ALBERT

Description: Anthropogenic emissions of CO2 to the atmosphere have modified the carbon cycle for more than 2 centuries. As the ocean stores most of the carbon on our planet, there is an important task in unraveling the natural and anthropogenic processes that drive the carbon cycle at different spatial and temporal scales. We contribute to this by designing a global monthly climatology of total dissolved inorganic carbon (TCO2), which offers a robust basis in carbon cycle modeling but also for other studies related to this cycle. A feedforward neural network (dubbed NNGv2LDEO) was configured to extract from the Global Ocean Data Analysis Project version 2.2019 (GLODAPv2.2019) and the Lamont–Doherty Earth Observatory (LDEO) datasets the relations between TCO2 and a set of variables related to the former's variability. The global root mean square error (RMSE) of mapping TCO2 is relatively low for the two datasets (GLODAPv2.2019: 7.2 µmol kg−1; LDEO: 11.4 µmol kg−1) and also for independent data, suggesting that the network does not overfit possible errors in data. The ability of NNGv2LDEO to capture the monthly variability of TCO2 was testified through the good reproduction of the seasonal cycle in 10 time series stations spread over different regions of the ocean (RMSE: 3.6 to 13.2 µmol kg−1). The climatology was obtained by passing through NNGv2LDEO the monthly climatological fields of temperature, salinity, and oxygen from the World Ocean Atlas 2013 and phosphate, nitrate, and silicate computed from a neural network fed with the previous fields. The resolution is 1∘×1∘ in the horizontal, 102 depth levels (0–5500 m), and monthly (0–1500 m) to annual (1550–5500 m) temporal resolution, and it is centered around the year 1995. The uncertainty of the climatology is low when compared with climatological values derived from measured TCO2 in the largest time series stations. Furthermore, a computed climatology of partial pressure of CO2 (pCO2) from a previous climatology of total alkalinity and the present one of TCO2 supports the robustness of this product through the good correlation with a widely used pCO2 climatology (Landschützer et al., 2017). Our TCO2 climatology is distributed through the data repository of the Spanish National Research Council (CSIC; https://doi.org/10.20350/digitalCSIC/10551, Broullón et al., 2020).

Description: A high-resolution dynamical model (Nucleus for European Modelling of the Ocean, Mediterranean configuration – NEMO-MED12) was used to give the first simulation of the distribution of radiocarbon (14C) across the whole Mediterranean Sea. The simulation provides a descriptive overview of both the natural pre-bomb 14C and the entire anthropogenic radiocarbon transient generated by the atmospheric bomb tests performed in the 1950s and early 1960s. The simulation was run until 2011 to give the post-bomb distribution. The results are compared to available in situ measurements and proxy-based reconstructions. The radiocarbon simulation allows an additional and independent test of the dynamical model, NEMO-MED12, and its performance to produce the thermohaline circulation and deep-water ventilation. The model produces a generally realistic distribution of radiocarbon when compared with available in situ data. The results demonstrate the major influence of the flux of Atlantic water through the Strait of Gibraltar on the inter-basin natural radiocarbon distribution and characterize the ventilation of intermediate and deep water especially through the propagation of the anthropogenic radiocarbon signal. We explored the impact of the interannual variability on the radiocarbon distribution during the Eastern Mediterranean Transient (EMT) event. It reveals a significant increase in 14C concentration (by more than 60 ‰) in the Aegean deep water and at an intermediate level (value up to 10 ‰) in the western basin. The model shows that the EMT makes a major contribution to the accumulation of radiocarbon in the eastern Mediterranean deep waters.

