Journal cover Journal topic
Biogeosciences An interactive open-access journal of the European Geosciences Union
Biogeosciences, 11, 7025-7050, 2014
https://doi.org/10.5194/bg-11-7025-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
11 Dec 2014
Identifying environmental controls on vegetation greenness phenology through model–data integration
M. Forkel1, N. Carvalhais1,2, S. Schaphoff3, W. v. Bloh3, M. Migliavacca1, M. Thurner1,4, and K. Thonicke3 1Max-Planck-Institute for Biogeochemistry, Department for Biogeochemical Integration, Hans-Knöll-Str. 10, 07745 Jena, Germany
2Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia, 2829-516, Caparica, Portugal
3Potsdam Institute for Climate Impact Research, Earth System Analysis, Telegraphenberg A31, 14473 Potsdam, Germany
4Stockholm University, Department of Applied Environmental Science and Bolin Centre for Climate Research, Svante Arrhenius väg 8, 10691 Stockholm, Sweden
Abstract. Existing dynamic global vegetation models (DGVMs) have a limited ability in reproducing phenology and decadal dynamics of vegetation greenness as observed by satellites. These limitations in reproducing observations reflect a poor understanding and description of the environmental controls on phenology, which strongly influence the ability to simulate longer-term vegetation dynamics, e.g. carbon allocation. Combining DGVMs with observational data sets can potentially help to revise current modelling approaches and thus enhance the understanding of processes that control seasonal to long-term vegetation greenness dynamics. Here we implemented a new phenology model within the LPJmL (Lund Potsdam Jena managed lands) DGVM and integrated several observational data sets to improve the ability of the model in reproducing satellite-derived time series of vegetation greenness. Specifically, we optimized LPJmL parameters against observational time series of the fraction of absorbed photosynthetic active radiation (FAPAR), albedo and gross primary production to identify the main environmental controls for seasonal vegetation greenness dynamics. We demonstrated that LPJmL with new phenology and optimized parameters better reproduces seasonality, inter-annual variability and trends of vegetation greenness. Our results indicate that soil water availability is an important control on vegetation phenology not only in water-limited biomes but also in boreal forests and the Arctic tundra. Whereas water availability controls phenology in water-limited ecosystems during the entire growing season, water availability co-modulates jointly with temperature the beginning of the growing season in boreal and Arctic regions. Additionally, water availability contributes to better explain decadal greening trends in the Sahel and browning trends in boreal forests. These results emphasize the importance of considering water availability in a new generation of phenology modules in DGVMs in order to correctly reproduce observed seasonal-to-decadal dynamics of vegetation greenness.

Citation: Forkel, M., Carvalhais, N., Schaphoff, S., v. Bloh, W., Migliavacca, M., Thurner, M., and Thonicke, K.: Identifying environmental controls on vegetation greenness phenology through model–data integration, Biogeosciences, 11, 7025-7050, https://doi.org/10.5194/bg-11-7025-2014, 2014.
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