南海及沿岸海基观测资料同化对华南暴雨预报的影响

IMPACT OF ASSIMILATING SEA-BASED OBSERVATIONS FROM THE SOUTH CHINA SEA AND COASTAL AREAS ON HEAVY RAINFALL FORECASTING IN SOUTH CHINA

关键词:  资料同化  暴雨  浮标  海洋观测  质量控制

Key words:  South China Sea  data assimilation  heavy rainfall  marine observation  quality control

摘要:

海基（浮标站、海岛站、平台站）现场观测作为海洋观测的主要来源，对大气和海洋科学的发展起到重要作用。探讨了南海及沿岸海基观测资料同化对华南前汛期暴雨预报的潜在影响。在地面站观测资料同化基础上，增加海基观测资料同化，并进行了连续循环同化试验。试验结果表明，连续循环同化方案显著优于冷启动同化方案的降水预报，通过连续循环同化海基观测资料可以有效改善分析场低层的湿度场和风场，进而改善了华南上游南海区域的水汽输送和动力条件。在降水预报方面，同化海基观测资料对陆地区域的降水预报改善不明显，但对沿岸及海上区域的降水预报改善显著，尤其是18 h和24 h的强降水预报。总体来看，增加海基观测资料同化对华南前汛期南海沿岸及海上区域暴雨预报产生了积极的正贡献，本研究对CMA-MESO模式实现更多海基观测资料业务同化、提高华南前汛期暴雨预报水平和开展南海海洋观测试验提供了重要依据。

Abstract:

Buoy, island stations, and platform stations play a crucial role in advancing atmospheric and ocean sciences by providing essential marine observational data. This paper explores the potential impact of assimilating sea-based observation data from the South China Sea and the coast on forecasts of heavy rainfall during annually first rainy seasons in South China. In addition to ground station observations, sea-based observations are added to conduct continuous cycle assimilation experiments. The experiment results suggest that the continuous cycle assimilation scheme significantly improves precipitation forecasting compared to the cold-start assimilation scheme. The assimilation of additional sea-based observations effectively enhances the humidity field and wind field at the lower levels of the analysis field, thereby improving the water vapor transport and dynamic conditions in the South China Sea region. While the assimilation of sea-based observations does not show significant improvement in precipitation forecasts over land areas, it notably enhances precipitation forecasts for coastal and offshore regions, particularly for heavy rainfall forecasts at 18- and 24-hour lead times. Overall, the inclusion of sea-based observations positively contributes to the prediction of heavy rainfall along the coastal and offshore regions of the South China Sea during annually first rainy seasons. This study provides an important basis for the CMA-MESO model to achieve more operational assimilation of sea-based observations, improve heavy rainfall forecasting in South China, and conduct marine observation experiments in the South China Sea.