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Publication details

Document type
Journal articles

Document subtype
Full paper

Title
High-resolution downscaling of CMIP6 Earth system and global climate models using deep learning for Iberia

Participants in the publication
Pedro M. M. Soares (Author)
Dep. Engenharia Geográfica, Geofísica e Energia
IDL
Frederico Johannsen (Author)
IDL
Daniela C. A. Lima (Author)
Dep. Engenharia Geográfica, Geofísica e Energia
IDL
Gil Lemos (Author)
IDL
Virgílio A. Bento (Author)
Dep. Engenharia Geográfica, Geofísica e Energia
IDL
Angelina Bushenkova (Author)
IDL

Date of Publication
2024-01-12

Where published
Geoscientific Model Development

Publication Identifiers
ISSN - 1991-9603

Publisher
Copernicus GmbH

Volume
17
Number
1

Number of pages
31
Starting page
229
Last page
259

Document Identifiers
DOI - https://doi.org/10.5194/gmd-17-229-2024
URL - https://doi.org/10.5194/gmd-17-229-2024

Rankings
Web Of Science Q1 (2023) - 4.0 - GEOSCIENCES, MULTIDISCIPLINARY
SCIMAGO Q1 (2023) - 2.055 - Earth and Planetary Sciences (miscellaneous)
SCOPUS Q1 (2023) - 8.6 - Earth and Planetary Sciences (all)


Export

APA
Pedro M. M. Soares, Frederico Johannsen, Daniela C. A. Lima, Gil Lemos, Virgílio A. Bento, Angelina Bushenkova, (2024). High-resolution downscaling of CMIP6 Earth system and global climate models using deep learning for Iberia. Geoscientific Model Development, 17, 229-259. ISSN 1991-9603. eISSN . https://doi.org/10.5194/gmd-17-229-2024

IEEE
Pedro M. M. Soares, Frederico Johannsen, Daniela C. A. Lima, Gil Lemos, Virgílio A. Bento, Angelina Bushenkova, "High-resolution downscaling of CMIP6 Earth system and global climate models using deep learning for Iberia" in Geoscientific Model Development, vol. 17, pp. 229-259, 2024. 10.5194/gmd-17-229-2024

BIBTEX
@article{64760, author = {Pedro M. M. Soares and Frederico Johannsen and Daniela C. A. Lima and Gil Lemos and Virgílio A. Bento and Angelina Bushenkova}, title = {High-resolution downscaling of CMIP6 Earth system and global climate models using deep learning for Iberia}, journal = {Geoscientific Model Development}, year = 2024, pages = {229-259}, volume = 17 }