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  • 1
    Publication Date: 2018-04-03
    Description: Fully coupled climate carbon cycle models are sophisticated tools that are used to predict future climate change and its impact on the land and ocean carbon cycles. These models should be able to adequately represent natural variability, requiring model validation by observations. The present study focuses on the ocean carbon cycle component, in particular the spatial and temporal variability in net primary productivity (PP) and export production (EP) of particulate organic carbon (POC). Results from three coupled climate carbon cycle models (IPSL, MPIM, NCAR) are compared with observation-based estimates derived from satellite measurements of ocean colour and results from inverse modelling (data assimilation). Satellite observations of ocean colour have shown that temporal variability of PP on the global scale is largely dominated by the permanently stratified, low-latitude ocean (Behrenfeld et al., 2006) with stronger stratification (higher sea surface temperature; SST) being associated with negative PP anomalies. Results from all three coupled models confirm the role of the low-latitude, permanently stratified ocean for anomalies in globally integrated PP, but only one model (IPSL) also reproduces the inverse relationship between stratification (SST) and PP. An adequate representation of iron and macronutrient co-limitation of phytoplankton growth in the tropical ocean has shown to be the crucial mechanism determining the capability of the models to reproduce observed interactions between climate and PP.
    Type: Article , PeerReviewed
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  • 2
    Publication Date: 2019-09-23
    Description: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere 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 a 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, consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil-fuel combustion and cement production (EFF) are based on energy statistics, 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 for the first time in this budget 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 forced by observed climate, CO2 and land cover change (some including nitrogen–carbon interactions). 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 (2003–2012), EFF was 8.6 ± 0.4 GtC yr−1, ELUC 0.9 ± 0.5 GtC yr−1, GATM 4.3 ± 0.1 GtC yr−1, SOCEAN 2.5 ± 0.5 GtC yr−1, and SLAND 2.8 ± 0.8 GtC yr−1. For year 2012 alone, EFF grew to 9.7 ± 0.5 GtC yr−1, 2.2% above 2011, reflecting a continued growing trend in these emissions, GATM was 5.1 ± 0.2 GtC yr−1, SOCEAN was 2.9 ± 0.5 GtC yr−1, and assuming an ELUC of 1.0 ± 0.5 GtC yr−1 (based on the 2001–2010 average), SLAND was 2.7 ± 0.9 GtC yr−1. GATM was high in 2012 compared to the 2003–2012 average, almost entirely reflecting the high EFF. The global atmospheric CO2 concentration reached 392.52 ± 0.10 ppm averaged over 2012. We estimate that EFF will increase by 2.1% (1.1–3.1%) to 9.9 ± 0.5 GtC in 2013, 61% above emissions in 1990, based on projections of world gross domestic product and recent changes in the carbon intensity of the economy. With this projection, cumulative emissions of CO2 will reach about 535 ± 55 GtC for 1870–2013, about 70% from EFF (390 ± 20 GtC) and 30% from ELUC (145 ± 50 GtC). This paper also documents any changes in the methods and data sets used in this new carbon budget from previous budgets (Le Quéré et al., 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2013_V2.3).
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
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  • 3
    Publication Date: 2021-04-21
    Description: The global ocean is a significant sink for anthropogenic carbon (C-ant), 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 C-ant 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 C-ant 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 C-ant 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 C-ant with numerical ocean circulation models. Such methods are especially useful for estimating the air-sea flux and interior transport of C-ant, 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 C-ant. Our review also highlights the importance of repeat measurements of hydro-graphic and biogeochemical parameters to estimate the storage of C-ant on decadal timescales in the presence of the variability in circulation that is neglected by other approaches. Data-based C-ant 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 C-ant 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.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
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  • 4
    Publication Date: 2020-05-13
    Description: Marine N2 fixing microorganisms, termed diazotrophs, are a key functional group in marine pelagic ecosystems. The biological fixation of dinitrogen (N2) to bioavailable nitrogen provides an important new source of nitrogen for pelagic marine ecosystems and influences primary productivity and organic matter export to the deep ocean. As one of a series of efforts to collect biomass and rates specific to different phytoplankton functional groups, we have constructed a database on diazotrophic organisms in the global pelagic upper ocean by compiling about 12 000 direct field measurements of cyanobacterial diazotroph abundances (based on microscopic cell counts or qPCR assays targeting the nifH genes) and N2 fixation rates. Biomass conversion factors are estimated based on cell sizes to convert abundance data to diazotrophic biomass. The database is limited spatially, lacking large regions of the ocean especially in the Indian Ocean. The data are approximately log-normal distributed, and large variances exist in most sub-databases with non-zero values differing 5 to 8 orders of magnitude. Reporting the geometric mean and the range of one geometric standard error below and above the geometric mean, the pelagic N2 fixation rate in the global ocean is estimated to be 62 (52–73) Tg N yr−1 and the pelagic diazotrophic biomass in the global ocean is estimated to be 2.1 (1.4–3.1) Tg C from cell counts and to 89 (43–150) Tg C from nifH-based abundances. Reporting the arithmetic mean and one standard error instead, these three global estimates are 140 ± 9.2 Tg N yr−1, 18 ± 1.8 Tg C and 590 ± 70 Tg C, respectively. Uncertainties related to biomass conversion factors can change the estimate of geometric mean pelagic diazotrophic biomass in the global ocean by about ±70%. It was recently established that the most commonly applied method used to measure N2 fixation has underestimated the true rates. As a result, one can expect that future rate measurements will shift the mean N2 fixation rate upward and may result in significantly higher estimates for the global N2 fixation. The evolving database can nevertheless be used to study spatial and temporal distributions and variations of marine N2 fixation, to validate geochemical estimates and to parameterize and validate biogeochemical models, keeping in mind that future rate measurements may rise in the future. The database is stored in PANGAEA (doi:10.1594/PANGAEA.774851).
    Type: Article , PeerReviewed
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