Empirical Distribution of Conditional Errors in Radar Rainfall Products

Abstract

Abstract Efficient quantification of conditional errors in radar rainfall (RR) products requires a realistic model of random error distribution. Nonparametric estimate of the probability density function ( pdf ) of standardized RR errors is obtained using a large data sample. The standardization is based on a second‐order separation of systematic and random effects. The estimated empirical distribution is skewed and has exponential shapes of its tails with two different scales. It cannot be modeled with the Gaussian law that was used in several previous studies. A good representation of the tails of the empirical distribution of RR errors is obtained with a three‐parameter modified Laplace model with a shift and unequal slopes of its two sides.