数值预报误差订正技术中相似-动力方法的发展

Development of the analogue-dynamical method for error correction of numerical forecasts

随着对天气和气候预测准确率要求的提高,在发展数值模式和资料同化技术的同时,很有必要在现有数值模式基础上开发误差订正技术。基于预报误差的不同类型对订正技术进行了分类,回顾了目前误差订正技术的研究进展。中国学者在该领域研究中将统计方法和动力模式相结合,发展了一种基于历史相似信息进行误差订正的相似-动力方法,实现了动力预报中历史资料的有效运用。重点介绍了该方法的基本原理、技术方案的演变过程,及其在不同时间尺度的天气和气候预测中的发展,结果表明该方法在中短期预报、延伸期预报、月平均环流预报和短期气候预测等各个时问尺度中均能够有效提高预报技巧。作为一项中国自主研发的创新技术,在天气预报和气候预测中发挥了重要作用,展现出广阔的应用前景。

Due to the increasing requirement for high-level weather and climate forecasting accuracy,it is necessary to exploit a strategy for model error correction while developing numerical modeling and data assimilation techniques.This study classifies the correction strategies according to the types of forecast errors,and reviews recent studies on these correction strategies.Among others,the analogue-dynamical method has been developed in China,which combines statistical methods with the dynamical model,corrects model errors based on analogue information,and effectively utilizes historical data in dynamical forecasts.In this study,the fundamental principles and technical solutions of the analogue-dynamical method and associated development history for forecasts on different timescales are introduced.It is shown that this method can effectively improve medium- and extended-range forecasts,monthly-average circulation forecast,and short-term climate prediction.As an innovative technique independently developed in China,the analogue-dynamical method plays an important role in both weather forecast and climate prediction,and has potential applications in wider fields.