Comparison between high-resolution climate simulations using single- and double-nesting approaches within the Big-Brother experimental protocol

作者：Matte Dominic; Laprise Rene; Theriault Julie Mireille

来源：Climate Dynamics, 2016, 47(12): 3613-3626.

DOI：10.1007/s00382-016-3031-9

• High-resolution climate simulation
• Big-Brother experiment
• Multiple dynamical downscaling
• Spatial spin-up

Regional climate models (RCM) are widely used to downscale global climate models' (GCMs) simulations. As the resolution of RCM increases faster than that of GCM used for climate-change projections till the end of this century, the resolution jump will become an issue. Cascade with multiple nesting offers an approach to reach high resolution while keeping reasonable computational cost. Few studies have addressed whether the best results are obtained with the single- or multiple-nesting approaches. In this study the results obtained with single and double nesting are compared within the idealised "perfect model" framework of the Big-Brother Experiment. This method consists in first realizing a simulation, nicknamed the Big-Brother (BB) simulation, on a relatively large domain at the desired resolution, to serve as reference dataset. The BB results are then processed by a low-pass filter to emulate a coarse-resolution dataset to be used as LBC to drive further simulations, nicknamed the Little-Brother (LB) simulations, using an identical model formulation and resolution as the BB simulation. For the single nesting, the LB simulations are directly simulated, while for the double nesting a surrogate intermediate-resolution simulation is used. The study of the time-mean (stationary) component shows that little difference is noted between the single- and double-nesting approaches. The time-deviation (transient-eddy) component, however, shows important differences. The double-nesting approach weakly degrades the large scales but allows a significant reduction of the required domain size to allow adequate spin-up of fine-scale features. This results in an important saving in the computational cost.

• 出版日期2016-12