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The original forecasts have been bias-adjusted by applying a quantile mapping method (Gudmundsson et al., 2011) on a monthly basis. ERA5 reanalysis at 0.25° upscaled at the same resolution as the seasonal forecast data, i.e. 1°, was employed as a reference dataset.
The temperature downscaling exploits information from a reference fine-scale temperature climatology (ERA5 at 0.25° resolution). The coarse-scale data are remapped to the target grid and adjusted pixel-by-pixel by an additive constant so that the resulting fine-scale climatology is identical to the reference climatology.
The precipitation downscaling is performed with the orographic RainFARM method (D'Onofrio et al., 2014, Terzago et al., 2018)
The data processing has been performed using the CSTools R package (Perez-Zanon et al., 2020)