2022
DOI: 10.5194/acp-22-8897-2022
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Interannual variability in the Australian carbon cycle over 2015–2019, based on assimilation of Orbiting Carbon Observatory-2 (OCO-2) satellite data

Abstract: Abstract. In this study, we employ a regional inverse modelling approach to estimate monthly carbon fluxes over the Australian continent for 2015–2019 using the assimilation of the total column-averaged mole fractions of carbon dioxide from the Orbiting Carbon Observatory-2 (OCO-2, version 9) satellite. Subsequently, we study the carbon cycle variations and relate their fluctuations to anomalies in vegetation productivity and climate drivers. Our 5-year regional carbon flux inversion suggests that Australia wa… Show more

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Cited by 8 publications
(11 citation statements)
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References 66 publications
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“…1) reveals a seasonal pattern above Australia with CO 2 drawdown in March, April, and May (MAM) and a CO 2 peak of variable magnitude at the end of the dry season in October, November, and December (OND). These patterns are consistent among two retrievals independently applied to GOSAT [GOSAT/RemoTeC ( 35 ) and GOSAT/ACOS ( 36 ); table S1], and they are present in CO 2 concentrations measured by the Orbiting Carbon Observatory-2 [OCO-2 ( 37 , 38 ), period 2015–2018; table S1) as well as in ground-based data of the Total Carbon Column Observing Network (TCCON) ( 39 ) (figs. S1 and S2).…”
Section: Atmospheric Co2 Peak Over Australiasupporting
confidence: 70%
“…1) reveals a seasonal pattern above Australia with CO 2 drawdown in March, April, and May (MAM) and a CO 2 peak of variable magnitude at the end of the dry season in October, November, and December (OND). These patterns are consistent among two retrievals independently applied to GOSAT [GOSAT/RemoTeC ( 35 ) and GOSAT/ACOS ( 36 ); table S1], and they are present in CO 2 concentrations measured by the Orbiting Carbon Observatory-2 [OCO-2 ( 37 , 38 ), period 2015–2018; table S1) as well as in ground-based data of the Total Carbon Column Observing Network (TCCON) ( 39 ) (figs. S1 and S2).…”
Section: Atmospheric Co2 Peak Over Australiasupporting
confidence: 70%
“…Previous studies have utilized OCO-2 based inversions to investigate regional carbon budgets using either global (Philip et al, 2022) or regional models (Villalobos et al, 2021), and their seasonal cycle and interannual variability (IAV) (Z. Peiro et al, 2022;Villalobos et al, 2022) and extreme climate impacts (Crowell et al, 2019;Kwon et al, 2021) over regions such as Australia, South Asia, and Siberia. However, such research on China is relatively scarce.…”
Section: Introductionmentioning
confidence: 99%
“…With a much smaller footprint size than the Greenhouse gases Observing Satellite (GOSAT), OCO‐2 collects about 100 times more samples per day (Crisp et al., 2022), offering greater data density and less spatially mixed atmospheric signals Therefore, OCO‐2 has potential to provide new insights into understanding carbon sources or sinks at regional scales (Philip et al., 2022). Previous studies have utilized OCO‐2 based inversions to investigate regional carbon budgets using either global (Philip et al., 2022) or regional models (Villalobos et al., 2021), and their seasonal cycle and interannual variability (IAV) (Z. Chen, Huntzinger, et al., 2021; Z. Chen, Liu, et al., 2021; Peiro et al., 2022; Villalobos et al., 2022) and extreme climate impacts (Crowell et al., 2019; Kwon et al., 2021) over regions such as Australia, South Asia, and Siberia. However, such research on China is relatively scarce.…”
Section: Introductionmentioning
confidence: 99%
“…OCO‐2 CMAQ regional CO 2 flux estimate was selected from Villalobos et al. (2022). This regional inverse system was set up to estimate fluxes across the Australian domain, including the New Zealand region, for 2015–2019.…”
Section: Methodsmentioning
confidence: 99%
“…Source/uncertainty reference Source/uncertainty reference SI Regional inversion CMAQ OCO-2 inversion (Villalobos et al, 2022)…”
Section: Top-downmentioning
confidence: 99%