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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21d.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34T/45T93QE
Repositorysid.inpe.br/mtc-m21d/2021/12.03.16.14   (restricted access)
Last Update2021:12.03.16.14.29 (UTC) administrator
Metadata Repositorysid.inpe.br/mtc-m21d/2021/12.03.16.14.29
Metadata Last Update2022:04.04.04.50.16 (UTC) administrator
DOI10.5194/esd-12-1191-2021
ISSN2190-4979
Citation KeySmallmanMiSoGeOmWi:2021:PaUnDo
TitleParameter uncertainty dominates C-cycle forecast errors over most of Brazil for the 21st century
Year2021
MonthNov.
Access Date2024, May 09
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size29722 KiB
2. Context
Author1 Smallman, Thoma Luke
2 Milodowski, David Thomas
3 Sousa Neto, Eraclito Rodrigues de
4 Gerbrand, Koren
5 Ometto, Jean Pierre Henry Balbaud
6 Williams, Mathew
Group1
2
3
4
5 DIPE3-COGPI-INPE-MCTI-GOV-BR
Affiliation1
2
3
4
5 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1
2
3 eraklito@gmail.com
4
5 jean.ometto@inpe.br
JournalEarth System Dynamics
Volume12
Number4
Pages1191-1237
History (UTC)2021-12-03 16:14:29 :: simone -> administrator ::
2022-04-04 04:50:16 :: administrator -> simone :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
AbstractIdentification of terrestrial carbon (C) sources and sinks is critical for understanding the Earth system as well as mitigating and adapting to climate change resulting from greenhouse gas emissions. Predicting whether a given location will act as a C source or sink using terrestrial ecosystem models (TEMs) is challenging due to net flux being the difference between far larger, spatially and temporally variable fluxes with large uncertainties. Uncertainty in projections of future dynamics, critical for policy evaluation, has been determined using multi-TEM intercomparisons, for various emissions scenarios. This approach quantifies structural and forcing errors. However, the role of parameter error within models has not been determined. TEMs typically have defined parameters for specific plant functional types generated from the literature. To ascertain the importance of parameter error in forecasts, we present a Bayesian analysis that uses data on historical and current C cycling for Brazil to parameterise five TEMs of varied complexity with a retrieval of model error covariance at 1 degrees spatial resolution. After evaluation against data from 2001-2017, the parameterised models are simulated to 2100 under four climate change scenarios spanning the likely range of climate projections. Using multiple models, each with per pixel parameter ensembles, we partition forecast uncertainties. Parameter uncertainty dominates across most of Brazil when simulating future stock changes in biomass C and dead organic matter (DOM). Uncertainty of simulated biomass change is most strongly correlated with net primary productivity allocation to wood (NPPwood) and mean residence time of wood (MRTwood). Uncertainty of simulated DOM change is most strongly correlated with MRTsoil and NPPwood. Due to the coupling between these variables and C stock dynamics being bi-directional, we argue that using repeat estimates of woody biomass will provide a valuable constraint needed to refine predictions of the future carbon cycle. Finally, evaluation of our multi-model analysis shows that wood litter contributes substantially to fire emissions, necessitating a greater understanding of wood litter C cycling than is typically considered in large-scale TEMs.
AreaCST
ArrangementParameter uncertainty dominates...
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4. Conditions of access and use
Languageen
Target Filesmallman-2021.pdf
User Groupsimone
Visibilityshown
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/46L2FGP
DisseminationWEBSCI; PORTALCAPES; SCOPUS.
Host Collectionurlib.net/www/2021/06.04.03.40
6. Notes
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