Identifying environmental controls on vegetation greenness phenology through model–data integration

摘要: Existing dynamic global vegetation models (DGVMs) have a limited ability in reproducing phenology and decadal dynamics of greenness as observed by satellites. These limitations observations reflect poor understanding description the environmental controls on phenology, which strongly influence to simulate longer-term dynamics, e.g. carbon allocation. Combining DGVMs with observational data sets can potentially help revise current modelling approaches thus enhance processes that control seasonal long-term dynamics. Here we implemented new model within LPJmL (Lund Potsdam Jena managed lands) DGVM integrated several improve satellite-derived time series greenness. Specifically, optimized parameters against fraction absorbed photosynthetic active radiation (FAPAR), albedo gross primary production identify main for We demonstrated better reproduces seasonality, inter-annual variability trends Our results indicate soil water availability is an important not only water-limited biomes but also boreal forests Arctic tundra. Whereas ecosystems during entire growing season, co-modulates jointly temperature beginning season regions. Additionally, contributes explain greening Sahel browning forests. emphasize importance considering generation modules order correctly reproduce seasonal-to-decadal