DOI: 10.1007/s10584-016-1694-1
Scopus记录号: 2-s2.0-84968658988
论文题名: Integrating parameter uncertainty of a process-based model in assessments of climate change effects on forest productivity
作者: Reyer C.P.O. ; Flechsig M. ; Lasch-Born P. ; van Oijen M.
刊名: Climatic Change
ISSN: 0165-0009
EISSN: 1573-1480
出版年: 2016
卷: 137, 期: 2018-03-04 起始页码: 395
结束页码: 409
语种: 英语
Scopus关键词: Calibration
; Climate models
; Ecosystems
; Forestry
; Uncertainty analysis
; Climate change impact
; Degree of uncertainty
; Effect of parameters
; Net primary productivity
; Parameter combination
; Parameter uncertainty
; Parameter variability
; Process-based modeling
; Climate change
; climate change
; climate effect
; climate modeling
; coniferous forest
; integrated approach
; net primary production
; research work
; uncertainty analysis
; Pinus sylvestris
英文摘要: The parameter uncertainty of process-based models has received little attention in climate change impact studies. This paper aims to integrate parameter uncertainty into simulations of climate change impacts on forest net primary productivity (NPP). We used either prior (uncalibrated) or posterior (calibrated using Bayesian calibration) parameter variations to express parameter uncertainty, and we assessed the effect of parameter uncertainty on projections of the process-based model 4C in Scots pine (Pinus sylvestris) stands under climate change. We compared the uncertainty induced by differences between climate models with the uncertainty induced by parameter variability and climate models together. The results show that the uncertainty of simulated changes in NPP induced by climate model and parameter uncertainty is substantially higher than the uncertainty of NPP changes induced by climate model uncertainty alone. That said, the direction of NPP change is mostly consistent between the simulations using the standard parameter setting of 4C and the majority of the simulations including parameter uncertainty. Climate change impact studies that do not consider parameter uncertainty may therefore be appropriate for projecting the direction of change, but not for quantifying the exact degree of change, especially if parameter combinations are selected that are particularly climate sensitive. We conclude that if a key objective in climate change impact research is to quantify uncertainty, parameter uncertainty as a major factor driving the degree of uncertainty of projections should be included. © 2016, Springer Science+Business Media Dordrecht. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/84249
Appears in Collections: 气候减缓与适应 气候变化事实与影响
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作者单位: Potsdam Institute for Climate Impact Research, Telegrafenberg, P.O. Boxs 601203, Potsdam, Germany; Department of Geography, Humboldt University Berlin, Berlin, Germany; Centre for Ecology and Hydrology, CEH-Edinburgh, Bush Estate, Penicuik, United Kingdom
Recommended Citation:
Reyer C.P.O.,Flechsig M.,Lasch-Born P.,et al. Integrating parameter uncertainty of a process-based model in assessments of climate change effects on forest productivity[J]. Climatic Change,2016-01-01,137(2018-03-04)