A Neural Network for Large-Scale Precipitation Forecasting
Skillful Twelve Hour Precipitation Forecasts using Large Context Neural Networks
Forecasting weather has been scientifically studied for centuries due to its high impact on human lives, transportation, food production and energy management, among others.Current operational forecasting models are based on physics and use supercomputers to simulate the atmosphereto make forecasts hours and days in advance.However, each additional hour of lead time poses a substantial challenge as it requires capturing ever larger spatial contexts and increases the uncertaintyof the prediction.In this work, we present a neural network that is capable of large-scale precipitation forecasting up to twelve hours ahead and, startingfrom the same atmospheric state, the model achieves greater skill than the state-of-the-art physics-based models that currently operate in the continental united states.These results represent a substantial step towards establishing a new paradigm of efficient forecasting with neural networks.
