Article

Abstract

• Data assimilation systems are used increasingly to constrain the budgets of reactive and long-lived gases measured in the atmosphere. Each trace gas has its own lifetime, dominant sources and sinks, and observational network (from flask sampling and in situ measurements to space-based remote sensing) and therefore comes with its own optimal configuration of the data assimilation. The CarbonTracker Europe data assimilation system for CO2 estimates global carbon sources and sinks, and updates are released annually and used in carbon cycle studies. CarbonTracker Europe simulations are performed using the new modular implementation of the data assimilation system: the CarbonTracker Data Assimilation Shell (CTDAS). Here, we present and document this redesign of the data assimilation code that forms the heart of CarbonTracker, specifically meant to enable easy extension and modification of the data assimilation system. This paper also presents the setup of the latest version of CarbonTracker Europe (CTE2016), including the use of the gridded state vector, and shows the resulting carbon flux estimates. We present the distribution of the carbon sinks over the hemispheres and between the land biosphere and the oceans. We show that with equal fossil fuel emissions, 2015 has a higher atmospheric CO2 growth rate compared to 2014, due to reduced net land carbon uptake in later year. The European carbon sink is especially present in the forests, and the average net uptake over 2001–2015 was 0. 17 ± 0. 11 PgC yr−1 with reductions to zero during drought years. Finally, we also demonstrate the versatility of CTDAS by presenting an overview of the wide range of applications for which it has been used so far.

Creator

• Velde, Ivar R. van der
• Chen, Huilin
• authors., Please see bottom of page for a full list of

Date Issued

• 2017-07-18

Academic Affiliation

• Cooperative Institute for Research in Environmental Sciences

Journal Title

• Geoscientific Model Development

Journal Issue/Number

• 7.0

Journal Volume

• 10.0

Last Modified

• 2019-12-06

Resource Type

• Article

Rights Statement

• In Copyright

DOI

•  http://dx.doi.org/10.5194/gmd-10-2785-2017

ISSN

• 1991-9603

Language

• English [eng]

License

• Attribution 3.0

Relationships

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