Global Air-sea CO2 Fluxes Research Articles

Temperature effect on seawater fCO2 revisited: theoretical basis, uncertainty analysis and implications for parameterising carbonic acid equilibrium constants

Abstract. The sensitivity of the fugacity of carbon dioxide in seawater (fCO2) to temperature (denoted υ, reported in % °C−1) is critical for the accurate fCO2 measurements needed to build global carbon budgets and for understanding the drivers of air–sea CO2 flux variability across the ocean. However, understanding and computing υ have been restricted to either using empirical functions fitted to experimental data or determining it as an emergent property of a fully resolved marine carbonate system, and these two approaches are not consistent with each other. The lack of a theoretical basis and an uncertainty estimate for υ has hindered resolving this discrepancy. Here, we develop a new approach for calculating the temperature sensitivity of fCO2 based on the equations governing the marine carbonate system and the van 't Hoff equation. This shows that, to first order, ln (fCO2) should be proportional to 1/tK (where tK is temperature in kelvin), rather than to temperature, as has previously been assumed. This new approach is, to first order, consistent with calculations from a fully resolved marine carbonate system, which we have incorporated into the PyCO2SYS software. Agreement with experimental data is less convincing but remains inconclusive due to the scarcity of direct measurements of υ, particularly above 25 °C. However, the new approach is consistent with field data, performing better than any other approach for adjusting fCO2 by up to 10 °C if spatiotemporal variability in its single fitted coefficient is accounted for. The uncertainty in υ arising from only measurement uncertainty in the main experimental dataset where υ has been directly measured is in the order of 0.04 % °C−1, which corresponds to a 0.04 % uncertainty in fCO2 adjusted by +1 °C. However, spatiotemporal variability in υ is several times greater than this, so the true uncertainty due to the temperature adjustment in fCO2 adjusted by +1 °C using the most widely used constant υ value is around 0.24 %. This can be reduced to around 0.06 % using the new approach proposed here, and this could be further reduced by more measurements. The spatiotemporal variability in υ arises mostly from the equilibrium constants for CO2 solubility and carbonic acid dissociation (K1∗ and K2∗), and its magnitude varies significantly depending on which parameterisation is used for K1∗ and K2∗. Seawater fCO2 can be measured accurately enough that additional experiments should be able to detect spatiotemporal variability in υ and distinguish between different parameterisations for K1∗ and K2∗. Because the most widely used constant υ was coincidentally measured from seawater with roughly global average υ, our results are unlikely to significantly affect global air–sea CO2 flux budgets, but they may have more important implications for regional budgets and studies that adjust by larger temperature differences.

A seamless ensemble-based reconstruction of surface ocean <i>p</i>CO<sub>2</sub> and air–sea CO<sub>2</sub> fluxes over the global coastal and open oceans

Abstract. We have estimated global air–sea CO2 fluxes (fgCO2) from the open ocean to coastal seas. Fluxes and associated uncertainty are computed from an ensemble-based reconstruction of CO2 sea surface partial pressure (pCO2) maps trained with gridded data from the Surface Ocean CO2 Atlas v2020 database. The ensemble mean (which is the best estimate provided by the approach) fits independent data well, and a broad agreement between the spatial distribution of model–data differences and the ensemble standard deviation (which is our model uncertainty estimate) is seen. Ensemble-based uncertainty estimates are denoted by ±1σ. The space–time-varying uncertainty fields identify oceanic regions where improvements in data reconstruction and extensions of the observational network are needed. Poor reconstructions of pCO2 are primarily found over the coasts and/or in regions with sparse observations, while fgCO2 estimates with the largest uncertainty are observed over the open Southern Ocean (44∘ S southward), the subpolar regions, the Indian Ocean gyre, and upwelling systems. Our estimate of the global net sink for the period 1985–2019 is 1.643±0.125 PgC yr−1 including 0.150±0.010 PgC yr−1 for the coastal net sink. Among the ocean basins, the Subtropical Pacific (18–49∘ N) and the Subpolar Atlantic (49–76∘ N) appear to be the strongest CO2 sinks for the open ocean and the coastal ocean, respectively. Based on mean flux density per unit area, the most intense CO2 drawdown is, however, observed over the Arctic (76∘ N poleward) followed by the Subpolar Atlantic and Subtropical Pacific for both open-ocean and coastal sectors. Reconstruction results also show significant changes in the global annual integral of all open- and coastal-ocean CO2 fluxes with a growth rate of +0.062±0.006 PgC yr−2 and a temporal standard deviation of 0.526±0.022 PgC yr−1 over the 35-year period. The link between the large interannual to multi-year variations of the global net sink and the El Niño–Southern Oscillation climate variability is reconfirmed.

