Project Leads: Andrew Hou and Nick Nastoski
Project Members: Ashley Moulton, Anthony Nguyen, Ayaan Attasery, Briza Tayagua, Chloe Taurel, Hannah Fishman, Tanish Rajit
Motivation:
Develop statistical post-processing methods to correct systematic bias in Great Lake features predictions.
Development Process:
Predicting climate data is often messy because Earth's atmosphere is chaotic, making forecasts very complex. We built a data processing pipeline to organize and find these error patterns using machine learning models. We then created a formula that automatically corrects them.
Codebase:
Coming Soon!