气候变化领域集成服务门户(CCPortal): Parametric Sensitivity of Vegetation Dynamics in the TRIFFID Model and the Associated Uncertainty in Projected Climate Change Impacts on Western U.S. Forests

CCPortal

DOI	10.1029/2018MS001577
	Parametric Sensitivity of Vegetation Dynamics in the TRIFFID Model and the Associated Uncertainty in Projected Climate Change Impacts on Western U.S. Forests
	Hawkins L.R.; Rupp D.E.; McNeall D.J.; Li S.; Betts R.A.; Mote P.W.; Sparrow S.N.; Wallom D.C.H.
发表日期	2019
ISSN	19422466
起始页码	2787
结束页码	2813
卷号	11 期号:8
英文摘要	Changing climate conditions impact ecosystem dynamics and have local to global impacts on water and carbon cycles. Many processes in dynamic vegetation models (DVMs) are parameterized, and the unknown/unknowable parameter values introduce uncertainty that has rarely been quantified in projections of forced changes. In this study, we identify processes and parameters that introduce the largest uncertainties in the vegetation state simulated by the DVM Top-down Representation of Interactive Foliage and Flora Including Dynamics (TRIFFID) coupled to a regional climate model. We adjust parameters simultaneously in an ensemble of equilibrium vegetation simulations and use statistical emulation to explore sensitivities to, and interactions among, parameters. We find that vegetation distribution is most sensitive to parameters related to carbon allocation and competition. Using a suite of statistical emulators, we identify regions of parameter space that reduce the error in modeled forest cover by 31±9%. We then generate large initial atmospheric condition ensembles with 10 improved DVM parameterizations under preindustrial, contemporary, and future climate conditions to assess uncertainty in the forced response due to parameterization. We find that while most parameterizations agree on the direction of future vegetation transitions in the western United States, the magnitude varies considerably: for example, in the northwest coast the expansion of broadleaf trees and corresponding decline of needleleaf trees ranges from 4 to 28% across 10 DVM parameterizations under projected future climate conditions. We demonstrate that model parameterization contributes to uncertainty in vegetation transition and carbon cycle feedback under nonstationary climate conditions, which has important implications for carbon stocks, ecosystem services, and climate feedback. © 2019. The Authors.
英文关键词	carbon allocation; dynamic global vegetation models; parameter uncertainty; sensitivity analysis; statistical emulator; vegetation transitions
语种	英语
scopus关键词	Carbon; Climate models; Digital voltmeters; Dynamics; Ecosystems; Forestry; Parameterization; Sensitivity analysis; Uncertainty analysis; Vegetation; Carbon allocation; Dynamic vegetation model; Initial atmospheric conditions; Parameter uncertainty; Regional climate modeling; statistical emulator; Vegetation distribution; Vegetation model; Climate change; biomass allocation; carbon cycle; climate change; climate conditions; ecological modeling; ecosystem dynamics; forest cover; parameter estimation; regional climate; sensitivity analysis; tree; uncertainty analysis; vegetation dynamics
来源期刊	Journal of Advances in Modeling Earth Systems
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156871
作者单位	Oregon Climate Change Research Institute, College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR, United States; Met Office Hadley Centre, Exeter, United Kingdom; Environmental Change Institute, School of Geography and the Environment, University of Oxford, Oxford, United Kingdom; Oxford e-Research Centre, University of Oxford, Oxford, United Kingdom; College of Life and Environmental Sciences, University of Exeter, Exeter, United Kingdom
推荐引用方式 GB/T 7714	Hawkins L.R.,Rupp D.E.,McNeall D.J.,et al. Parametric Sensitivity of Vegetation Dynamics in the TRIFFID Model and the Associated Uncertainty in Projected Climate Change Impacts on Western U.S. Forests[J],2019,11(8).
APA	Hawkins L.R..,Rupp D.E..,McNeall D.J..,Li S..,Betts R.A..,...&Wallom D.C.H..(2019).Parametric Sensitivity of Vegetation Dynamics in the TRIFFID Model and the Associated Uncertainty in Projected Climate Change Impacts on Western U.S. Forests.Journal of Advances in Modeling Earth Systems,11(8).
MLA	Hawkins L.R.,et al."Parametric Sensitivity of Vegetation Dynamics in the TRIFFID Model and the Associated Uncertainty in Projected Climate Change Impacts on Western U.S. Forests".Journal of Advances in Modeling Earth Systems 11.8(2019).