scholarly journals A global monthly climatology of oceanic total dissolved inorganic carbon: a neural network approach

2020 ◽  
Vol 12 (3) ◽  
pp. 1725-1743
Author(s):  
Daniel Broullón ◽  
Fiz F. Pérez ◽  
Antón Velo ◽  
Mario Hoppema ◽  
Are Olsen ◽  
...  
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Carbon Cycle ◽  
Inorganic Carbon ◽  
Dissolved Inorganic Carbon ◽  
World Ocean ◽  
National Research Council ◽  
Total Alkalinity ◽  
Global Ocean ◽  
Total Dissolved Inorganic Carbon

Abstract. 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).

scholarly journals A global monthly climatology of oceanic total dissolved inorganic carbon: a neural network approach

2020 ◽  
Author(s):  
Daniel Broullón ◽  
Fiz F. Pérez ◽  
Antón Velo Lanchas ◽  
Mario Hoppema ◽  
Are Olsen ◽  
...  
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Carbon Cycle ◽  
Inorganic Carbon ◽  
Dissolved Inorganic Carbon ◽  
World Ocean ◽  
National Research Council ◽  
Total Alkalinity ◽  
Global Ocean ◽  
Total Dissolved Inorganic Carbon

Abstract. Anthropogenic emissions of CO2 to the atmosphere have modified the carbon cycle for more than two 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-squared 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 in capturing the monthly variability of TCO2 was testified through the good reproduction of the seasonal cycle in ten time-series stations spread over different regions of the ocean (RMSE: 3.6 to 13.1 µmol kg−1). The climatology was obtained by passing through NNGv2LDEO the monthly climatological fields of temperature, salinity and oxygen from World Ocean Atlas 2013, and phosphate, nitrate and silicate computed from a neural network fed with the previous fields. The resolution is 1º x 1º in the horizontal, 102 depth levels (0–5500 m) and monthly (0–1500 m) to annual (1550–5500 m), and it is centered in 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., 2016). Our TCO2 climatology is distributed through the data repository of the Spanish National Research Council (CSIC; http://dx.doi.org/10.20350/digitalCSIC/10551, Broullón et al., 2020).

scholarly journals A global monthly climatology of total alkalinity: a neural network approach

2018 ◽  
Author(s):  
Daniel Broullón ◽  
Fiz F. Pérez ◽  
Antón Velo ◽  
Mario Hoppema ◽  
Are Olsen ◽  
...  
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Carbon Cycle ◽  
Ocean Acidification ◽  
World Ocean ◽  
National Research Council ◽  
Total Alkalinity ◽  
Global Ocean ◽  
Data Repository ◽  
Spatiotemporal Resolution

Abstract. Global climatologies of the seawater CO2 chemistry variables are necessary to assess the marine carbon cycle in depth. The seasonal variability should be adequately captured in them to properly address issues such as ocean acidification. Total alkalinity (AT) is one variable of the seawater CO2 chemistry system involved in ocean acidification and frequently measured during campaigns assessing the marine carbon cycle. We took advantage of the data product Global Ocean Data Analysis Project version 2 (GLODAPv2) to extract the relations between the drivers of the AT variability and this variable using a neural network to generate a monthly climatology. 99% of the GLODAPv2 dataset used was modelled by the network with a root-mean-squared error (RMSE) of 5.1 µmol kg-1. The validation carried out using independent datasets revealed the good generalization of the network. Five ocean time-series stations used as an independent test showed an acceptable RMSE in the range of 3.1-6.2 µmol kg-1. The successful modeling of the monthly variability of AT in the time-series makes our network a good candidate to generate a monthly climatology. It was obtained passing the climatologies of the World Ocean Atlas 2013 (WOA13) through the network. The spatiotemporal resolution of the climatology is determined by the one of WOA13: 1ºx1º in the horizontal, 102 depth levels (0-5500m) in the vertical, and 12 months. We offer the product as a service to the scientific community at the data repository of the Spanish National Research Council (CSIC; doi: http://dx.doi.org/10.20350/digitalCSIC/8564) with the purpose to contribute to a continuous improvement of the understanding of the global carbon cycle.

scholarly journals A global monthly climatology of total alkalinity: a neural network approach

2019 ◽  
Vol 11 (3) ◽  
pp. 1109-1127 ◽  
Author(s):  
Daniel Broullón ◽  
Fiz F. Pérez ◽  
Antón Velo ◽  
Mario Hoppema ◽  
Are Olsen ◽  
...  
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Carbon Cycle ◽  
Ocean Acidification ◽  
World Ocean ◽  
National Research Council ◽  
Total Alkalinity ◽  
Global Ocean ◽  
Data Repository ◽  
Spatiotemporal Resolution

