Why are surface ocean pH and CaCO 3 saturation state often out of phase in spatial patterns and seasonal cycles?

Author(s):  
Liang Xue ◽  
Wei‐Jun Cai ◽  
Li‐Qing Jiang ◽  
Qinsheng Wei
2008 ◽  
Vol 72 (1) ◽  
pp. 251-256 ◽  
Author(s):  
C. de Bodt ◽  
J. Harlay ◽  
L. Chou

AbstractCoccolithophores, among which Emiliania huxleyi is the most abundant and widespread species, are considered the most productive calcifying organism on earth. The export of organic carbon and calcification are the main drivers of the biological CO2 pump and are expected to change with oceanic acidification. Coccolithophores are further known to produce transparent exopolymer particles (TEP) that promote particle aggregation. As a result, the TEP and biogenic calcium carbonate (CaCO3) contribute to the export of carbon from the surface ocean to deep waters. In this context, we followed the development and the decline of E. huxleyi using batch experiments with monospecific cultures. We studied the link between different processes such as photosynthesis, calcification and the production of TEP. The onset of calcification was delayed in relation to photosynthesis. The timing and the general feature of the dynamics of calcification were closely related to the saturation state of seawater with respect to calcite, Ωcal. The production of TEP was enhanced after the decline of phytoplankton growth. After nutrient exhaustion, particulate organic carbon (POC) concentration increased linearly with increasing TEP concentration, suggesting that TEP contributes to the POC increase. The production of CaCO3 is also strongly correlated with that of TEP, suggesting that calcification may be considered as a source of TEP precursors.


2021 ◽  
Vol 13 (2) ◽  
pp. 777-808
Author(s):  
Luke Gregor ◽  
Nicolas Gruber

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 CO2 (pCO2), pH, and the saturation state with respect to mineral CaCO3 (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 CO2 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 https://doi.org/10.5281/zenodo.4455354, 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 µatm and 13 µmol kg−1, respectively. Taking into account also the measurement and representation errors, the total uncertainty increases to 14 µatm and 21 µmol 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 µmol 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 µmol kg−1 per decade for DIC, −0.016 ± 0.000 per decade for pH, 16.5 ± 0.1 µatm per decade for pCO2, and −0.07 ± 0.00 per decade for Ω. The OceanSODA-ETHZ data can be downloaded from https://doi.org/10.25921/m5wx-ja34 (Gregor and Gruber, 2020).


2015 ◽  
Vol 12 (21) ◽  
pp. 6321-6335 ◽  
Author(s):  
N. S. Lovenduski ◽  
M. C. Long ◽  
K. Lindsay

Abstract. We investigate variability in the surface ocean carbonate ion concentration ([CO32−]) on the basis of a~long control simulation with an Earth System Model. The simulation is run with a prescribed, pre-industrial atmospheric CO2 concentration for 1000 years, permitting investigation of natural [CO32−] variability on interannual to multi-decadal timescales. We find high interannual variability in surface [CO32−] in the tropical Pacific and at the boundaries between the subtropical and subpolar gyres in the Northern Hemisphere, and relatively low interannual variability in the centers of the subtropical gyres and in the Southern Ocean. Statistical analysis of modeled [CO32−] variance and autocorrelation suggests that significant anthropogenic trends in the saturation state of aragonite (Ωaragonite) are already or nearly detectable at the sustained, open-ocean time series sites, whereas several decades of observations are required to detect anthropogenic trends in Ωaragonite in the tropical Pacific, North Pacific, and North Atlantic. The detection timescale for anthropogenic trends in pH is shorter than that for Ωaragonite, due to smaller noise-to-signal ratios and lower autocorrelation in pH. In the tropical Pacific, the leading mode of surface [CO32−] variability is primarily driven by variations in the vertical advection of dissolved inorganic carbon (DIC) in association with El Niño–Southern Oscillation. In the North Pacific, surface [CO32−] variability is caused by circulation-driven variations in surface DIC and strongly correlated with the Pacific Decadal Oscillation, with peak spectral power at 20–30-year periods. North Atlantic [CO32−] variability is also driven by variations in surface DIC, and exhibits weak correlations with both the North Atlantic Oscillation and the Atlantic Multidecadal Oscillation. As the scientific community seeks to detect the anthropogenic influence on ocean carbonate chemistry, these results will aid the interpretation of trends calculated from spatially and temporally sparse observations.


