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Title: The Southern Ocean as a constraint to reduce uncertainty in future ocean carbon sinks

Abstract

Earth system model (ESM) simulations exhibit large biases compares to observation-based estimates of the present ocean CO2 sink. The inter-model spread in projections increases nearly 2-fold by the end of the 21st century and therefore contributes significantly to the uncertainty of future climate projections. In this study, the Southern Ocean (SO) is shown to be one of the hot-spot regions for future uptake of anthropogenic CO2, characterized by both the solubility pump and biologically mediated carbon drawdown in the spring and summer. Here, we show, by analyzing a suite of fully interactive ESMs simulations from the Coupled Model Intercomparison Project phase 5 (CMIP5) over the 21st century under the high-CO2 Representative Concentration Pathway (RCP) 8.5 scenario, that the SO is the only region where the atmospheric CO2 uptake rate continues to increase toward the end of the 21st century. Furthermore, our study discovers a strong inter-model link between the contemporary CO2 uptake in the Southern Ocean and the projected global cumulated uptake over the 21st century. This strong correlation suggests that models with low (high) carbon uptake rate in the contemporary SO tend to simulate low (high) uptake rate in the future. None the less, our analysis also shows that none ofmore » the models fully capture the observed biophysical mechanisms governing the CO2 fluxes in the SO. The inter-model spread for the contemporary CO2 uptake in the Southern Ocean is attributed to the variations in the simulated seasonal cycle of surface pCO2. Two groups of model behavior have been identified. The first one simulates anomalously strong SO carbon uptake, generally due to both too strong a net primary production and too low a surface pCO2 in December–January. The second group simulates an opposite CO2 flux seasonal phase, which is driven mainly by the bias in the sea surface temperature variability. Furthermore, we show that these biases are persistent throughout the 21st century, which highlights the urgent need for a sustained and comprehensive biogeochemical monitoring system in the Southern Ocean to better constrain key processes represented in current model systems.« less

Authors:
 [1];  [2]
  1. Bjerknes Centre for Climate Research, Bergen (Norway). Uni Research Climate; Pierre and Marie Curie Univ., Paris (France)
  2. Bjerknes Centre for Climate Research, Bergen (Norway). Uni Research Climate
Publication Date:
Research Org.:
Uni Research Climate, Bergen (Norway); Bjerknes Centre for Climate Research, Bergen (Norway)
Sponsoring Org.:
USDOE
OSTI Identifier:
1375436
Grant/Contract Number:  
239965; 229771; 229791; 317699
Resource Type:
Accepted Manuscript
Journal Name:
Earth System Dynamics (Online)
Additional Journal Information:
Journal Name: Earth System Dynamics (Online); Journal Volume: 7; Journal Issue: 2; Journal ID: ISSN 2190-4987
Publisher:
European Geosciences Union
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES

Citation Formats

Kessler, A., and Tjiputra, J. The Southern Ocean as a constraint to reduce uncertainty in future ocean carbon sinks. United States: N. p., 2016. Web. doi:10.5194/esd-7-295-2016.
Kessler, A., & Tjiputra, J. The Southern Ocean as a constraint to reduce uncertainty in future ocean carbon sinks. United States. https://doi.org/10.5194/esd-7-295-2016
Kessler, A., and Tjiputra, J. Thu . "The Southern Ocean as a constraint to reduce uncertainty in future ocean carbon sinks". United States. https://doi.org/10.5194/esd-7-295-2016. https://www.osti.gov/servlets/purl/1375436.
@article{osti_1375436,
title = {The Southern Ocean as a constraint to reduce uncertainty in future ocean carbon sinks},
author = {Kessler, A. and Tjiputra, J.},
abstractNote = {Earth system model (ESM) simulations exhibit large biases compares to observation-based estimates of the present ocean CO2 sink. The inter-model spread in projections increases nearly 2-fold by the end of the 21st century and therefore contributes significantly to the uncertainty of future climate projections. In this study, the Southern Ocean (SO) is shown to be one of the hot-spot regions for future uptake of anthropogenic CO2, characterized by both the solubility pump and biologically mediated carbon drawdown in the spring and summer. Here, we show, by analyzing a suite of fully interactive ESMs simulations from the Coupled Model Intercomparison Project phase 5 (CMIP5) over the 21st century under the high-CO2 Representative Concentration Pathway (RCP) 8.5 scenario, that the SO is the only region where the atmospheric CO2 uptake rate continues to increase toward the end of the 21st century. Furthermore, our study discovers a strong inter-model link between the contemporary CO2 uptake in the Southern Ocean and the projected global cumulated uptake over the 21st century. This strong correlation suggests that models with low (high) carbon uptake rate in the contemporary SO tend to simulate low (high) uptake rate in the future. None the less, our analysis also shows that none of the models fully capture the observed biophysical mechanisms governing the CO2 fluxes in the SO. The inter-model spread for the contemporary CO2 uptake in the Southern Ocean is attributed to the variations in the simulated seasonal cycle of surface pCO2. Two groups of model behavior have been identified. The first one simulates anomalously strong SO carbon uptake, generally due to both too strong a net primary production and too low a surface pCO2 in December–January. The second group simulates an opposite CO2 flux seasonal phase, which is driven mainly by the bias in the sea surface temperature variability. Furthermore, we show that these biases are persistent throughout the 21st century, which highlights the urgent need for a sustained and comprehensive biogeochemical monitoring system in the Southern Ocean to better constrain key processes represented in current model systems.},
doi = {10.5194/esd-7-295-2016},
journal = {Earth System Dynamics (Online)},
number = 2,
volume = 7,
place = {United States},
year = {Thu Apr 07 00:00:00 EDT 2016},
month = {Thu Apr 07 00:00:00 EDT 2016}
}

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