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Open accessJournal ArticleDOI: 10.5194/ESSD-13-777-2021

OceanSODA-ETHZ: a global gridded data set of the surface ocean carbonate system for seasonal to decadal studies of ocean acidification

02 Mar 2021-Earth System Science Data (Copernicus GmbH)-Vol. 13, Iss: 2, pp 777-808
Abstract: . Ocean acidification has profoundly altered the ocean's carbonate chemistry since preindustrial times, with potentially serious consequences for marine life. Yet, no long-term, global observation-based data set exists that allows us to study changes in ocean acidification for all carbonate system parameters over the last few decades. Here, we fill this gap and present a methodologically consistent global data set of all relevant surface ocean parameters, i.e., dissolved inorganic carbon (DIC), total alkalinity (TA), partial pressure of CO 2 ( pCO2 ), pH, and the saturation state with respect to mineral CaCO 3 ( Ω ) at a monthly resolution over the period 1985 through 2018 at a spatial resolution of 1 ∘ × 1 ∘ . This data set, named OceanSODA-ETHZ, was created by extrapolating in time and space the surface ocean observations of pCO2 (from the Surface Ocean CO 2 Atlas, SOCAT) and total alkalinity (TA; from the Global Ocean Data Analysis Project, GLODAP) using the newly developed Geospatial Random Cluster Ensemble Regression (GRaCER) method (code available at , Gregor , 2021 ). This method is based on a two-step (cluster-regression) approach but extends it by considering an ensemble of such cluster regressions, leading to improved robustness. Surface ocean DIC, pH, and Ω were then computed from the globally mapped pCO2 and TA using the thermodynamic equations of the carbonate system. For the open ocean, the cluster-regression method estimates pCO2 and TA with global near-zero biases and root mean squared errors of 12 µ atm and 13 µ mol kg −1 , respectively. Taking into account also the measurement and representation errors, the total uncertainty increases to 14 µ atm and 21 µ mol kg −1 , respectively. We assess the fidelity of the computed parameters by comparing them to direct observations from GLODAP, finding surface ocean pH and DIC global biases of near zero, as well as root mean squared errors of 0.023 and 16 µ mol kg −1 , respectively. These uncertainties are very comparable to those expected by propagating the total uncertainty from pCO2 and TA through the thermodynamic computations, indicating a robust and conservative assessment of the uncertainties. We illustrate the potential of this new data set by analyzing the climatological mean seasonal cycles of the different parameters of the surface ocean carbonate system, highlighting their commonalities and differences. Further, this data set provides a novel constraint on the global- and basin-scale trends in ocean acidification for all parameters. Concretely, we find for the period 1990 through 2018 global mean trends of 8.6 ± 0.1 µ mol kg −1 per decade for DIC, − 0.016 ± 0.000 per decade for pH, 16.5 ± 0.1 µ atm per decade for p CO 2 , and − 0.07 ± 0.00 per decade for Ω . The OceanSODA-ETHZ data can be downloaded from ( Gregor and Gruber , 2020 ) .

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8 results found

Open access
01 Jan 2007-
Abstract: Upwelling and ice cover exert an important control on dissolved inorganic carbon (DIC) and the fugacity of carbon dioxide (fCO2) in Weddell Sea surface waters in early spring. Ultimately these processes drive CO2 air-sea fluxes. Data were collected during cruise ANT XX/2 on RV Polarstern from December 2002 to January 2003. Deep CTD sections were made along 0°W, a northwest-southeast cross-section and along 20°E. Warm Circumpolar Deep Water (CDW, later WDW) enters the Weddell Gyre on the southeastern side of the gyre, roughly at 20-30°E. The upward movement of this water (upwelling) creates a source for CO2 in the Weddell Gyre. The effects of upwelling and entrainment on surface water characteristics were notably large in the southern Weddell Gyre, both at 0°W and 20°E, confirming observations by Gordon and Huber (1990). Entrainment during the winter months had increased the fCO2 difference across the sea surface, dfCO2(w-a), to 20-40 µatm and had preconditioned a CO2 source upon disappearance of the ice cover. Surface water fCO2 was close to the atmospheric value in areas with less upwelling. Once the ice had gone, biological activity locally reduced dfCO2(w-a) to -50 µatm, thus creating CO2 sinks. Despite the tendency of upwelling to cause CO2 oversaturation, the Weddell Gyre may thus still be a CO2 sink on an annual basis. It is probable that the CO2 source originating from upwelling of old, pre-industrial CDW is declining as atmospheric CO2 levels continue to increase (Hoppema, 2004). The relatively small residence time of surface waters in the gyre (2.5 years on average, considerably less in the southern part of the gyre Gordon and Huber, 1990) and prolonged ice cover (up to 8 months per year) partly explain the low anthropogenic CO2 content of bottom waters originating in the Weddell Gyre (Hoppema et al., 2001).

