A 10-year global monthly averaged terrestrial net ecosystem exchange dataset inferred from the ACOS GOSAT v9 XCO 2 retrievals (GCAS2021)
In: Earth System Science Data, Vol 14, Pp 3013-3037 (2022, 2022
Online
academicJournal
Zugriff:
A global gridded net ecosystem exchange (NEE) of CO 2 dataset is vital in global and regional carbon cycle studies. Top-down atmospheric inversion is one of the major methods to estimate the global NEE; however, the existing global NEE datasets generated through inversion from conventional CO 2 observations have large uncertainties in places where observational data are sparse. Here, by assimilating the GOSAT ACOS v9 XCO 2 product, we generate a 10-year (2010–2019) global monthly terrestrial NEE dataset using the Global Carbon Assimilation System, version 2 (GCASv2), which is named GCAS2021. It includes gridded ( 1 ∘ × 1 ∘ ), globally, latitudinally, and regionally aggregated prior and posterior NEE and ocean (OCN) fluxes and prescribed wildfire (FIRE) and fossil fuel and cement (FFC) carbon emissions. Globally, the decadal mean NEE is - 3.73 ± 0.52 PgC yr −1 , with an interannual amplitude of 2.73 PgC yr −1 . Combining the OCN flux and FIRE and FFC emissions, the net biosphere flux (NBE) and atmospheric growth rate (AGR) as well as their inter-annual variabilities (IAVs) agree well with the estimates of the Global Carbon Budget 2020. Regionally, our dataset shows that eastern North America, the Amazon, the Congo Basin, Europe, boreal forests, southern China, and Southeast Asia are carbon sinks, while the western United States, .
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A 10-year global monthly averaged terrestrial net ecosystem exchange dataset inferred from the ACOS GOSAT v9 XCO 2 retrievals (GCAS2021)
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Autor/in / Beteiligte Person: | Jiang, F. ; Ju, W. ; He, W. ; Wu, M. ; Wang, H. ; Wang, J. ; Jia, M. ; Feng, S. ; Zhang, L. ; Chen, J. M. |
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Zeitschrift: | Earth System Science Data, Vol 14, Pp 3013-3037 (2022, 2022 |
Veröffentlichung: | Copernicus Publications, 2022 |
Medientyp: | academicJournal |
ISSN: | 1866-3508 (print) ; 1866-3516 (print) |
DOI: | 10.5194/essd-14-3013-2022 |
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