The collection of methods includes interpolation from a coarse to fine grid (also known as regridding) plus post-processing, which can be performed using calibration methods, linear or logistic regressions, and can be seen as a bias adjustment of model values by employing observations as reference data. The software enables downscaling through various interpolation, calibration, and regression approaches, depending on the predictors and their implementation techniques. Besides, the analogs method, which looks for fields with similar conditions to the one being predicted, has also been included. All these methods are designed to be applied in cross-validation, that is, excluding data from the specific time step being post-processed to avoid overfitting and, consequently, the overestimation of the actual prediction skill.