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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21c.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34R/3SG96SS
Repositorysid.inpe.br/mtc-m21c/2019/01.04.14.10
Last Update2019:01.04.14.10.44 (UTC) simone
Metadata Repositorysid.inpe.br/mtc-m21c/2019/01.04.14.10.44
Metadata Last Update2021:01.02.22.16.29 (UTC) administrator
DOI10.5194/gmd-11-5203-2018
ISSN1991-959X
Citation KeyRammigHHVBCCDFGGHJKLMPOTVZR:2018:ExAmRe
TitleA generic pixel-to-point comparison for simulated large-scale ecosystem properties and ground-based observations: an example from the Amazon region
Year2018
Access Date2024, Apr. 25
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size2359 KiB
2. Context
Author 1 Rammig, Anja
 2 Heinke, Jens
 3 Hofhansl, Florian
 4 Verbeeck, Hans
 5 Baker, Timothy R.
 6 Christoffersen, Bradley
 7 Ciais, Philippe
 8 De Deurwaerder, Hannes
 9 Fleischer, Katrin
10 Galbraith, David
11 Guimberteau, Matthieu
12 Huth, Andreas
13 Johnson, Michelle
14 Krujit, Bart
15 Langerwisch, Fanny
16 Meir, Patrick Meir
17 Papastefanou, Phillip
18 Oliveira, Gilvan Sampaio de
19 Thonicke, Kirsten
20 Von Randow, Celso
21 Zang, Christian
22 Rödig, Edna
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18 8JMKD3MGP5W/3C9JHBE
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Affiliation 1 Technical University of Munich
 2 Potsdam Institute for Climate Impact Research
 3 IIASA International Institute for Applied Systems Analysis
 4 CAVElab Computational & Applied Vegetation Ecology
 5 School of Geography, University of Leeds
 6 The University of Texas Rio Grande Valley
 7 Université Paris-Saclay
 8 4CAVElab Computational & Applied Vegetation Ecology, Department of Applied Ecology and Environmental Biology, Faculty of Bioscience Engineering
 9 Technical University of Munich
10 University of Leeds
11 Université Paris-Saclay
12 Helmholtz Centre for Environmental Research (UFZ)
13 University of Leeds
14 ALTERRA
15 Potsdam Institute for Climate Impact Research
16 University of Edinburgh
17 Technical University of Munich
18 Instituto Nacional de Pesquisas Espaciais (INPE)
19 Potsdam Institute for Climate Impact Research
20 Instituto Nacional de Pesquisas Espaciais (INPE)
21 Technical University of Munich
22 Helmholtz Centre for Environmental Research (UFZ)
Author e-Mail Address 1 anja.rammig@tum.de
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JournalGeoscientific Model Development
Volume11
Pages5203-5215
History (UTC)2019-01-04 14:10:44 :: simone -> administrator ::
2019-01-04 14:10:44 :: administrator -> simone :: 2018
2019-01-04 14:14:12 :: simone -> administrator :: 2018
2021-01-02 22:16:29 :: administrator -> simone :: 2018
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
AbstractComparing model output and observed data is an important step for assessing model performance and quality of simulation results. However, such comparisons are often hampered by differences in spatial scales between local point observations and large-scale simulations of grid cells or pixels. In this study, we propose a generic approach for a pixel-to-point comparison and provide statistical measures accounting for the uncertainty resulting from landscape variability and measurement errors in ecosystem variables. The basic concept of our approach is to determine the statistical properties of small-scale (within-pixel) variability and observational errors, and to use this information to correct for their effect when large-scale area averages (pixel) are compared to small-scale point estimates. We demonstrate our approach by comparing simulated values of aboveground biomass, woody productivity (woody net primary productivity, NPP) and residence time of woody biomass from four dynamic global vegetation models (DGVMs) with measured inventory data from permanent plots in the Amazon rainforest, a region with the typical problem of low data availability, potential scale mismatch and thus high model uncertainty. We find that the DGVMs under- and overestimate aboveground biomass by 25 % and up to 60 %, respectively. Our comparison metrics provide a quantitative measure for modeldata agreement and show moderate to good agreement with the region-wide spatial biomass pattern detected by plot observations. However, all four DGVMs overestimate woody productivity and underestimate residence time of woody biomass even when accounting for the large uncertainty range of the observational data. This is because DGVMs do not represent the relation between productivity and residence time of woody biomass correctly. Thus, the DGVMs may simulate the correct large-scale patterns of biomass but for the wrong reasons. We conclude that more information about the underlying processes driving biomass distribution are necessary to improve DGVMs. Our approach provides robust statistical measures for any pixel-to-point comparison, which is applicable for evaluation of models and remote-sensing products.
AreaMET
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGP3W34R/3SG96SS
zipped data URLhttp://urlib.net/zip/8JMKD3MGP3W34R/3SG96SS
Languageen
Target Filerammig_generic.pdf
User Groupsimone
Reader Groupadministrator
simone
Visibilityshown
Archiving Policyallowpublisher allowfinaldraft
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3F3T29H
8JMKD3MGPCW/43SQKNE
Citing Item Listsid.inpe.br/mtc-m21/2012/07.13.14.49.24 4
sid.inpe.br/bibdigital/2013/10.19.20.40 1
DisseminationWEBSCI; PORTALCAPES.
Host Collectionurlib.net/www/2017/11.22.19.04
6. Notes
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