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GriddingMachine, a database and software for Earth system modeling at global and regional scales.
Wang, Yujie; Köhler, Philipp; Braghiere, Renato K; Longo, Marcos; Doughty, Russell; Bloom, A Anthony; Frankenberg, Christian.
Afiliação
  • Wang Y; Division of Geological and Planetary Sciences, California Institute of Technology, 1200 E California Blvd, Pasadena, 91125, California, USA. wyujie@caltech.edu.
  • Köhler P; Division of Geological and Planetary Sciences, California Institute of Technology, 1200 E California Blvd, Pasadena, 91125, California, USA.
  • Braghiere RK; Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr, Pasadena, 91109, California, USA.
  • Longo M; Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, 405 Hilgard Avenue, Los Angeles, 90095, California, USA.
  • Doughty R; Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr, Pasadena, 91109, California, USA.
  • Bloom AA; Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Rd, Berkeley, 94720, California, USA.
  • Frankenberg C; Division of Geological and Planetary Sciences, California Institute of Technology, 1200 E California Blvd, Pasadena, 91125, California, USA.
Sci Data ; 9(1): 258, 2022 06 01.
Article em En | MEDLINE | ID: mdl-35650204
ABSTRACT
Land and Earth system modeling is moving towards more explicit biophysical representations, requiring increasing variety of datasets for initialization and benchmarking. However, researchers often have difficulties in identifying and integrating non-standardized datasets from various sources. We aim towards a standardized database and one-stop distribution method of global datasets. Here, we present the GriddingMachine as (1) a database of global-scale datasets commonly used to parameterize or benchmark the models, from plant traits to vegetation indices and geophysical information and (2) a cross-platform open source software to download and request a subset of datasets with only a few lines of code. The GriddingMachine datasets can be accessed either manually through traditional HTTP, or automatically using modern programming languages including Julia, Matlab, Octave, Python, and R. The GriddingMachine collections can be used for any land and Earth modeling framework and ecological research at the regional and global scales, and the number of datasets will continue to grow to meet the increasing needs of research communities.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Sci Data Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Sci Data Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos