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Reference TypeConference Paper (Conference Proceedings)
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Sitemtc-m21d.sid.inpe.br (namespace prefix: upn:44QHRCS)
Identifier8JMKD3MGP3W34T/4AC7UGB
Repositorysid.inpe.br/mtc-m21d/2023/12.11.13.00
Metadata Repositorysid.inpe.br/mtc-m21d/2023/12.11.13.00.42
Metadata Last Update2024:01.02.17.16.56 (UTC) administrator
Secondary KeyINPE--PRE/
Citation KeyYunLiByWeOtGaMc:2023:QuErRe
TitleQuantifying errors in regional terrestrial biosphere CO2 fluxes in OCO-2 MIP models using aircraft measurements
Year2023
Access Date2026, Oct. 25
Secondary TypePRE CI
2. Context
Author1 Yun, Jeongmin
2 Liu, Junjie
3 Byrne, Brendan
4 Weir, Brad
5 Ott, Lesley E.
6 Gatti, Luciana Vanni
7 McKain, Kathryn
Group1
2
3
4
5
6 DIIAV-CGCT-INPE-MCTI-GOV-BR
Affiliation1 California Institute of Technology
2 California Institute of Technology
3 California Institute of Technology
4 NASA Goddard Space Flight Center
5 NASA Goddard Space Flight Center
6 Instituto Nacional de Pesquisas Espaciais (INPE)
7 NOAA ESRL Global Monitoring Division
Author e-Mail Address1
2
3
4
5
6 luciana.gatti@inpe.br
Conference NameAGU FAll Meeting
Conference LocationSan Francisco, CA
Date11-15 Dec. 2023
PublisherAGU
Book TitleProceedings
Host Collectionurlib.net/www/2021/06.04.03.40 upn:44QHRCS
History (UTC)2023-12-11 13:00:42 :: simone -> administrator ::
2024-01-02 17:16:56 :: administrator -> simone :: 2023
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
AbstractMulti-inverse modeling inter-comparison projects (MIPs) provide a chance to assess the uncertainties in inversion estimates arising from various sources such as atmospheric CO2 observations, transport models, and prior fluxes. However, accurately quantifying ensemble flux errors remains challenging, often relying on the ensemble spread as a surrogate. This presentation proposes an approach to quantify the errors of regional terrestrial CO2 flux estimates from ten inverse models within the Orbiting Carbon Observatory-2 MIP by utilizing independent aircraft CO2 measurements for the period 2015-2017. We first calculate the root-mean-square error (RMSE) between the ensemble mean of posterior CO2 concentrations and aircraft observations and then isolates the CO2 concentration errors caused solely by posterior CO2 fluxes by subtracting the errors of representation, transport, and observation in seven regions. Our analysis reveals significant regional variations in the average monthly RMSE over three years, ranging from 0.90 to 2.04 ppm. Posterior flux error is a major component that accounts for 57-83% of the mean RMSE. We further show that in five regions, the true posterior flux errors projected in CO2 space exceed the atmospheric CO2 errors resulted from the ensemble spread of posterior CO2 flux estimates by 1.4-1.9 times, implying underestimation of the true posterior flux errors, while their magnitudes are comparable in two regions. By identifying most sensitive areas to aircraft measurements through adjoint sensitivity analysis, we find that the underestimation of terrestrial flux errors is prominent in eastern parts of Australia and East Asia, western parts of Europe and Southeast Asia, and midlatitude North America. However, no such underestimation is observed in southern Alaska and northeastern South America, suggesting the presence of systematic biases related to anthropogenic CO2 emissions in inversion estimates. Our study highlights the critical role of aircraft measurements not only for qualitatively evaluating inversion performance but also for quantifying regional errors in ensemble flux estimates.
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Languageen
User Groupsimone
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/46KUATE
6. Notes
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