An artificial neural network effectively predicts slowdowns in decadal warming trends of global mean surface temperature by leveraging tropical ocean heat content anomalies. It reveals that transitions in the interdecadal Pacific oscillation are closely linked to these warming slowdown predictions. The research is documented in a 2022 paper by Labe and Barnes in Geophysical Research Letters.

1. 1. An artificial neural network
predicts the onset of slowdowns
in decadal warming trends of
global mean surface
temperature
2. Explainable AI reveals the neural
network is leveraging tropical
patterns of ocean heat content
anomalies to make its
predictions
3. Transitions in the phase of the
Interdecadal Pacific Oscillation
are frequently associated with
warming slowdown predictions
in CESM2-LE
Temporary slowdowns in decadal warming
predictions by a neural network
Labe, Z.M. and E.A. Barnes (2022), Predicting
slowdowns in decadal climate warming trends with
explainable neural networks. Geophysical Research
Letters, DOI:10.1029/2022GL098173
Paper