Convolutional Neural Network Workshop

CNNs for Predicting daily orographic precipitation gradients for atmospheric downscaling

Day 2 Session 1 (11:00 AM MDT)

This workshop offers participants an introduction to convolutional neural networks (CNNs) for their application in hydro-meteorology. Core concepts to be covered include the layers within a CNN, the learning process of the CNN, and techniques related to Explainable AI (XAI). The hands-on portion of the workshop focuses on customizing a CNN through hyperparameter exploration, adjusting CNN layers, and manipulating inputs. Participants will gain an understanding of CNN architecture, practical skills in customizing a CNN, and the apply the models in Northern Utah for downscaling ERA5 data for the quantity of liquid precipitation. Participants will use GitHub to fork the repository and clone to their machine using the CIROH Cloud Computing environment.