Preprints
https://doi.org/10.5194/esd-2020-93
https://doi.org/10.5194/esd-2020-93

  08 Jan 2021

08 Jan 2021

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

Modelled land use and land cover change emissions – A spatio-temporal comparison of different approaches

Wolfgang A. Obermeier1, Julia E. M. S. Nabel2, Tammas Loughran1, Kerstin Hartung1,a, Ana Bastos3, Felix Havermann1, Peter Anthoni4, Almut Arneth4, Daniel S. Goll5, Sebastian Lienert6, Danica Lombardozzi7, Sebastiaan Luyssaert8, Patrick C. McGuire9, Joe R. Melton10, Benjamin Poulter11, Stephen Sitch12, Michael O. Sullivan12, Hanqin Tian13, Anthony P. Walker14, Andrew J. Wiltshire12,15, Soenke Zaehle4, and Julia Pongratz1,2 Wolfgang A. Obermeier et al.
  • 1Department of Geography, Ludwig Maximilians Universität, Luisenstrasse 37, 80333 Munich, Germany
  • 2Max Planck Institute for Meteorology, 20146 Hamburg, Germany
  • 3Max Planck Institute for Biogeochemistry, 07745 Jena, Germany
  • 4Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research / Atmospheric Environmental Research, 82467 Garmisch-Partenkirchen, Germany
  • 5Laboratoire des Sciences du Climat et de l’Environnement (LSCE), 91191 Gif-sur-Yvette, France
  • 6Climate and Environmental Physics, Physics Institute and Oeschger Centre for Climate Change Research, University of Bern, Bern 3012, Switzerland
  • 7National Center for Atmospheric Research (NCAR), Climate & Global Dynamics Lab, Boulder, USA
  • 8Department of Ecological Science, Vrije Universiteit Amsterdam, 1081HV Amsterdam, the Netherlands
  • 9Department of Meteorology, University of Reading, Earley Gate, Reading RG6 6BB, UK
  • 10Climate Processes Section, Climate Research Division, Environment and Climate Change Canada, Victoria, BC, Canada
  • 11NASA Goddard Space Flight Center, Biospheric Sciences Laboratory, Greenbelt, Maryland 20771, USA
  • 12College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4RJ, UK
  • 13School of Forestry and Wildlife Sciences, Auburn University, 602 Ducan Drive, Auburn, AL 36849, USA
  • 14Climate Change Science Institute & Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
  • 15Met Office Hadley Centre, FitzRoy Road, Exeter EX1 3PB, UK
  • anow at: German Aerospace Center, Institute of Athmospheric Physics, 82234 Oberpfaffenhofen, Germany

Abstract. Quantifying the net carbon flux from land use and land cover changes (fLULCC) is critical for understanding the global carbon cycle, and hence, to support climate change mitigation. However, large-scale fLULCC is not directly measurable, but has to be inferred from models instead, such as semi-empirical bookkeeping models, and process-based dynamic global vegetation models (DGVMs). By definition, fLULCC estimates are not directly comparable between these two different model types. As an example, DGVM-based fLULCC in the annual global carbon budgets is estimated under transient environmental forcing and includes the so-called Loss of Additional Sink Capacity (LASC). The LASC accounts for the impact of environmental changes on land carbon storage potential of managed land compared to potential vegetation which is not represented in bookkeeping models. In addition, fLULCC from transient DGVM simulations differs depending on the arbitrary chosen simulation time period and the historical timing of land use and land cover changes (including different accumulation periods for legacy effects). An approximation of fLULCC by DGVMs that is independent of the timing of land use and land cover changes and their legacy effects requires simulations assuming constant pre-industrial or present-day environmental forcings. Here, we analyze three DGVM-derived fLULCC estimations for twelve models within 18 regions and quantify their differences as well as climate- and CO2-induced components. The three estimations stem from the commonly performed simulation with transiently changing environmental conditions and two simulations that keep environmental conditions fixed, at pre-industrial and present-day conditions. Averaged across the models, we find a global fLULCC (under transient conditions) of 2.0 ± 0.6 PgC yr-1 for 2009–2018, of which ∼40 % are attributable to the LASC (0.8 ± 0.3 PgC yr-1). From 1850 onward, fLULCC accumulated to 189 ± 56 PgC with 40 ± 15 PgC from the LASC. Regional hotspots of high cumulative and annual LASC values are found in the USA, China, Brazil, Equatorial Africa and Southeast Asia, mainly due to deforestation for cropland. Distinct negative LASC estimates, in Europe (early reforestation) and from 2000 onward in the Ukraine (recultivation of post-Soviet abandoned agricultural land), indicate that fLULCC estimates in these regions are lower in transient DGVM- compared to bookkeeping-approaches. By unraveling spatio-temporal variability in three alternative DGVM-derived fLULCC estimates, our results call for a harmonized attribution of model-derived fLULCC. We propose an approach that bridges bookkeeping and DGVM approaches for fLULCC estimation by adopting a mean DGVM-ensemble LASC for a defined reference period.

Wolfgang A. Obermeier et al.

Status: open (until 19 Feb 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on esd-2020-93', Anonymous Referee #1, 18 Jan 2021 reply

Wolfgang A. Obermeier et al.

Wolfgang A. Obermeier et al.

Viewed

Total article views: 310 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
230 68 12 310 4 4
  • HTML: 230
  • PDF: 68
  • XML: 12
  • Total: 310
  • BibTeX: 4
  • EndNote: 4
Views and downloads (calculated since 08 Jan 2021)
Cumulative views and downloads (calculated since 08 Jan 2021)

Viewed (geographical distribution)

Total article views: 225 (including HTML, PDF, and XML) Thereof 221 with geography defined and 4 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 22 Jan 2021
Download
Short summary
This study, for the first time, presents a spatio-temporally explicit comparison of different model-derived land-use and land cover change emissions (ELUCs) based on the TRENDY v8 dynamic global vegetation models (used in the Global Carbon Budget of 2019). We find huge regional ELUC differences resulting from environmental assumptions, simulated periods and the timing of land use and land cover changes and propose a modified definition to standardize ELUC attribution across time and space.
Altmetrics