Description: © The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Biogeosciences 10 (2013): 6225-6245, doi:10.5194/bg-10-6225-2013.

Description: Ocean ecosystems are increasingly stressed by human-induced changes of their physical, chemical and biological environment. Among these changes, warming, acidification, deoxygenation and changes in primary productivity by marine phytoplankton can be considered as four of the major stressors of open ocean ecosystems. Due to rising atmospheric CO2 in the coming decades, these changes will be amplified. Here, we use the most recent simulations performed in the framework of the Coupled Model Intercomparison Project 5 to assess how these stressors may evolve over the course of the 21st century. The 10 Earth system models used here project similar trends in ocean warming, acidification, deoxygenation and reduced primary productivity for each of the IPCC's representative concentration pathways (RCPs) over the 21st century. For the "business-as-usual" scenario RCP8.5, the model-mean changes in the 2090s (compared to the 1990s) for sea surface temperature, sea surface pH, global O2 content and integrated primary productivity amount to +2.73 (±0.72) °C, −0.33 (±0.003) pH unit, −3.45 (±0.44)% and −8.6 (±7.9)%, respectively. For the high mitigation scenario RCP2.6, corresponding changes are +0.71 (±0.45) °C, −0.07 (±0.001) pH unit, −1.81 (±0.31)% and −2.0 (±4.1)%, respectively, illustrating the effectiveness of extreme mitigation strategies. Although these stressors operate globally, they display distinct regional patterns and thus do not change coincidentally. Large decreases in O2 and in pH are simulated in global ocean intermediate and mode waters, whereas large reductions in primary production are simulated in the tropics and in the North Atlantic. Although temperature and pH projections are robust across models, the same does not hold for projections of subsurface O2 concentrations in the tropics and global and regional changes in net primary productivity. These high uncertainties in projections of primary productivity and subsurface oxygen prompt us to continue inter-model comparisons to understand these model differences, while calling for caution when using the CMIP5 models to force regional impact models.

Description: This work was supported by EU FP7 project CARBOCHANGE (under grant agreement No. 264879), EU FP7 project MEECE (under grant agreement No. 212085), EU FP7 project SOCCLI (under grant agreement No. 317699), and ANR project MACROES. S. C. Doney acknowledges the US National Science Foundation (AGS-1048827). This work has been supported by the Research Council of Norway through the EarthClim (207711/E10) and NOTUR/NorStore projects. M. Vichi acknowledges the support of the Italian Ministry of Education, University and Research and the Ministry for Environment, Land and Sea through the project GEMINA.

Description: Author Posting. © American Geophysical Union, 2010. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 24 (2010): GB3020, doi:10.1029/2009GB003655.

Description: The performance of 36 models (22 ocean color models and 14 biogeochemical ocean circulation models (BOGCMs)) that estimate depth-integrated marine net primary productivity (NPP) was assessed by comparing their output to in situ 14C data at the Bermuda Atlantic Time series Study (BATS) and the Hawaii Ocean Time series (HOT) over nearly two decades. Specifically, skill was assessed based on the models' ability to estimate the observed mean, variability, and trends of NPP. At both sites, more than 90% of the models underestimated mean NPP, with the average bias of the BOGCMs being nearly twice that of the ocean color models. However, the difference in overall skill between the best BOGCM and the best ocean color model at each site was not significant. Between 1989 and 2007, in situ NPP at BATS and HOT increased by an average of nearly 2% per year and was positively correlated to the North Pacific Gyre Oscillation index. The majority of ocean color models produced in situ NPP trends that were closer to the observed trends when chlorophyll-a was derived from high-performance liquid chromatography (HPLC), rather than fluorometric or SeaWiFS data. However, this was a function of time such that average trend magnitude was more accurately estimated over longer time periods. Among BOGCMs, only two individual models successfully produced an increasing NPP trend (one model at each site). We caution against the use of models to assess multiannual changes in NPP over short time periods. Ocean color model estimates of NPP trends could improve if more high quality HPLC chlorophyll-a time series were available.

Description: This research was supported by a grant from the National Aeronautics and Space Agency Ocean Biology and Biogeochemistry program (NNG06GA03G).

