| Summary: | A globally integrated carbon observation and anal-ysis system is needed to improve the fundamental under-standing of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of poli-cies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon obser-vation system requires transformational advances from the existing sparse, exploratory framework towards a dense, ro-bust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial bio-sphere. The paper is addressed to scientists, policymakers, and funding agencies who need to have a global picture of the current state of the (diverse) carbon observations. We identify the current state of carbon observations, and the needs and notional requirements for a global integrated carbon observa-tion system that can be built in the next decade. A key conclu-sion is the substantial expansion of the ground-based obser-vation networks required to reach the high spatial resolution for CO2 and CH4 ?uxes, and for carbon stocks for address-ing policy-relevant objectives, and attributing ?ux changes to underlying processes in each region. In order to establish ?ux and stock diagnostics over areas such as the southern oceans, tropical forests, and the Arctic, in situ observations will have to be complemented with remote-sensing measure-ments. Remote sensing offers the advantage of dense spatial coverage and frequent revisit. A key challenge is to bring remote-sensing measurements to a level of long-term consis-tency and accuracy so that they can be ef?ciently combined in models to reduce uncertainties, in synergy with ground-based data. Bringing tight observational constraints on fossil fuel and land use change emissions will be the biggest chal-lenge for deployment of a policy-relevant integrated carbon observation system. This will require in situ and remotely sensed data at much higher resolution and density than currently ...
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