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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/gmd-2017-84
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Model description paper
30 May 2017
Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Geoscientific Model Development (GMD).
A multi-species data assimilation system to retrieve 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 1Department of Meteorology and Air Quality, Wageningen University and Research, Wageningen, The Netherlands
2Global Monitoring Division, NOAA Earth System Research Laboratory, Boulder, CO, United States
3Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, United States
4Institute for Arctic and Alpine Research, University of Colorado, Boulder, CO, United States
5National Snow and Ice Data Center, University of Colorado, Boulder, CO, United States
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 multi-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 13CO2/12CO213C). 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 multi-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 potentially also to 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.


Citation: van der Velde, I. R., Miller, J. B., van der Molen, M. K., Tans, P. P., Vaughn, B. H., White, J. W. C., Schaefer, K., and Peters, W.: A multi-species data assimilation system to retrieve information on land-atmosphere exchange processes, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-84, in review, 2017.
Ivar R. van der Velde et al.
Ivar R. van der Velde et al.
Ivar R. van der Velde et al.

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Short summary
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 to improve the representation of the biosphere in carbon-climate models, especially 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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