气候变化领域集成服务门户(CCPortal): Carbon Flux Variability From a Relatively Simple Ecosystem Model With Assimilated Data Is Consistent With Terrestrial Biosphere Model Estimates

CCPortal

DOI	10.1029/2019MS001889
	Carbon Flux Variability From a Relatively Simple Ecosystem Model With Assimilated Data Is Consistent With Terrestrial Biosphere Model Estimates
	Quetin G.R.; Bloom A.A.; Bowman K.W.; Konings A.G.
发表日期	2020
ISSN	19422466
卷号	12 期号:3
英文摘要	Modeling the net carbon balance is challenging due to the knowledge gaps in the variability and processes controlling gross carbon fluxes. Terrestrial carbon cycle modeling is susceptible to several sources of bias, including meteorological uncertainty, model structural uncertainty, and model parametric uncertainty. To determine the impact of these uncertainties, we compare three model-derived representations of the global terrestrial carbon balance across 1997–2009: (1) observation-constrained model-data fusion (CARBon Data Model FraMEwork, CARDAMOM), (2) the reanalysis-driven Trends in Net Land-Atmosphere Carbon Exchange (TRENDY) land biosphere model ensemble, and (3) the Coupled Model Intercomparison Project 5 (CMIP5) Earth System Model ensemble. We consider the spread in carbon cycle simulations attributable primarily to parametric uncertainty (CARDAMOM), structural uncertainty (TRENDY), and combined structural and simulated meteorological uncertainty (CMIP5). We find that the spread across the CARDAMOM ensemble long-term mean—produced by parameter uncertainty—is larger than the spread of TRENDY and CMIP5 for net biosphere exchange (NBE) but similar for gross primary productivity (GPP). The carbon flux dynamics of CARDAMOM compares to models in TRENDY as well as models in TRENDY compare to each other in many regions for NBE seasonal (nine of 12), NBE interannual (11 of 12), and GPP seasonal variability (7 of 12), although not for GPP interannual variability (2 of 12). The simple model structure of CARDAMOM and systematic assimilation of observations is sufficient to produce carbon dynamics within the range of more complex models. These results are encouraging for the use of model-data fusion products with empirically estimated uncertainty for global carbon cycle studies. © 2020. The Authors.
英文关键词	carbon cycle; carbon modeling; data assimilation
语种	英语
scopus关键词	Biospherics; Carbon; Climate models; Data fusion; Earth atmosphere; Forestry; Carbon cycles; Carbon models; Coupled Model Intercomparison Project; Data assimilation; Gross primary productivity; Model structural uncertainties; Parametric uncertainties; Terrestrial carbon cycle; Uncertainty analysis; biosphere; carbon balance; carbon flux; CMIP; data assimilation; ecosystem modeling; estimation method; net ecosystem exchange; terrestrial ecosystem; uncertainty analysis
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/156753
作者单位	Department of Earth System Science, Stanford University, Stanford, CA, United States; Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States; Joint Institute for Regional Earth System Science and Engineering (JIFRESSE), University of California, Los Angeles, CA, United States
推荐引用方式 GB/T 7714	Quetin G.R.,Bloom A.A.,Bowman K.W.,et al. Carbon Flux Variability From a Relatively Simple Ecosystem Model With Assimilated Data Is Consistent With Terrestrial Biosphere Model Estimates[J],2020,12(3).
APA	Quetin G.R.,Bloom A.A.,Bowman K.W.,&Konings A.G..(2020).Carbon Flux Variability From a Relatively Simple Ecosystem Model With Assimilated Data Is Consistent With Terrestrial Biosphere Model Estimates.Journal of Advances in Modeling Earth Systems,12(3).
MLA	Quetin G.R.,et al."Carbon Flux Variability From a Relatively Simple Ecosystem Model With Assimilated Data Is Consistent With Terrestrial Biosphere Model Estimates".Journal of Advances in Modeling Earth Systems 12.3(2020).