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Topics: Ocean gyre (71%), Weddell Sea Bottom Water (70%), Upwelling (57%) ... show more

4 Citations

Open accessJournal ArticleDOI: 10.1029/2020GL092263
Abstract: The decline in global emissions of carbon dioxide due to the COVID-19 pandemic provides a unique opportunity to investigate the sensitivity of the global carbon cycle and climate system to emissions reductions. Recent efforts to study the response to these emissions declines has not addressed their impact on the ocean, yet ocean carbon absorption is particularly susceptible to changing atmospheric carbon concentrations. Here, we use ensembles of simulations conducted with an Earth system model to explore the potential detection of COVID-related emissions reductions in the partial pressure difference in carbon dioxide between the surface ocean and overlying atmosphere (ΔpCO2), a quantity that is regularly measured. We find a unique fingerprint in global-scale ΔpCO2 that is attributable to COVID, though the fingerprint is difficult to detect in individual model realizations unless we force the model with a scenario that has four times the observed emissions reduction.

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Topics: Atmospheric carbon cycle (60%), Carbon cycle (56%), Carbon dioxide (51%)

2 Citations

Open accessJournal ArticleDOI: 10.5194/ESSD-13-4693-2021
Abstract: . Air–sea flux of carbon dioxide (CO 2 ) is a critical component of the global carbon cycle and the climate system with the ocean removing about a quarter of the CO 2 emitted into the atmosphere by human activities over the last decade. A common approach to estimate this net flux of CO 2 across the air–sea interface is the use of surface ocean CO 2 observations and the computation of the flux through a bulk parameterization approach. Yet, the details for how this is done in order to arrive at a global ocean CO 2 uptake estimate vary greatly, enhancing the spread of estimates. Here we introduce the ensemble data product, SeaFlux (Gregor and Fay, 2021, ​​​​​​​, , last access: 9 September 2021​​​​​​​); this resource enables users to harmonize an ensemble of products that interpolate surface ocean CO 2 observations to near-global coverage with a common methodology to fill in missing areas in the products. Further, the dataset provides the inputs to calculate fluxes in a consistent manner. Utilizing six global observation-based mapping products (CMEMS-FFNN, CSIR-ML6, JENA-MLS, JMA-MLR, MPI-SOMFFN, NIES-FNN), the SeaFlux ensemble approach adjusts for methodological inconsistencies in flux calculations. We address differences in spatial coverage of the surface ocean CO 2 between the mapping products, which ultimately yields an increase in CO 2 uptake of up to 17 % for some products. Fluxes are calculated using three wind products (CCMPv2, ERA5, and JRA55). Application of a scaled gas exchange coefficient has a greater impact on the resulting flux than solely the choice of wind product. With these adjustments, we present an ensemble of global surface ocean p CO 2 and air–sea carbon flux estimates. This work aims to support the community effort to perform model–data intercomparisons which will help to identify missing fluxes as we strive to close the global carbon budget.

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2 Citations


110 results found

Open accessJournal ArticleDOI: 10.1023/A:1010933404324
Leo Breiman1Institutions (1)
01 Oct 2001-
Abstract: Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error for forests converges a.s. to a limit as the number of trees in the forest becomes large. The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the correlation between them. Using a random selection of features to split each node yields error rates that compare favorably to Adaboost (Y. Freund & R. Schapire, Machine Learning: Proceedings of the Thirteenth International conference, aaa, 148–156), but are more robust with respect to noise. Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the splitting. Internal estimates are also used to measure variable importance. These ideas are also applicable to regression.

