Description: The Ocean Model Intercomparison Project (OMIP) focuses on the physics and biogeochemistry of the ocean component of Earth system models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). OMIP aims to provide standard protocols and diagnostics for ocean models, while offering a forum to promote their common assessment and improvement. It also offers to compare solutions of the same ocean models when forced with reanalysis data (OMIP simulations) vs. when integrated within fully coupled Earth system models (CMIP6). Here we detail simulation protocols and diagnostics for OMIP's biogeochemical and inert chemical tracers. These passive-tracer simulations will be coupled to ocean circulation models, initialized with observational data or output from a model spin-up, and forced by repeating the 1948–2009 surface fluxes of heat, fresh water, and momentum. These so-called OMIP-BGC simulations include three inert chemical tracers (CFC-11, CFC-12, SF6) and biogeochemical tracers (e.g., dissolved inorganic carbon, carbon isotopes, alkalinity, nutrients, and oxygen). Modelers will use their preferred prognostic BGC model but should follow common guidelines for gas exchange and carbonate chemistry. Simulations include both natural and total carbon tracers. The required forced simulation (omip1) will be initialized with gridded observational climatologies. An optional forced simulation (omip1-spunup) will be initialized instead with BGC fields from a long model spin-up, preferably for 2000 years or more, and forced by repeating the same 62-year meteorological forcing. That optional run will also include abiotic tracers of total dissolved inorganic carbon and radiocarbon, CTabio and 14CTabio, to assess deep-ocean ventilation and distinguish the role of physics vs. biology. These simulations will be forced by observed atmospheric histories of the three inert gases and CO2 as well as carbon isotope ratios of CO2. OMIP-BGC simulation protocols are founded on those from previous phases of the Ocean Carbon-Cycle Model Intercomparison Project. They have been merged and updated to reflect improvements concerning gas exchange, carbonate chemistry, and new data for initial conditions and atmospheric gas histories. Code is provided to facilitate their implementation.

Description: The Ocean Model Intercomparison Project (OMIP) focuses on the physics and biogeochemistry of the ocean component of Earth system models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). OMIP aims to provide standard protocols and diagnostics for ocean models, while offering a forum to promote their common assessment and improvement. It also offers to compare solutions of the same ocean models when forced with reanalysis data (OMIP simulations) vs. when integrated within fully coupled Earth system models (CMIP6). Here we detail simulation protocols and diagnostics for OMIP’s biogeochemical and inert chemical tracers. These passive-tracer simulations will be coupled to ocean circulation models, initialized with observational data or output from a model spin-up, and forced by repeating the 1948– 2009 surface fluxes of heat, fresh water, and momentum. These so-called OMIP-BGC simulations include three inert chemical tracers (CFC-11, CFC-12, SF6) and biogeochemical tracers (e.g., dissolved inorganic carbon, carbon isotopes, alkalinity, nutrients, and oxygen). Modelers will use their preferred prognostic BGC model but should follow common guidelines for gas exchange and carbonate chemistry. Simulations include both natural and total carbon tracers. The required forced simulation (omip1) will be initialized with gridded observational climatologies. An optional forced simulation (omip1-spunup) will be initialized instead with BGC fields from a long model spin-up, preferably for 2000 years or more, and forced by repeating the same 62-year meteorological forcing. That optional run will also include abiotic tracers of total dissolved inorganic carbon and radiocarbon, Cabio T and 14Cabio T , to assess deep-ocean ventilation and distinguish the role of physics vs. biology. These simulations will be forced by observed atmospheric histories of the three inert gases and CO2 as well as carbon isotope ratios of CO2. OMIP-BGC simulation protocols are founded on those from previous phases of the Ocean Carbon-Cycle Model Intercomparison Project. They have been merged and updated to reflect improvements concerning gas exchange, carbonate chemistry, and new data for initial conditions and atmospheric gas histories. Code is provided to facilitate their implementation.

Description: Author Posting. © American Geophysical Union, 2017. 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 31 (2017): 922–940, doi:10.1002/2016GB005615.

