Submitted as: development and technical paper |
| 04 Nov 2013
Status: this preprint was under review for the journal GMD but the revision was not accepted.
Are vegetation-specific model parameters required for estimating gross primary production?
W. Yuan,S. Liu,W. Cai,W. Dong,J. Chen,A. Arain,P. D. Blanken,A. Cescatti,G. Wohlfahrt,T. Georgiadis,L. Genesio,D. Gianelle,A. Grelle,G. Kiely,A. Knohl,D. Liu,M. Marek,L. Merbold,L. Montagnani,O. Panferov,M. Peltoniemi,S. Rambal,A. Raschi,A. Varlagin,and J. Xia
Abstract. Models of gross primary production (GPP) are currently parameterized with vegetation-specific parameter sets and therefore require accurate information on the distribution of vegetation to drive them. Can this parameterization scheme be replaced with a vegetation-invariant set of parameter that can maintain or increase model applicability by reducing errors introduced from the uncertainty of land cover classification? Based on the measurements of ecosystem carbon fluxes from 150 globally distributed sites in a range of vegetation types, we examined the predictive capacity of seven light use efficiency (LUE) models. Two model experiments were conducted: (i) a constant set of parameters for various vegetation types and (ii) vegetation-specific parameters. The results showed no significant differences in model performances to simulate GPP while using both sets of parameters. These results indicate that a universal set of parameters, which is independent of vegetation cover type and characteristics can be adopted in prevalent LUE models. Availability of this well tested and universal set of parameters would help to improve the accuracy and applicability of LUE models in various biomes and geographic regions.
Received: 19 Sep 2013 – Discussion started: 04 Nov 2013
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State Key Laboratory of Cryospheric Sciences, Cold and Arid Regions Environmental and Engineering Research Institute, The Chinese Academy of Sciences, Lanzhou, Gansu 730000, China
State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
S. Liu
State Engineering Laboratory of Southern Forestry Applied Ecology and Technology, Central South University of Forestry and Technology, Changsha, Hunan 410004, China
W. Cai
State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
W. Dong
State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
J. Chen
International Center for Ecology, Meteorology and Environment, School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Department of Environmental Sciences, University of Toledo, Toledo, OH 43606, USA