Does Nudging Squelch the Extremes in Regional Climate Modeling?

Abstract An important question in regional climate downscaling is whether to constrain (nudge) the interior of the limited-area domain toward the larger-scale driving fields. Prior research has demonstrated that interior nudging can increase the skill of regional climate predictions originating from historical data. However, there is concern that nudging may also inhibit the regional model’s ability to properly develop and simulate mesoscale features, which may reduce the value added from downscaling by altering the representation of local climate extremes. Extreme climate events can result in large economic losses and human casualties, and regional climate downscaling is one method for projecting how climate change scenarios will affect extreme events locally. In this study, the effects of interior nudging are explored on the downscaled simulation of temperature and precipitation extremes. Multidecadal, continuous Weather Research and Forecasting model simulations of the contiguous United States are performed using coarse reanalysis fields as proxies for global climate model fields. The results demonstrate that applying interior nudging improves the accuracy of simulated monthly means, variability, and extremes over the multidecadal period. The results in this case indicate that interior nudging does not inappropriately squelch the prediction of temperature and precipitation extremes and is essential for simulating extreme events that are faithful in space and time to the driving large-scale fields.