Journal cover Journal topic
Earth System Science Data The Data Publishing Journal
doi:10.5194/essd-2016-67
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Review article
06 Jan 2017
Review status
This discussion paper is under review for the journal Earth System Science Data (ESSD).
Using ERA-Interim Reanalysis output for creating datasets of energy-relevant climate variables
Philip D. Jones1,4, Colin Harpham1, Alberto Troccoli2, Benoit Gschwind3, Thierry Ranchin3, Lucien Wald3, Clare M. Goodess1, and Stephen Dorling2 1Climatic Research Unit (CRU), School of Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, UK
2School of Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, UK
3MINES ParisTech, PSL Research University, O.I.E. – Centre Observation, Impacts, Energy, 06904 Sophia Antipolis, France
4Center of Excellence for Climate Change Research, Department of Meteorology, King Abdulaziz University, Jeddah, Saudi Arabia
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 bias-adjustment approaches have been proposed. Here we modify the parameters of different distributions (depending on the variable), adjusting those calculated from ERA-Interim to those 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, available at either 3 or 6 h timescales over the period 1979-2014. This dataset is available to anyone 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 observations.

Citation: Jones, P. D., Harpham, C., Troccoli, A., Gschwind, B., Ranchin, T., Wald, L., Goodess, C. M., and Dorling, S.: Using ERA-Interim Reanalysis output for creating datasets of energy-relevant climate variables, Earth Syst. Sci. Data Discuss., doi:10.5194/essd-2016-67, in review, 2017.
Philip D. Jones et al.
Philip D. Jones et al.
Philip D. Jones et al.

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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. Bias-adjustment enables the dataset (available for 1979 to 2014) to be more widely used in climate applications. The work was undertaken specifically for renewable energy, so two of the variables are radiation and wind speed. The dataset is available at 6-hour resolution for a large European window.
The construction of a bias-adjusted dataset of climate variables at the near surface using...
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