Abstract

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.

Highlights

  • The CarbonTracker data assimilation system for CO2 estimates global carbon sources and sinks and was originally developed at the National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL) in the period 2005–2007 (Peters et al, 2005, 2007)

  • The CarbonTracker Data Assimilation Shell (CTDAS) code is based on the use of seven Python classes, each representing a different part of the data assimilation system

  • Following from the uncertainty estimate taken as the range of the different versions, we can state that the change between CTE was in 2008 (CTE2008)–CTE2013 to CTE2014– CTE2016-FT has a significant effect on the resulting carbon flux estimates, which is a result of the used convective fluxes

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Summary

Introduction

The CarbonTracker data assimilation system for CO2 estimates global carbon sources and sinks and was originally developed at the National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL) in the period 2005–2007 (Peters et al, 2005, 2007). This lead to the new object-oriented implementation in the Python programming language and is called the CarbonTracker Data Assimilation Shell (CTDAS) It is designed in a modular fashion that allows for new observation types to be introduced, changes in the structure of the underlying state vector to be made, and even replacement of the transport model (e.g. the Lagrangian model STILT) or the optimization method (e.g. four-dimensional variational, 4DVar), with only minimal additional code within one module. CTDAS is currently used in at least seven institutes that perform ensemble data assimilation of trace gases, with applications in CO2, CH4, 13CO2, carbonyl sulfide (COS), and SF6 These applications have helped to improve its code base and test its implementation in several setups. In this paper we (1) document the CTDAS code base (Sect. 2), (2) present the setup of the latest version of the CarbonTracker Europe (CTE2016), together with the resulting carbon flux estimates (Sect. 3) and (3) demonstrate the versatility of CTDAS by presenting an overview of the applications it has been used in so far (Sect. 4)

Data assimilation in CarbonTracker
Motivation for CTDAS
Modular structure of CTDAS
Platform
CTDAS documentation and version control
Updates and results from the latest version for CO2
General setup for CarbonTracker Europe for CO2
The gridded CO2 state vector
CTE2016 results
Comparison of CTE2016 with previous releases
Overview of applications using CTDAS
Findings
Conclusions and outlook
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