Description: Extensive biogeochemical transformation of organic matter takes place in the shallow continental shelf seas of Siberia. This, in combination with brine production from sea-ice formation, results in cold bottom waters with relatively high salinity and nutrient concentrations, as well as low oxygen and pH levels. Data from the SWERUS-C3 expedition with icebreaker Oden, from July to September 2014, show the distribution of such nutrient-rich, cold bottom waters along the continental margin from about 140 to 180° E. The water with maximum nutrient concentration, classically named the upper halocline, is absent over the Lomonosov Ridge at 140° E, while it appears in the Makarov Basin at 150° E and intensifies further eastwards. At the intercept between the Mendeleev Ridge and the East Siberian continental shelf slope, the nutrient maximum is still intense, but distributed across a larger depth interval. The nutrient-rich water is found here at salinities of up to ∼ 34.5, i.e. in the water classically named lower halocline. East of 170° E transient tracers show significantly less ventilated waters below about 150 m water depth. This likely results from a local isolation of waters over the Chukchi Abyssal Plain as the boundary current from the west is steered away from this area by the bathymetry of the Mendeleev Ridge. The water with salinities of ∼ 34.5 has high nutrients and low oxygen concentrations as well as low pH, typically indicating decay of organic matter. A deficit in nitrate relative to phosphate suggests that this process partly occurs under hypoxia. We conclude that the high nutrient water with salinity ∼ 34.5 are formed on the shelf slope in the Mendeleev Ridge region from interior basin water that is trapped for enough time to attain its signature through interaction with the sediment.

Description: The distribution of the main water masses in the Atlantic Ocean are investigated with the Optimal Multi-Parameter (OMP) method. The properties of the main water masses in the Atlantic Ocean are described in a companion article; here these definitions are used to map out the general distribution of those water masses. Six key properties, including conservative (potential temperature and salinity) and non-conservative (oxygen, silicate, phosphate and nitrate), are incorporated into the OMP analysis to determine the contribution of the water masses in the Atlantic Ocean based on the GLODAP v2 observational data. To facilitate the analysis the Atlantic Ocean is divided into four vertical layers based on potential density. Due to the high seasonal variability in the mixed layer, this layer is excluded from the analysis. Central waters are the main water masses in the upper/central layer, generally featuring high potential temperature and salinity and low nutrient concentrations and are easily distinguished from the intermediate water masses. In the intermediate layer, the Antarctic Intermediate Water (AAIW) from the south can be detected to ~30 °N, whereas the Subarctic Intermediate Water (SAIW), having similarly low salinity to the AAIW flows from the north. Mediterranean Overflow Water (MOW) flows from the Strait of Gibraltar as a high salinity water. NADW dominates the deep and overflow layer both in the North and South Atlantic. In the bottom layer, AABW is the only natural water mass with high silicate signature spreading from the Antarctic to the North Atlantic. Due to the change of water mass properties, in this work we renamed to North East Antarctic Bottom Water NEABW north of the equator. Similarly, the distributions of Labrador Sea Water (LSW), Iceland Scotland Overflow Water (ISOW), and Denmark Strait Overflow Water (DSOW) forms upper and lower portion of NADW, respectively roughly south of the Grand Banks between ~50 and 66 °N. In the far south the distributions of Circumpolar Deep Water (CDW) and Weddell Sea Bottom Water (WSBW) are of significance to understand the formation of the AABW.

Description: The storage of anthropogenic carbon in the ocean's interior is an important process which modulates the increasing carbon dioxide concentrations in the atmosphere. The polar regions are expected to be net sinks for anthropogenic carbon. Transport estimates of dissolved inorganic carbon and the anthropogenic offset can thus provide information about the magnitude of the corresponding storage processes. Here we present a transient tracer, dissolved inorganic carbon (DIC) and total alkalinity (TA) data set along 78°50′ N sampled in the Fram Strait in 2012. A theory on tracer relationships is introduced, which allows for an application of the inverse-Gaussian–transit-time distribution (IG-TTD) at high latitudes and the estimation of anthropogenic carbon concentrations. Mean current velocity measurements along the same section from 2002–2010 were used to estimate the net flux of DIC and anthropogenic carbon by the boundary currents above 840 m through the Fram Strait. The new theory explains the differences between the theoretical (IG-TTD-based) tracer age relationship and the specific tracer age relationship of the field data, by saturation effects during water mass formation and/or the deliberate release experiment of SF6 in the Greenland Sea in 1996, rather than by different mixing or ventilation processes. Based on this assumption, a maximum SF6 excess of 0.5–0.8 fmol kg−1 was determined in the Fram Strait at intermediate depths (500–1600 m). The anthropogenic carbon concentrations are 50–55 µmol kg−1 in the Atlantic Water/Recirculating Atlantic Water, 40–45 µmol kg−1 in the Polar Surface Water/warm Polar Surface Water and between 10 and 35 µmol kg−1 in the deeper water layers, with lowest concentrations in the bottom layer. The net fluxes through the Fram Strait indicate a net outflow of  ∼  0.4 DIC and  ∼  0.01 PgC yr−1 anthropogenic carbon from the Arctic Ocean into the North Atlantic, albeit with high uncertainties.

