Articles | Volume 15, issue 1
https://doi.org/10.5194/bg-15-187-2018
https://doi.org/10.5194/bg-15-187-2018
Research article
 | 
10 Jan 2018
Research article |  | 10 Jan 2018

Evaluation and uncertainty analysis of regional-scale CLM4.5 net carbon flux estimates

Hanna Post, Harrie-Jan Hendricks Franssen, Xujun Han, Roland Baatz, Carsten Montzka, Marius Schmidt, and Harry Vereecken

Related authors

Actual evapotranspiration and precipitation measured by lysimeters: a comparison with eddy covariance and tipping bucket
S. Gebler, H.-J. Hendricks Franssen, T. Pütz, H. Post, M. Schmidt, and H. Vereecken
Hydrol. Earth Syst. Sci., 19, 2145–2161, https://doi.org/10.5194/hess-19-2145-2015,https://doi.org/10.5194/hess-19-2145-2015, 2015
Uncertainty analysis of eddy covariance CO2 flux measurements for different EC tower distances using an extended two-tower approach
H. Post, H. J. Hendricks Franssen, A. Graf, M. Schmidt, and H. Vereecken
Biogeosciences, 12, 1205–1221, https://doi.org/10.5194/bg-12-1205-2015,https://doi.org/10.5194/bg-12-1205-2015, 2015
Short summary

Related subject area

Biogeochemistry: Modelling, Terrestrial
Future methane fluxes of peatlands are controlled by management practices and fluctuations in hydrological conditions due to climatic variability
Vilna Tyystjärvi, Tiina Markkanen, Leif Backman, Maarit Raivonen, Antti Leppänen, Xuefei Li, Paavo Ojanen, Kari Minkkinen, Roosa Hautala, Mikko Peltoniemi, Jani Anttila, Raija Laiho, Annalea Lohila, Raisa Mäkipää, and Tuula Aalto
Biogeosciences, 21, 5745–5771, https://doi.org/10.5194/bg-21-5745-2024,https://doi.org/10.5194/bg-21-5745-2024, 2024
Short summary
Understanding and simulating cropland and non-cropland burning in Europe using the BASE (Burnt Area Simulator for Europe) model
Matthew Forrest, Jessica Hetzer, Maik Billing, Simon P. K. Bowring, Eric Kosczor, Luke Oberhagemann, Oliver Perkins, Dan Warren, Fátima Arrogante-Funes, Kirsten Thonicke, and Thomas Hickler
Biogeosciences, 21, 5539–5560, https://doi.org/10.5194/bg-21-5539-2024,https://doi.org/10.5194/bg-21-5539-2024, 2024
Short summary
Representation of the terrestrial carbon cycle in CMIP6
Bettina K. Gier, Manuel Schlund, Pierre Friedlingstein, Chris D. Jones, Colin Jones, Sönke Zaehle, and Veronika Eyring
Biogeosciences, 21, 5321–5360, https://doi.org/10.5194/bg-21-5321-2024,https://doi.org/10.5194/bg-21-5321-2024, 2024
Short summary
Does dynamically modeled leaf area improve predictions of land surface water and carbon fluxes? Insights into dynamic vegetation modules
Sven Armin Westermann, Anke Hildebrandt, Souhail Bousetta, and Stephan Thober
Biogeosciences, 21, 5277–5303, https://doi.org/10.5194/bg-21-5277-2024,https://doi.org/10.5194/bg-21-5277-2024, 2024
Short summary
Observational benchmarks inform representation of soil organic carbon dynamics in land surface models
Kamal Nyaupane, Umakant Mishra, Feng Tao, Kyongmin Yeo, William J. Riley, Forrest M. Hoffman, and Sagar Gautam
Biogeosciences, 21, 5173–5183, https://doi.org/10.5194/bg-21-5173-2024,https://doi.org/10.5194/bg-21-5173-2024, 2024
Short summary

Cited articles

Abramowitz, G., Leuning, R., Clark, M., and Pitman, A.: Evaluating the performance of land surface models, J. Climate, 21, 5468–5481, 2008.
Ahlstrom, A., Schurgers, G., Arneth, A., and Smith, B.: Robustness and uncertainty in terrestrial ecosystem carbon response to CMIP5 climate change projections, Environ. Res. Lett., 7, 4, https://doi.org/10.1088/1748-9326/7/4/044008, 2012.
Ali, M., Montzka, C., Stadler, A., Menz, G., Thonfeld, F., and Vereecken, H.: Estimation and Validation of RapidEye-Based Time-Series of Leaf Area Index for Winter Wheat in the Rur Catchment (Germany), Remote Sens., 7, 2808–2831, https://doi.org/10.3390/rs70302808, 2015.
Anderson, M. C., Kustas, W. P., and Norman, J. M.: Upscaling and Downscaling – A Regional View of the Soil–Plant–Atmosphere Continuum, Agron. J., 95, 1408–1423, https://doi.org/10.2134/agronj2003.1408, 2003.
Arora, V. K., Boer, G. J., Friedlingstein, P., Eby, M., Jones, C. D., Christian, J. R., Bonan, G., Bopp, L., Brovkin, V., Cadule, P., Hajima, T., Ilyina, T., Lindsay, K., Tjiputra, J. F., and Wu, T.: Carbon–Concentration and Carbon–Climate Feedbacks in CMIP5 Earth System Models, J. Climate, 26, 5289–5314, https://doi.org/10.1175/JCLI-D-12-00494.1, 2013.
Download
Short summary
Estimated values of selected key CLM4.5-BGC parameters obtained with the Markov chain Monte Carlo (MCMC) approach DREAM(zs) strongly altered catchment-scale NEE predictions in comparison to global default parameter values. The effect of perturbed meteorological input data on the uncertainty of the predicted carbon fluxes was notably higher for C3-grass and C3-crop than for coniferous and deciduous forest. A future distinction of different crop types including management is considered essential.
Altmetrics
Final-revised paper
Preprint