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https://doi.org/10.5194/bg-2020-7
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-2020-7
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  10 Feb 2020

10 Feb 2020

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A revised version of this preprint is currently under review for the journal BG.

Evaluating two soil carbon models within a global land surface model using surface and spaceborne observations of atmospheric CO2 mole fractions

Tea Thum1, Julia E. S. M. Nabel2, Aki Tsuruta3, Tuula Aalto3, Edward J. Dlugokencky4, Jari Liski3, Ingrid T. Luijkx5, Tiina Markkanen3, Julia Pongratz6, Yukio Yoshida7, and Sönke Zaehle1 Tea Thum et al.
  • 1Max Planck Institute for Biogeochemistry, Jena, Germany
  • 2Max Planck Institute for Meteorology, Hamburg, Germany
  • 3The Finnish Meteorological Institute, Helsinki, Finland
  • 4NOAA ESRL Global Monitoring Division, Boulder CO, USA
  • 5Meteorology and Air Quality Group, Wageningen University and Research, Wageningen, the Netherlands
  • 6Department of Geography, Ludwig-Maximilians-Universität, Munich, Germany
  • 7Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan

Abstract. The trajectories of soil carbon (C) in the changing climate are of utmost importance, as soil carbon is a substantial carbon storage with a large potential to impact the atmospheric carbon dioxide (CO2) burden. Atmospheric CO2 observations integrate all processes affecting C exchange between the surface and the atmosphere. Therefore they provide a benchmark for carbon cycle models. We evaluated two distinct soil carbon models (CBALANCE and YASSO) that were implemented to a global land surface model (JSBACH) against atmospheric CO2 observations. We transported the biospheric carbon fluxes obtained by JSBACH using the atmospheric transport model TM5 to obtain atmospheric CO2. We then compared these results with surface observations from Global Atmosphere Watch (GAW) stations as well as with column XCO2 retrievals from the GOSAT satellite. The seasonal cycles of atmospheric CO2 estimated by the two different soil models differed. The estimates from the CBALANCE soil model were more in line with the surface observations at low latitudes (0 N–45 N) with only 1 % bias in the seasonal cycle amplitude (SCA), whereas YASSO was underestimating the SCA in this region by 32 %. YASSO gave more realistic seasonal cycle amplitudes of CO2 at northern boreal sites (north of 45 N) with underestimation of 15 % compared to 30 % overestimation by CBALANCE. Generally, the estimates from CBALANCE were more successful in capturing the seasonal patterns and seasonal cycle amplitudes of atmospheric CO2 even though it overestimated soil carbon stocks by 225 % (compared to underestimation of 36 % by YASSO) and its predictions of the global distribution of soil carbon stocks was unrealistic. The reasons for these differences in the results are related to the different environmental drivers and their functional dependencies of these two soil carbon models. In the tropical region the YASSO model showed earlier increase in season of the heterotophic respiration since it is driven by precipitation instead of soil moisture as CBALANCE. In the temperate and boreal region the role of temperature is more dominant. There the heterotophic respiration from the YASSO model had larger annual variability, driven by air temperature, compared to the CBALANCE which is driven by soil temperature. The results underline the importance of using sub-yearly data in the development of soil carbon models when they are used in shorter than annual time scales.

Tea Thum et al.

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Tea Thum et al.

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Latest update: 18 Sep 2020
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Short summary
Global vegetation models are important tools in estimating the impacts of global climate change. The fate of soil carbon is of upmost importance, as its emissions to atmosphere will enhance atmospheric carbon dioxide concentration. To evaluate the skill of the global vegetation models to model the soil carbon and its responses to environmental factors, it is important to use different data sources. We evaluated two different soil carbon models by using atmospheric carbon dioxide concentrations.
Global vegetation models are important tools in estimating the impacts of global climate change....
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