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Codominant water control on global interannual variability and trends in land surface phenology and greenness

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Forkel,  Matthias
Model-Data Integration, Dr. Nuno Carvalhais, 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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Migliavacca,  Mirco
Biosphere-Atmosphere Interactions and Experimentation, Dr. M. Migliavacca, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Reichstein,  Markus
Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Weber,  Ulrich
Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Carvalhais,  Nuno
Model-Data Integration, Dr. Nuno Carvalhais, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Citation

Forkel, M., Migliavacca, M., Thonicke, K., Reichstein, M., Schaphoff, S., Weber, U., et al. (2015). Codominant water control on global interannual variability and trends in land surface phenology and greenness. Global Change Biology, 21(9), 3414-3435. doi:10.1111/gcb.12950.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0026-B8E5-7
Abstract
Identifying the relative importance of climatic and other environmental controls on the inter-annual variability and trends in global land surface phenology and greenness is challenging. Firstly, quantifications of land surface phenology and greenness dynamics are impaired by differences between satellite datasets and phenology detection methods. Secondly, dynamic global vegetation models (DGVM) that can be used to diagnose controls still reveal structural limitations and contrasting sensitivities to environmental drivers. Thus we assessed the performance of a new developed phenology module within the LPJmL (Lund Potsdam Jena managed Lands) DGVM with a comprehensive ensemble of three satellite datasets of vegetation greenness and ten phenology detection methods, thereby thoroughly accounting for observational uncertainties. The improved and tested model allows us quantifying the relative importance of environmental controls on inter-annual variability and trends of land surface phenology and greenness at regional and global scales. We found that start of growing season inter-annual variability and trends are in addition to cold temperature mainly controlled by incoming radiation and water availability in temperate and boreal forests. Warming-induced prolongations of the growing season in high latitudes are dampened by a limited availability of light. For peak greenness, inter-annual variability and trends are dominantly controlled by water availability and land use and land cover change (LULCC) in all regions. Stronger greening trends in boreal forests of Siberia than in North America are associated to a stronger increase in water availability from melting permafrost soils. Our findings emphasize that in addition to cold temperatures, water availability is a co-dominant control for start of growing season and peak greenness trends at the global scale.