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We investigated the simulated iron budget in ocean surface waters in the 1990s and 2090s using the Community Earth System Model version 1 and the Representative Concentration Pathway 8.5 future CO2 emission scenario. We assumed that exogenous iron inputs did not change during the whole simulation period; thus, iron budget changes were attributed solely to changes in ocean circulation and mixing in response to projected global warming, and the resulting impacts on marine biogeochemistry. The model simulated the major features of ocean circulation and dissolved iron distribution for the present climate. Detailed iron budget analysis revealed that roughly 70% of the iron supplied to surface waters in high-nutrient, low-chlorophyll (HNLC) regions is contributed by ocean circulation and mixing processes, but the dominant supply mechanism differed by region: upwelling in the eastern equatorial Pacific and vertical mixing in the Southern Ocean. For the 2090s, our model projected an increased iron supply to HNLC waters, even though enhanced stratification was predicted to reduce iron entrainment from deeper waters. This unexpected result is attributed largely to changes in gyre-scale circulations that intensified the advective supply of iron to HNLC waters. The simulated primary and export production in the 2090s decreased globally by 6 and 13%, respectively, whereas in the HNLC regions, they increased by 11 and 6%, respectively. Roughly half of the elevated production could be attributed to the intensified iron supply. The projected ocean circulation and mixing changes are consistent with recent observations of responses to the warming climate and with other Coupled Model Intercomparison Project model projections. We conclude that future ocean circulation has the potential to increase iron supply to HNLC waters and will potentially buffer future reductions in ocean productivity.

Volcanic eruptions induce a dynamical response in the climate system characterized by short-term global reductions in both surface temperature and precipitation, as well as a response in biogeochemistry. The available observations of these responses to volcanic eruptions, such as to Pinatubo, provide a valuable method to compare against model simulations. Here, the Community Climate System Model Version 3 (CCSM3) reproduces the physical climate response to volcanic eruptions in a realistic way, as compared to direct observations from the 1991 eruption of Mount Pinatubo. The model's biogeochemical response to eruptions is smaller in magnitude than observed, but because of the lack of observations, it is not clear why or where the modeled carbon response is not strong enough. Comparison to other models suggests that this model response is much weaker over tropical land; however, the precipitation response in other models is not accurate, suggesting that other models could be getting the right response for the wrong reason. The underestimated carbon response in the model compared to observations could also be due to the ash and lava input of biogeochemically important species to the ocean, which are not included in the simulation. A statistically significant reduction in the simulated carbon dioxide growth rate is seen at the 90% level in the average of 12 large eruptions over the period 1870–2000, and the net uptake of carbon is primarily concentrated in the tropics, with large spatial variability. In addition, a method for computing the volcanic response in model output without using a control ensemble is tested against a traditional methodology using two separate ensembles of runs; the method is found to produce similar results in the global average. These results suggest that not only is simulating volcanoes a good test of coupled carbon–climate models, but also that this test can be performed without a control simulation in cases where it is not practical to run separate ensembles with and without volcanic eruptions.

Mechanisms controlling the dissolved iron distribution in the North Pacific are investigated using the Biogeochemical Elemental Cycling (BEC) model with a resolution of approximately 1° in latitude and longitude and 60 vertical levels. The model is able to reproduce the general distribution of iron as revealed in available field data: surface concentrations are generally below 0.2 nM; concentrations increase with depth; and values in the lower pycnocline are especially high in the northwestern Pacific and off the coast of California. Sensitivity experiments changing scavenging regimes and external iron sources indicate that lateral transport of sedimentary iron from continental margins into the open ocean causes the high concentrations in these regions. This offshore penetration only appears under a scavenging regime where iron has a relatively long residence time at high concentrations, namely, the order of years. Sedimentary iron is intensively supplied around continental margins, resulting in locally high concentrations; the residence time with respect to scavenging determines the horizontal scale of elevated iron concentrations. Budget analysis for iron reveals the processes by which sedimentary iron is transported to the open ocean. Horizontal mixing transports sedimentary iron from the boundary into alongshore currents, which then carry high iron concentrations into the open ocean in regions where the alongshore currents separate from the coast, most prominently in the northwestern Pacific and off of California.