Abstract. Global climatologies of the seawater CO2 chemistry variables are necessary to assess the marine carbon cycle in depth. The climatologies should adequately capture seasonal variability to properly address ocean acidification and similar issues related to the carbon cycle. Total alkalinity (AT) is one variable of the seawater CO2 chemistry system involved in ocean acidification and frequently measured. We used the Global Ocean Data Analysis Project version 2.2019 (GLODAPv2) to extract relationships among the drivers of the AT variability and AT concentration using a neural network (NNGv2) to generate a monthly climatology. The GLODAPv2 quality-controlled dataset used was modeled by the NNGv2 with a root-mean-squared error (RMSE) of 5.3 µmol kg−1. Validation tests with independent datasets revealed the good generalization of the network. Data from five ocean time-series stations showed an acceptable RMSE range of 3–6.2 µmol kg−1. Successful modeling of the monthly AT variability in the time series suggests that the NNGv2 is a good candidate to generate a monthly climatology. The climatological fields of AT were obtained passing through the NNGv2 the World Ocean Atlas 2013 (WOA13) monthly climatologies of temperature, salinity, and oxygen and the computed climatologies of nutrients from the previous ones with a neural network. The spatiotemporal resolution is set by WOA13: 1∘ × 1∘ in the horizontal, 102 depth levels (0–5500 m) in the vertical and monthly (0–1500 m) to annual (1550–5500 m) temporal resolution. The product is distributed through the data repository of the Spanish National Research Council (CSIC; https://doi.org/10.20350/digitalCSIC/8644, Broullón et al., 2019).

scholarly journals The Global Ocean Data Analysis Project version 2 (GLODAPv2) – an internally consistent data product for the world ocean

2016 ◽  
Vol 8 (2) ◽  
pp. 297-323 ◽  
Author(s):  
Are Olsen ◽  
Robert M. Key ◽  
Steven van Heuven ◽  
Siv K. Lauvset ◽  
Anton Velo ◽  
...  
Keyword(s):  
Quality Control ◽  
Data Analysis ◽  
Inorganic Carbon ◽  
Dissolved Inorganic Carbon ◽  
World Ocean ◽  
Total Alkalinity ◽  
The Arctic ◽  
Global Ocean ◽  
Systematic Evaluation ◽  
Data Product

Abstract. 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.

scholarly journals Climatological variations of total alkalinity and total dissolved inorganic carbon in the Mediterranean Sea surface waters

2015 ◽  
Vol 6 (2) ◽  
pp. 789-800 ◽  
Author(s):  
E. Gemayel ◽  
A. E. R. Hassoun ◽  
M. A. Benallal ◽  
C. Goyet ◽  
P. Rivaro ◽  
...  
Keyword(s):  
Mediterranean Sea ◽  
Surface Waters ◽  
Inorganic Carbon ◽  
Dissolved Inorganic Carbon ◽  
World Ocean ◽  
Sea Surface ◽  
Total Alkalinity ◽  
Eastern Basin ◽  
Total Dissolved Inorganic Carbon ◽  
The Mediterranean

Abstract. A compilation of data from several cruises between 1998 and 2013 was used to derive polynomial fits that estimate total alkalinity (AT) and total dissolved inorganic carbon (CT) from measurements of salinity and temperature in the Mediterranean Sea surface waters. The optimal equations were chosen based on the 10-fold cross-validation results and revealed that second- and third-order polynomials fit the AT and CT data respectively. The AT surface fit yielded a root mean square error (RMSE) of ± 10.6 μmol kg−1, and salinity and temperature contribute to 96 % of the variability. Furthermore, we present the first annual mean CT parameterization for the Mediterranean Sea surface waters with a RMSE of ± 14.3 μmol kg−1. Excluding the marginal seas of the Adriatic and the Aegean, these equations can be used to estimate AT and CT in case of the lack of measurements. The identified empirical equations were applied on the 0.25° climatologies of temperature and salinity, available from the World Ocean Atlas 2013. The 7-year averages (2005–2012) showed that AT and CT have similar patterns with an increasing eastward gradient. The variability is influenced by the inflow of cold Atlantic waters through the Strait of Gibraltar and by the oligotrophic and thermohaline gradient that characterize the Mediterranean Sea. The summer–winter seasonality was also mapped and showed different patterns for AT and CT. During the winter, the AT and CT concentrations were higher in the western than in the eastern basin. The opposite was observed in the summer where the eastern basin was marked by higher AT and CT concentrations than in winter. The strong evaporation that takes place in this season along with the ultra-oligotrophy of the eastern basin determines the increase of both AT and CT concentrations.

