Bias Correction of Terrestrial Water Availability: Comparison of Trend-Preserving Cumulative Distribution Function Matching Methods

Abstract

Terrestrial water availability, quantified by precipitation minus evapotranspiration (P−E), is essential in Earth's water cycle, whereas model simulation of P−E is still largely biased and requires a post-processing procedure. This study introduces the grid-by-grid cumulative distribution function (CDF) matching method to correct simulation bias in P−E, based on the ERA5-Land dataset and outputs from 13 selected CMIP6 global climate models. The CDF matching method has a particular advantage in preserving the trends simulated by laws of physics in climate models, and three (additive, multiplicative, and additive–multiplicative mixed) trend preservation strategies are compared in this study. The cross-validation from 1951 to 2014 indicates that all the trend preservation strategies effectively improve the simulated spatial characteristics of P−E with increased spatial correlation, enhanced sign agreement and reduced mean absolute error. Specifically, the additive strategy outperforms in improving the spatial similarity and accuracy of P−E in the humid region and global average, whereas the mixed strategy is the optimal in the hyper-arid, arid, and semi-arid regions. Furthermore, the mixed strategy has a significant advantage in preserving the signs of P−E across the globe. This study exhibits a computationally efficient statistical approach for bias correction of P−E simulation, and validates its flexible correction strategies regarding different terrestrial aridity conditions.