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1. Identificação
Tipo de ReferênciaArtigo em Evento (Conference Proceedings)
Sitemtc-m21c.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W34R/3SB3NUB
Repositóriosid.inpe.br/mtc-m21c/2018/12.03.14.30
Última Atualização2021:02.11.13.30.02 (UTC) simone
Repositório de Metadadossid.inpe.br/mtc-m21c/2018/12.03.14.30.14
Última Atualização dos Metadados2021:02.11.13.30.03 (UTC) simone
Chave SecundáriaINPE--PRE/
Chave de CitaçãoLiRKBGZGCBMTTLNLPIDBLMSSB:2018:GlGrSt
TítuloGlobal groundwater storage estimates through assimilation of GRACE data into a land surface model
Ano2018
Data de Acesso23 jun. 2024
Tipo SecundárioPRE CI
Número de Arquivos1
Tamanho78 KiB
2. Contextualização
Autor 1 Li, Bailing
 2 Rodell, Matthew
 3 Kumar, Sujay
 4 Beaudoing, Hiroko
 5 Getirana, Augusto
 6 Zaitchik, Benjamin F.
 7 Gonçalves, Luís Gustavo Gonçalves de
 8 Cossetin, Camila
 9 Bhanja, Soumendra Nath
10 Mukherjee, Abhijit
11 Tian, Siyuan
12 Tangdamrongsub, Nattharchet
13 Long, Di
14 Nanteza, Jamiat
15 Lee, Jejung
16 Policelli, Frederick S.
17 Ibrahim, Goni
18 Djoret, Daira
19 Bila, Mohammed D.
20 De Lannoy, Gabrielle
21 Mocko, David M.
22 Steele-Dunne, Susan C.
23 Save, Himanshu
24 Bettadpur, Srinivas V.
Grupo 1
 2
 3
 4
 5
 6
 7 DIDMD-CGCPT-INPE-MCTIC-GOV-BR
Afiliação 1 University of Maryland College Park
 2 NASA Goddard Space Flight Center
 3 SAIC
 4 SAIC
 5 NASA Goddard Space Flight Center
 6 Johns Hopkins University
 7 Instituto Nacional de Pesquisas Espaciais (INPE)
 8 Climatempo
 9 Indian Institute of Technology Kharagpur
10 Indian Institute of Technology Kharagpur
11 Australian National University
12 School of Engineering, University of Newcastle
13 Tsinghua University
14
15 Univ Missouri-Kansas City
16 NASA Goddard Space Flight Center
17
18 Lake Chad Basin Commission
19
20 Katholieke Universiteit Leuven
21 SAIC
22 Technische Universiteit Delft
23 University of Texas at Austin
24 University of Texas at Austin
Endereço de e-Mail do Autor 1
 2
 3
 4
 5
 6
 7 luis.goncalves@inpe.br
Nome do EventoAGU Fall Meeting
Localização do EventoWashington, D. C.
Data10-14 dec.
Histórico (UTC)2018-12-03 14:30:14 :: simone -> administrator ::
2019-01-04 16:57:14 :: administrator -> simone :: 2018
2019-01-07 14:22:11 :: simone -> administrator :: 2018
2021-01-02 03:54:26 :: administrator -> simone :: 2018
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo do ConteúdoExternal Contribution
ResumoGroundwater is one of the most important natural resources for the global community, with more than 2 billion people relying exclusively on groundwater for drinking water and 43% of irrigation water being supplied by aquifers. However, the scarcity of groundwater variation data at the global scale hinders our ability to monitor and manage groundwater resources effectively. The terrestrial water storage (TWS) changes derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission have shown great promise in detecting groundwater storage changes around the world. The application of GRACE data for groundwater hydrology can be facilitated by GRACE data assimilation, which constrains model estimates while providing vertical disaggregation and spatial downscaling. Building upon previous studies at regional to continental scales, this study assimilates a state-of-the-art GRACE TWS product into NASAs Catchment land surface model (CLSM) at the global scale with an improved ensemble smoother. The GRACE data were derived using a regional mass concentration approach with time variable constraints applied during the inversion of satellite ranging observations (as opposed to after inversion) to better preserve the information in those measurements. Time series of in situ data from nearly 4,000 wells located in different continents and climate zones were obtained to evaluate the impact of GRACE data assimilation on CLSM estimated groundwater. The comparison shows that GRACE data assimilation has a strong positive impact on simulated groundwater storage, with estimation errors reduced by 36% and 10% and correlation improved by 16% and 22% at the regional and point scales, respectively. The improvements are climate dependent, with the largest observed in regions with substantial interannual variability in precipitation, where simulated groundwater responds too strongly to changes in atmospheric forcing. We discuss the impacts of GRACE data assimilation on the temporal and spatial variability of TWS and groundwater storage and model deficiencies, including the lack of groundwater pumping, that limit its ability to distribute assimilated TWS properly. Application of this dataset for groundwater drought monitoring is also described.
ÁreaMET
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4. Condições de acesso e uso
URL dos dadoshttp://mtc-m21c.sid.inpe.br/ibi/8JMKD3MGP3W34R/3SB3NUB
URL dos dados zipadoshttp://mtc-m21c.sid.inpe.br/zip/8JMKD3MGP3W34R/3SB3NUB
Idiomaen
Arquivo Alvoli_global.pdf
Grupo de Usuáriossimone
Grupo de Leitoresadministrator
simone
Visibilidadeshown
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Unidades Imediatamente Superiores8JMKD3MGPCW/43SKC35
Lista de Itens Citando
Acervo Hospedeirourlib.net/www/2017/11.22.19.04
6. Notas
Campos Vaziosarchivingpolicy archivist booktitle callnumber copyholder copyright creatorhistory descriptionlevel dissemination doi e-mailaddress edition editor format isbn issn keywords label lineage mark mirrorrepository nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress readpermission resumeid rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle sponsor subject tertiarymark tertiarytype type url versiontype volume
7. Controle da descrição
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