C/year. By additionally using the constraint of present‐day CO₂ measurements, we estimate that the preindustrial LS was neutral or a weak source of CO₂ to the atmosphere. Our estimates are subject to possible error due to the assumption of steady‐state transport and carbon biochemistry.

We apply to the Indian Ocean a novel technique to estimate the distribution, total mass, and net air‐sea flux of anthropogenic carbon. Chlorofluorocarbon data are used to constrain distributions of transit times from the surface to the interior that are constructed to accommodate a range of mixing scenarios, from no mixing (pure bulk advection) to strong mixing. The transit time distributions are then used to propagate to the interior the surface water history of anthropogenic carbon estimated in a way that includes temporal variation in CO₂ air‐sea disequilibrium. By allowing for mixing in transport and for variable air‐sea disequilibrium, we remove two sources of positive bias common in other studies. We estimate that the anthropogenic carbon mass in the Indian Ocean was 14.3–20.5 Gt in 2000, and the net air‐sea flux was 0.26–0.36 Gt/yr. The upper bound of this range, the no‐mixing limit, generally coincides with previous studies, while the lower bound, the strong‐mixing limit, is significantly below previous studies.

The Mars Orbiter Camera on board the Mars Global Surveyor spacecraft has returned images of numerous dark streaks that are the result of down‐slope mass movement occurring under present‐day martian climatic conditions. We systematically analyze over 23,000 high‐resolution images and demonstrate that slope streaks form exclusively in regions of low thermal inertia (confirming earlier results), steep slopes, and, remarkably, only where peak temperatures exceed 275 K. The northernmost streaks, which form in the coldest environment, form preferentially on warmer south‐facing slopes. Repeat images of sites with slope streaks show changes only if the time interval between the two images includes the warm season. Surprisingly (in light of the theoretically short residence time of H₂O close to the surface), the data support the possibility that small amounts of water are transiently present in low‐latitude near‐surface regions of Mars and undergo phase transitions at times of high insolation, triggering the observed mass movements.

Measurements of the H₂¹⁸O/H₂¹⁶O ratio of water from two sections crossing the Eurasian Basin in 1991 and 1996 show that the observed decrease in the freshwater contained in the upper waters of the Eurasian Basin during the 1990s is due to decrease in meteoric water (mainly river runoff). The decrease in meteoric water inventories between 1991 and 1996 calculated from balances of mass, salinity, δ¹⁸O, and PO₄* is about 3 meters and accounts for basically the entire freshwater change inferred from salinity budgets. Climatological data are used to ensure that the two sections can be considered to belong to the same hydrographic regime. The data also suggest that in 96 the formation of sea ice from the upper waters in the Amundsen Basin was lower by about 1 meter (3 m in 1996 compared to 4 m in 1991).

Low‐dimensional models can give insight into the climate system, in particular its response to externally imposed forcing such as the anthropogenic emission of green‐house gases. Here, we use the Lorenz system, a chaotic dynamical system characterized by two “regimes”, to examine the effect of a weak imposed forcing. We show that the probability density functions (PDF's) of time‐spent in the two regimes are exponential, and that the most dramatic response to forcing is a change in the frequency of occurrence of extremely persistent events, rather than the weaker change in the mean persistence time. This enhanced sensitivity of the “tails” of the PDF's to forcing is quantitatively explained by changes in the stability of the regimes. We demonstrate similar behavior in a stochastically forced double well system. Our results suggest that the most significant effect of anthropogenic forcing may be to change the frequency of occurrence of persistent climate events, such as droughts, rather than the mean.

Regions of oceanic deep convection such as the Labrador Sea are prone to baroclinic instability. The resulting geostrophic eddies play a crucial role in the post‐convection adjustment process which involves both rearrangement of mass so as to release available potential energy and exchange of heat and salt with the boundaries. In this study it is proposed that the slumping of isopycnals associated with baroclinic instability drives an eddy‐induced “overturning circulation” consisting of a surface intensified flow transporting low salinity water from the boundary currents into the interior; sinking motion in the interior; and an “outflow” at depth transporting newly ventilated Labrador Sea Water towards the boundaries. Typical eddy‐induced velocities estimated from hydrographic data are roughly 0.5 cm/s for the surface inflow, 1 m/day for the vertical motion, and 0.1 cm/s for the deeper outflow, in close agreement with those calculated in a numerical model.

Oxygen isotope (H₂¹⁸O/H₂¹⁶O)/salinity data identify freshwater sources along the northeastern North American continental margin. The oxygen isotope (δ¹⁸O)‐salinity (S) properties of various water types are distinguished. Sea ice formation on the Labrador Shelf is shown to influence δ¹⁸O‐S values. It is estimated that 2–3 m of freshwater is extracted from the water column to form sea ice. It is hypothesized that waters on the Scotian Shelf, Gulf of Maine, and the Middle Atlantic Bight are composed of slope water diluted by an upstream low‐salinity source. This upstream source is a mixture of brine‐enriched Labrador Shelf Water and St. Lawrence River water. The δ¹⁸O value of the apparent freshwater component (δ¹⁸O_S=0) of waters on the Scotian Shelf and farther south is ≈−20‰, which has been used to suggest a sole high‐latitude freshwater source. We show instead that the St. Lawrence River contributes ≈35% of the freshwater on the Scotian Shelf, in agreement with the physical oceanographic evidence. The remaining freshwater is supplied by high‐latitude rivers dominated by Arctic runoff. Finally, the isotope evidence identifies Baffin Bay as an important pathway by which freshwater from the Arctic Ocean can reach the Labrador Sea.

Helium isotope data (³He/⁴He ratios and ⁴He concentrations) and H₂¹⁸O/H₂¹⁶O ratios obtained from stations occupied during the drift of Ice Station Weddell (February to June 1992) are used, together with hydrographic data, to study formation of deep and bottom water in the western Weddell Sea. The data indicate deep and bottom water formation along the entire track of the ice station (71.4 to 65.8°S, ≈53°W). Ice Shelf Water (ISW) seems to contribute significantly to the formation of Weddell Sea Deep Water (WSDW) and Weddell Sea Bottom Water (WSBW) in the southern part of the drift track. Toward the north, the fraction of ISW contained in WSDW/WSBW decreases. This trend is overlaid by high ISW fractions in the deep and bottom waters found in the vicinity of the Larsen Ice Shelf. The fraction of Western Shelf Water (WSW) in WSBW shows the opposite trend, increasing from south to north. The combined fraction of ISW and WSW in waters with potential temperatures below 0°C is about 20%, corresponding to a roughly 200 m thick layer. Overall, WSW seems to contribute approximately 2 to 3 times more water than ISW to the water column below the 0°C isotherm. Using the estimated flow of ISW over the sill north of the Filchner Depression of 1 Sv [Foldvik et al., 1985a] together with the ratio of WSW plus Winter Water (WW) to ISW, we calculate a value of about 5 Sv for the formation rate of WSBW with a potential temperature of −0.7°C. About one third of this flux represents near‐surface waters (WSW/WW) which have recently been equilibrated with the atmosphere, whereas pure ISW contributes about 10%.