Description: A coupled global numerical simulation (conducted with the Community Earth System Model) is used in conjunction with satellite remote sensing observations to examine the role of top-down (grazing pressure) and bottom-up (light, nutrients) controls on marine phytoplankton bloom dynamics in the Southern Ocean. Phytoplankton seasonal phenology is evaluated in the context of the recently proposed “disturbance-recovery” hypothesis relative to more traditional, exclusively “bottom-up” frameworks. All blooms occur when phytoplankton division rates exceed loss rates to permit sustained net population growth; however, the nature of this decoupling period varies regionally in Community Earth System Model. Regional case studies illustrate how unique pathways allow blooms to emerge despite very poor division rates or very strong grazing rates. In the Subantarctic, southeast Pacific small spring blooms initiate early cooccurring with deep mixing and low division rates, consistent with the disturbance-recovery hypothesis. Similar systematics are present in the Subantarctic, southwest Atlantic during the spring but are eclipsed by a subsequent, larger summer bloom that is coincident with shallow mixing and the annual maximum in division rates, consistent with a bottom-up, light limited framework. In the model simulation, increased iron stress prevents a similar summer bloom in the southeast Pacific. In the simulated Antarctic zone (70°S–65°S) seasonal sea ice acts as a dominant phytoplankton-zooplankton decoupling agent, triggering a delayed but substantial bloom as ice recedes. Satellite ocean color remote sensing and ocean physical reanalysis products do not precisely match model-predicted phenology, but observed patterns do indicate regional variability in mechanism across the Atlantic and Pacific.

Description: NDSEG Graduate Fellowship; National Aeronautics and Space Administration Ocean Biology and Biogeochemistry Program Grant Number: NNX14L86G; NSF Poloar Programs Award Grant Number: 1440435; National Aeronautics and Space Administration Grant Number: NNX14AL86G; NDSEG; National Science Foundation Grant Number: 1440435

Description: 2017-11-30

Description: Author Posting. © American Geophysical Union, 2017. 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 31 (2017): 96–113, doi:10.1002/2016GB005374.

Description: Using the Community Earth System Model, we explore the role of human land use and land cover change (LULCC) in modifying the terrestrial carbon budget in simulations forced by Representative Concentration Pathway 8.5, extended to year 2300. Overall, conversion of land (e.g., from forest to croplands via deforestation) results in a model-estimated, cumulative carbon loss of 490 Pg C between 1850 and 2300, larger than the 230 Pg C loss of carbon caused by climate change over this same interval. The LULCC carbon loss is a combination of a direct loss at the time of conversion and an indirect loss from the reduction of potential terrestrial carbon sinks. Approximately 40% of the carbon loss associated with LULCC in the simulations arises from direct human modification of the land surface; the remaining 60% is an indirect consequence of the loss of potential natural carbon sinks. Because of the multicentury carbon cycle legacy of current land use decisions, a globally averaged amplification factor of 2.6 must be applied to 2015 land use carbon losses to adjust for indirect effects. This estimate is 30% higher when considering the carbon cycle evolution after 2100. Most of the terrestrial uptake of anthropogenic carbon in the model occurs from the influence of rising atmospheric CO2 on photosynthesis in trees, and thus, model-projected carbon feedbacks are especially sensitive to deforestation.

Description: National Science Foundation Grant Numbers: AGS 1049033, CCF-1522054

Description: 2017-07-23

Description: © The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Geoscientific Model Development 10 (2017): 2169-2199, doi:10.5194/gmd-10-2169-2017.

Description: The Ocean Model Intercomparison Project (OMIP) focuses on the physics and biogeochemistry of the ocean component of Earth system models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). OMIP aims to provide standard protocols and diagnostics for ocean models, while offering a forum to promote their common assessment and improvement. It also offers to compare solutions of the same ocean models when forced with reanalysis data (OMIP simulations) vs. when integrated within fully coupled Earth system models (CMIP6). Here we detail simulation protocols and diagnostics for OMIP's biogeochemical and inert chemical tracers. These passive-tracer simulations will be coupled to ocean circulation models, initialized with observational data or output from a model spin-up, and forced by repeating the 1948–2009 surface fluxes of heat, fresh water, and momentum. These so-called OMIP-BGC simulations include three inert chemical tracers (CFC-11, CFC-12, SF6) and biogeochemical tracers (e.g., dissolved inorganic carbon, carbon isotopes, alkalinity, nutrients, and oxygen). Modelers will use their preferred prognostic BGC model but should follow common guidelines for gas exchange and carbonate chemistry. Simulations include both natural and total carbon tracers. The required forced simulation (omip1) will be initialized with gridded observational climatologies. An optional forced simulation (omip1-spunup) will be initialized instead with BGC fields from a long model spin-up, preferably for 2000 years or more, and forced by repeating the same 62-year meteorological forcing. That optional run will also include abiotic tracers of total dissolved inorganic carbon and radiocarbon, CTabio and 14CTabio, to assess deep-ocean ventilation and distinguish the role of physics vs. biology. These simulations will be forced by observed atmospheric histories of the three inert gases and CO2 as well as carbon isotope ratios of CO2. OMIP-BGC simulation protocols are founded on those from previous phases of the Ocean Carbon-Cycle Model Intercomparison Project. They have been merged and updated to reflect improvements concerning gas exchange, carbonate chemistry, and new data for initial conditions and atmospheric gas histories. Code is provided to facilitate their implementation.