scholarly journals Two decades of inorganic carbon dynamics along the West Antarctic Peninsula

2015 ◽  
Vol 12 (22) ◽  
pp. 6761-6779 ◽  
Author(s):  
C. Hauri ◽  
S. C. Doney ◽  
T. Takahashi ◽  
M. Erickson ◽  
G. Jiang ◽  
...  
Keyword(s):  
Antarctic Peninsula ◽  
Ocean Circulation ◽  
Inorganic Carbon ◽  
Dissolved Inorganic Carbon ◽  
World Ocean ◽  
Nutrient Utilization ◽  
Total Alkalinity ◽  
Data Set ◽  
Molar Ratios ◽  
Wide Range

Abstract. We present 20 years of seawater inorganic carbon measurements collected along the western shelf and slope of the Antarctic Peninsula. Water column observations from summertime cruises and seasonal surface underway pCO2 measurements provide unique insights into the spatial, seasonal, and interannual variability in this dynamic system. Discrete measurements from depths > 2000 m align well with World Ocean Circulation Experiment observations across the time series and underline the consistency of the data set. Surface total alkalinity and dissolved inorganic carbon data showed large spatial gradients, with a concomitant wide range of Ωarag (< 1 up to 3.9). This spatial variability was mainly driven by increasing influence of biological productivity towards the southern end of the sampling grid and meltwater input along the coast towards the northern end. Large inorganic carbon drawdown through biological production in summer caused high near-shore Ωarag despite glacial and sea-ice meltwater input. In support of previous studies, we observed Redfield behavior of regional C / N nutrient utilization, while the C / P (80.5 ± 2.5) and N / P (11.7 ± 0.3) molar ratios were significantly lower than the Redfield elemental stoichiometric values. Seasonal salinity-based predictions of Ωarag suggest that surface waters remained mostly supersaturated with regard to aragonite throughout the study. However, more than 20 % of the predictions for winters and springs between 1999 and 2013 resulted in Ωarag < 1.2. Such low levels of Ωarag may have implications for important organisms such as pteropods. Even though we did not detect any statistically significant long-term trends, the combination of on\\-going ocean acidification and freshwater input may soon induce more unfavorable conditions than the ecosystem experiences today.

scholarly journals What drives the latitudinal gradient in open-ocean surface dissolved inorganic carbon concentration?

2019 ◽  
Vol 16 (13) ◽  
pp. 2661-2681 ◽  
Author(s):  
Yingxu Wu ◽  
Mathis P. Hain ◽  
Matthew P. Humphreys ◽  
Sue Hartman ◽  
Toby Tyrrell
Keyword(s):  
Southern Ocean ◽  
High Latitude ◽  
Latitudinal Gradient ◽  
Inorganic Carbon ◽  
Dissolved Inorganic Carbon ◽  
Latitudinal Gradients ◽  
Total Alkalinity ◽  
Global Ocean ◽  
Low Latitude ◽  
Surface Ocean

Abstract. Previous work has not led to a clear understanding of the causes of spatial pattern in global surface ocean dissolved inorganic carbon (DIC), which generally increases polewards. Here, we revisit this question by investigating the drivers of observed latitudinal gradients in surface salinity-normalized DIC (nDIC) using the Global Ocean Data Analysis Project version 2 (GLODAPv2) database. We used the database to test three different hypotheses for the driver producing the observed increase in surface nDIC from low to high latitudes. These are (1) sea surface temperature, through its effect on the CO2 system equilibrium constants, (2) salinity-related total alkalinity (TA), and (3) high-latitude upwelling of DIC- and TA-rich deep waters. We find that temperature and upwelling are the two major drivers. TA effects generally oppose the observed gradient, except where higher values are introduced in upwelled waters. Temperature-driven effects explain the majority of the surface nDIC latitudinal gradient (182 of the 223 µmol kg−1 increase from the tropics to the high-latitude Southern Ocean). Upwelling, which has not previously been considered as a major driver, additionally drives a substantial latitudinal gradient. Its immediate impact, prior to any induced air–sea CO2 exchange, is to raise Southern Ocean nDIC by 220 µmol kg−1 above the average low-latitude value. However, this immediate effect is transitory. The long-term impact of upwelling (brought about by increasing TA), which would persist even if gas exchange were to return the surface ocean to the same CO2 as without upwelling, is to increase nDIC by 74 µmol kg−1 above the low-latitude average.

