Predicting the weather with deep learning
Published in
Jul 9, 2018
Predicting the weather is one of the most challenging tasks in machine learning due to the fact that physical phenomena are dynamic and riche of events. Moreover, most of traditional approaches to climate forecast are computationally prohibitive.
It seems that a joint research between the Earth System Science at the University of California, Irvine and the faculty of Physics at LMU Munich has an interesting improvement on the scalability and accuracy of climate predictive modeling.
The solution is… superparameterization and deep learning.
Listen to the podcast episode
I hope you enjoy!
