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Anthropogenically forced changes in ocean biogeochemistry are underway and critical for the ocean carbon sink and marine habitat. Detecting such changes in ocean biogeochemistry will require quantification of the magnitude of the change (anthropogenic signal) and the natural variability inherent to the climate system (noise). Here we use Large Ensemble (LE) experiments from four Earth system models (ESMs) with multiple emissions scenarios to estimate Time of Emergence (ToE) and partition projection uncertainty for anthropogenic signals in five biogeochemically important upper‐ocean variables. We find ToEs are robust across ESMs for sea surface temperature and the invasion of anthropogenic carbon; emergence time scales are 20–30 yr. For the biological carbon pump, and sea surface chlorophyll and salinity, emergence time scales are longer (50+ yr), less robust across the ESMs, and more sensitive to the forcing scenario considered. We find internal variability uncertainty, and model differences in the internal variability uncertainty, can be consequential sources of uncertainty for projecting regional changes in ocean biogeochemistry over the coming decades. In combining structural, scenario, and internal variability uncertainty, this study represents the most comprehensive characterization of biogeochemical emergence time scales and uncertainty to date. Our findings delineate critical spatial and duration requirements for marine observing systems to robustly detect anthropogenic change., Key Points Anthropogenic changes in sea surface temperature and air‐sea CO2 fluxes emerge decades prior to changes in the biological carbon pump, ocean color, and sea surface salinityDetecting anthropogenic changes in ocean biogeochemistry requires sustained monitoring from observing systems with large spatial footprintsInternal variability, model uncertainty, and scenario uncertainty are all important sources of uncertainty for projecting future changes in ocean biogeochemistry

One important theme of modern biological oceanography has been the attempt to develop models of how the marine ecosystem responds to variations in the physical forcing functions such as solar radiation and the wind field. The authors have addressed the problem by embedding simple ecosystem models into a seasonally forced three-dimensional general circulation model of the North Atlantic ocean. In this paper first, some of the underlying biological assumptions of the ecosystem model are presented, followed by an analysis of how well the model predicts the seasonal cycle of the biological variables at Bermuda Station s' and Ocean Weather Station India. The model gives a good overall fit to the observations but does not faithfully model the whole seasonal ecosystem model. 57 refs., 25 figs., 5 tabs.

[1] Results are presented of export production, dissolved organic matter (DOM) and dissolved oxygen simulated by 12 global ocean models participating in the second phase of the Ocean Carbon-cycle Model Intercomparison Project. A common, simple biogeochemical model is utilized in different coarse-resolution ocean circulation models. The model mean (±1σ) downward flux of organic matter across 75 m depth is 17 ± 6 Pg C yr−1. Model means of globally averaged particle export, the fraction of total export in dissolved form, surface semilabile dissolved organic carbon (DOC), and seasonal net outgassing (SNO) of oxygen are in good agreement with observation-based estimates, but particle export and surface DOC are too high in the tropics. There is a high sensitivity of the results to circulation, as evidenced by (1) the correlation of surface DOC and export with circulation metrics, including chlorofluorocarbon inventory and deep-ocean radiocarbon, (2) very large intermodel differences in Southern Ocean export, and (3) greater export production, fraction of export as DOM, and SNO in models with explicit mixed layer physics. However, deep-ocean oxygen, which varies widely among the models, is poorly correlated with other model indices. Cross-model means of several biogeochemical metrics show better agreement with observation-based estimates when restricted to those models that best simulate deep-ocean radiocarbon. Overall, the results emphasize the importance of physical processes in marine biogeochemical modeling and suggest that the development of circulation models can be accelerated by evaluating them with marine biogeochemical metrics.

[1] Differing models of the ocean circulation support different rates of ventilation, which in turn produce different distributions of radiocarbon, oxygen, and export production. We examine these fields within a suite of general circulation models run to examine the sensitivity of the circulation to the parameterization of subgridscale mixing and surface forcing. We find that different models can explain relatively high fractions of the spatial variance in some fields such as radiocarbon, and that newer estimates of the rate of biological cycling are in better agreement with the models than previously published estimates. We consider how different models achieve such agreement and show that they can accomplish this in different ways. For example, models with high vertical diffusion move young surface waters into the Southern Ocean, while models with high winds move more young North Atlantic water into this region. The dependence on parameter values is not simple. Changes in the vertical diffusion coefficient, for example, can produce major changes in advective fluxes. In the coarse-resolution models studied here, lateral diffusion plays a major role in the tracer budget of the deep ocean, a somewhat worrisome fact as it is poorly constrained both observationally and theoretically. INDEX TERMS: 4275 Oceanography: General: Remote sensing and electromagnetic processes (0689); 4532 Oceanography: Physical: General circulation; 4568 Oceanography: Physical: Turbulence, diffusion, and mixing processes; 4845 Oceanography: Biological and Chemical: Nutrients and nutrient cycling; KEYWORDS: biogeochemical cycles, particle export, vertical exchange

