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The main phenomena driving rain events in the western United States during the rainy season (October-April) are Atmospheric Rivers. Accurately forecasting rainfall from these events is critical due to the impacts they have on the water supply as well as the severe flooding risks they pose. The Landfalling Event Atmospheric River Neural Network (LEARN2) is a neural-network-based decision support tool that considers forecast guidance from NOAA/National Centers for Environmental Prediction (NCEP's) Global Ensemble Forecast System (GEFS) and the European Center for Medium-Range Weather Forecasting Ensembles (ECMWF), remotely sensed fields, and subseasonal-to-seasonal indices, to produce extreme rainfall predictions. In LEARN2, products are run through both convolutional and fully connected neural networks and a novel" voting" algorithm that leverages the power of ensemble forecast systems …