Terrestrial Biological Nitrogen Fixation in CMIP6 Models
- 1University of Exeter, University of Exeter, College of Engineering, Mathamatics and Physical Sciences, Bristol, United Kingdom of Great Britain and Northern Ireland (t.davies-barnard@exeter.ac.uk)
- 2Max Planck Institute for Biogeochemistry, Jena, Germany
- 3Laboratoire de Meteorologie Dynamique, Institut Pierre-Simon Laplace, CNRS-ENS-UPMC-X, Departement de Geosciences, Ecole Normale Superieure, 24 rue Lhomond, 75005 Paris, France
- 4Max Planck Institute for Meteorology, Hamburg, Germany
- 5NORCE Norwegian Research Centre, Bjerknes Centre for Climate Research, Bergen, Norway
- 6Harvard University, Cambridge, USA
- 7National Center for Atmospheric Research, Boulder, Colorado, USA
- 8Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique, Toulouse, France
- 9Met Office Hadley Centre, Exeter, UK
- 10Fondazione Centro euro-Mediterraneo sui Cambiamenti Climatici, Bologna, Italy
- 11Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
- 12Hawkesbury Institute for the Environment, Western Sydney University, Richmond, Australia
- 13CSIRO Oceans and Atmosphere, Aspendale, VIC, 3195, Australia
Biological nitrogen fixation (BNF) is a key contributor to sustaining the terrestrial carbon cycle, providing nitrogen input that plants require. This is particularly salient for projections of carbon uptake under increased atmospheric carbon dioxide concentrations, which may allow for so-called ‘carbon dioxide fertilisation’ if other plant requirements, such as nitrogen, do not prevent increases in productivity. The amount, processes, and global distribution of BNF is highly disputed and consequently land surface models represent it in varying ways. Looking at the latest generation of CMIP6 earth system models with terrestrial nitrogen cycles, we consider their performance with regard to BNF. We assess models against a new comprehensive meta-analysis of BNF field measurements that gives a global range and site-specific values. We find that compared to the wide range of upscaled observations, the models still have a larger range, with under and overestimates.
How to cite: Davies-Barnard, T., Meyerholt, J., Zaehle, S., Friedlingstein, P., Brovkin, V., Fan, Y., Fisher, R., Jones, C., Lee, H., Peano, D., Smith, B., Wårlind, D., Wiltshire, A., and Ziehn, T.: Terrestrial Biological Nitrogen Fixation in CMIP6 Models, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1951, https://doi.org/10.5194/egusphere-egu2020-1951, 2020
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Very interesting! Do any models consider both NPP and EP to project BNF? Do any model use process-based (opposed to empirical) BNF representation? Does inclusion/exclusion of BNF cause any uncertainty on GPP estimation by ESM?
Hi, thanks for your comment. Responses below:
> Do any models consider both NPP and EP to project BNF?
Although no models use both NPP and ET simultaneously, there are studies on the effect of calculating BNF in different ways with a single model, including NPP and ET (Meyerholt et al. (2016), Variability of projected terrestrial biosphere responses to elevated levels of atmospheric CO2 due to uncertainty in biological nitrogen fixation).
> Do any model use process-based (opposed to empirical) BNF representation?
Yes, to be fair to CLM5 and ACCESS, they are both (more) process based. Both are underpinned by NPP, which is why I call it an 'indirect' relationship with NPP. But robust process based functions of BNF are tricky because: 1) the total amount and spatial distribution of BNF is not well constrained (see Davies-Barnard and Friedlingstein 2020), 2) the processes controlling BNF are not well understood, 3) BNF occurs in a very wide range of organisms, each of which responds differently to stimulus (see Reed et al. 2011, Functional Ecology of Free-Living Nitrogen Fixation: A Contemporary Perspective).
> Does inclusion/exclusion of BNF cause any uncertainty on GPP estimation by ESM?
This is really a question about inclusion of the N cycle, (as BNF will only be included in an ESM within an N cycle, and a terrestrial N cycle must include BNF). At the global scale GPP is fairly well constrained (by, for instance, Jung et al. 2011) and well represented by both C only and CN models. But there is evidence that omission of the N cycle can have large effects on regional GPP projections (Zaehle et al. 2014, Nitrogen Availability Reduces CMIP5 Projections of Twenty-First-Century Land Carbon Uptake).
Thank you very much for the detailed response and for the references!