Abstract
Midlatitude prediction on subseasonal timescales is difficult due to the
chaotic nature of the atmosphere and often requires the identification
of favorable atmospheric conditions that may lead to enhanced skill
(“forecasts of opportunity”). Here, we demonstrate that an artificial
neural network can identify such opportunities for
tropical-extratropical circulation teleconnections within the North
Atlantic (40N, 325E) at a lead of 22 days using the network’s confidence
in a given prediction. Furthermore, layer-wise relevance propagation, an
ANN explainability technique, pinpoints the relevant tropical features
the ANN uses to make accurate predictions. We find that layer-wise
relevance propagation identifies tropical hot spots that correspond to
known favorable regions for midlatitude teleconnections and reveals a
potential new pattern for prediction in the North Atlantic on
subseasonal timescales.