scholarly journals Measurements of total alkalinity and inorganic dissolved carbon in the Atlantic Ocean and adjacent Southern Ocean between 2008 and 2010

2013 ◽  
Vol 6 (2) ◽  
pp. 621-639
Author(s):  
U. Schuster ◽  
A. J. Watson ◽  
D. C. E. Bakker ◽  
A. M. de Boer ◽  
E. M. Jones ◽  
...  
Keyword(s):  
Quality Control ◽  
Atlantic Ocean ◽  
Southern Ocean ◽  
Inorganic Carbon ◽  
Dissolved Inorganic Carbon ◽  
Drake Passage ◽  
Total Alkalinity ◽  
Global Ocean ◽  
Atlantic Sector ◽  
Dissolved Carbon

Abstract. Water column dissolved inorganic carbon and total alkalinity were measured during five hydrographic sections in the Atlantic Ocean and Drake Passage. The work was funded through the Strategic Funding Initiative of the UK's Oceans2025 programme, which ran from 2007 to 2012. The aims of this programme were to establish the regional budgets of natural and anthropogenic carbon in the North Atlantic, the South Atlantic, and the Atlantic sector of the Southern Ocean, as well as the rates of change of these budgets. This paper describes the dissolved inorganic carbon and total alkalinity data collected along east-west sections at 55–60° N (Arctic Gateway), 24.5° N, and 24° S in the Atlantic and across two Drake Passage sections. Other hydrographic and biogeochemical parameters were measured during these sections, yet are not covered in this paper. Over 95% of samples taken during the 24.5° N, 24° S, and the Drake Passage sections were analysed onboard and subjected to a 1st level quality control addressing technical and analytical issues. Samples taken during Arctic Gateway were analysed and subjected to quality control back in the laboratory. Complete post-cruise 2nd level quality control was performed using cross-over analysis with historical data in the vicinity of measurements, and data are available through the Carbon Dioxide Information Analysis Center (CDIAC) and are included in the Global Ocean Data Analyses Project, version 2 (GLODAP 2).

scholarly journals A new global interior ocean mapped climatology: the 1° × 1° GLODAP version 2

2016 ◽  
Author(s):  
Siv K. Lauvset ◽  
Robert M. Key ◽  
Are Olsen ◽  
Steven van Heuven ◽  
Anton Velo ◽  
...  
Keyword(s):  
Inorganic Carbon ◽  
Dissolved Inorganic Carbon ◽  
Mapping Method ◽  
Total Alkalinity ◽  
The Arctic ◽  
Global Ocean ◽  
Information Analysis ◽  
Phosphate Silicate ◽  
Analysis Center ◽  
Standard Pressure

Abstract. 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/).

scholarly journals Total dissolved inorganic carbon and physicochemical characteristics of surface microlayer and upper mixed layer water from Lagos Lagoon, Nigeria

2015 ◽  
Vol 17 (2) ◽  
pp. 334-343 ◽  
Keyword(s):  
Mixed Layer ◽  
Coastal Lagoon ◽  
Water Samples ◽  
Inorganic Carbon ◽  
Dissolved Inorganic Carbon ◽  
Physicochemical Characteristics ◽  
Total Alkalinity ◽  
Surface Microlayer ◽  
Total Dissolved Inorganic Carbon ◽  
Upper Mixed Layer

<p>The carbonate and physicochemical characteristics of the surface microlayer and upper mixed layer of a tropical coastal lagoon were investigated. Data on the physicochemical parameters generally indicated a moderately polluted ecosystem. The influence of the ocean environment over the Lagoon system was evident by elevated salinity levels. The mean total dissolved inorganic carbon (DIC) for the surface microlayer (SML) and subsurface water (SSW) samples were 2626.6 and 2550.9 &micro;mol/kg SW respectively. The dominant inorganic form of DIC in the lagoon water samples was HCO<sub>3</sub><sup>-</sup> with a calculated average abundance &gt;95.4% in the SML and &gt;94% in the SSW. The bicarbonate species derived abundance varied between 1.6% (SML) and 8.4% (SSW), while the aqueous carbon dioxide were generally low in percentages ranging from 0.4 in SSW to 1.5 in SML water samples. In general, the occurrence of the carbonate species was in the order HCO<sub>3</sub><sup>-</sup> &gt; CO<sub>3</sub><sup>2-</sup> &gt; CO<sub>2</sub>. Results showed that total alkalinity (A<sub>T</sub>) was relatively greater than the DIC. Long term monitoring studies in the coastal lagoon systems is needed to understand the coastal water chemistry and pollution status.</p>

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