CHELSAcerra-daily (Europe) (V1.0)
type: Dataset
comment: This dataset metadata was generated with the use of AI and reviewed by an expert. If you see any mistakes please file an issue on GitHub at https://github.com/earthcube/communityCollections/issues.
description: CHELSAcerra-daily is a high-resolution climate dataset for air temperatures generated with the CHELSA downscaling model using the Copernicus European Regional ReAnalysis (CERRA) for Europe.
version: 1.0
creator: WSL (Swiss Federal Institute for Forest, Snow and Landscape Research)
publisher: WSL (Swiss Federal Institute for Forest, Snow and Landscape Research)
keywords: CHELSA
keywords: CERRA
keywords: Europe
keywords: downscaling
keywords: daily temperature
keywords: regional reanalysis
variable measured: Daily Mean Near-Surface Air Temperature
  type: PropertyValue
  alternate name: tas
  unit text: K
  description: Near-surface, usually 2 meter, air temperature.
  temporal coverage: 1985-01-01/2015-12-31
  spatial coverage: Europe
  temporal resolution: not detected
  spatial resolution: not detected
distribution: CHELSAcerra-daily downloads (portal)
  type: DataDownload
  description: Download portal linked from the CHELSA catalog entry for CHELSAcerra-daily.
  encoding format: text/html
citation: Climatologies at high resolution for the earth's land surface areas
  type: ScholarlyArticle
  author: D. N. Karger
  author: O. Conrad
  author: J. Böhner
  author: T. Kawohl
  author: H. Kreft
  author: R. W. Soria-Auza
  author: N. E. Zimmermann
  author: H. P. Linder
  author: M. Kessler
  date published: 2017
  is part of: Scientific Data
  volume number: 4
  pagination: 170122
citation: CHELSAcerra-daily
  type: Dataset
  author: D. N. Karger
  author: J. Janzing
  publisher: EnviDat
  date published: 2025
about: Downscaled regional reanalysis (Europe)
about: Daily air temperature

WSL (Swiss Federal Institute for Forest, Snow and Landscape Research)
type: Organization

PropertyValue
property ID: doi
value: 10.1038/sdata.2017.122

PropertyValue
property ID: doi
value: 10.16904/envidat.703