Neural networks are increasingly used in environmental science applications. Furthermore,
neural network models are trained by minimizing a loss function, and it is crucial to choose
the loss function very carefully for environmental science applications, as it determines what
exactly is being optimized. Standard loss functions do not cover all the needs of the
environmental sciences, which makes it important for scientists to be able to develop their
own custom loss functions so that they can implement many of the classic performance …