Weather Prediction and computational aspects of Icosahedral-Hexagonal Gridpoint Model GME

摘要

In prediction viewpoint, hindcast experiment of GME was performed by specifying observed SSTs every day based on ECMWF Re-analysis (ERA) dataset. In brief GME incorporates many of the positive features of spectral models and finite difference models into a single framework. GME generally employs the same methods and procedures applied in other numerical weather prediction (NWP) grid schemes. However, the uniformity of the GME grid avoids unnecessary physics calculations in over resolved high-latitude zones that commonly occur in grids with polar singularities. Implementation of model on high performance computer based on Linux clusters can provide added advantage. High resolution of GME can play key role in the study of server weather phenomenon such as heavy rainfall, snowfall and typhoon cases. Seasonal prediction experiments (hindcast experiments) were conducted for selected cases. In dry and hot summer of 1994, GME model is able to capture negative anomalies over Korean peninsula. In wet summer of 2003, GME depicts stronger positive anomalies over entire Korean Peninsula. We strongly believe that geodesic grids based on icosahedron hold a great deal of promise for the future of the atmospheric general circulation modeling.