时空投影模型STPM的次季节至季节预测应用进展
投稿时间:2019-10-28  修订日期:2019-10-28  点此下载全文
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作者单位E-mail
徐邦琪 南京信息工程大学 Pang-Chi Hsu@gmail.com 
臧钰歆 南京信息工程大学  
基金项目:国家重点研发计划
中文摘要:随着数值天气预报技术和季节动力预报系统的发展,短期天气预报及长期气候预测的能力持续提高,然而介于两者之间的次季节至季节(S2S,两周至三个月)预测技巧偏低,成为当今气象学界和业务服务的难题。南京信息工程大学国家特聘专家李天明教授团队于2012年研发了基于时空投影技术的统计预报模型(STPM),成功地对中国大陆降水和气温距平,以及区域极端降水、夏季高温、冬季低温和西太平洋台风群发事件等高影响天气进行提前10~30天的预报,并在国家气候中心及多个省份开展了业务应用。STPM也成功应用于台湾春雨预报、南海季风爆发和ENSO预测等季节至年际变化的预测。本文对S2S预测的理论基础、STPM的发展和应用进行了完整的介绍,并讨论了S2S预测业务中所面临的挑战和未来展望。
中文关键词:时空投影模型 次季节至季节预测 延伸期天气预报 可预报性来源 极端天气
 
Subseasonal-to-seasonal Prediction Using the Spatial-temporal Projection Model
Abstract:With the developments of numerical weather forecasting technology and seasonal prediction system, the ability of short-term weather forecast and long-term climate prediction continues to improve. However, the subseasonal to seasonal (S2S, two weeks to three months) prediction skill is relatively low and has become a challenging issue for the meteorological community and operational services. The research team led by Prof. Tim Li at Nanjing University of Information Science & Technology developed the spatial-temporal projection model (STPM) in 2012. The STPM shows good skill in predicting the rainfall and temperature anomalies and extreme events in China, such as extreme precipitation, heatwave, extreme cold days and typhoon clustering events at the lead time of 10 to 30 days. The real-time extended-range weather forecast using the STPM have been carried out in the National Climate Center and several provinces. In addition to the subseasonal forecast, the STPM has also been successfully applied to the forecasts of spring rain in Taiwan, the onset of South China Sea monsoon and ENSO. In this paper, we will introduce the physical basis of S2S prediction, the development and application of STPM, and discuss the challenges and future prospects of S2S prediction.
keywords:Spatial-temporal Projection Model  Subseasonal-to-seasonal Prediction  Extended-range weather forecast  Source of predictability  Extreme weather
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