## Climate data processing

The modelling system comprises tools to generate time series of bio-climatic variables (minimum and maximum temperature, precipitation, reference evapotranspiration, growing season onset and length of the growing season) from observed weather time series as well as from Global Climate Models (GCM) outputs.

A statistical downscaling tool based on the DAD Portal (Data Access and Downscaling) by the Santander Meteorology Group of the University of Cantabria. This tool has been designed to perform statistical downscaling of coarse climate grids generated by GCMs. The data (precipitation, minimum and maximum temperature) can be downscaled simultenously for a set of weather stations, provided that enough observation records are available for each of them. Several methods keeping spatial consistency are available, as for instance weather typing methods and regression methods. The tool also includes a weather generator to derive time series of the weather variables needed.

A second tool has been developped to interpolate the climate data over the study area using the method AURELHY (Benichou and Le Breton, 1986). AURELHY ("Analyse Utilisant le RElief pour l'Hydrométéorologie") is an interpolation method for meteorological and hydrological data based on the analysis of the topography. The tool consists in a R package, freely available on the R packages repositories.

A routine has been written to compute the reference evapotranspiration using Hargreaves' method (Hargreaves and Samani, 1982) directly from interpolated rasters of minimum and maximum temperatures.

Finally, the modelling system also includes a tool to estimate the onset of the growing season and the length of the growing cycle. This tool called PLD was extracted from AgroMetShell, the FAO crop yield forecasting software, and adapted for the project. The two variables are estimated from the analysis of the time series of precipiration and reference evapotranspiration based on the method of Cochemé and Franquin, 1967.