Description: © The Authors, 2010. This article is distributed under the terms of the Creative Commons Attribution 3.0 License. The definitive version was published in Biogeosciences 7 (2010): 621-640, doi:10.5194/bg-7-621-2010

Description: Global climate change is predicted to alter the ocean's biological productivity. But how will we recognise the impacts of climate change on ocean productivity? The most comprehensive information available on its global distribution comes from satellite ocean colour data. Now that over ten years of satellite-derived chlorophyll and productivity data have accumulated, can we begin to detect and attribute climate change-driven trends in productivity? Here we compare recent trends in satellite ocean colour data to longer-term time series from three biogeochemical models (GFDL, IPSL and NCAR). We find that detection of climate change-driven trends in the satellite data is confounded by the relatively short time series and large interannual and decadal variability in productivity. Thus, recent observed changes in chlorophyll, primary production and the size of the oligotrophic gyres cannot be unequivocally attributed to the impact of global climate change. Instead, our analyses suggest that a time series of ~40 years length is needed to distinguish a global warming trend from natural variability. In some regions, notably equatorial regions, detection times are predicted to be shorter (~20–30 years). Analysis of modelled chlorophyll and primary production from 2001–2100 suggests that, on average, the climate change-driven trend will not be unambiguously separable from decadal variability until ~2055. Because the magnitude of natural variability in chlorophyll and primary production is larger than, or similar to, the global warming trend, a consistent, decades-long data record must be established if the impact of climate change on ocean productivity is to be definitively detected.

Description: S. A. H. was supported by NASA grants NNG06GE77G and NNX07AL81G. J. L. S. and C. B. acknowledge support from the Carbon Mitigation Initiative funded by BP Amoco. S. C. D. and I. L. were supported by NSF grant EF-0424599. L. B. acknowledges support from the ANR-GlobPhy and FP7-MEECE projects.

Description: © The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Biogeosciences 10 (2013): 2711-2724, doi:10.5194/bg-10-2711-2013.

Description: Global climate change is expected to affect the ocean's biological productivity. The most comprehensive information available about the global distribution of contemporary ocean primary productivity is derived from satellite data. Large spatial patchiness and interannual to multidecadal variability in chlorophyll a concentration challenges efforts to distinguish a global, secular trend given satellite records which are limited in duration and continuity. The longest ocean color satellite record comes from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), which failed in December 2010. The Moderate Resolution Imaging Spectroradiometer (MODIS) ocean color sensors are beyond their originally planned operational lifetime. Successful retrieval of a quality signal from the current Visible Infrared Imager Radiometer Suite (VIIRS) instrument, or successful launch of the Ocean and Land Colour Instrument (OLCI) expected in 2014 will hopefully extend the ocean color time series and increase the potential for detecting trends in ocean productivity in the future. Alternatively, a potential discontinuity in the time series of ocean chlorophyll a, introduced by a change of instrument without overlap and opportunity for cross-calibration, would make trend detection even more challenging. In this paper, we demonstrate that there are a few regions with statistically significant trends over the ten years of SeaWiFS data, but at a global scale the trend is not large enough to be distinguished from noise. We quantify the degree to which red noise (autocorrelation) especially challenges trend detection in these observational time series. We further demonstrate how discontinuities in the time series at various points would affect our ability to detect trends in ocean chlorophyll a. We highlight the importance of maintaining continuous, climate-quality satellite data records for climate-change detection and attribution studies.

Description: CB and JLS acknowledge financial support from the Carbon Mitigation Initiative with support from BP. JLS and RRR were partly supported by the NF-UBC Nereus Program. SAH was supported by NERC grant NE/G013055/1. SCD acknowledges support from NSF grant EF-0424599.

Description: Author Posting. © American Geophysical Union, 2013. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Biogeosciences 118 (2013): 385–399, doi:10.1002/jgrg.20032.

Description: The sea-air biological O2 flux assessed from measurements of surface O2 supersaturation in excess of Ar supersaturation (“O2 bioflux”) is increasingly being used to constrain net community production (NCP) in the upper ocean mixed layer. In making these calculations, one generally assumes that NCP is at steady state, mixed layer depth is constant, and there is no O2 exchange across the base of the mixed layer. The object of this paper is to evaluate the magnitude of errors introduced by violations of these assumptions. Therefore, we examine the differences between the sea-air biological O2 flux and NCP in the Southern Ocean mixed layer as calculated using two ocean biogeochemistry general circulation models. In this approach, NCP is considered a known entity in the prognostic model, whereas O2 bioflux is estimated using the model-predicted O2/Ar ratio to compute the mixed layer biological O2 saturation and the gas transfer velocity to calculate flux. We find that the simulated biological O2 flux gives an accurate picture of the regional-scale patterns and trends in model NCP. However, on local scales, violations of the assumptions behind the O2/Ar method lead to significant, non-uniform differences between model NCP and biological O2 flux. These errors arise from two main sources. First, venting of biological O2 to the atmosphere can be misaligned from NCP in both time and space. Second, vertical fluxes of oxygen across the base of the mixed layer complicate the relationship between NCP and the biological O2 flux. Our calculations show that low values of O2 bioflux correctly register that NCP is also low (〈10 mmol m−2 day−1), but fractional errors are large when rates are this low. Values between 10 and 40 mmol m−2 day−1 in areas with intermediate mixed layer depths of 30 to 50 m have the smallest absolute and relative errors. Areas with O2 bioflux higher than 30 mmol m−2 day−1 and mixed layers deeper than 40 m tend to underestimate NCP by up to 20 mmol m−2 day−1. Excluding time periods when mixed layer biological O2 is undersaturated, O2 bioflux underestimates time-averaged NCP by 5%–15%. If these time periods are included, O2 bioflux underestimates mixed layer NCP by 20%–35% in the Southern Ocean. The higher error estimate is relevant if one wants to estimate seasonal NCP since a significant amount of biological production takes place when mixed layer biological O2 is undersaturated.