Coupled-carbon-climate simulations are an essential tool for predicting the impact of human activity onto the climate and biogeochemistry. Here we incorporate prognostic desert dust and anthropogenic aerosols into the CCSM3.1 coupled carbon-climate model and explore the resulting interactions with climate and biogeochemical dynamics through a series of transient anthropogenic simulations (20th and 21st centuries) and sensitivity studies. The inclusion of prognostic aerosols into this model has a small net global cooling effect on climate but does not significantly impact the globally averaged carbon cycle; we argue that this is likely to be because the CCSM3.1 model has a small climate feedback onto the carbon cycle. We propose a mechanism for including desert dust and anthropogenic aerosols into a simple carbon-climate feedback analysis to explain the results of our and previous studies. Inclusion of aerosols has statistically significant impacts on regional climate and biogeochemistry, in particular through the effects on the ocean nitrogen cycle and primary productivity of altered iron inputs from desert dust deposition.

Desert dust perturbs climate by directly and indirectly interacting with incoming solar and outgoing long wave radiation, thereby changing precipitation and temperature, in addition to modifying ocean and land biogeochemistry. While we know that desert dust is sensitive to perturbations in climate and human land use, previous studies have been unable to determine whether humans were increasing or decreasing desert dust in the global average. Here we present observational estimates of desert dust based on paleodata proxies showing a doubling of desert dust during the 20th century over much, but not all the globe. Large uncertainties remain in estimates of desert dust variability over 20th century due to limited data. Using these observational estimates of desert dust change in combination with ocean, atmosphere and land models, we calculate the net radiative effect of these observed changes (top of atmosphere) over the 20th century to be −0.14 ± 0.11 W/m2 (1990–1999 vs. 1905–1914). The estimated radiative change due to dust is especially strong between the heavily loaded 1980–1989 and the less heavily loaded 1955–1964 time periods (−0.57 ± 0.46 W/m2), which model simulations suggest may have reduced the rate of temperature increase between these time periods by 0.11 °C. Model simulations also indicate strong regional shifts in precipitation and temperature from desert dust changes, causing 6 ppm (12 PgC) reduction in model carbon uptake by the terrestrial biosphere over the 20th century. Desert dust carries iron, an important micronutrient for ocean biogeochemistry that can modulate ocean carbon storage; here we show that dust deposition trends increase ocean productivity by an estimated 6% over the 20th century, drawing down an additional 4 ppm (8 PgC) of carbon dioxide into the oceans. Thus, perturbations to desert dust over the 20th century inferred from observations are potentially important for climate and biogeochemistry, and our understanding of these changes and their impacts should continue to be refined.

Changes in marine net primary productivity (PP) and export of particulate organic carbon (EP) are projected over the 21st century with four global coupled carbon cycle-climate models. These include representations of marine ecosystems and the carbon cycle of different structure and complexity. All four models show a decrease in global mean PP and EP between 2 and 20% by 2100 relative to preindustrial conditions, for the SRES A2 emission scenario. Two different regimes for productivity changes are consistently identified in all models. The first chain of mechanisms is dominant in the low- and mid-latitude ocean and in the North Atlantic: reduced input of macro-nutrients into the euphotic zone related to enhanced stratification, reduced mixed layer depth, and slowed circulation causes a decrease in macro-nutrient concentrations and in PP and EP. The second regime is projected for parts of the Southern Ocean: an alleviation of light and/or temperature limitation leads to an increase in PP and EP as productivity is fueled by a sustained nutrient input. A region of disagreement among the models is the Arctic, where three models project an increase in PP while one model projects a decrease. Projected changes in seasonal and interannual variability are modest in most regions. Regional model skill metrics are proposed to generate multi-model mean fields that show an improved skill in representing observation-based estimates compared to a simple multi-model average. Model results are compared to recent productivity projections with three different algorithms, usually applied to infer net primary production from satellite observations.

