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Journal Article

LPJmL4 - a dynamic global vegetation model with managed land: Part II – Model evaluation

MPS-Authors
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Knauer,  Jürgen
Terrestrial Biosphere Modelling, Dr. Sönke Zähle, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;
IMPRS International Max Planck Research School for Global Biogeochemical Cycles, Max Planck Institute for Biogeochemistry, Max Planck Society;

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BGC2706D.pdf
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BGC2706s1.pdf
(Supplementary material), 10MB

Citation

Schaphoff, S., Forkel, M., Müller, C., Knauer, J., von Bloh, W., Gerten, D., et al. (2017). LPJmL4 - a dynamic global vegetation model with managed land: Part II – Model evaluation. Geoscientific Model Development Discussions. doi:10.5194/gmd-2017-146.


Cite as: https://hdl.handle.net/11858/00-001M-0000-002D-FE3C-B
Abstract
The dynamic global vegetation model LPJmL4 is a process-based model that simulates climate and land-use change impacts on the terrestrial biosphere, the water and carbon cycle and on agricultural production. Different versions of the model have been developed and applied to evaluate the role of natural and managed ecosystems in the Earth system and potential impacts of global environmental change. A comprehensive model description of the new model version, LPJmL4, is provided in a companion paper (Schaphoff et al., submitted). Here, we provide a full picture of the model performance, going beyond standard benchmark procedures, give hints of the strengths and shortcomings of the model to identify the need of further model improvement. Specifically, we evaluate LPJmL4 against various datasets from in-situ measurement sites, satellite observations, and agricultural yield statistics. We apply a range of metrics to evaluate the quality of the model to simulate stocks and flows of carbon and water in natural and managed ecosystems at different temporal and spatial scales. We show that an advanced phenology scheme improves the simulation of seasonal fluctuations in the atmospheric CO2 concentration while the permafrost scheme improves estimates of carbon stocks. The full LPJmL4 code including the new developments will be supplied Open Source through a Gitlab repository. We hope that this will lead to new model developments and applications that improve model performance and possibly build up a new understanding of the terrestrial biosphere.