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Abstract The El Niño‐Southern Oscillation (ENSO) in the equatorial Pacific is the dominant mode of global air‐sea carbon dioxide (CO2) flux interannual variability (IAV). Air‐sea CO2fluxes are driven by the difference between atmospheric and surface ocean pCO2, with variability of the latter driving flux variability. Previous studies found that models in Coupled Model Intercomparison Project Phase 5 (CMIP5) failed to reproduce the observed ENSO‐related pattern of CO2fluxes and had weak pCO2IAV, which were explained by both weak upwelling IAV and weak mean vertical dissolved inorganic carbon (DIC) gradients. We assess whether the latest generation of CMIP6 models can reproduce equatorial Pacific pCO2IAV by validating models against observations‐based data products. We decompose pCO2IAV into thermally and non‐thermally driven anomalies to examine the balance between these competing anomalies, which explain the total pCO2IAV. The majority of CMIP6 models underestimate pCO2IAV, while they overestimate sea surface temperature IAV. Insufficient compensation of non‐thermal pCO2to thermal pCO2IAV in models results in weak total pCO2IAV. We compare the relative strengths of the vertical transport of temperature and DIC and evaluate their contributions to thermal and non‐thermal pCO2anomalies. Model‐to‐observations‐based product comparisons reveal that modeled mean vertical DIC gradients are biased weak relative to their mean vertical temperature gradients, but upwelling acting on these gradients is insufficient to explain the relative magnitudes of thermal and non‐thermal pCO2anomalies.
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Multiscale Temporal Variability of the Global Air‐Sea CO 2 Flux Anomaly
Abstract The global air‐sea CO2flux (F) impacts and is impacted by a plethora of climate‐related processes operating at multiple time scales. In bulk mass transfer formulations, F is driven by physico‐ and bio‐chemical factors such as the air‐sea partial pressure difference (∆pCO2), gas transfer velocity, sea surface temperature, and salinity–all varying at multiple time scales. To de‐convolve the impact of these factors on variability in F at different time scales, time‐resolved estimates of F were computed using a global data set assembled between 1988 and 2015. The F anomalies were defined as temporal deviations from the 28‐year time‐averaged value. Spectral analysis revealed four dominant timescales of variability in F–subseasonal, seasonal, interannual, and decadal with relative amplitude differences varying across regions. A second‐order Taylor series expansion was then conducted along these four timescales to separate drivers across differing regions. The analysis showed that on subseasonal timescales, wind speed variability explains some 66% of the global F anomaly and is the dominant driver. On seasonal, interannual, and decadal timescales, the ∆pCO2effect controlled by the ∆pCO2anomaly, explained much of the F anomaly. On decadal timescales, the F anomaly was almost entirely governed by the ∆pCO2effect with large contributions from high latitudes. The main drivers across timescales also dominate the regional F anomaly, particularly in the mid‐high latitude regions. Finally, the driver of the ∆pCO2effect was closely connected with the relative strength of atmospheric pCO2and the nonthermal component of oceanic pCO2anomaly associated with dissolved inorganic carbon and alkalinity.
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- Award ID(s):
- 2028633
- PAR ID:
- 10426712
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Biogeosciences
- Volume:
- 128
- Issue:
- 6
- ISSN:
- 2169-8953
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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