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AmeriFlux BASE data pipeline to support network growth and data sharing.
Chu, Housen; Christianson, Danielle S; Cheah, You-Wei; Pastorello, Gilberto; O'Brien, Fianna; Geden, Joshua; Ngo, Sy-Toan; Hollowgrass, Rachel; Leibowitz, Karla; Beekwilder, Norman F; Sandesh, Megha; Dengel, Sigrid; Chan, Stephen W; Santos, André; Delwiche, Kyle; Yi, Koong; Buechner, Christin; Baldocchi, Dennis; Papale, Dario; Keenan, Trevor F; Biraud, Sébastien C; Agarwal, Deborah A; Torn, Margaret S.
Afiliação
  • Chu H; Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA. hchu@lbl.gov.
  • Christianson DS; Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
  • Cheah YW; Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
  • Pastorello G; Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
  • O'Brien F; Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
  • Geden J; Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
  • Ngo ST; Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
  • Hollowgrass R; Department of Environmental Science, Policy, and Management, University of California Berkeley, Berkeley, CA, 94720, USA.
  • Leibowitz K; HyperArts, Inc, Oakland, CA, 94607, USA.
  • Beekwilder NF; Department of Computer Science, University of Virginia, Charlottesville, VA, 22903, USA.
  • Sandesh M; Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
  • Dengel S; Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
  • Chan SW; Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
  • Santos A; Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
  • Delwiche K; Department of Environmental Science, Policy, and Management, University of California Berkeley, Berkeley, CA, 94720, USA.
  • Yi K; Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
  • Buechner C; Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
  • Baldocchi D; Department of Environmental Science, Policy, and Management, University of California Berkeley, Berkeley, CA, 94720, USA.
  • Papale D; DIBAF, University of Tuscia, Viterbo, 01100, Italy.
  • Keenan TF; Euro-Mediterranean Center on Climate Change CMCC IAFES, Viterbo, 01100, Italy.
  • Biraud SC; Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
  • Agarwal DA; Department of Environmental Science, Policy, and Management, University of California Berkeley, Berkeley, CA, 94720, USA.
  • Torn MS; Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
Sci Data ; 10(1): 614, 2023 09 11.
Article em En | MEDLINE | ID: mdl-37696825
ABSTRACT
AmeriFlux is a network of research sites that measure carbon, water, and energy fluxes between ecosystems and the atmosphere using the eddy covariance technique to study a variety of Earth science questions. AmeriFlux's diversity of ecosystems, instruments, and data-processing routines create challenges for data standardization, quality assurance, and sharing across the network. To address these challenges, the AmeriFlux Management Project (AMP) designed and implemented the BASE data-processing pipeline. The pipeline begins with data uploaded by the site teams, followed by the AMP team's quality assurance and quality control (QA/QC), ingestion of site metadata, and publication of the BASE data product. The semi-automated pipeline enables us to keep pace with the rapid growth of the network. As of 2022, the AmeriFlux BASE data product contains 3,130 site years of data from 444 sites, with standardized units and variable names of more than 60 common variables, representing the largest long-term data repository for flux-met data in the world. The standardized, quality-ensured data product facilitates multisite comparisons, model evaluations, and data syntheses.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article
Texto completo
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PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article