气候变化领域集成服务门户(CCPortal): INFERRING CHANGES TO THE GLOBAL CARBON CYCLE WITH WOMBAT V2.0, A HIERARCHICAL FLUX-INVERSION FRAMEWORK

CCPortal

DOI	10.1214/23-AOAS1790
	INFERRING CHANGES TO THE GLOBAL CARBON CYCLE WITH WOMBAT V2.0, A HIERARCHICAL FLUX-INVERSION FRAMEWORK
	Bertolacci, Michael; Zammit-Mangion, Andrew; Schuh, Andrew; Bukosa, Beata; Fisher, Jenny A.; Cao, Yi; Kaushik, Aleya; Cressie, Noel
发表日期	2024
ISSN	1932-6157
EISSN	1941-7330
起始页码	18
结束页码	1
卷号	18 期号:1
英文摘要	The natural cycles of the surface-to-atmosphere fluxes of carbon dioxide (CO2) and other important greenhouse gases are changing in response to human influences. These changes need to be quantified to understand climate change and its impacts, but this is difficult to do because natural fluxes occur over large spatial and temporal scales and cannot be directly observed. Flux inversion is a technique that estimates the spatiotemporal distribution of a gas' fluxes using observations of the gas' mole fraction and a chemical transport model. To infer trends in fluxes and identify phase shifts and amplitude changes in flux seasonal cycles, we construct a flux-inversion system that uses a novel spatially-varying time-series decomposition of the fluxes. We incorporate this decomposition into the Wollongong Methodology for Bayesian Assimilation of Trace-gases (WOMBAT, Zammit-Mangion et al., Geosci. Model Dev., 15, 2022), a Bayesian hierarchical flux-inversion framework that yields posterior distributions for all unknowns in the underlying model. We also extend WOMBAT to accommodate physical constraints on the fluxes and to take direct in situ and flask measurements of trace-gas mole fractions as observations. We apply the new method, which we call WOMBAT v2.0, to a mix of satellite observations of CO2 mole fraction from the Orbiting Carbon Observatory-2 (OCO-2) satellite and direct measurements of CO2 mole fraction from a variety of sources. We estimate the changes in the natural cycles of CO2 fluxes that occurred from January 2015 to December 2020, and compare our posterior estimates to those from an alternative method based on a bottom-up understanding of the physical processes involved. We find substantial trends in the fluxes, including that tropical ecosystems trended from being a net source to a net sink of CO2 over the study period. We also find that the amplitude of the global seasonal cycle of ecosystem CO2 fluxes increased over the study period by 0.11 PgC/month (an increase of 8%) and that the seasonal cycle of ecosystem CO2 fluxes in the northern temperate and northern boreal regions shifted earlier in the year by 0.4-0.7 and 0.4- 0.9 days, respectively (2.5th to 97.5th posterior percentiles), consistent with expectations for the carbon cycle under a warming climate.
英文关键词	Carbon cycle; hierarchical; Bayesian; flux inversion; carbon dioxide
语种	英语
WOS研究方向	Mathematics
WOS类目	Statistics & Probability
WOS记录号	WOS:001162997500022
来源期刊	ANNALS OF APPLIED STATISTICS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/306147
作者单位	University of Wollongong; Colorado State University; National Institute of Water & Atmospheric Research (NIWA) - New Zealand; University of Wollongong; University of Colorado System; University of Colorado Boulder
推荐引用方式 GB/T 7714	Bertolacci, Michael,Zammit-Mangion, Andrew,Schuh, Andrew,et al. INFERRING CHANGES TO THE GLOBAL CARBON CYCLE WITH WOMBAT V2.0, A HIERARCHICAL FLUX-INVERSION FRAMEWORK[J],2024,18(1).
APA	Bertolacci, Michael.,Zammit-Mangion, Andrew.,Schuh, Andrew.,Bukosa, Beata.,Fisher, Jenny A..,...&Cressie, Noel.(2024).INFERRING CHANGES TO THE GLOBAL CARBON CYCLE WITH WOMBAT V2.0, A HIERARCHICAL FLUX-INVERSION FRAMEWORK.ANNALS OF APPLIED STATISTICS,18(1).
MLA	Bertolacci, Michael,et al."INFERRING CHANGES TO THE GLOBAL CARBON CYCLE WITH WOMBAT V2.0, A HIERARCHICAL FLUX-INVERSION FRAMEWORK".ANNALS OF APPLIED STATISTICS 18.1(2024).