2007 ◽  
Vol 4 (5) ◽  
pp. 3229-3265 ◽  
Author(s):  
H. S. Findlay ◽  
T. Tyrrell ◽  
R. G. J. Bellerby ◽  
A. Merico ◽  
I. Skjelvan

Abstract. A coupled carbon-ecosystem model is compared to recent data from Ocean Weather Ship M (66° N, 02° E) and used to investigate nutrient and carbon processes within the Norwegian Sea. Nitrate is consumed by phytoplankton in the surface layers over the summer; however the data show that silicate does not become rapidly limiting for diatoms, in contrast to the model prediction and in contrast to data from other temperate locations. The model estimates atmosphere-ocean CO2 flux to be 37 g C m−2 yr−1. A detailed comparison of the carbonate system at other ocean locations reveals that although coccolithophore blooms occur at OWS M, they are not as prevalent here as other areas. The seasonal cycles of calcite saturation state and [CO32−] are similar in the model and in data: values range from ~3 and ~120 μmol kg−1 respectively in winter, to ~4 and ~170 μmol kg−1 respectively in summer. The timing of coccolithophore blooms within the year therefore coincides with a time of high calcite saturation state, as predicted by previous modelling work.


2015 ◽  
Vol 12 (15) ◽  
pp. 13123-13157
Author(s):  
N. S. Lovenduski ◽  
M. C. Long ◽  
K. Lindsay

Abstract. We investigate variability in the surface ocean carbonate ion concentration ([CO32−]) on the basis of a long control simulation with a fully-coupled Earth System Model. The simulation is run with a prescribed, pre-industrial atmospheric CO2 concentration for 1000 years, permitting investigation of natural [CO32−] variability on interannual to multi-decadal timescales. We find high interannual variability in surface [CO32−] in the tropical Pacific and at the boundaries between the subtropical and subpolar gyres in the Northern Hemisphere, and relatively low interannual variability in the centers of the subtropical gyres and in the Southern Ocean. Statistical analysis of modeled [CO32−] variance and autocorrelation suggests that significant anthropogenic trends in the saturation state of aragonite (Ωaragonite) are already or nearly detectable at the sustained, open-ocean timeseries sites, whereas several decades of observations are required to detect anthropogenic trends in Ωaragonite in the tropical Pacific, North Pacific, and North Atlantic. The detection timescale for anthropogenic trends in pH is shorter than that for Ωaragonite, due to smaller noise-to-signal ratios and lower autocorrelation in pH. In the tropical Pacific, the leading mode of surface [CO32−] variability is primarily driven by variations in the vertical advection of dissolved inorganic carbon (DIC) in association with El Niño–Southern Oscillation. In the North Pacific, surface [CO32−] variability is caused by circulation-driven variations in surface DIC and strongly correlated with the Pacific Decadal Oscillation, with peak spectral power at 20–30 year periods. North Atlantic [CO32−] variability is also driven by variations in surface DIC, and exhibits weak correlations with both the North Atlantic Oscillation and the Atlantic Multidecadal Oscillation. As the scientific community seeks to detect the anthropogenic influence on ocean carbonate chemistry, these results will aid the interpretation of trends calculated from spatially- and temporally-sparse observations.