Description: This work was supported in part by funding from the National Aeronautic and Space Administration (NASA NNX08AF12G) and National Science Foundation (NSF OPP-0823101).

Description: Author Posting. © American Geophysical Union, 2009. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 114 (2009): C12099, doi:10.1029/2009JC005835.

Description: Author Posting. © American Geophysical Union, 2007. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 112 (2007): C08001, doi:10.1029/2006JC003852.

Description: Application of biogeochemical models to the study of marine ecosystems is pervasive, yet objective quantification of these models' performance is rare. Here, 12 lower trophic level models of varying complexity are objectively assessed in two distinct regions (equatorial Pacific and Arabian Sea). Each model was run within an identical one-dimensional physical framework. A consistent variational adjoint implementation assimilating chlorophyll-a, nitrate, export, and primary productivity was applied and the same metrics were used to assess model skill. Experiments were performed in which data were assimilated from each site individually and from both sites simultaneously. A cross-validation experiment was also conducted whereby data were assimilated from one site and the resulting optimal parameters were used to generate a simulation for the second site. When a single pelagic regime is considered, the simplest models fit the data as well as those with multiple phytoplankton functional groups. However, those with multiple phytoplankton functional groups produced lower misfits when the models are required to simulate both regimes using identical parameter values. The cross-validation experiments revealed that as long as only a few key biogeochemical parameters were optimized, the models with greater phytoplankton complexity were generally more portable. Furthermore, models with multiple zooplankton compartments did not necessarily outperform models with single zooplankton compartments, even when zooplankton biomass data are assimilated. Finally, even when different models produced similar least squares model-data misfits, they often did so via very different element flow pathways, highlighting the need for more comprehensive data sets that uniquely constrain these pathways.

Description: This research was supported by the U.S. National Science Foundation through the JGOFS Synthesis and Modeling Project (OCE-0097285) and the National Aeronautics and Space Agency (NAG5-11259 and NNG05GO04G), as well as numerous other grants to the various investigators who participated.

Description: Author Posting. © American Geophysical Union, 2009. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 114 (2009): C09013, doi:10.1029/2008JC005183.

Description: Here we use observations and ocean models to identify mechanisms driving large seasonal to interannual variations in dissolved inorganic carbon (DIC) and dissolved oxygen (O2) in the upper ocean. We begin with observations linking variations in upper ocean DIC and O2 inventories with changes in the physical state of the ocean. Models are subsequently used to address the extent to which the relationships derived from short-timescale (6 months to 2 years) repeat measurements are representative of variations over larger spatial and temporal scales. The main new result is that convergence and divergence (column stretching) attributed to baroclinic Rossby waves can make a first-order contribution to DIC and O2 variability in the upper ocean. This results in a close correspondence between natural variations in DIC and O2 column inventory variations and sea surface height (SSH) variations over much of the ocean. Oceanic Rossby wave activity is an intrinsic part of the natural variability in the climate system and is elevated even in the absence of significant interannual variability in climate mode indices. The close correspondence between SSH and both DIC and O2 column inventories for many regions suggests that SSH changes (inferred from satellite altimetry) may prove useful in reducing uncertainty in separating natural and anthropogenic DIC signals (using measurements from Climate Variability and Predictability's CO2/Repeat Hydrography program).

Description: This report was prepared by K.B.R. under awards NA17RJ2612 and NA08OAR4320752, which includes support through the NOAA Office of Climate Observations (OCO). The statements, findings, conclusions, and recommendations are those of the authors and do not necessarily reflect the views of the National Oceanic and Atmospheric Administration or the U.S. Department of Commerce. Support for K.B.R. was also provided by the Carbon Mitigation Initiative (CMI) through the support of BP, Amaco, and Ford. R.M.K. was supported by NOAA grants NA17RJ2612, NA08OAR4320752, and NA08OAR4310820. F.F.P. was supported by the European Union FP6 CARBOOCEAN Integrated project (contract 51176), the French OVIDE project, and the Spanish Salvador de Madariaga program (PR2006– 0523). This work was also supported by the European NOCES project (EVK2-CT201-00134). Y.Y. and A.I. are partly supported by CREST, JST of Japan. The long-term OISO observational program in the South Indian Ocean is supported by the following three French institutes: INSU (Institut National des Sciences de l’Univers), IPSL (Institute Pierre-Simon Laplace), and IPEV (Institut Paul-Emile Victor).

