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• W84647586 abstract "Publisher Summary The long lifetime and rapid mixing of CO2 in the atmosphere provide a large-scale integration of surface fluxes, while with sufficient measurement precision, signatures of individual surface source or sink regions can still be detected. The three-dimensional Bayesian synthesis inversion technique was introduced into global carbon cycle modeling. Measurements of atmospheric CO2 mixing ratios and stable carbon isotope ratios from globally distributed sampling sites for selected years were interpreted using an atmospheric transport model to determine regional sources and sinks of atmospheric carbon. The inversion process is inherently unstable, and requires additional constraints, in this case the spatial distribution of known sources and sinks, and prior estimates of the surface fluxes. When those prior estimates are independently and rigorously determined, the Bayesian technique provides a promising framework within which the various studies of regional carbon fluxes (and associated process information) can be reconciled with changes in the global atmospheric carbon content. A particular advantage is the potential for systematic treatment of uncertainty in the various components of the inversion. Application of the Bayesian technique to global carbon budgeting is still in the early stages of development." @default.
• W84647586 created "2016-06-24" @default.
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• W84647586 date "2001-01-01" @default.
• W84647586 modified "2023-10-18" @default.
• W84647586 title "Constraining the Global Carbon Budget from Global to Regional Scales—The Measurement Challenge" @default.
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• W84647586 doi "https://doi.org/10.1016/b978-012631260-7/50021-2" @default.
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