Meteorological normalization proceeds with the learned model f as follows: To compensate the effect of meteorological variables X (e.g. temp, press, rh, ws) on the target Y for a fixed set of (non-meteorological) descriptors T = t (e.g., Julian day), the learned model f is evaluated for realizations r i of X drawn from the dataset D with replacement. We denote the random draws from