Description: J. C. Orr and L. Bopp were supported by the EU H2020 CRESCENDO project (grant 641816). J. L. Bullister was supported by the NOAA Climate Program Office H. Graven was supported by an EU Marie Curie Career Integration Grant. A. Mouchet benefited from an EU H2020 Marie Curie project (grant 660893). R. G. Najjar was supported by NASA’s Ocean Biology and Biogeochemistry Program and NASA’s Interdisciplinary Science Program. F. Joos was supported by the Swiss National Science Foundation.

Description: © The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Frontiers in Marine Science 3 (2016): 22, doi:10.3389/fmars.2016.00022.

Description: Ocean ecosystems play a critical role in the Earth's carbon cycle and the quantification of their impacts for both present conditions and for predictions into the future remains one of the greatest challenges in oceanography. The goal of the EXport Processes in the Ocean from Remote Sensing (EXPORTS) Science Plan is to develop a predictive understanding of the export and fate of global ocean net primary production (NPP) and its implications for present and future climates. The achievement of this goal requires a quantification of the mechanisms that control the export of carbon from the euphotic zone as well as its fate in the underlying “twilight zone” where some fraction of exported carbon will be sequestered in the ocean's interior on time scales of months to millennia. Here we present a measurement/synthesis/modeling framework aimed at quantifying the fates of upper ocean NPP and its impacts on the global carbon cycle based upon the EXPORTS Science Plan. The proposed approach will diagnose relationships among the ecological, biogeochemical, and physical oceanographic processes that control carbon cycling across a range of ecosystem and carbon cycling states leading to advances in satellite diagnostic and numerical prognostic models. To collect these data, a combination of ship and robotic field sampling, satellite remote sensing, and numerical modeling is proposed which enables the sampling of the many pathways of NPP export and fates. This coordinated, process-oriented approach has the potential to foster new insights on ocean carbon cycling that maximizes its societal relevance through the achievement of research goals of many international research agencies and will be a key step toward our understanding of the Earth as an integrated system.

Description: The development of the EXPORTS Science Plan was supported by NASA Ocean Biology and Biogeochemistry program (award NNX13AC35G).

Description: © The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Environmental Research Letters 12 (2017): 094016, doi:10.1088/1748-9326/aa836d.

Description: While carbon dioxide emissions from energy use must be the primary target of climate change mitigation efforts, land use and land cover change (LULCC) also represent an important source of climate forcing. In this study we compute time series of global surface temperature change separately for LULCC and non-LULCC sources (primarily fossil fuel burning), and show that because of the extra warming associated with the co-emission of methane and nitrous oxide with LULCC carbon dioxide emissions, and a co-emission of cooling aerosols with non-LULCC emissions of carbon dioxide, the linear relationship between cumulative carbon dioxide emissions and temperature has a two-fold higher slope for LULCC than for non-LULCC activities. Moreover, projections used in the Intergovernmental Panel on Climate Change (IPCC) for the rate of tropical land conversion in the future are relatively low compared to contemporary observations, suggesting that the future projections of land conversion used in the IPCC may underestimate potential impacts of LULCC. By including a ‘business as usual’ future LULCC scenario for tropical deforestation, we find that even if all non-LULCC emissions are switched off in 2015, it is likely that 1.5 ◦C of warming relative to the preindustrial era will occur by 2100. Thus, policies to reduce LULCC emissions must remain a high priority if we are to achieve the low to medium temperature change targets proposed as a part of the Paris Agreement. Future studies using integrated assessment models and other climate simulations should include more realistic deforestation rates and the integration of policy that would reduce LULCC emissions.

Description: We would like to acknowledge the support from grants NSF-ATM1049033, NSF-CCF-1522054, NSFAGS- 1048827 and DOE-SC0016362, DOE Office of Science Biogeochemical Cycles Feedbacks and ACME Science Focus Areas as well as assistance from the Atkinson Center for a Sustainable Future

Description: © The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Earth System Science Data 8 (2016): 605-649, doi:10.5194/essd-8-605-2016.

