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

Abstract : The construction of a bias-adjusted dataset of climate variables at the near surface using ERA-Interim reanalysis is presented. A number of different, variable-dependent, bias-adjustment approaches have been proposed. Here we modify the parameters of different distributions (depending on the variable), adjusting ERA-Interim based on gridded station or direct station observations. The variables are air temperature, dewpoint temperature, precipitation (daily only), solar radiation, wind speed, and relative humidity. These are available on either 3 or 6 h timescales over the period 1979–2016. 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. The benefit of performing bias adjustment is demonstrated by comparing initial and bias-adjusted ERA-Interim data against gridded observational fields.
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Earth System Science Data, Copernicus Publications, 2017, 9, pp.471 - 495. 〈10.5194/essd-9-471-2017〉
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Philip Jones, Colin Harpham, Alberto Troccoli, Benoît Gschwind, Thierry Ranchin, et al.. Using ERA-Interim reanalysis for creating datasets of energy-relevant climate variables. Earth System Science Data, Copernicus Publications, 2017, 9, pp.471 - 495. 〈10.5194/essd-9-471-2017〉. 〈hal-01567493〉

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