Description: The stable carbon isotope composition of dissolved inorganic carbon (δ13C-DIC) can be used to quantify fluxes within the carbon system. For example, knowing the δ13C signature of the inorganic carbon pool can help in describing the amount of anthropogenic carbon in the water column. The measurements can also be used for evaluating modeled carbon fluxes, for making basin-wide estimates of anthropogenic carbon, and for studying seasonal and interannual variability or decadal trends in interior ocean biogeochemistry. For all these purposes, it is not only important to have a sufficient amount of data, but these data must also be internally consistent and of high quality. In this study, we present a δ13C-DIC dataset for the North Atlantic which has undergone secondary quality control. The data originate from oceanographic research cruises between 1981 and 2014. During a primary quality control step based on simple range tests, obviously bad data were flagged. In a second quality control step, biases between measurements from different cruises were quantified through a crossover analysis using nearby data of the respective cruises, and values of biased cruises were adjusted in the data product. The crossover analysis was possible for 24 of the 32 cruises in our dataset, and adjustments were applied to 11 cruises. The internal accuracy of this dataset is 0.017 ‰. The dataset is available via the Carbon Dioxide Information Analysis Center (CDIAC) at http://cdiac.ornl.gov/oceans/ndp_096/NAC13v1.html, doi:10.3334/CDIAC/OTG.NAC13v1.

Description: We present a mapped climatology (GLODAPv2.2016b) of ocean biogeochemical variables based on the new GLODAP version 2 data product (Olsen et al., 2016; Key et al., 2015), which covers all ocean basins over the years 1972 to 2013. The quality-controlled and internally consistent GLODAPv2 was used to create global 1°  ×  1° mapped climatologies of salinity, temperature, oxygen, nitrate, phosphate, silicate, total dissolved inorganic carbon (TCO2), total alkalinity (TAlk), pH, and CaCO3 saturation states using the Data-Interpolating Variational Analysis (DIVA) mapping method. Improving on maps based on an earlier but similar dataset, GLODAPv1.1, this climatology also covers the Arctic Ocean. Climatologies were created for 33 standard depth surfaces. The conceivably confounding temporal trends in TCO2 and pH due to anthropogenic influence were removed prior to mapping by normalizing these data to the year 2002 using first-order calculations of anthropogenic carbon accumulation rates. We additionally provide maps of accumulated anthropogenic carbon in the year 2002 and of preindustrial TCO2. For all parameters, all data from the full 1972–2013 period were used, including data that did not receive full secondary quality control. The GLODAPv2.2016b global 1°  ×  1° mapped climatologies, including error fields and ancillary information, are available at the GLODAPv2 web page at the Carbon Dioxide Information Analysis Center (CDIAC; doi:10.3334/CDIAC/OTG.NDP093_GLODAPv2).

