Daily station-level records of air temperature, snow depth, and ground temperature in the Northern Hemisphere.
Journal
Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192
Informations de publication
Date de publication:
18 Jun 2024
18 Jun 2024
Historique:
received:
20
10
2023
accepted:
06
06
2024
medline:
19
6
2024
pubmed:
19
6
2024
entrez:
18
6
2024
Statut:
epublish
Résumé
Air temperature (Ta), snow depth (Sd), and soil temperature (Tg) are crucial variables for studying the above- and below-ground thermal conditions, especially in high latitudes. However, in-situ observations are frequently sparse and inconsistent across various datasets, with a significant amount of missing data. This study has assembled a comprehensive dataset of in-situ observations of Ta, Sd, and Tg for the Northern Hemisphere (higher than 30°N latitude), spanning 1960-2021. This dataset encompasses metadata and daily data time series for 27,768, 32,417, and 659 gages for Ta, Sd, and Tg, respectively. Using the ERA5-Land reanalysis data product, we applied deep learning methodology to reconstruct the missing data that account for 54.5%, 59.3%, and 74.3% of Ta, Sd, and Tg daily time series, respectively. The obtained high temporal resolution dataset can be used to better understand physical phenomena and relevant mechanisms, such as the dynamics of land-surface-atmosphere energy exchange, snowpack, and permafrost.
Identifiants
pubmed: 38890309
doi: 10.1038/s41597-024-03483-x
pii: 10.1038/s41597-024-03483-x
doi:
Substances chimiques
Soil
0
Types de publication
Dataset
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
645Subventions
Organisme : National Science Foundation (NSF)
ID : 2053429
Informations de copyright
© 2024. The Author(s).
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