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Abstract The ocean has absorbed about 25% of the carbon emitted by humans to date. To better predict how much climate will change, it is critical to understand how this ocean carbon sink will respond to future emissions. Here, we examine the ocean carbon sink response to low emission (SSP1-1.9, SSP1-2.6), intermediate emission (SSP2-4.5, SSP5-3.4-OS), and high emission (SSP5-8.5) scenarios in CMIP6 Earth System Models and in MAGICC7, a reduced-complexity climate carbon system model. From 2020–2100, the trajectory of the global-mean sink approximately parallels the trajectory of anthropogenic emissions. With increasing cumulative emissions during this century (SSP5-8.5 and SSP2-4.5), the cumulative ocean carbon sink absorbs 20%–30% of cumulative emissions since 2015. In scenarios where emissions decline, the ocean absorbs an increasingly large proportion of emissions (up to 120% of cumulative emissions since 2015). Despite similar responses in all models, there remains substantial quantitative spread in estimates of the cumulative sink through 2100 within each scenario, up to 50 PgC in CMIP6 and 120 PgC in the MAGICC7 ensemble. We demonstrate that for all but SSP1-2.6, approximately half of this future spread can be eliminated if model results are adjusted to agree with modern observation-based estimates. Considering the spatial distribution of air-sea CO2fluxes in CMIP6, we find significant zonal-mean divergence from the suite of newly-available observation-based constraints. We conclude that a significant portion of future ocean carbon sink uncertainty is attributable to modern-day errors in the mean state of air-sea CO2fluxes, which in turn are associated with model representations of ocean physics and biogeochemistry. Bringing models into agreement with modern observation-based estimates at regional to global scales can substantially reduce uncertainty in future role of the ocean in absorbing anthropogenic CO2from the atmosphere and mitigating climate change.
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Assessment of Global Ocean Biogeochemistry Models for Ocean Carbon Sink Estimates in RECCAP2 and Recommendations for Future Studies
Abstract The ocean is a major carbon sink and takes up 25%–30% of the anthropogenically emitted CO2. A state‐of‐the‐art method to quantify this sink are global ocean biogeochemistry models (GOBMs), but their simulated CO2uptake differs between models and is systematically lower than estimates based on statistical methods using surface oceanpCO2and interior ocean measurements. Here, we provide an in‐depth evaluation of ocean carbon sink estimates from 1980 to 2018 from a GOBM ensemble. As sources of inter‐model differences and ensemble‐mean biases our study identifies (a) the model setup, such as the length of the spin‐up, the starting date of the simulation, and carbon fluxes from rivers and into sediments, (b) the simulated ocean circulation, such as Atlantic Meridional Overturning Circulation and Southern Ocean mode and intermediate water formation, and (c) the simulated oceanic buffer capacity. Our analysis suggests that a late starting date and biases in the ocean circulation cause a too low anthropogenic CO2uptake across the GOBM ensemble. Surface ocean biogeochemistry biases might also cause simulated anthropogenic fluxes to be too low, but the current setup prevents a robust assessment. For simulations of the ocean carbon sink, we recommend in the short‐term to (a) start simulations at a common date before the industrialization and the associated atmospheric CO2increase, (b) conduct a sufficiently long spin‐up such that the GOBMs reach steady‐state, and (c) provide key metrics for circulation, biogeochemistry, and the land‐ocean interface. In the long‐term, we recommend improving the representation of these metrics in the GOBMs.
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- Award ID(s):
- 1948955
- PAR ID:
- 10519192
- Publisher / Repository:
- John Wiley and Sons
- Date Published:
- Journal Name:
- Journal of Advances in Modeling Earth Systems
- Volume:
- 16
- Issue:
- 3
- ISSN:
- 1942-2466
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1029/2023MS003840