Carbonate chemistry variability in the southern Yellow Sea and East China Sea during spring of 2017 and summer of 2018.

Marginal seas are highly productive and disproportionately large contributors to global air-sea CO2 fluxes. Due to complex physical and biogeochemical conditions, the southern Yellow-East China Sea is an ideal site for studying carbonate chemistry variability. The carbonate system was investigated in the area in spring of 2017 and summer of 2018. Dissolved inorganic carbon (DIC) and total alkalinity (TA) concentrations were higher in the SYS than the ECS due to material from carbonate weathering and erosion carried by the Yellow River. High pH and low DIC and TA were observed in the Zhe-Min Coastal Current in spring due to high primary productivity caused by Changjiang River input and the Taiwan Warm Current. Temperature and biological activity were the primary drivers controlling the partial pressure of CO2 (pCO2) in the SYS, pCO2 was controlled by primary productivity related to nutrients carried by the Changjiang River and physical mixing in the Changjiang River plume and inner/middle shelves of the ECS, whereas temperature was the dominant factor determining pCO2 distributions in the ECS outer shelf waters influenced by the Kuroshio Current. Overall, the entire study area shifted from a CO2 sink (-4.18±5.60mmolm-2 d-1) to a weak source (1.02±4.87mmolm-2 d-1) from spring to summer. Specifically, the SYS and ECS offshore waters changed from CO2 sinks in spring to sources in summer, while the Changjiang River plume was always a CO2 sink.

Global Air–Sea CO2 Flux in 22 CMIP5 Models: Multiyear Mean and Interannual Variability*

Abstract To assess the capability of the latest Earth system models (ESMs) in representing historical global air–sea CO2 flux, 22 models from phase 5 of the Coupled Model Intercomparision Project (CMIP5) are analyzed, with a focus on the spatial distribution of multiyear mean and interannual variability. Results show that the global distribution of air–sea CO2 flux is reasonable in most of the models and that the main differences between models and observationally based results exist in regions with strong vertical movement. The annual mean flux in the 18-member multimodel ensemble (MME; four models were excluded because of their poor performances) mean during 1996–2004 is 1.95 Pg C yr−1 (1 Pg = 1015 g; positive values mean into the ocean), and all but one model describe the rapid increasing trend of air–sea CO2 flux observed during 1960–2000. The first mode of the global air–sea CO2 flux variability during 1870–2000 in six of the models represents the El Niño–Southern Oscillation (ENSO) mode. The remaining 12 models fail to represent this important character for the following reasons: in five models, the tropical Pacific does not play a dominant role in the interannual variability of global air–sea CO2 flux because of stronger interannual variability in the Southern Ocean; two models poorly represent the interannual fluctuation of dissolved inorganic carbon (DIC) in the surface ocean of the tropical Pacific; and four models have shorter periods of the air–sea CO2 flux, which are out of the period range of ENSO events.