Description: © The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Biogeosciences 11 (2014): 709-734, doi:10.5194/bg-11-709-2014.

Description: Air–sea CO2 fluxes over the Pacific Ocean are known to be characterized by coherent large-scale structures that reflect not only ocean subduction and upwelling patterns, but also the combined effects of wind-driven gas exchange and biology. On the largest scales, a large net CO2 influx into the extratropics is associated with a robust seasonal cycle, and a large net CO2 efflux from the tropics is associated with substantial interannual variability. In this work, we have synthesized estimates of the net air–sea CO2 flux from a variety of products, drawing upon a variety of approaches in three sub-basins of the Pacific Ocean, i.e., the North Pacific extratropics (18–66° N), the tropical Pacific (18° S–18° N), and the South Pacific extratropics (44.5–18° S). These approaches include those based on the measurements of CO2 partial pressure in surface seawater (pCO2sw), inversions of ocean-interior CO2 data, forward ocean biogeochemistry models embedded in the ocean general circulation models (OBGCMs), a model with assimilation of pCO2sw data, and inversions of atmospheric CO2 measurements. Long-term means, interannual variations and mean seasonal variations of the regionally integrated fluxes were compared in each of the sub-basins over the last two decades, spanning the period from 1990 through 2009. A simple average of the long-term mean fluxes obtained with surface water pCO2 diagnostics and those obtained with ocean-interior CO2 inversions are −0.47 ± 0.13 Pg C yr−1 in the North Pacific extratropics, +0.44 ± 0.14 Pg C yr−1 in the tropical Pacific, and −0.37 ± 0.08 Pg C yr−1 in the South Pacific extratropics, where positive fluxes are into the atmosphere. This suggests that approximately half of the CO2 taken up over the North and South Pacific extratropics is released back to the atmosphere from the tropical Pacific. These estimates of the regional fluxes are also supported by the estimates from OBGCMs after adding the riverine CO2 flux, i.e., −0.49 ± 0.02 Pg C yr−1 in the North Pacific extratropics, +0.41 ± 0.05 Pg C yr−1 in the tropical Pacific, and −0.39 ± 0.11 Pg C yr−1 in the South Pacific extratropics. The estimates from the atmospheric CO2 inversions show large variations amongst different inversion systems, but their median fluxes are consistent with the estimates from climatological pCO2sw data and pCO2sw diagnostics. In the South Pacific extratropics, where CO2 variations in the surface and ocean interior are severely undersampled, the difference in the air–sea CO2 flux estimates between the diagnostic models and ocean-interior CO2 inversions is larger (0.18 Pg C yr−1). The range of estimates from forward OBGCMs is also large (−0.19 to −0.72 Pg C yr−1). Regarding interannual variability of air–sea CO2 fluxes, positive and negative anomalies are evident in the tropical Pacific during the cold and warm events of the El Niño–Southern Oscillation in the estimates from pCO2sw diagnostic models and from OBGCMs. They are consistent in phase with the Southern Oscillation Index, but the peak-to-peak amplitudes tend to be higher in OBGCMs (0.40 ± 0.09 Pg C yr−1) than in the diagnostic models (0.27 ± 0.07 Pg C yr−1).

Description: M. Ishii acknowledges the Meteorological Research Institute’s priority research fund for ocean carbon cycle changes, JSPS Grant-in-Aid for Scientific Research (B) No. 22310017, and MEXT Grant-in-Aid for Scientific Research on Innovative Areas No. 24121003. Support for K. B. Rodgers came under awards NA17RJ2612 and NA08OAR4320752, and support for K. B. Rodgers and R. A. Feely from the NOAA Office of Oceanic and Atmospheric Research (OAR) through the office of Climate Observations (OCO), as well as by funds from NASA’s Research Opportunities in Space and Earth Sciences through award #NNX09AI13G. SMF’s contributions were funded through the NIWA National Centre for Atmosphere’s core research funding. S. C. Doney and I. Lima acknowledge support from US National Science Foundation award AGS-1048827. E. T. Buitenhuis acknowledges support from the EU (CarboChange, contract 264879). A. Lenton acknowledges support from the Australian Climate Change Science Program. T. Takahashi is supported by grants from the NOAA (NA08OAR4320754) and the Comer Science and Education Foundation (CSEF CP70).