Using ERA-Interim reanalysis for creating datasets of energy-relevant climate variables
- 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
- 5World Energy & Meteorology Council (WEMC), Norwich, NR4 7TJ, UK
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.