Using Green’s Functions to initialize and adjust a global, eddying ocean biogeochemistry general circulation model

The NASA Carbon Monitoring System (CMS) Flux Project aims to attribute changes in the atmospheric accumulation of carbon dioxide to spatially resolved fluxes by utilizing the full suite of NASA data, models, and assimilation capabilities. For the oceanic part of this project, we introduce ECCO2-Darwin, a new ocean biogeochemistry general circulation model based on combining the following pre-existing components: (i) a full-depth, eddying, global-ocean configuration of the Massachusetts Institute of Technology general circulation model (MITgcm), (ii) an adjoint-method-based estimate of ocean circulation from the Estimating the Circulation and Climate of the Ocean, Phase II (ECCO2) project, (iii) the MIT ecosystem model “Darwin”, and (iv) a marine carbon chemistry model. Air–sea gas exchange coefficients and initial conditions of dissolved inorganic carbon, alkalinity, and oxygen are adjusted using a Green’s Functions approach in order to optimize modeled air–sea CO2 fluxes. Data constraints include observations of carbon dioxide partial pressure (pCO2) for 2009–2010, global air–sea CO2 flux estimates, and the seasonal cycle of the Takahashi et al. (2009) Atlas. The model sensitivity experiments (or Green’s Functions) include simulations that start from different initial conditions as well as experiments that perturb air–sea gas exchange parameters and the ratio of particulate inorganic to organic carbon. The Green’s Functions approach yields a linear combination of these sensitivity experiments that minimizes model-data differences. The resulting initial conditions and gas exchange coefficients are then used to integrate the ECCO2-Darwin model forward. Despite the small number (six) of control parameters, the adjusted simulation is significantly closer to the data constraints (37% cost function reduction, i.e., reduction in the model-data difference, relative to the baseline simulation) and to independent observations (e.g., alkalinity). The adjusted air–sea gas exchange parameter differs by only 3% from the baseline value and has little impact (−0.1%) on the cost function. The particulate inorganic to organic carbon ratio was increased more than threefold and reduced the cost function by 22% relative to the baseline integration, indicating a significant influence of biology on air–sea gas exchange. The largest contribution to cost reduction (35%) comes from the adjustment of initial conditions. In addition to reducing biases relative to observations, the adjusted simulation exhibits smaller model drift than the baseline. We estimate drift by integrating the model with repeated 2009 atmospheric forcing for seven years and find a volume-weighted drift reduction of, for example, 12.5% for nitrate and 30% for oxygen in the top 300 m. Although there remain several regions with large model-data discrepancies, for example, overly strong carbon uptake in the Southern Ocean, the adjusted simulation is a first step towards a more accurate representation of the ocean carbon cycle at high spatial and temporal resolution.

Effect of a many kinds of wind speed data set on global air-sea CO2 flux

Effect of a many kinds of wind speed data set on global air-sea CO2 flux

Side effects and accounting aspects of hypothetical large-scale Southern Ocean iron fertilization

Abstract. Recent suggestions to slow down the increase in atmospheric carbon dioxide have included ocean fertilization by addition of the micronutrient iron to Southern Ocean surface waters, where a number of natural and artificial iron fertilization experiments have shown that low ambient iron concentrations limit phytoplankton growth. Using a coupled carbon-climate model with the marine biology's response to iron addition calibrated against data from natural iron fertilization experiments, we examine biogeochemical side effects of a hypothetical large-scale Southern Ocean Iron Fertilization (OIF) that need to be considered when attempting to account for possible OIF-induced carbon offsets. In agreement with earlier studies our model simulates an OIF-induced increase in local air-sea CO2 fluxes by about 73 GtC over a 100-year period, which amounts to about 48% of the OIF-induced increase in organic carbon export out of the fertilized area. Offsetting CO2 return fluxes outside the region and after stopping the fertilization at 1, 7, 10, 50, and 100 years are quantified for a typical accounting period of 100 years. For continuous Southern Ocean iron fertilization, the CO2 return flux outside the fertilized area cancels about 20% of the fertilization-induced CO2 air-sea flux within the fertilized area on a 100-yr timescale. This "leakage" effect has a radiative impact more than twice as large as the simulated enhancement of marine N2O emissions. Other side effects not yet discussed in terms of accounting schemes include a decrease in Southern Ocean oxygen levels and a simultaneous shrinking of tropical suboxic areas, and accelerated ocean acidification in the entire water column in the Southern Ocean at the expense of reduced globally-averaged surface-water acidification. A prudent approach to account for the OIF-induced carbon sequestration would account for global air-sea CO2 fluxes rather than for local fluxes into the fertilized area only. However, according to our model, this would underestimate the potential for offsetting CO2 emissions by about 20% on a 100 year accounting timescale. We suggest that a fair accounting scheme applicable to both terrestrial and marine carbon sequestration has to be based on emission offsets rather than on changes in individual carbon pools.

