Article Title: Using ERA-Interim Reanalysis for creating datasets of energy-relevant climate variables.
This article was published from the construction of a bias-adjusted dataset of climate variables at the near surface using ERA-Interim reanalysis which is presented in this interactive website. Variables include; wind speed at 10m, temperature and solar radiation. Users in the energy sector are much more interested in the extremes of the distribution so this article adjusts the whole ERA-Interim distribution on the daily and sub-daily timescales, using a different statistical distribution for each variable.
Wind speed uses a 2-parameter Weibull distribution. Surface air temperature and dewpoint temperature use a normal distribution. Precipitation uses a gamma distribution. Three methods are described for solar radiation; ratio, affine and quantile mapping. Quantile mapping consists of adjusting the cumulative distribution function of ERA-Interim to the observations.
Thoughts for our research:
- Input and output data is available online.
- These bias-adjustment methods can be replicated.