Articles | Volume 18, issue 20
Biogeosciences, 18, 5639–5668, 2021
https://doi.org/10.5194/bg-18-5639-2021
Biogeosciences, 18, 5639–5668, 2021
https://doi.org/10.5194/bg-18-5639-2021

Research article 20 Oct 2021

Research article | 20 Oct 2021

Assessing the representation of the Australian carbon cycle in global vegetation models

Lina Teckentrup et al.

Data sets

Annual global automated MODIS vegetation continuous fields (MOD44B) at 250 m spatial resolution for data years beginning day 65, 2000–2014, collection 5 percent tree cover, version 6 C. M. DiMiceli, M. L. Carroll, R. A. Sohlberg, C. Huang, M. C. Hansen, and J. R. G. Townshend https://lpdaac.usgs.gov/products/mod44bv006/

Australian and New Zealand Flux Research and Monitoring OzFlux http://www.ozflux.org.au/

Recent reversal in loss of global terrestrial biomass (http://wald.anu.edu.au/global-biomass/) Y. Y. Liu, A. I. J. M. van Dijk, R. A. M. de Jeu, J. G. Canadell, M. F. McCabe, J. P. Evans, and G. Wang https://doi.org/10.1038/nclimate2581

A Global, 0.05-Degree Product of Solar-Induced Chlorophyll Fluorescence Derived from OCO-2, MODIS, and Reanalysis Data (https://globalecology.unh.edu/data/GOSIF-GPP.html) X. Li and J. Xiao https://doi.org/10.3390/rs11050517

CAMS Global Fire Assimilation System ECMWF https://apps.ecmwf.int/datasets/data/cams-gfas/

Global fire emissions estimates during 1997–2016 (https://globalfiredata.org/pages/data/) G. R. van der Werf, J. T. Randerson, L. Giglio, T. T. van Leeuwen, Y. Chen, B. M. Rogers, M. Mu, M. J. E. van Marle, D. C. Morton, G. J. Collatz, R. J. Yokelson, and P. S. Kasibhatla https://doi.org/10.5194/essd-9-697-2017

Model code and software

lteckentrup/TRENDY_v8_Australia: v1.0.0 (v1.0.0) Lina Teckentrup https://doi.org/10.5281/zenodo.5570974

Download
Short summary
The Australian continent is included in global assessments of the carbon cycle such as the global carbon budget, yet the performance of dynamic global vegetation models (DGVMs) over Australia has rarely been evaluated. We assessed simulations by an ensemble of dynamic global vegetation models over Australia and highlighted a number of key areas that lead to model divergence on both short (inter-annual) and long (decadal) timescales.
Altmetrics
Final-revised paper
Preprint