Preprints
https://doi.org/10.5194/esd-2020-92
https://doi.org/10.5194/esd-2020-92

  11 Jan 2021

11 Jan 2021

Review status: this preprint is currently under review for the journal ESD.

Comparison of uncertainties in land-use change fluxes from bookkeeping model parameterization

Ana Bastos1,2, Kerstin Hartung1, Tobias B. Nützel1, Julia E. M. S. Nabel3, Richard A. Houghton4, and Julia Pongratz1,3 Ana Bastos et al.
  • 1Department of Geography, Ludwig Maximilian University of Munich, 80333 Munich, Germany
  • 2Max Planck Institute for Biogeochemistry, Department of Biogeochemical Integration, 07745 Jena, Germany
  • 3Max Planck Institute for Meteorology, 20146 Hamburg, Germany
  • 4Woods Hole Research Center, Falmouth, 02540, USA

Abstract. Fluxes from deforestation, changes in land-cover, land-use and management practices (FLUC for simplicity) contributed to circa 14 % of anthropogenic CO2 emissions in 2009–2018. Estimating FLUC accurately in space and in time remains, however, challenging, due to multiple sources of uncertainty in the calculation of these fluxes. This uncertainty, in turn, is propagated to global and regional carbon budget estimates, hindering the compilation of a consistent carbon budget and preventing us from constraining other terms, such as the natural land sink. Uncertainties in FLUC estimates arise from many different sources, including differences in model structure (e.g., process- based vs. bookkeeping) and model parameterization. Quantifying the uncertainties from each source requires controlled simulations to separate their effects.

Here we analyze differences between the two bookkeeping models used regularly in the global carbon budget estimates since 2017: the model by Hansis et al. (Hansis et al., 2015) (BLUE) and that by Houghton and Nassikas (Houghton and Nassikas, 2017) (HN2017). The two models have a very similar structure and philosophy, but differ significantly both with respect to FLUC intensity and spatio-temporal variability. This is due to differences in the land-use forcing, but also in the model parameterization.

We find that the larger emissions in BLUE compared to HN2017 are largely due to differences in C densities between natural and managed vegetation or primary and secondary vegetation, and higher allocation of cleared and harvested material to fast turnover pools in BLUE than in HN2017. Beside parameterization and the use of different forcing, other model assumptions cause differences, in particular that BLUE represents gross transitions which leads to overall higher carbon losses that are also more quickly realized than HN2017.

Ana Bastos et al.

Status: open (until 22 Feb 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Ana Bastos et al.

Ana Bastos et al.

Viewed

Total article views: 227 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
189 36 2 227 0 1
  • HTML: 189
  • PDF: 36
  • XML: 2
  • Total: 227
  • BibTeX: 0
  • EndNote: 1
Views and downloads (calculated since 11 Jan 2021)
Cumulative views and downloads (calculated since 11 Jan 2021)

Viewed (geographical distribution)

Total article views: 179 (including HTML, PDF, and XML) Thereof 177 with geography defined and 2 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 22 Jan 2021
Download
Short summary
Fluxes from land-use change and management (FLUC) are a large source of uncertainty in global and regional carbon budgets. Here we evaluate the impact of different model parameterizarions on FLUC. We show that carbon stock densities and allocation of carbon following transitions contribute more to uncertainty in FLUC than response times. Uncertainty in FLUC could thus, in principle, be reduced by available earth-observation data on carbon densities at global scale.
Altmetrics