Multiscale four-dimensional data assimilation

Abstract

A multiscale nudging approach that utilizes grid nesting is investigated for the generation of complete, dynamically consistent datasets for the mesobeta scale. These datasets are suitable for input into air quality models, but can also be used for other diagnostic purposes including model initialization. A multiscale nudging strategy is used here to simulate the wind flow for two cases over the Colorado Plateau and Grand Canyon region. The special data included Doppler sodars, profilers, rawinsondes, and surface stations. Combinations of these data and conventional mesoalpha-scale data were assimilated into a nested version of the Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model to investigate the importance of scale interaction and scale separation during FDDA. -from Authors