Inclusion of fundamental ecological interactions between carbon and nitrogen cycles in the land component of an atmosphere-ocean general circulation model (AOGCM) leads to decreased carbon uptake associated with CO2 fertilization, and increased carbon uptake associated with warming of the climate system. The balance of these two opposing effects is to reduce the fraction of anthropogenic CO2 predicted to be sequestered in land ecosystems. The primary mechanism responsible for increased land carbon storage under radiatively forced climate change is shown to be fertilization of plant growth by increased mineralization of nitrogen directly associated with increased decomposition of soil organic matter under a warming climate, which in this particular model results in a negative gain for the climate-carbon feedback. Estimates for the land and ocean sink fractions of recent anthropogenic emissions are individually within the range of observational estimates, but the combined land plus ocean sink fractions produce an airborne fraction which is too high compared to observations. This bias is likely due in part to an underestimation of the ocean sink fraction. Our results show a significant growth in the airborne fraction of anthropogenic CO2 emissions over the coming century, attributable in part to a steady decline in the ocean sink fraction. Comparison to experimental studies on the fate of radio-labeled nitrogen tracers in temperate forests indicates that the model representation of competition between plants and microbes for new mineral nitrogen resources is reasonable. Our results suggest a weaker dependence of net land carbon flux on soil moisture changes in tropical regions, and a stronger positive growth response to warming in those regions, than predicted by a similar AOGCM implemented without land carbon-nitrogen interactions. We expect that the between-model uncertainty in predictions of future atmospheric CO2 concentration and associated anthropogenic climate change will be reduced as additional climate models introduce carbon-nitrogen cycle interactions in their land components.

Phytoplankton photosynthesis links global ocean biology and climate-driven fluctuations in the physical environment. These interactions are largely expressed through changes in phytoplankton physiology, but physiological status has proven extremely challenging to characterize globally. Phytoplankton fluorescence does provide a rich source of physiological information long exploited in laboratory and field studies, and is now observed from space. Here we evaluate the physiological underpinnings of global variations in satellite-based phytoplankton chlorophyll fluorescence. The three dominant factors influencing fluorescence distributions are chlorophyll concentration, pigment packaging effects on light absorption, and light-dependent energy-quenching processes. After accounting for these three factors, resultant global distributions of quenching-corrected fluorescence quantum yields reveal a striking consistency with anticipated patterns of iron availability. High fluorescence quantum yields are typically found in low iron waters, while low quantum yields dominate regions where other environmental factors are most limiting to phytoplankton growth. Specific properties of photosynthetic membranes are discussed that provide a mechanistic view linking iron stress to satellite-detected fluorescence. Our results present satellite-based fluorescence as a valuable tool for evaluating nutrient stress predictions in ocean ecosystem models and give the first synoptic observational evidence that iron plays an important role in seasonal phytoplankton dynamics of the Indian Ocean. Satellite fluorescence may also provide a path for monitoring climate-phytoplankton physiology interactions and improving descriptions of phytoplankton light use efficiencies in ocean productivity models.

Atmospheric aerosol deposition is an important source of nutrients and trace metals to the open ocean that can enhance ocean productivity and carbon sequestration and thus influence atmospheric carbon dioxide concentrations and climate. Using aerosol samples from different back trajectories in incubation experiments with natural communities, we demonstrate that the response of phytoplankton growth to aerosol additions depends on specific components in aerosols and differs across phytoplankton species. Aerosol additions enhanced growth by releasing nitrogen and phosphorus, but not all aerosols stimulated growth. Toxic effects were observed with some aerosols, where the toxicity affected picoeukaryotes and Synechococcus but notProchlorococcus. We suggest that the toxicity could be due to high copper concentrations in these aerosols and support this by laboratory copper toxicity tests preformed with Synechococcus cultures. However, it is possible that other elements present in the aerosols or unknown synergistic effects between these elements could have also contributed to the toxic effect. Anthropogenic emissions are increasing atmospheric copper deposition sharply, and based on coupled atmosphere–ocean calculations, we show that this deposition can potentially alter patterns of marine primary production and community structure in high aerosol, low chlorophyll areas, particularly in the Bay of Bengal and downwind of South and East Asia.

Precision requirements are determined for space-based column-averaged CO2 dry air mole fraction data. These requirements result from an assessment of spatial and temporal gradients in the relationship between precision and surface CO2 flux uncertainties inferred from inversions of the data, and the effects of biases on the fidelity of CO2 flux inversions. Observational system simulation experiments and synthesis inversion modeling demonstrate that the Orbiting Carbon Observatory mission design and sampling strategy provide the means to achieve these data precision requirements.

