A seamless ensemble-based reconstruction of surface ocean pCO.sub.2 and air-sea CO.sub.2 fluxes over the global coastal and open oceans
We have estimated global air-sea CO.sub.2 fluxes (fgCO.sub.2) from the open ocean to coastal seas. Fluxes and associated uncertainty are computed from an ensemble-based reconstruction of CO.sub.2 sea surface partial pressure (pCO.sub.2) maps trained with gridded data from the Surface Ocean CO.sub.2...
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Veröffentlicht in: | Biogeosciences 2022-02, Vol.19 (4), p.1087 |
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description | We have estimated global air-sea CO.sub.2 fluxes (fgCO.sub.2) from the open ocean to coastal seas. Fluxes and associated uncertainty are computed from an ensemble-based reconstruction of CO.sub.2 sea surface partial pressure (pCO.sub.2) maps trained with gridded data from the Surface Ocean CO.sub.2 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 ±1Ï. 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 pCO.sub.2 are primarily found over the coasts and/or in regions with sparse observations, while fgCO.sub.2 estimates with the largest uncertainty are observed over the open Southern Ocean (44.sup." S southward), the subpolar regions, the Indian Ocean gyre, and upwelling systems. |
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Fluxes and associated uncertainty are computed from an ensemble-based reconstruction of CO.sub.2 sea surface partial pressure (pCO.sub.2) maps trained with gridded data from the Surface Ocean CO.sub.2 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 ±1Ï. 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 pCO.sub.2 are primarily found over the coasts and/or in regions with sparse observations, while fgCO.sub.2 estimates with the largest uncertainty are observed over the open Southern Ocean (44.sup." 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Fluxes and associated uncertainty are computed from an ensemble-based reconstruction of CO.sub.2 sea surface partial pressure (pCO.sub.2) maps trained with gridded data from the Surface Ocean CO.sub.2 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 ±1Ï. 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 pCO.sub.2 are primarily found over the coasts and/or in regions with sparse observations, while fgCO.sub.2 estimates with the largest uncertainty are observed over the open Southern Ocean (44.sup." 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Fluxes and associated uncertainty are computed from an ensemble-based reconstruction of CO.sub.2 sea surface partial pressure (pCO.sub.2) maps trained with gridded data from the Surface Ocean CO.sub.2 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 ±1Ï. 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 pCO.sub.2 are primarily found over the coasts and/or in regions with sparse observations, while fgCO.sub.2 estimates with the largest uncertainty are observed over the open Southern Ocean (44.sup." S southward), the subpolar regions, the Indian Ocean gyre, and upwelling systems.</abstract><pub>Copernicus GmbH</pub><tpages>1087</tpages></addata></record> |
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title | A seamless ensemble-based reconstruction of surface ocean pCO.sub.2 and air-sea CO.sub.2 fluxes over the global coastal and open oceans |
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