Earth and Space Science (Jul 2020)
Evaluation of a Customized Variable‐Resolution Global Model and its Application for High‐Resolution Weather Forecasts in East Asia
Abstract
Abstract The performance of a variable‐resolution global model, based on the Model for Prediction Across Scales‐Atmosphere (MPAS‐A) framework and with customized 160‐to‐1 km resolution grid mesh, was tested by simulating idealized flow fields as well as forecasting the evolution of actual weather systems. The mesh contains five levels of refinement, with 20, 15, 9, 3, and 1 km resolution covering central to East Asia, central to southern China, southeastern China, and Greater Bay Area/Hong Kong, respectively. Using a shallow‐water solver and MPAS‐A's solver, the mesh was evaluated against standard circularly refined meshes in simulating idealized steady‐state flows. Conservation properties and error growths in the 160‐to‐1 km and counterpart simulations were fairly comparable. By perturbing the steady flow, realistic baroclinic wave evolutions could be captured. Initialized by Global Forecast System (GFS), parallel experiments were further conducted with new‐Tiedtke (nTDK), Kain‐Fritsch (KF), and Tiedtke (TDK) cumulus schemes and a convection‐permitting suite (CP). Experiments showed that the model can give reasonable 5‐day outlooks and evolution of synoptic‐scale weather systems typically found in East Asia in various seasons. In particular, it can reproduce the mesoscale precipitation related to the Meiyu rainband (cold fronts) in summer (winter). When compared with station data, promising skills in predicting local temperature, humidity, and wind changes were found. It also performed slightly better using nTDK, KF, and TDK schemes, than adopting CP. Overall, by capturing multiscale features concurrently, these experiments gave reasonable global, regional, and local weather predictions, thereby demonstrating the practicality of using customized variable‐resolution meshes for high‐resolution short‐range weather forecasts under MPAS‐A framework.