Description: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates and consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models. We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2006–2015), EFF was 9.3 ± 0.5 GtC yr−1, ELUC 1.0 ± 0.5 GtC yr−1, GATM 4.5 ± 0.1 GtC yr−1, SOCEAN 2.6 ± 0.5 GtC yr−1, and SLAND 3.1 ± 0.9 GtC yr−1. For year 2015 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1, showing a slowdown in growth of these emissions compared to the average growth of 1.8 % yr−1 that took place during 2006–2015. Also, for 2015, ELUC was 1.3 ± 0.5 GtC yr−1, GATM was 6.3 ± 0.2 GtC yr−1, SOCEAN was 3.0 ± 0.5 GtC yr−1, and SLAND was 1.9 ± 0.9 GtC yr−1. GATM was higher in 2015 compared to the past decade (2006–2015), reflecting a smaller SLAND for that year. The global atmospheric CO2 concentration reached 399.4 ± 0.1 ppm averaged over 2015. For 2016, preliminary data indicate the continuation of low growth in EFF with +0.2 % (range of −1.0 to +1.8 %) based on national emissions projections for China and USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. In spite of the low growth of EFF in 2016, the growth rate in atmospheric CO2 concentration is expected to be relatively high because of the persistence of the smaller residual terrestrial sink (SLAND) in response to El Niño conditions of 2015–2016. From this projection of EFF and assumed constant ELUC for 2016, cumulative emissions of CO2 will reach 565 ± 55 GtC (2075 ± 205 GtCO2) for 1870–2016, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015b, a, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2016).

Description: Australia, Integrated Marine Observing System and Antarctic Climate and Ecosystems CRC BT; European Commission (EC) Copernicus Atmosphere Monitoring Service, European Centre for Medium-Range Weather Forecasts (ECMWF) FC; EC H2020 (AtlantOS; grant no. 633211) NL, AO; EC H2020 (CRESCENDO; grant no. 641816) CD, RS, OA, PF; EC H2020 European Research Council (ERC) (QUINCY; grant no. 647204). SZ; EC H2020 ERC Synergy grant (IMBALANCE-P; grant no. ERC-2013-SyG-610028) PC; France, BNP Paribas Foundation grant to support the Global Carbon Atlas PC; French Institut National des Sciences de l’Univers (INSU) and Institut Paul Emile Victor (IPEV) for OISO cruises NM; French Institut de recherche pour le développement (IRD) NL; German Federal Ministry of Education and Research (grant no. 01LK1224I ICOS-D) MH; German Research Foundation’s Emmy Noether Programme (grant no. PO1751/1-1) JN; German Max Planck Society CR, SZ; Germany, Federal Ministry of Education and Research (BMBF) AK; Germany, Helmholtz Postdoc Programme (Initiative and Networking Fund of the Helmholtz Association) JH; Japan Ministry of Agriculture, Forestry and Fisheries (MAFF) OT; Japan Ministry of Environment SN; Japan Ministry of Environment (grant no. ERTDF S-10) EK; NASA LCLUC programme (grant no. NASA NNX14AD94G) AJ; New Zealand National Institute of Water and Atmospheric Research (NIWA) Core Funding KC; Norway Research Council (grant no. 229752) AMO; Norway Research Council (grant no. 569980) GPP, RMA, JIK; Norway Research Council (project EVA; grant no. 229771) JS; Norwegian Environment Agency (grant no. 16078007) IS; Research Fund – Flanders (FWO; formerly Hercules Foundation) TG; South Africa Council for Scientific and Industrial Research (CSIR) PMSM; UK Natural Environment Research Council (RAGANRAoCC; grant no. NE/K002473/1) US; UK Newton Fund through the Met Office Climate Science for Service Partnership Brazil (CSSP Brazil) AJW; US Department of Agriculture, National Institute of Food and Agriculture (grant no. 2015-67003- 23485) DL; US Department of Energy (grant no. DE-FC03-97ER62402/A010) DL; US Department of Energy, Biological and Environmental Research Program, Office of Science (grant no. DE-AC05-00OR22725) APW; US Department of Commerce, NOAA’s Climate Observation Division of the Climate Program Office SRA, AJS; US Department of Energy, Office of Science and BER programme (grant no. DOE DE-SC0016323) AJ; US National Science Foundation (grant no. AGS-1048827) SD; US National Science Foundation (grant no. AOAS-1543457) DRM; US National Science Foundation (grant no. AOAS-1341647) DRM; US NOAA’s Climate Observation Division of the Climate Program Office (grant no. N8R1SE3P00); US NOAA’s Ocean Acidification Program (grant no. N8R3CEAP00) DP, LB; US National Science Foundation (grant no. NSF AGS 12-43071)