Articles | Volume 9, issue 2
Earth Syst. Sci. Data, 9, 471–495, 2017
https://doi.org/10.5194/essd-9-471-2017
Earth Syst. Sci. Data, 9, 471–495, 2017
https://doi.org/10.5194/essd-9-471-2017

Review article 21 Jul 2017

Review article | 21 Jul 2017

Using ERA-Interim reanalysis for creating datasets of energy-relevant climate variables

Philip D. Jones et al.

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Cited articles

Becker, A., Finger, P., Meyer-Christoffer, A., Rudolf, B., Schamm, K., Schneider, U., and Ziese, M.: A description of the global land-surface precipitation data products of the Global Precipitation Climatology Centre with sample applications including centennial (trend) analysis from 1901–present, Earth Syst. Sci. Data, 5, 71–99, https://doi.org/10.5194/essd-5-71-2013, 2013.
Blanc, P., Gschwind, B., Lefèvre, M., and Wald, L.: The HelioClim project: Surface solar irradiance data for climate applications, Remote Sensing, 3, 343–361, https://doi.org/10.3390/rs3020343, 2011.
Bojinski, S., Verstraete, M., Peterson, T. C., Richter, C., Simmons, A., and Zemp, M.: The concept of essential climate variables in support of climate research, applications, and policy, B. Am. Meteor. Soc., 95, 1431–1443, https://doi.org/10.1175/BAMS-D-13-00047.1, 2014.
Boilley, A. and Wald, L.: Comparison between meteorological re-analyses from ERA-Interim and MERRA and measurements of daily solar irradiation at surface, Renew. Energ., 75, 135–143, https://doi.org/10.1016/j.renene.2014.09.042, 2015.
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Short summary
The construction of a bias-adjusted dataset of climate variables at the near surface using ERA-Interim reanalysis is presented. The variables are air temperature, dewpoint temperature, precipitation (daily only), solar radiation, wind speed, and relative humidity.The resulting bias-adjusted dataset is available through the Climate Data Store (CDS) of the Copernicus Climate Change Data Store (C3S), and can be accessed at present from ftp://ecem.climate.copernicus.eu.