Dynamical Global Downscaling of Global Reanalysis

Abstract With the aim of producing higher-resolution global reanalysis datasets from coarse-resolution reanalysis, a global version of the dynamical downscaling using a global spectral model is developed. A variant of spectral nudging, the modified form of scale-selective bias correction developed for regional models is adopted. The method includes 1) nudging of temperature in addition to the zonal and meridional components of winds, 2) nudging to the perturbation field rather than to the perturbation tendency, and 3) no nudging and correction of the humidity. The downscaling experiment was performed using a T248L28 (about 50-km resolution) global model, driven by the so-called R-2 reanalysis (T62L28 resolution, or about 200-km resolution) during 2001. Evaluation with high-resolution observations showed that the monthly averaged global surface temperature and daily variation of precipitation were much improved. Over North America, surface wind speed and temperature are much better, and over Japan, the diurnal pattern of surface temperature is much improved, as are wind speed and precipitation, but not humidity. Three well-known synoptic/subsynoptic-scale weather patterns over the United States, Europe, and Antarctica were shown to become more realistic. This study suggests that the global downscaling is a viable and economical method for obtaining high-resolution reanalysis without rerunning a very expensive high-resolution full data assimilation.