Evaluating NA-CORDEX historical performance and future change of western U.S. precipitation patterns and modes of variability

Abstract

The western U.S. precipitation climatology, simulated by the NA-CORDEX regional climate model ensembles, with spatial resolutions of 0.44° (14 model members) and 0.22° (15 model members), is examined to evaluate the capability of these ensembles to reproduce (1) the annual and semi-annual precipitation cycle of several hydrologically-important western U.S. regions and (2) localized seasonality in the amount and timing of precipitation. Similar to previous organized downscaling projects, NA-CORDEX ensembles continue to over-simulate wintertime precipitation over mountainous regions. However, both NA-CORDEX ensembles showed improvements to the Desert Southwest's summertime precipitation associated with the North American Monsoon. Furthermore, the predominant dry bias found throughout the 0.44° ensemble was improved in many of the higher resolution 0.22° ensemble members; associated with enhanced mesoscale processes and improved thermodynamics driving the model's convective parameterizations. When compared against observation-based gridded precipitation, the ability to capture the annual and semi-annual modes of variability was starkly improved in the higher resolution 0.22° ensemble. The higher resolution members reproduced more consistent spatial patterns of variance featuring lower errors in magnitude—especially with respect to the winter-summer and spring-fall seasonality. A great deal of spread in model performance was found for the semi-annual cycles, although the higher-resolution ensemble exhibited better clustering of performance metrics. Ultimately, NA-CORDEX model performance is still tied to the fidelity of the large-scale parent model although we found performance is also closely related to which regional climate model was used while the future trend was more related to the parent GCM. Additionally, the value-added via finer domain grid spacing is clear. Lastly, future projections of precipitation patterns were analysed to examine trends in the seasonality of precipitation intensity and modes of variability.