[1] Regional air-sea fluxes of anthropogenic CO2 are estimated using a Green's function inversion method that combines data-based estimates of anthropogenic CO2 in the ocean with information about ocean transport and mixing from a suite of Ocean General Circulation Models (OGCMs). In order to quantify the uncertainty associated with the estimated fluxes owing to modeled transport and errors in the data, we employ 10 OGCMs and three scenarios representing biases in the data-based anthropogenic CO2 estimates. On the basis of the prescribed anthropogenic CO2 storage, we find a global uptake of 2.2 +/- 0.25 Pg C yr(-1), scaled to 1995. This error estimate represents the standard deviation of the models weighted by a CFC-based model skill score, which reduces the error range and emphasizes those models that have been shown to reproduce observed tracer concentrations most accurately. The greatest anthropogenic CO2 uptake occurs in the Southern Ocean and in the tropics. The flux estimates imply vigorous northward transport in the Southern Hemisphere, northward cross-equatorial transport, and equatorward transport at high northern latitudes. Compared with forward simulations, we find substantially more uptake in the Southern Ocean, less uptake in the Pacific Ocean, and less global uptake. The large-scale spatial pattern of the estimated flux is generally insensitive to possible biases in the data and the models employed. However, the global uptake scales approximately linearly with changes in the global anthropogenic CO2 inventory. Considerable uncertainties remain in some regions, particularly the Southern Ocean.

Climate variability drives significant changes in the physical state of the North Pacific, and there may be important impacts of this variability on the upper ocean carbon balance across the basin. We address this issue by considering the response of seven biogeochemical ocean models to climate variability in the North Pacific. The models' upper ocean pCO2 and air-sea CO2 flux respond similarly to climate variability on seasonal to decadal timescales. Modeled seasonal cycles of pCO2 and its temperature- and non-temperature-driven components at three contrasting oceanographic sites capture the basic features found in observations (Takahashi et al., 2002, 2006; Keeling et al., 2004; Brix et al., 2004). However, particularly in the Western Subarctic Gyre, the models have difficulty representing the temporal structure of the total pCO2 seasonal cycle because it results from the difference of these two large and opposing components. In all but one model, the air-sea CO2 flux interannual variability (1σ) in the North Pacific is smaller (ranges across models from 0.03 to 0.11 PgC/yr) than in the Tropical Pacific (ranges across models from 0.08 to 0.19 PgC/yr), and the time series of the first or second EOF of the air-sea CO2 flux has a significant correlation with the Pacific Decadal Oscillation (PDO). Though air-sea CO2 flux anomalies are correlated with the PDO, their magnitudes are small (up to ±0.025 PgC/yr (1σ)). Flux anomalies are damped because anomalies in the key drivers of pCO2 (temperature, dissolved inorganic carbon (DIC), and alkalinity) are all of similar magnitude and have strongly opposing effects that damp total pCO2 anomalies.

Estimating discrimination against 13C during photosynthesis at landscape, regional, and biome scales is difficult because of large-scale variability in plant stress, vegetation composition, and photosynthetic pathway. Here we present estimates of 13C discrimination for northern biomes based on a biosphere-atmosphere model and on National Oceanic and Atmospheric Administration Climate Monitoring and Diagnostics Laboratory and Institute of Arctic and Alpine Research remote flask measurements. With our inversion approach, we solved for three ecophysiological parameters of the northern biosphere (13C discrimination, a net primary production light use efficiency, and a temperature sensitivity of heterotrophic respiration (a Q10 factor)) that provided a best fit between modeled and observed δ13C and CO2. In our analysis we attempted to explicitly correct for fossil fuel emissions, remote C4 ecosystem fluxes, ocean exchange, and isotopic disequilibria of terrestrial heterotrophic respiration caused by the Suess effect. We obtained a photosynthetic discrimination for arctic and boreal biomes between 19.0 and 19.6‰. Our inversion analysis suggests that Q10 and light use efficiency values that minimize the cost function covary. The optimal light use efficiency was 0.47 gC MJ−1 photosynthetically active radiation, and the optimal Q10 value was 1.52. Fossil fuel and ocean exchange contributed proportionally more to month-to-month changes in the atmospheric growth rate of δ13C and CO2 during winter months, suggesting that remote atmospheric observations during the summer may yield more precise estimates of the isotopic composition of the biosphere.