LPJmL4 – a dynamic global vegetation model with managed land – Part 2: Model evaluation
- 1Potsdam Institute for Climate Impact Research, Telegraphenberg, P.O. Box 60 12 03, 14412 Potsdam, Germany
- 2TU Wien, Climate and Environmental Remote Sensing Group, Department of Geodesy and Geoinformation, Gusshausstraße 25–29, 1040 Vienna, Austria
- 3Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745 Jena, Germany
- 4Humboldt Universität zu Berlin, Department of Geography, Unter den Linden 6, 10099 Berlin, Germany
- 5Technical University of Munich, School of Life Sciences Weihenstephan, 85354 Freising, Germany
- 6CSIRO Agriculture & Food, 306 Carmody Rd, St Lucia QLD 4067, Australia
Abstract. The dynamic global vegetation model LPJmL4 is a process-based model that simulates climate and land use change impacts on the terrestrial biosphere, agricultural production, and the water and carbon cycle. Different versions of the model have been developed and applied to evaluate the role of natural and managed ecosystems in the Earth system and the 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., 2018c). Here, we provide a full picture of the model performance, going beyond standard benchmark procedures and give hints on the strengths and shortcomings of the model to identify the need for 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 https://gitlab.pik-potsdam.de/lpjml/LPJmL. We hope that this will lead to new model developments and applications that improve the model performance and possibly build up a new understanding of the terrestrial biosphere.