2019 Volume 25 Pages 97-102
In this study, we developed spatio-temporal downscaling method for rainfall prediction using deep learning. We adopted convolutional neural network for statistical downscaling model, and our model can convert 3hours/20km resolution data into 1hour/5km. Our model’s parameter has updated by past 11 years observed radar datasets. Furthermore, we applied our model to GSM (Global Spectral Model) Guidance’s rainfall prediction provided by JMA (Japan Meteorological Agency).
As a result, statistical downscaled rainfall prediction can smoothly describe rainfall area move and quantity change. Moreover, spatio-temporal downscaled rainfall prediction can generate peak time and quantity that is not given by GSM Guidance.
