Physically Interpretable Neural Networks for the Geosciences: Applications to Earth System Variability

Understand

Neural networks have become increasingly prevalent within the geosciences, although a common limitation of their usage has been a lack of methods to interpret what the networks learn and how they make decisions.

• As such, neural networks have often been used within the geosciences to most accurately identify a desired output given a set of inputs, with the interpretation of what the network learns used as a secondary metric to ensure the network is making the right decision for the right reason.
• Neural network interpretation techniques have become more advanced in recent years, however, and we therefore propose that the ultimate objective of using a neural network can also be the interpretation of what the network has learned rather than the output itself.
• We show that the interpretation of neural networks can enable the discovery of scientifically meaningful connections within geoscientific data.