Effective approaches to extending medium-term forecasting of persistent severe precipitation in regional models

• Published in: Atmospheric and oceanic science letters = Daqi-he-haiyang-kexue-kuaibao Vol. 11; no. 2; pp. 150 - 156
• Main Authors: WANG, Dong-Hai, ZHAO, Yan-Feng
• Format: Journal Article
• Language: English
• Published: Beijing KeAi Publishing Communications Ltd 04.03.2018; KeAi Communications Co., Ltd
• Subjects: Atmospheric precipitations; Correlation coefficient; dynamic extended medium-term forecasting; Forecasting; lateral boundary filtering; Methods; Persistent severe precipitation; Precipitation; Rain; Rainfall; spectral nudging; updated initial conditions; Weather forecasting
• ISSN: 1674-2834; 2376-6123
• DOI: 10.1080/16742834.2018.1423227

A set of methods designed to improve (i.e. extend) the medium-term forecasting of persistent severe rainfall (PSR) events in China using the regional Weather Research and Forecasting model are summarized. Simulations show that achieving a more efficient use of large-scale atmospheric variations of the global model and retaining small-scale features in the regional model are critical for better forecasting PSR events. For precipitation, the larger the magnitude and longer the lead time, the more significant the improvement—especially for the methods of spectral nudging and updated initial conditions. In terms of large-scale circulation, the anomaly correlation coefficient can be distinctly improved for 1–5-day lead times by adopting the spectral nudging technique, whereas lateral boundary filtering results in marked improvement for 7–11-day lead times.