Description: Version 2 of the Global Ocean Data Analysis Project (GLODAPv2) data product is composed of data from 724 scientific cruises covering the global ocean. It includes data assembled during the previous efforts GLODAPv1.1 (Global Ocean Data Analysis Project version 1.1) in 2004, CARINA (CARbon IN the Atlantic) in 2009/2010, and PACIFICA (PACIFic ocean Interior CArbon) in 2013, as well as data from an additional 168 cruises. Data for 12 core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, CFC-11, CFC-12, CFC-113, and CCl4) have been subjected to extensive quality control, including systematic evaluation of bias. The data are available in two formats: (i) as submitted but updated to WOCE exchange format and (ii) as a merged and internally consistent data product. In the latter, adjustments have been applied to remove significant biases, respecting occurrences of any known or likely time trends or variations. Adjustments applied by previous efforts were re-evaluated. Hence, GLODAPv2 is not a simple merging of previous products with some new data added but a unique, internally consistent data product. This compiled and adjusted data product is believed to be consistent to better than 0.005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, 4 µmol kg−1 in dissolved inorganic carbon, 6 µmol kg−1 in total alkalinity, 0.005 in pH, and 5 % for the halogenated transient tracers.The original data and their documentation and doi codes are available at the Carbon Dioxide Information Analysis Center (http://cdiac.ornl.gov/oceans/GLODAPv2/). This site also provides access to the calibrated data product, which is provided as a single global file or four regional ones – the Arctic, Atlantic, Indian, and Pacific oceans – under the doi:10.3334/CDIAC/OTG.NDP093_GLODAPv2. The product files also include significant ancillary and approximated data. These were obtained by interpolation of, or calculation from, measured data. This paper documents the GLODAPv2 methods and products and includes a broad overview of the secondary quality control results. The magnitude of and reasoning behind each adjustment is available on a per-cruise and per-variable basis in the online Adjustment Table.

Description: The stable carbon isotope composition of dissolved inorganic carbon (δ13C-DIC) can be used to quantify fluxes within the carbon system. For example, knowing the δ13C-DIC signature of the inorganic carbon pool can help to describe the exchange between ocean and atmosphere as well as the amount of anthropogenic carbon in the water column. The measurements can also be used for evaluating modeled carbon fluxes, for making basin wide estimates, studying seasonal and interannual variability or decadal trends in interior ocean biogeochemistry. For all these purposes, it is not only important to have a sufficient amount of data, but these data must also be internally consistent and of high quality. In this study, we present a δ13C-DIC dataset for the North Atlantic, which has undergone secondary quality control. The data originate from oceanographic research cruises between 1981 and 2012. During a primary quality control step based on simple range tests obviously bad data were flagged. In a second quality control step, biases between measurements from different cruises were quantified through a crossover analysis using nearby data of the respective cruises and absolute values of biased cruises were adjusted in the data product. the crossover analysis was possible for 22 of the 29 cruises in our dataset and adjustments were applied to 10 of these. The internal accuracy of this dataset is 0.017 ‰. The dataset is available via CDIAC at http://cdiac.ornl.gov/oceans/ndp_096/NAC13v1.html, doi:10.3334/CDIAC/OTG.NAC13v1.

Description: We here present the new GLODAP version 2 (GLODAPv2) mapped climatology, which is based on data from all ocean basins up to and including 2013. In contrast to its predecessor, GLODAPv1.1, this climatology also covers the Arctic Ocean and Mediterranean Sea. The quality controlled and internally consistent data product files of GLODAPv2 (Olsen et al., 2015; Key et al., 2015) were used to create global 1° × 1° mapped climatologies of total dissolved inorganic carbon, total alkalinity, and pH using the Data-Interpolating Variational Analysis (DIVA) mapping method. Climatologies were created for 33 standard pressure surfaces. To minimize the risk of translating temporal variability in the input data to spatial variations in the mapped climatologies, layers with pressures of 1000 dbar, or less, were mapped for two different time periods: 1986–1999 and 2000–2013, roughly corresponding to the "WOCE" and "CLIVAR" eras of global ocean surveys. All data from the 1972–2013 period were used in the mapping of pressures higher than 1000 dbar. In addition to the marine CO2 chemistry parameters listed above, nitrate, phosphate, silicate, oxygen, salinity and theta were also mapped using DIVA. For these parameters all data from the full 1972–2013 period were used on all 33 surfaces. The GLODAPv2 global 1° × 1° mapped climatologies, including error fields and ancillary information have been made available at the GLODAPv2 web page at the Carbon Dioxide Information Analysis Center (CDIAC, http://cdiac.ornl.gov/oceans/GLODAPv2/).