Journal cover Journal topic
Earth System Science Data The data publishing journal
Journal topic

Journal metrics

Journal metrics

  • IF value: 10.951 IF 10.951
  • IF 5-year value: 9.899 IF 5-year
    9.899
  • CiteScore value: 9.74 CiteScore
    9.74
  • SNIP value: 3.111 SNIP 3.111
  • IPP value: 8.99 IPP 8.99
  • SJR value: 5.229 SJR 5.229
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 38 Scimago H
    index 38
  • h5-index value: 33 h5-index 33
Preprints
https://doi.org/10.5194/essd-2020-28
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2020-28
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: data description paper 28 Apr 2020

Submitted as: data description paper | 28 Apr 2020

Review status
This preprint is currently under review for the journal ESSD.

WFDE5: bias adjusted ERA5 reanalysis data for impact studies

Marco Cucchi1, Graham P. Weedon2, Alessandro Amici1, Nicolas Bellouin3, Stefan Lange4, Hannes Müller Schmied5,6, Hans Hersbach7, and Carlo Buontempo7 Marco Cucchi et al.
  • 1B-Open Solutions srl, Rome, Italy
  • 2Met Office, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxfordshire, OX10 8BB, UK
  • 3Department of Meteorology, University of Reading, Reading, RG6 6BB, UK
  • 4Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 60 12 03, 14412 Potsdam, Germany
  • 5Institute of Physical Geography, Goethe University Frankfurt, Frankfurt am Main, Germany
  • 6Senckenberg Leibniz Biodiversity and Climate Research Centre (SBiK-F), Frankfurt am Main, Germany
  • 7European Centre for Medium-Range Weather Forecasts, Reading, UK

Abstract. The WFDE5 dataset (C3S, 2020) has been generated using the WATCH Forcing Data (WFD) methodology applied to surface meteorological variables from the ERA5 reanalysis. The WFDEI dataset had previously been generated by applying the WFD methodology to ERA-Interim. The WFDE5 is provided at 0.5° spatial resolution, but has higher temporal resolution (hourly) compared to WFDEI (3-hourly). It also has higher spatial variability since it was generated by aggregation of the higher-resolution ERA5 rather than by interpolation of the lower resolution ERA-Interim data. Evaluation against meteorological observations at 13 globally distributed FLUXNET2015 sites shows that, on average, WFDE5 has lower mean absolute error and higher correlation than WFDEI for all variables. Bias-adjusted monthly precipitation totals of WFDE5 results in more plausible global hydrological water balance components as analyzed in an uncalibrated hydrological model (WaterGAP) than use of raw ERA5 data for model forcing. The dataset, which can be downloaded from https://doi.org/10.24381/cds.20d54e34 (C3S, 2020), is distributed by the Copernicus Climate Change Service (C3S) through its Climate Data Store (CDS, Copernicus Climate Change Service, 2020) and currently spans from the start of January 1979 to the end of 2018. The dataset has been produced using a number of CDS Toolbox applications, whose source code is available with the data – allowing users to re-generate part of the dataset or apply the same approach on other data. Future updates are expected spanning from 1950 to the most recent year. A sample of the complete dataset, which covers the whole 2016 year, is accessible without registration to the CDS at https://doi.org/10.21957/935p-cj60.

Marco Cucchi et al.

Interactive discussion

Status: open (until 23 Jun 2020)
Status: open (until 23 Jun 2020)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement

Marco Cucchi et al.

Data sets

Near surface meteorological variables from 1979 to 2018 derived from bias-corrected reanalysis C3S https://doi.org/10.24381/cds.20d54e34

Near surface meteorological variables from 1979 to 2018 derived from bias-corrected reanalysis - 2016 sample M. Cucchi, G. P. Weedon, A. Amici, N. Bellouin, S. Lange, H. Müller Schmied, H. Hersbach, and C. Buontempo https://doi.org/10.21957/935p-cj60

Model code and software

Near surface meteorological variables from 1979 to 2018 derived from bias-corrected reanalysis C3S https://doi.org/10.24381/cds.20d54e34

Marco Cucchi et al.

Viewed

Total article views: 282 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
217 63 2 282 1 1
  • HTML: 217
  • PDF: 63
  • XML: 2
  • Total: 282
  • BibTeX: 1
  • EndNote: 1
Views and downloads (calculated since 28 Apr 2020)
Cumulative views and downloads (calculated since 28 Apr 2020)

Viewed (geographical distribution)

Total article views: 236 (including HTML, PDF, and XML) Thereof 224 with geography defined and 12 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved

No saved metrics found.

Discussed

No discussed metrics found.
Latest update: 01 Jun 2020
Download
Short summary
WFDE5 is a novel meteorological forcing dataset for running land surface and global hydrological models. It has been generated using the WATCH Forcing Data methodology applied to surface meteorological variables from the ERA5 reanalysis. It is publicly available, along with its source code, through the C3S Climate Data Store at ECMWF. Results of the evaluations described in the paper highlight the benefits of using WFDE5 compared to both ERA5 and its predecessor WFDEI.
WFDE5 is a novel meteorological forcing dataset for running land surface and global hydrological...
Citation