Deep Learning for Subseasonal Global Precipitation Prediction - Maria Molina
Explore deep learning techniques for subseasonal global precipitation prediction in this conference talk from the Machine Learning for Climate KITP conference. Delve into how big data and machine learning algorithms are revolutionizing climate science, enabling researchers to analyze Earth system processes with unprecedented detail. Discover how these advanced methods can inform society about potential future changes at regional and local scales. Learn about the opportunities for descriptive inference, causal analysis, and theory validation in climate research. Gain insights into the interdisciplinary collaboration between earth system and computational sciences in addressing climate change challenges. Understand the potential of combining machine learning with modeling experiments and parameterizations to answer complex climate questions.