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1. Identificação
Tipo de ReferênciaArtigo em Revista Científica (Journal Article)
Sitemtc-m21d.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W34T/47J5DFE
Repositóriosid.inpe.br/mtc-m21d/2022/09.05.15.20
Última Atualização2022:09.05.15.20.42 (UTC) simone
Repositório de Metadadossid.inpe.br/mtc-m21d/2022/09.05.15.20.42
Última Atualização dos Metadados2023:01.03.16.46.15 (UTC) administrator
DOI10.5194/bg-19-3843-2022
ISSN1726-4170
Chave de CitaçãoPapastefanouZACJRRSSTVVVR:2022:AsDiPr
TítuloRecent extreme drought events in the Amazon rainforest: assessment of different precipitation and evapotranspiration datasets and drought indicators
Ano2022
Data de Acesso18 maio 2024
Tipo de Trabalhojournal article
Tipo SecundárioPRE PI
Número de Arquivos1
Tamanho4138 KiB
2. Contextualização
Autor 1 Papastefanou, Phillip
 2 Zang, Christian S.
 3 Angelov, Zlatan
 4 Castro, Aline Anderson de
 5 Jimenez, Juan Carlos
 6 Rezende, Luiz Felipe Campos de
 7 Ruscica, Romina C.
 8 Sakschewski, Boris
 9 Sörensson, Anna A.
10 Thonicke, Kirsten
11 Vera, Carolina
12 Viovy, Nicolas
13 Von Randow, Celso
14 Rammig, Anja
Grupo 1
 2
 3
 4 DIIAV-CGCT-INPE-MCTI-GOV-BR
 5
 6 YYY-CGCT-INPE-MCTI-GOV-BR
 7
 8
 9
10
11
12
13 DIIAV-CGCT-INPE-MCTI-GOV-BR
Afiliação 1 Technical University of Munich
 2 Weihenstephan-Triesdorf University of Applied Sciences
 3 Technical University of Munich
 4 Instituto Nacional de Pesquisas Espaciais (INPE)
 5 University of Valencia
 6 Instituto Nacional de Pesquisas Espaciais (INPE)
 7 Universidad de Buenos Aires
 8 Potsdam Institute for Climate Impact Research (PIK)
 9 Universidad de Buenos Aires
10 Potsdam Institute for Climate Impact Research (PIK)
11 Universidad de Buenos Aires
12 Université Paris-Saclay
13 Instituto Nacional de Pesquisas Espaciais (INPE)
14 Technical University of Munich
Endereço de e-Mail do Autor 1 papa@tum.de
 2
 3
 4 acaline@gmail.com
 5
 6 luizfeliperezende@gmail.com
 7
 8
 9
10
11
12
13 celso.vonrandow@inpe.br
RevistaBiogeosciences
Volume19
Páginas3843-3861
Nota SecundáriaA1_INTERDISCIPLINAR A1_GEOCIÊNCIAS A1_CIÊNCIAS_AMBIENTAIS A1_CIÊNCIAS_AGRÁRIAS_I A1_BIODIVERSIDADE A2_CIÊNCIAS_BIOLÓGICAS_I B1_ASTRONOMIA_/_FÍSICA
Histórico (UTC)2022-09-05 15:20:42 :: simone -> administrator ::
2022-09-05 15:20:46 :: administrator -> simone :: 2022
2022-09-05 15:22:24 :: simone -> administrator :: 2022
2023-01-03 16:46:15 :: administrator -> simone :: 2022
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo do ConteúdoExternal Contribution
Tipo de Versãopublisher
ResumoOver the last decades, the Amazon rainforest has been hit by multiple severe drought events. Here, we assess the severity and spatial extent of the extreme drought years 2005, 2010 and 2015/16 in the Amazon region and their impacts on the regional carbon cycle. As an indicator of drought stress in the Amazon rainforest, we use the widely applied maximum cumulative water deficit (MCWD). Evaluating nine state-of-the-art precipitation datasets for the Amazon region, we find that the spatial extent of the drought in 2005 ranges from 2.2 to 3.0 (mean = 2.7) ×106 km2 (37 % 51 % of the Amazon basin, mean = 45 %), where MCWD indicates at least moderate drought conditions (relative MCWD anomaly < −0.5). In 2010, the affected area was about 16 % larger, ranging from 3.0 up to 4.4 (mean = 3.6) ×106 km2 (51 %74 %, mean = 61 %). In 2016, the mean area affected by drought stress was between 2005 and 2010 (mean = 3.2 × 106 km2 ; 55 % of the Amazon basin), but the general disagreement between datasets was larger, ranging from 2.4 up to 4.1 × 106 km2 (40 %69 %). In addition, we compare differences and similarities among datasets using the self-calibrating Palmer Drought Severity Index (scPDSI) and a dry-season rainfall anomaly index (RAI). We find that scPDSI shows a stronger and RAI a much weaker drought impact in terms of extent and severity for the year 2016 compared to MCWD. We further investigate the impact of varying evapotranspiration on the drought indicators using two state-of-the-art evapotranspiration datasets. Generally, the variability in drought stress is most dependent on the drought indicator (60 %), followed by the choice of the precipitation dataset (20 %) and the evapotranspiration dataset (20 %). Using a fixed, constant evapotranspiration rate instead of variable evapotranspiration can lead to an overestimation of drought stress in the parts of Amazon basin that have a more pronounced dry season (for example in 2010). We highlight that even for well-known drought events the spatial extent and intensity can strongly depend upon the drought indicator and the data sources it is calculated with. Using only one data source and drought indicator has the potential danger of under- or overestimating drought stress in regions with high measurement uncertainty, such as the Amazon basin.
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4. Condições de acesso e uso
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URL dos dados zipadoshttp://urlib.net/zip/8JMKD3MGP3W34T/47J5DFE
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Arquivo Alvobg-19-3843-2022.pdf
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5. Fontes relacionadas
Unidades Imediatamente Superiores8JMKD3MGPCW/46KUATE
Lista de Itens Citandosid.inpe.br/bibdigital/2022/04.03.22.23 3
DivulgaçãoWEBSCI; PORTALCAPES; SCOPUS.
Acervo Hospedeirourlib.net/www/2021/06.04.03.40
6. Notas
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