Simulation and assimilation of global ocean pCO2 and air–sea CO2 fluxes using ship observations of surface ocean pCO2 in a simplified biogeochemical offline model

We used an offline tracer transport model, driven by reanalysis ocean currents and coupled to a simple biogeochemical model, to synthesize the surface ocean pCO2 and air–sea CO2 flux of the global ocean from 1996 to 2004, using a variational assimilation method. This oceanic CO2 flux analysis system was developed at the National Institute for Environmental Studies (NIES), Japan, as part of a project that provides prior fluxes for atmospheric inversions using CO2 measurements made from an on-board instrument attached to the Greenhouse gas Observing SATellite (GOSAT). Nearly 250 000 pCO2 observations from the database of Takahashi et al. (2007) have been assimilated into the model with a strong constraint provide by ship-track observations while maintaining a weak constraint of 20% on global averages of monthly mean pCO2 in regions where observations are limited. The synthesized global air–sea CO2 flux shows a net sink of 1.48 PgC yr-1. The Southern Ocean air–sea CO2 flux is a sink of 0.41 PgC yr-1. The interannual variability of synthesized CO2 flux from the El Niño region suggests a weaker source (by an amplitude of 0.4 PgC yr-1) during the El Niño events in 1997/1998 and 2003/2004. The assimilated air–sea CO2 flux shows remarkable correlations with the CO2 fluxes obtained from atmospheric inversions on interannual time-scales.

The influence of short‐term wind variability on air‐sea CO2 exchange

Quantifying the regional and global exchange of CO2 between the ocean and atmosphere requires knowledge of the factors that affect CO2 gas transfer (e.g., wind speed) and the air‐sea difference in partial pressure of CO2 (pCO2). A major uncertainty is the effect of short‐term variability on air‐sea CO2 flux. Using high sampling frequency wind speed and pCO2 data collected during deployments of the autonomous CARbon Interface OCean Atmosphere (CARIOCA) buoy, we compare CO2 fluxes at different sampling frequency of wind speed (i.e., hourly versus daily averaged). Air‐sea CO2 flux was up to three times greater if high frequency wind data was used rather than daily average values. This difference arises from the non‐linear relationship between wind speed and CO2 gas transfer coefficient, and a better representation of wind distribution at a higher frequency (i.e., hourly) of sampling. This finding has significant implications for determining regional and global air‐sea CO2 fluxes, and understanding of the global carbon cycle.

Modelling the monthly sea surface fCO2 fields in the Indian Ocean

In order to construct monthly fields of sea surface fugacity of carbon dioxide (fCO2) on a large scale in the Indian Ocean, we use a one-dimensional model which takes into account the main physical and biogeochemical processes controlling fCO2 variations in the ocean. Physical and biogeochemical processes are constrained by the monthly variations of sea surface temperature, salinity, chlorophyll concentration, wind speed and mixed-layer depth. The model is applied to four locations in the Indian Ocean and it well predicts observed temporal variations in fCO2 at these locations. Regarding to monthly fCO2 observations, the model also well simulates the fCO2 distribution and its temporal variations along a track located between 20 ° and 50 °S with a maximal error of + 10 μatm. The model is also used to predict fCO2 for 2 ° × 2 ° grids over the entire Indian Ocean and simulates seasonal cycles that are consistent with observations. The monthly fCO2 fields derived from the model are used to estimate a global air-sea CO2 flux over the Indian Ocean basin. We estimate a net sink of 0.5 Gtyr C for the Indian Ocean (20 °N-50 °S), with the main sink located between 20 ° and 50 °S.