我国无缝隙精细化网格天气预报技术进展与挑战
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摘要
本文总结了2014年以来我国无缝隙精细化网格天气预报业务的技术进展,讨论了未来发展所面临的关键技术难点。无缝隙精细化网格预报技术的发展,得益于综合气象观测数据和多源资料融合分析网格实况产品的支撑,更依赖于多尺度数值预报模式和实时快速更新同化预报系统的快速发展。经过近5年的探索和努力,我国已经初步建立了针对不同预报时效的无缝隙精细化网格预报技术体系。对于0～4 h预报时效,主要基于全国雷达拼图和GRAPES-Meso模式预报,发展临近分钟级滚动外推预报技术;对于4 h到30 d预报时效,主要通过对区域或全球不同时空分辨率模式预报进行偏差订正、客观解释应用以及降尺度分析,提高预报的准确度和精细度。与此同时,研发了自动化、智能化的交互式预报制作平台,以满足客观高效制作与预报员对极端或高影响天气主观预报优势相结合的需求。发展了以格点实况分析场为参照的空间分析检验方法,初步实现了对高分辨率网格预报的质量跟踪和性能评估。未来的网格预报技术体系,需要吸纳前沿的技术研究成果,包括人工智能应用技术、高级多模式统计后处理技术和协调一致性关键技术等,并且建立统一完整的技术架构和开发标准等。
This paper reviews the development of the technology for seamless fine gridded weather forecasting in China since 2014. And the key technical difficulties in the future development are analyzed. It is pointed out that the high spatio-temporal resolution observations capturing the fine structure of weather systems, the analysis products by multi-source data fusion, the real-time rapid updating assimilation and prediction system, the high resolution regional model providing short-time and short-term weather prediction, the global numerical forecast model providing 10 days' weather forecasting, and the ocean-atmosphere coupled ensemble prediction system providing 46 days' weather prediction, have jointly established the premise and foundation of the seamless gridded weather forecasts. After nearly 5 years ' exploration and constant efforts, the technology system of seamless fine gridded forecasting with different temporal resolutions has been established. The high-frequency lagrangian extrapolation skills are used for 0-4 h forecasting based on GRAPES-Meso model forecast products and radar data over China. For the 4 h to30 d lead-time forecasting, it mainly depends on the downscaling, error correction, model output statistics and post-processing methodologies based on regional and global models of different spatio-temporal resolutions to improve forecast skills and resolution. At the same time, automatic and intelligent interactive forecasting platform is developed to meet the demand of combining efficient objective forecasting with forecasters' subjective intelligence. In order to assess and track the performance of high resolution gridded forecasting, a spatial analysis verification method based on gridded observation data is developed. It is also stressed that the future gridded forecasting technology system should be able to reflect the latest technology development including the artificial intelligence application, more advanced statistical post-processing skills,key technics for consistency forecasting and unified complete technical architecture and standards.
This paper reviews the development of the technology for seamless fine gridded weather forecasting in China since 2014. And the key technical difficulties in the future development are analyzed. It is pointed out that the high spatio-temporal resolution observations capturing the fine structure of weather systems, the analysis products by multi-source data fusion, the real-time rapid updating assimilation and prediction system, the high resolution regional model providing short-time and short-term weather prediction, the global numerical forecast model providing 10 days' weather forecasting, and the ocean-atmosphere coupled ensemble prediction system providing 46 days' weather prediction, have jointly established the premise and foundation of the seamless gridded weather forecasts. After nearly 5 years ' exploration and constant efforts, the technology system of seamless fine gridded forecasting with different temporal resolutions has been established. The high-frequency lagrangian extrapolation skills are used for 0-4 h forecasting based on GRAPES-Meso model forecast products and radar data over China. For the 4 h to30 d lead-time forecasting, it mainly depends on the downscaling, error correction, model output statistics and post-processing methodologies based on regional and global models of different spatio-temporal resolutions to improve forecast skills and resolution. At the same time, automatic and intelligent interactive forecasting platform is developed to meet the demand of combining efficient objective forecasting with forecasters' subjective intelligence. In order to assess and track the performance of high resolution gridded forecasting, a spatial analysis verification method based on gridded observation data is developed. It is also stressed that the future gridded forecasting technology system should be able to reflect the latest technology development including the artificial intelligence application, more advanced statistical post-processing skills,key technics for consistency forecasting and unified complete technical architecture and standards.
引文
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*2018年全国智能网格预报业务工作部署会议报告。
*2018年成都智能网格预报和实况数据分析业务研讨会议交流报告“全国智能网格实况分析产品研制与评估应用”。
*2018年10月全国气象台长会议交流报告《大数据与人工智能技术在天气预报中的应用》。
曹勇,刘凑华,宗志平,等,2016.国家级格点化定量降水预报系统[J].气象,42(12):1476-1482.Cao Y,Liu C H,Zong Z P,et al,2016. State-level gridded quantitative precipitation forecasting system[J]. Meteor Mon,42(12):1476-1482(in Chinese).
陈法敬,陈静,韦青,等,2019.一种基于可预报性的暴雨预报评分新方法Ⅱ:暴雨检验评分模型及评估试验[J].气象学报,77(1):28-42. Chen F J,Chen J,Wei Q,et al,2019. A new verification method for heavy rainfall forecast based on predictabilityⅡ:verification method and test[J]. Acta Meteor Sin,77(1):28-42(in Chinese).
陈力强,周小珊,杨森,2005.短期集合预报中定量降水预报集合方法初探[J].南京气象学院学报,28(4):543-548. Chen L Q,Zhou X S,Yang S,2005. A quantitative precipitation forecasts method for short-range ensemble forecasting[J]. J Nanjing Inst Meteor,28(4):543-548(in Chinese).
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*2018年全国智能网格预报业务工作部署会议报告。
*2018年成都智能网格预报和实况数据分析业务研讨会议交流报告“全国智能网格实况分析产品研制与评估应用”。
*2018年10月全国气象台长会议交流报告《大数据与人工智能技术在天气预报中的应用》。