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Volume 11, issue 1 | Copyright
Geosci. Model Dev., 11, 283-304, 2018
https://doi.org/10.5194/gmd-11-283-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

Model description paper 22 Jan 2018

Model description paper | 22 Jan 2018

The CarbonTracker Data Assimilation System for CO2 and δ13C (CTDAS-C13 v1.0): retrieving information on land–atmosphere exchange processes

Ivar R. van der Velde1,2,3, John B. Miller2, Michiel K. van der Molen1, Pieter P. Tans2, Bruce H. Vaughn4, James W. C. White4, Kevin Schaefer5, and Wouter Peters1,6 Ivar R. van der Velde et al.
  • 1Department of Meteorology and Air Quality, Wageningen University and Research, Wageningen, the Netherlands
  • 2Global Monitoring Division, NOAA Earth System Research Laboratory, Boulder, CO, USA
  • 3Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA
  • 4Institute for Arctic and Alpine Research, University of Colorado, Boulder, CO, USA
  • 5National Snow and Ice Data Center, University of Colorado, Boulder, CO, USA
  • 6Centre for Isotope Research, University of Groningen, Groningen, the Netherlands

Abstract. To improve our understanding of the global carbon balance and its representation in terrestrial biosphere models, we present here a first dual-species application of the CarbonTracker Data Assimilation System (CTDAS). The system's modular design allows for assimilating multiple atmospheric trace gases simultaneously to infer exchange fluxes at the Earth surface. In the prototype discussed here, we interpret signals recorded in observed carbon dioxide (CO2) along with observed ratios of its stable isotopologues 13CO212CO2 (δ13C). The latter is in particular a valuable tracer to untangle CO2 exchange from land and oceans. Potentially, it can also be used as a proxy for continent-wide drought stress in plants, largely because the ratio of 13CO2 and 12CO2 molecules removed from the atmosphere by plants is dependent on moisture conditions.

The dual-species CTDAS system varies the net exchange fluxes of both 13CO2 and CO2 in ocean and terrestrial biosphere models to create an ensemble of 13CO2 and CO2 fluxes that propagates through an atmospheric transport model. Based on differences between observed and simulated 13CO2 and CO2 mole fractions (and thus δ13C) our Bayesian minimization approach solves for weekly adjustments to both net fluxes and isotopic terrestrial discrimination that minimizes the difference between observed and estimated mole fractions.

With this system, we are able to estimate changes in terrestrial δ13C exchange on seasonal and continental scales in the Northern Hemisphere where the observational network is most dense. Our results indicate a decrease in stomatal conductance on a continent-wide scale during a severe drought. These changes could only be detected after applying combined atmospheric CO2 and δ13C constraints as done in this work. The additional constraints on surface CO2 exchange from δ13C observations neither affected the estimated carbon fluxes nor compromised our ability to match observed CO2 variations. The prototype presented here can be of great benefit not only to study the global carbon balance but also to potentially function as a data-driven diagnostic to assess multiple leaf-level exchange parameterizations in carbon-climate models that influence the CO2, water, isotope, and energy balance.

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We explored an inverse modeling technique to interpret global atmospheric measurements of CO2 and the ratio of its stable carbon isotopes (δ13C). We detected the possible underestimation of drought stress in biosphere models after applying combined atmospheric CO2 and δ13C constraints. This study highlights the importance of improving the representation of the biosphere in carbon–climate models, in particular in a world where droughts become more extreme and more frequent.
We explored an inverse modeling technique to interpret global atmospheric measurements of CO2...
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