Abstract
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.
Highlights
The greenness of the terrestrial vegetation is directly linked to plant productivity, surface roughness and albedo and affects the climate system (Richardson et al, 2013)
The newly developed LPJmL-growing season index (GSI) phenology model resulted in significantly higher correlations with monthly GIMMS3g fraction of absorbed photosynthetic active radiation (FAPAR) than LPJmL-OP in all plant functional types (PFTs) except in the tropical broadleaved evergreen (TrBE) and boreal broadleaved summergreen (BoBS) PFTs (Fig. 4)
The use of the newly developed LPJmL-GSI phenology model already significantly improved the correlation with monthly GIMMS3g FAPAR in all PFTs except in the temperate herbaceous (TeH) and BoBS PFTs
Summary
The greenness of the terrestrial vegetation is directly linked to plant productivity, surface roughness and albedo and affects the climate system (Richardson et al, 2013). Decadal satellite observations of NDVI demonstrate widespread positive trends (“greening”) especially in the high-latitude regions (Lucht et al, 2002; Myneni et al, 1997a; Xu et al, 2013) and in the Sahel, southern Africa and southern Australia (Fensholt and Proud, 2012; de Jong et al, 2011, 2013b). Greening trends in high latitudes are associated with decreasing surface albedo (Urban et al, 2013) which alters the surface radiation budget (Loranty et al, 2011) This can potentially further contribute to a warming of Arctic regions (Chapin et al, 2005). Satellite observations of vegetation greenness demonstrate the recent interactions and changes between terrestrial vegetation dynamics and the climate system
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