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Topics: Random forest (63%), Multivariate random variable (57%), Random subspace method (57%) ... show more

58,232 Citations

Open accessJournal Article
Abstract: Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a general-purpose high-level language. Emphasis is put on ease of use, performance, documentation, and API consistency. It has minimal dependencies and is distributed under the simplified BSD license, encouraging its use in both academic and commercial settings. Source code, binaries, and documentation can be downloaded from

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33,540 Citations

Open accessPosted Content
02 Jan 2012-arXiv: Learning
Abstract: Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a general-purpose high-level language. Emphasis is put on ease of use, performance, documentation, and API consistency. It has minimal dependencies and is distributed under the simplified BSD license, encouraging its use in both academic and commercial settings. Source code, binaries, and documentation can be downloaded from this http URL.

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28,898 Citations

Open accessJournal ArticleDOI: 10.1038/NATURE04095
29 Sep 2005-Nature
Abstract: Today's surface ocean is saturated with respect to calcium carbonate, but increasing atmospheric carbon dioxide concentrations are reducing ocean pH and carbonate ion concentrations, and thus the level of calcium carbonate saturation. Experimental evidence suggests that if these trends continue, key marine organisms—such as corals and some plankton—will have difficulty maintaining their external calcium carbonate skeletons. Here we use 13 models of the ocean–carbon cycle to assess calcium carbonate saturation under the IS92a 'business-as-usual' scenario for future emissions of anthropogenic carbon dioxide. In our projections, Southern Ocean surface waters will begin to become undersaturated with respect to aragonite, a metastable form of calcium carbonate, by the year 2050. By 2100, this undersaturation could extend throughout the entire Southern Ocean and into the subarctic Pacific Ocean. When live pteropods were exposed to our predicted level of undersaturation during a two-day shipboard experiment, their aragonite shells showed notable dissolution. Our findings indicate that conditions detrimental to high-latitude ecosystems could develop within decades, not centuries as suggested previously.

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Topics: Ocean acidification (68%), Aragonite (62%), Carbonate (61%) ... show more

3,898 Citations

Open accessJournal ArticleDOI: 10.1126/SCIENCE.1097403
Christopher L. Sabine1, Richard A. Feely1, Nicolas Gruber2, R.M. Key3  +11 moreInstitutions (10)
16 Jul 2004-Science
Abstract: Using inorganic carbon measurements from an international survey effort in the 1990s and a tracer-based separation technique, we estimate a global oceanic anthropogenic carbon dioxide (CO2) sink for the period from 1800 to 1994 of 118 19 petagrams of carbon. The oceanic sink accounts for48% of the total fossil-fuel and cement-manufacturing emissions, implying that the terrestrial biosphere was a net source of CO 2 to the atmosphere of about 39 28 petagrams of carbon for this period. The current fraction of total anthropogenic CO2 emissions stored in the ocean appears to be about one-third of the long-term potential. Since the beginning of the industrial period in the late 18th century, i.e., over the anthropocene (1), humankind has emitted large quantities of CO2 into the atmosphere, mainly as a result of fossil-fuel burning, but also because of land-use practices, e.g., deforestation (2). Measurements and reconstructions of the atmospheric CO2 history reveal, however, that less than half of these emissions remain in the atmosphere (3). The anthropogenic CO2 that did not accumulate in the atmosphere must have been taken up by the ocean, by the land biosphere, or by a combination of both. The relative roles of the ocean and land biosphere as sinks for anthropogenic CO2 over the anthropocene are currently not known. Although the anthropogenic CO2 budget for the past two decades, i.e., the 1980s and 1990s, has been investigated in detail (3), the estimates of the ocean sink have not been based on direct measurements of changes in the oceanic inventory of dissolved inorganic carbon (DIC). Recognizing the need to constrain the oceanic uptake, transport, and storage of anthropogenic CO 2 for the anthropocene and to provide a baseline for future estimates of oceanic CO 2 uptake, two international ocean research programs, the World Ocean Circulation Experiment (WOCE) and the Joint Global Ocean Flux Study (JGOFS), jointly conducted a comprehensive survey of inorganic carbon distributions in the global ocean in the 1990s (4). After completion of the U.S. field program in 1998, a 5-year effort was begun to compile and rigorously quality-control the U.S. and international data sets, in

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Topics: Ocean heat content (59%), World Ocean Circulation Experiment (59%), Ocean acidification (58%) ... show more

2,896 Citations

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