An edited version of this paper was published by AGU. Copyright 2004 American Geophysical Union. A suite of standard ocean hydrographic and circulation metrics are applied to the equilibrium physical solutions from 13 global carbon models participating in phase 2 of the Ocean Carbon-cycle Model Intercomparison Project (OCMIP-2). Model-data comparisons are presented for sea surface temperature and salinity, seasonal mixed layer depth, meridional heat and freshwater transport, 3-D hydrographic fields, and meridional overturning. Considerable variation exists among the OCMIP-2 simulations, with some of the solutions falling noticeably outside available observational constraints. For some cases, model-model and model-data differences can be related to variations in surface forcing, subgrid-scale parameterizations, and model architecture. These errors in the physical metrics point to significant problems in the underlying model representations of ocean transport and dynamics, problems that directly affect the OCMIP predicted ocean tracer and carbon cycle variables (e.g., air-sea CO2 flux, chlorofluorocarbon and anthropogenic CO2 uptake, and export production). A substantial fraction of the large model-model ranges in OCMIP-2 biogeochemical fields (±25–40%) represents the propagation of known errors in model physics. Therefore the model-model spread likely overstates the uncertainty in our current understanding of the ocean carbon system, particularly for transport-dominated fields such as the historical uptake of anthropogenic CO2. A full error assessment, however, would need to account for additional sources of uncertainty such as more complex biological-chemical-physical interactions, biases arising from poorly resolved or neglected physical processes, and climate change.

International audience; We examine six different coupled climate model simulations to determine the ocean biological response to climate warming between the beginning of the industrial revolution and 2050. We use vertical velocity, maximum winter mixed layer depth, and sea ice cover to define six biomes. Climate warming leads to a contraction of the highly productive marginal sea ice biome by 42% in the Northern Hemisphere and 17% in the Southern Hemisphere, and leads to an expansion of the low productivity permanently stratified subtropical gyre biome by 4.0% in the Northern Hemisphere and 9.4% in the Southern Hemisphere. In between these, the subpolar gyre biome expands by 16% in the Northern Hemisphere and 7% in the Southern Hemisphere, and the seasonally stratified subtropical gyre contracts by 11% in both hemispheres. The low-latitude (mostly coastal) upwelling biome area changes only modestly. Vertical stratification increases, which would be expected to decrease nutrient supply everywhere, but increase the growing season length in high latitudes. We use satellite ocean color and climatological observations to develop an empirical model for predicting chlorophyll from the physical properties of the global warming simulations. Four features stand out in the response to global warming: (1) a drop in chlorophyll in the North Pacific due primarily to retreat of the marginal sea ice biome, (2) a tendency toward an increase in chlorophyll in the North Atlantic due to a complex combination of factors, (3) an increase in chlorophyll in the Southern Ocean due primarily to the retreat of and changes at the northern boundary of the marginal sea ice zone, and (4) a tendency toward a decrease in chlorophyll adjacent to the Antarctic continent due primarily to freshening within the marginal sea ice zone. We use three different primary production algorithms to estimate the response of primary production to climate warming based on our estimated chlorophyll concentrations. The three algorithms give a global increase in primary production of 0.7% at the low end to 8.1% at the high end, with very large regional differences. The main cause of both the response to warming and the variation between algorithms is the temperature sensitivity of the primary production algorithms. We also show results for the period between the industrial revolution and 2050 and 2090.

[1] Increasing oceanic productivity by fertilizing nutrient-rich regions with iron has been proposed as a mechanism to offset anthropogenic emissions of carbon dioxide. Earlier studies examined the impact of large-scale fertilization of vast reaches of the ocean for long periods of time. We use an ocean general circulation model to consider more realistic scenarios involving fertilizing small regions (a few hundred kilometers on a side) for limited periods of time (of order 1 month). A century after such a fertilization event, the reduction of atmospheric carbon dioxide is between 2% and 44% of the initial pulse of organic carbon export to the abyssal ocean. The fraction depends on how rapidly the surface nutrient and carbon fields recover from the fertilization event. The modeled recovery is very sensitive to the representation of biological productivity and remineralization. Direct verification of the uptake would be nearly impossible since changes in the air-sea flux due to fertilization would be much smaller than those resulting from natural spatial variability. Because of the sensitivity of the uptake to the long-term fate of the iron and organic matter, indirect verification by measurement of the organic matter flux would require high vertical resolution and long-term monitoring. Finally, the downward displacement of the nutrient profile resulting from an iron-induced productivity spurt may paradoxically lead to a long-term reduction in biological productivity. In the worst-case scenario, removing 1 ton of carbon from the atmosphere for a century is associated with a 30-ton reduction in biological export of carbon.

[1] We use an ocean biogeochemical-transport box model of the top 100 m of the water column to estimate the CaCO3 to organic carbon export ratio from observations of the vertical gradients of potential alkalinity and nitrate. We find a global average molar export ratio of 0.06 ± 0.03. This is substantially smaller than earlier estimates of 0.25 on which a majority of ocean biogeochemical models had based their parameterization of CaCO3 production. Contrary to the pattern of coccolithophore blooms determined from satellite observations, which show high latitude predominance, we find maximum export ratios in the equatorial region and generally smaller ratios in the subtropical and subpolar gyres. Our results suggest a dominant contribution to global calcification by low-latitude nonbloom forming coccolithophores or other organisms such as foraminifera and pteropods.