Global Climate Models (GCMs) are used to project the future climate of our earth, but they are not enough for climate change impact studies, because the resolution is quite coarse. Therefore, the project generated by GCM need to be downscaled to make its resolution finer. I wrote a series of ipython notebooks to conduct the whole procedure of statistical downscaling GCMs based on machine learning approaches using Scikit-learn and the visualization works including maps using Cartopy and charts using Matplotlib as well as Seaborn. All of these works have been uploaded to GitHub at https://github.com/Yafei777/Climate-Downscaling , also, a scientific paper I wrote that employed the downscaling methods I mentioned above has been under peer-viewing.