001022139 001__ 1022139
001022139 005__ 20240226075430.0
001022139 0247_ $$2doi$$a10.5194/egusphere-egu23-11629
001022139 037__ $$aFZJ-2024-01260
001022139 1001_ $$0P:(DE-Juel1)169794$$aNaz, Bibi S.$$b0$$eCorresponding author
001022139 1112_ $$aEGU General Assembly 2023$$cVienna$$d2023-04-24 - 2023-04-28$$wAustria
001022139 245__ $$aParameter sensitivity analysis of vegetation and carbon dynamics using land surface model (CLM5-FATES) at European forest sites.
001022139 260__ $$c2023
001022139 3367_ $$033$$2EndNote$$aConference Paper
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001022139 3367_ $$0PUB:(DE-HGF)6$$2PUB:(DE-HGF)$$aConference Presentation$$bconf$$mconf$$s1706772574_9293$$xPlenary/Keynote
001022139 520__ $$aChanging environmental conditions impact ecosystem dynamics which have important implications for the land–atmosphere carbon and water exchanges. Land surface models coupled with dynamic vegetation models can be used to understand the impact of changes in terrestrial ecosystems on carbon and water cycles and their interactions with climate. However, process-based vegetation models are highly parameterized and have a large number of uncertain parameters, which lead to uncertainties in the model outputs. Here, we use a dynamic vegetation model, the Functionally Assembled Terrestrial Simulator (FATES) coupled to the Community Land Model (CLM v5) to analyze parameter sensitivities and its effects on forest growth, carbon storage and fluxes. We first calibrate allometry parameters to accurately describe plant functional types, representative of most abundant tree species across Europe (such as Norway spruce and European Beach), at three different European sites. Further, an ensemble of model simulations with perturbed parameters were performed and compared against observations to explore uncertainties in simulated vegetation structure and distributions (forest density, tree basal areas and above ground biomass) and their effects on ecosystem functioning (carbon, water and energy fluxes). Comparison with observation shows that the CLM5-FATES model is able to capture the interannual variability well for water and carbon fluxes (such as ET and GPP), but shows larger uncertainties for simulated forest structure (growth, establishment, and mortality). Future work will focus on parameter optimization to further improve model performance in simulating vegetation growth and composition for different vegetation distributions and climate conditions.
001022139 536__ $$0G:(DE-HGF)POF4-2173$$a2173 - Agro-biogeosystems: controls, feedbacks and impact (POF4-217)$$cPOF4-217$$fPOF IV$$x0
001022139 536__ $$0G:(EU-Grant)871128$$aeLTER PLUS - European long-term ecosystem, critical zone and socio-ecological systems research infrastructure PLUS (871128)$$c871128$$fH2020-INFRAIA-2019-1$$x1
001022139 588__ $$aDataset connected to CrossRef
001022139 7001_ $$0P:(DE-Juel1)180763$$aPoppe, Christian$$b1
001022139 7001_ $$0P:(DE-Juel1)138662$$aHendricks-Franssen, Harrie-Jan$$b2$$ufzj
001022139 773__ $$a10.5194/egusphere-egu23-11629
001022139 8564_ $$uhttps://meetingorganizer.copernicus.org/EGU23/EGU23-11629.html
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001022139 9141_ $$y2023
001022139 920__ $$lyes
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