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Introduction

This report gives an overview of the statistical downscaling of daily aggregated ERA5 reanalysis data towards a 0.1° grid. This downscaling is realized by applying grid and parameter-specific regression equations to an interpolated ERA5 data set. The equations are trained on operational ECMWF HRES model data.
The approach consists of the following main steps:

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1. The selected bias correction method has its largest benefits in mountainous areas, at coast lines and at lakes
2. Seasonal correction on top of the simple bias correction further improves the accuracy of the derived correction equations.
3. The approach works remarkable well for 3 of 4 groups of elements. The averaged relative reduction of MAE is between 30% and 60%. These are:
   1. Temperature parameters
   2. Humidity parameters
   3. Wind speed
4. The correction models for solar radiation flux reach a MAE improvement of 2% to 14%.
5. For cloud cover the correction has only a minor effect for most of the grid points. However, mountainous regions still benefit from the correction with a MAE improvement of 2%-8%.

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