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: We estimated monthly air–sea CO2 fluxes in the Arctic Ocean and its adjacent seas north of 60° N from 1997 to 2014, after mapping partial pressure of CO2 in the surface water (pCO2w) using a self-organizing map (SOM) technique incorporating chlorophyll-a concentration (Chl-a), sea surface temperature, sea surface salinity, sea ice concentration, atmospheric CO2 mixing ratio, and geographical position. The overall relationship between pCO2w and Chl-a is negative in most regions when Chl-a ≤ 1 mg m−3, whereas there is no significant relationship when Chl-a 〉 1 mg m−3. In the Kara Sea and the East Siberian Sea and the Bering Strait, however, the relationship is typically positive in summer. The addition of Chl-a as a parameter in the SOM process enabled us to improve the estimate of pCO2w via better representation of its decline in spring, which resulted from biologically mediated pCO2w reduction. Mainly as a result of the inclusion of Chl-a, the uncertainty in the CO2 flux estimate was reduced, and a net annual Arctic Ocean CO2 uptake of 180 ± 130 TgC y−1 was determined to be significant.

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 Surface Ocean CO2 Atlas (SOCAT) is a synthesis of quality-controlled fCO2 (fugacity of carbon dioxide) values for the global surface oceans and coastal seas with regular updates. Version 3 of SOCAT has 14.5 million fCO2 values from 3646 data sets covering the years 1957 to 2014. This latest version has an additional 4.4 million fCO2 values relative to version 2 and extends the record from 2011 to 2014. Version 3 also significantly increases the data availability for 2005 to 2013. SOCAT has an average of approximately 1.2 million surface water fCO2 values per year for the years 2006 to 2012. Quality and documentation of the data has improved. A new feature is the data set quality control (QC) flag of E for data from alternative sensors and platforms. The accuracy of surface water fCO2 has been defined for all data set QC flags. Automated range checking has been carried out for all data sets during their upload into SOCAT. The upgrade of the interactive Data Set Viewer (previously known as the Cruise Data Viewer) allows better interrogation of the SOCAT data collection and rapid creation of high-quality figures for scientific presentations. Automated data upload has been launched for version 4 and will enable more frequent SOCAT releases in the future. High-profile scientific applications of SOCAT include quantification of the ocean sink for atmospheric carbon dioxide and its long-term variation, detection of ocean acidification, as well as evaluation of coupled-climate and ocean-only biogeochemical models. Users of SOCAT data products are urged to acknowledge the contribution of data providers, as stated in the SOCAT Fair Data Use Statement. This ESSD (Earth System Science Data) "Living Data" publication documents the methods and data sets used for the assembly of this new version of the SOCAT data collection and compares these with those used for earlier versions of the data collection (Pfeil et al., 2013; Sabine et al., 2013; Bakker et al., 2014).

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: 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: No abstract available.

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/).

Description: The Surface Ocean CO2 Atlas (SOCAT) is a synthesis of quality-controlled fCO2 (fugacity of carbon dioxide) values for the global surface oceans and coastal seas with regular updates. Version 3 of SOCAT has 14.7 million fCO2 values from 3646 data sets covering the years 1957 to 2014. This latest version has an additional 4.6 million fCO2 values relative to version 2 and extends the record from 2011 to 2014. Version 3 also significantly increases the data availability for 2005 to 2013. SOCAT has an average of approximately 1.2 million surface water fCO2 values per year for the years 2006 to 2012. Quality and documentation of the data has improved. A new feature is the data set quality control (QC) flag of E for data from alternative sensors and platforms. The accuracy of surface water fCO2 has been defined for all data set QC flags. Automated range checking has been carried out for all data sets during their upload into SOCAT. The upgrade of the interactive Data Set Viewer (previously known as the Cruise Data Viewer) allows better interrogation of the SOCAT data collection and rapid creation of high-quality figures for scientific presentations. Automated data upload has been launched for version 4 and will enable more frequent SOCAT releases in the future. High-profile scientific applications of SOCAT include quantification of the ocean sink for atmospheric carbon dioxide and its long-term variation, detection of ocean acidification, as well as evaluation of coupled-climate and ocean-only biogeochemical models. Users of SOCAT data products are urged to acknowledge the contribution of data providers, as stated in the SOCAT Fair Data Use Statement. This ESSD (Earth System Science Data) "living data" publication documents the methods and data sets used for the assembly of this new version of the SOCAT data collection and compares these with those used for earlier versions of the data collection (Pfeil et al., 2013; Sabine et al., 2013; Bakker et al., 2014). Individual data set files, included in the synthesis product, can be downloaded here: doi:10.1594/PANGAEA.849770. The gridded products are available here: doi:10.3334/CDIAC/OTG.SOCAT_V3_GRID.