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Biogeosciences An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/bg-2019-256
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-2019-256
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 15 Jul 2019

Submitted as: research article | 15 Jul 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Biogeosciences (BG).

Leveraging the signature of heterotrophic respiration on atmospheric CO2 for model benchmarking

Samantha J. Basile1, Xin Lin1, William R. Wieder2,3, Melannie D. Hartman2,4, and Gretchen Keppel-Aleks1 Samantha J. Basile et al.
  • 1Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI, 48105, USA
  • 2Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO, 80305, USA
  • 3Institute of Arctic and Alpine Research, University of Colorado, Boulder, CO, 80309, USA
  • 4Natural Resource Ecology Laboratory, Colorado State University, Fort Collins CO, 80523, USA

Abstract. Spatial and temporal variations in atmospheric carbon dioxide (CO2) reflect large-scale net carbon exchange between the atmosphere and terrestrial ecosystems. Soil heterotrophic respiration (HR) is one of the component fluxes that drive this net exchange but, given observational limitations, it is difficult to quantify this flux or to evaluate global-scale model simulations thereof. Here, we show that atmospheric CO2 can provide a useful constraint on large-scale patterns of soil heterotrophic respiration. We analyze three soil model configurations (CASA-CNP, MIMICS and CORPSE) that simulate HR fluxes within a biogeochemical testbed that provides each model with identical net primary productivity (NPP) and climate forcings. We subsequently quantify the effects of variation in simulated terrestrial carbon fluxes (NPP and HR from the three soil testbed models) on atmospheric CO2 distributions using a three-dimensional atmospheric tracer transport model. Our results show that atmospheric CO2 observations can be used to identify deficiencies in model simulations of the seasonal cycle and interannual variability in HR relative to NPP. In particular, the two models that explicitly simulated microbial processes (MIMICS and CORPSE) were more variable than observations at interannual timescales and showed a stronger than observed temperature sensitivity. Our results prompt future research directions to use atmospheric CO2, in combination with additional constraints on terrestrial productivity or soil carbon stocks, for evaluating HR fluxes.

Samantha J. Basile et al.
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Status: open (until 16 Sep 2019)
Status: open (until 16 Sep 2019)
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Samantha J. Basile et al.
Data sets

Simulated CO2 dataset using the atmospheric transport model GEOSChem v12.0.0: Response to regional land carbon fluxes S. Basile, X. Lin, and G. Keppel-Aleks https://doi.org/10.7302/xjzc-xy05

Samantha J. Basile et al.
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Short summary
Soil heterotrophic respiration (HR) is an important component of land-atmosphere carbon exchange, but is difficult to observe globally. We analyzed the imprint that this flux leaves on atmospheric CO2 using a set of simulations from HR models with common inputs. Models that represent microbial processes are more variable and have stronger temperature sensitivity than those that do not. Our results show that we can use atmospheric CO2 observations to evaluate and improve models of HR.
Soil heterotrophic respiration (HR) is an important component of land-atmosphere carbon...
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