Downscaling comparison between spectral nudging and grid nudging techniques using the Weather Research and Forecast model

In order to investigate how future regional-scale air quality will respond to different emission scenarios under various climate-change responsive control strategies, high resolution regional meteorology fields that are consistent with future climate predictions need to be developed. Downscaling coarse-scale fields from global climate models (GCMs) using a regional meteorological model (RCM) equipped with nudging techniques such as Weather Research and Forecast (WRF) model is a scientific sound choice. Grid nudging has been intensively applied to downscaling reanalysis data for regional air quality modeling of historical episodes. However, spectral nudging is postulated to have advantages over grid nudging in capturing large-scale features of GCMs climate predictions, but not over-nudging at smaller scales. We investigate how grid- and spectral nudging perform in balancing the ability to add small-scale features and the ability to retain large-scale features provided by GCMs. NCEP-NCAR reanalysis data are downscaled using WRF and the results are evaluated by assessing similarity at large and small scales, respectively.