These pages show a comparison of two WAVEWATCH III® implementations:
The mean difference between the model and observations, measures the tendency of the model process to over- or under-estimate the value of a parameter. Smaller absolute bias values indicate better agreement between measured and calculated values. Positive bias means overprediction, negative means underprediction.
diff = model_data - observations bias = diff.mean()
Also called the root-mean-squared deviation, it's a measure of the differences between the observed and predicted values. Smaller RMSE values indicate better agreement between measured and calculated values.
rmse=(diff**2).mean()**0.5