A Combined Approach to Improving the Regional Model Forecasts for the Rainy Season in China

Abstract

A combined forecasting methodology, into which the spectral nudging, lateral boundary filtering, and update initial conditions methods are incorporated, was employed in the regional Weather Research and Forecasting (WRF) Model. The intent was to investigate the potential for improving the prediction capability for the rainy season in China via using as many merits of the global model having better predictability as it does for the large-scale circulation and of the regional model as it does for the small-scale features. The combined methodology was found to be successful in improving the prediction of the regional atmospheric circulation and precipitation. It performed best for the larger magnitude precipitation, the relative humidity above 800 hPa, and wind fields below 300 hPa. Furthermore, the larger the magnitude and the longer the lead time, the more obvious is the improvement in terms of the accumulated rainfall of persistent severe rainfall events.