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Journal Article

Description and evaluation of the process-based forest model 4C v2.2 at four European forest sites


Lasch-Born,  Petra
Potsdam Institute for Climate Impact Research;


Suckow,  Felicitas
Potsdam Institute for Climate Impact Research;


Reyer,  Christopher P. O.
Potsdam Institute for Climate Impact Research;


Gutsch,  Martin
Potsdam Institute for Climate Impact Research;


Kollas,  Chris
Potsdam Institute for Climate Impact Research;

Badeck,  Franz-Werner
External Organizations;

Bugmann,  Harald K. M.
External Organizations;

Grote,  Rüdiger
External Organizations;

Fürstenau,  Cornelia
External Organizations;

Lindner,  Marcus

Schaber,  Jörg
External Organizations;

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Lasch-Born, P., Suckow, F., Reyer, C. P. O., Gutsch, M., Kollas, C., Badeck, F.-W., Bugmann, H. K. M., Grote, R., Fürstenau, C., Lindner, M., Schaber, J. (2020): Description and evaluation of the process-based forest model 4C v2.2 at four European forest sites. - Geoscientific Model Development, 13, 11, 5311-5343.

Cite as: https://publications.pik-potsdam.de/pubman/item/item_24497
The process-based model 4C (FORESEE) has been developed over the past twenty years. The objective of this paper is to give a comprehensive description of the main features of 4C and to present an evaluation of the model at four different forest sites across Europe. The evaluation was focused on growth parameters, carbon, water and heat fluxes. The main data source for the evaluation was the PROFOUND database. We applied different statistical metrics of evaluation and compared the inter-annual and inter-monthly variability of observed and simulated carbon and water fluxes. The ability to reproduce forest growth differs from site to site and is best for the pine stand site Peitz. The model's performance in simulating carbon and water fluxes was very satisfactory on daily and monthly time scales in contrast to the annual time scale. This underlines the conclusion that processes that are either not represented in dependence on on medium- to long-term dynamic influences such as allocation, or those that are not represented at all but may have a large impact at specific sites – such as the dynamics of non-structural carbohydrates (NSC) and ground vegetation growth – need to be elaborated for general forest growth investigations under climate change. On the other hand, 4C has shown a great potential for improvement since it emphasizes the representation of boundary conditions such as soil temperature at different depths. Therefore, more spatial differentiation of processes such as organ-specific respiration should easily be accomplished. Nonetheless, by using the PROFOUND database we were able to demonstrate the applicability and reliability of 4C.