globalchange  > 气候变化与战略
DOI: 10.1029/2018GB006086
论文题名:
Quantifying the Impact of Atmospheric Transport Uncertainty on CO2 Surface Flux Estimates
作者: Schuh A.E.; Jacobson A.R.; Basu S.; Weir B.; Baker D.; Bowman K.; Chevallier F.; Crowell S.; Davis K.J.; Deng F.; Denning S.; Feng L.; Jones D.; Liu J.; Palmer P.I.
刊名: Global Biogeochemical Cycles
ISSN: 0886-6236
EISSN: 1944-9224
出版年: 2019
卷: 33, 期:4
语种: 英语
英文关键词: atmospheric chemistry ; atmospheric modeling ; atmospheric transport ; carbon dioxide ; data inversion ; EOS ; quantitative analysis ; satellite altimetry ; software ; source-sink dynamics ; surface flux ; uncertainty analysis
学科: atmosphere ; carbon ; GEOS-Chem ; inversions ; OCO-2 ; TM5
中文摘要: We show that transport differences between two commonly used global chemical transport models, GEOS-Chem and TM5, lead to systematic space-time differences in modeled distributions of carbon dioxide and sulfur hexafluoride. The distribution of differences suggests inconsistencies between the transport simulated by the models, most likely due to the representation of vertical motion. We further demonstrate that these transport differences result in systematic differences in surface CO2 flux estimated by a collection of global atmospheric inverse models using TM5 and GEOS-Chem and constrained by in situ and satellite observations. While the impact on inferred surface fluxes is most easily illustrated in the magnitude of the seasonal cycle of surface CO2 exchange, it is the annual carbon budgets that are particularly relevant for carbon cycle science and policy. We show that inverse model flux estimates for large zonal bands can have systematic biases of up to 1.7 PgC/year due to large-scale transport uncertainty. These uncertainties will propagate directly into analysis of the annual meridional CO2 flux gradient between the tropics and northern midlatitudes, a key metric for understanding the location, and more importantly the processes, responsible for the annual global carbon sink. The research suggests that variability among transport models remains the largest source of uncertainty across global flux inversion systems and highlights the importance both of using model ensembles and of using independent constraints to evaluate simulated transport. ©2019. The Authors
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/160134
Appears in Collections:气候变化与战略

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作者单位: Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, United States; University of Colorado Boulder and NOAA Earth System Research Laboratory, Boulder, CO, United States; Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, United States; Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States; Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, L'Orme des Merisiers, GifsurYvette, Paris, France; School of Meteorology, University of Oklahoma, Norman, OK, United States; Department of Meteorology and Atmospheric Science, Pennsylvania State University, University Park, PA, United States; Department of Physics, University of Toronto, Toronto, ON, Canada; Department of Atmospheric Sciences, Colorado State University, Fort Collins, CO, United States; School of GeoSciences, University of Edinburgh, Edinburgh, United Kingdom; National Centre for Earth Observation, Edinburgh, United Kingdom

Recommended Citation:
Schuh A.E.,Jacobson A.R.,Basu S.,et al. Quantifying the Impact of Atmospheric Transport Uncertainty on CO2 Surface Flux Estimates[J]. Global Biogeochemical Cycles,2019-01-01,33(4)
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