Journal metrics

Journal metrics

  • IF value: 4.252 IF 4.252
  • IF 5-year value: 4.890 IF 5-year 4.890
  • CiteScore value: 4.49 CiteScore 4.49
  • SNIP value: 1.539 SNIP 1.539
  • SJR value: 2.404 SJR 2.404
  • IPP value: 4.28 IPP 4.28
  • h5-index value: 40 h5-index 40
  • Scimago H index value: 51 Scimago H index 51
Volume 11, issue 4 | Copyright
Geosci. Model Dev., 11, 1517-1536, 2018
https://doi.org/10.5194/gmd-11-1517-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

Model description paper 17 Apr 2018

Model description paper | 17 Apr 2018

Assimilating solar-induced chlorophyll fluorescence into the terrestrial biosphere model BETHY-SCOPE v1.0: model description and information content

Alexander J. Norton1, Peter J. Rayner1, Ernest N. Koffi2, and Marko Scholze3 Alexander J. Norton et al.
  • 1School of Earth Sciences, University of Melbourne, Melbourne, Australia
  • 2European Commission Joint Research Centre, Ispra, Italy
  • 3Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden

Abstract. The synthesis of model and observational information using data assimilation can improve our understanding of the terrestrial carbon cycle, a key component of the Earth's climate–carbon system. Here we provide a data assimilation framework for combining observations of solar-induced chlorophyll fluorescence (SIF) and a process-based model to improve estimates of terrestrial carbon uptake or gross primary production (GPP). We then quantify and assess the constraint SIF provides on the uncertainty in global GPP through model process parameters in an error propagation study. By incorporating 1 year of SIF observations from the GOSAT satellite, we find that the parametric uncertainty in global annual GPP is reduced by 73% from ±19.0 to ±5.2Pg C yr−1. This improvement is achieved through strong constraint of leaf growth processes and weak to moderate constraint of physiological parameters. We also find that the inclusion of uncertainty in shortwave down-radiation forcing has a net-zero effect on uncertainty in GPP when incorporated into the SIF assimilation framework. This study demonstrates the powerful capacity of SIF to reduce uncertainties in process-based model estimates of GPP and the potential for improving our predictive capability of this uncertain carbon flux.

Download & links
Publications Copernicus
Download
Short summary
It is difficult to estimate how much CO2 plants absorb via photosynthesis and even more difficult to model this for the whole globe. Here, we present a framework to combine a new satellite measurement "solar-induced chlorophyll fluorescence" with a global photosynthesis model. We then quantify how this new measurement constrains model uncertainties and find highly effective constraint. These results pave a novel pathway for improving estimates and modelling abilities of photosynthesis globally.
It is difficult to estimate how much CO2 plants absorb via photosynthesis and even more...
Citation
Share