2020 ◽  
Author(s):  
Luke Gregor ◽  
Nicolas Gruber

Abstract. Ocean acidification has altered the ocean's carbonate chemistry profoundly since preindustrial times, with potentially serious consequences for marine life. Yet, no long-term global observation-based data set exists that permits 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 CO2 (pCO2), pH, and the saturation state with respect to mineral CaCO3 (Ω) at 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 CO2 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. This method is based on a two-step (cluster-regression) approach, but extends it by considering an ensemble of such cluster-regressions, leading to higher 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 µatm and 13 µmol kg−1, respectively. Taking into account also the measurement and representation errors, the total error increases to 14 µatm and 21 µmol 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, and root mean squared errors of 0.023 and 16 µmol kg−1, respectively. These errors are very comparable to those expected by propagating the total errors from pCO2 and TA through the thermodynamic computations, indicating a robust and conservative assessment of the errors. We illustrate the potential of this new dataset by analyzing the climatological mean seasonal cycles of the different parameters of the surface ocean carbonate system, highlighting their commonalities and differences. The OceanSODA-ETHZ data can be downloaded from https://doi.org/10.25921/m5wx-ja34 (Gregor and Gruber, 2020).


2008 ◽  
Vol 5 (5) ◽  
pp. 1395-1410 ◽  
Author(s):  
H. S. Findlay ◽  
T. Tyrrell ◽  
R. G. J. Bellerby ◽  
A. Merico ◽  
I. Skjelvan

Abstract. A coupled carbon-ecosystem model is compared to recent data from Ocean Weather Station M (66° N, 02° E) and used as a tool to investigate nutrient and carbon processes within the Norwegian Sea. Nitrate is consumed by phytoplankton in the surface layers over the summer; however the data show that silicate does not become rapidly limiting for diatoms, in contrast to the model prediction and in contrast to data from other temperate locations. The model estimates atmosphere-ocean CO2 flux to be 37 g C m−2 yr−1. The seasonal cycle of the carbonate system at OWS M resembles the cycles suggested by data from other high-latitude ocean locations. The seasonal cycles of calcite saturation state and [CO32-] are similar in the model and in data at OWS M: values range from ~3 and ~120 μmol kg−1 respectively in winter, to ~4 and ~170 μmol kg−1 respectively in summer. The model and data provide further evidence (supporting previous modelling work) that the summer is a time of high saturation state within the annual cycle at high-latitude locations. This is also the time of year that coccolithophore blooms occur at high latitudes.


2014 ◽  
Vol 10 (2) ◽  
pp. 1933-1975
Author(s):  
M. Heinze ◽  
T. Ilyina

Abstract. The Late Paleocene is characterized by warm and stable climatic conditions which served as the background climate for the Paleocene-Eocene Thermal Maximum (PETM, ~55 million years ago). With respect to feedback processes in the carbon cycle, the ocean biogeochemical background state is of major importance for projecting the climatic response to a carbon perturbation related to the PETM. Therefore we use the Hamburg Ocean Carbon Cycle model HAMOCC, embedded into the ocean general circulation model of the Max Planck Institute for Meteorology, MPIOM, to constrain the ocean biogeochemistry of the Late Paleocene. We focus on the evaluation of modeled spatial and vertical distributions of the ocean carbon cycle parameters in a long-term warm steady-state ocean, based on a 560 ppm CO2 atmosphere. Model results are discussed in the context of available proxy data and simulations of pre-industrial conditions. Our results illustrate that ocean biogeochemistry is shaped by the warm and sluggish ocean state of the Late Paleocene, which affects the strength and spatial variation of the different carbon pumps. Primary production is only slightly reduced in comparison to present-day; it is intensified along the equator, especially in the Atlantic. This enhances remineralization of organic matter, resulting in strong oxygen minimum zones and CaCO3 dissolution in intermediate waters. We show that an equilibrium CO2 exchange without increasing total alkalinity concentrations above today's values is achieved. Yet, the surface ocean pH and the saturation state with respect to CaCO3 are lower than today. Our results indicate that under such conditions, the surface ocean carbonate chemistry is expected to be more sensitive to a carbon perturbation (i.e. the PETM) due to lower CO32− concentration, whereas the deep ocean calcite sediments would be less vulnerable to dissolution due to the sluggish ocean.


2007 ◽  
Vol 339 ◽  
pp. 301-306 ◽  
Author(s):  
A McQuatters-Gollop ◽  
DE Raitsos ◽  
M Edwards ◽  
MJ Attrill

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