Achieving Conservation of Energy in Neural Network Emulators for Climate Modeling

15 Jun 2019Tom BeuclerStephan RaspMichael PritchardPierre Gentine

Artificial neural-networks have the potential to emulate cloud processes with higher accuracy than the semi-empirical emulators currently used in climate models. However, neural-network models do not intrinsically conserve energy and mass, which is an obstacle to using them for long-term climate predictions... (read more)

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