CMA全球混合四维变分同化系统的方法研究  

A methodological study of the CMA global hybrid four-dimensional variational data assimilation system

作　　者：王凡[1] 龚建东[2] 王瑞春[2] 陈耀登[1] WANG Fan;GONG Jiandong;WANG Ruichun;CHEN Yaodeng(Key Laboratory of Meteorological Disaster,Ministry of Education/International Joint Laboratory on Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science and Technology,Nanjing 210044,China;CMA Earth System Modeling and Prediction Centre(CEMC),Beijing 100081,China)

机构地区：[1]南京信息工程大学气象灾害教育部重点实验室/气候与环境变化国际合作联合实验室/气象灾害预报预警与评估协同创新中心,南京210044 [2]中国气象局地球系统数值预报中心,北京100081

出　　处：《气象学报》2024年第5期709-720,共12页Acta Meteorologica Sinica

基　　金：国家重点研发计划项目(2022YFC3004002)。

摘　　要：随流型演变的变量间背景误差协方差特征非常重要,而变分系统中传统气候背景误差很难描述这些信息。虽然四维变分同化(4DVar)能通过切线性和伴随模式隐式演变初始背景误差协方差,但其存在开发维护复杂、计算成本昂贵等问题,而且在高精度可扩展全球大气模式中尤为突出。为规避切线性和伴随模式,将四维集合预报误差引入CMA全球资料同化系统,发展了H-4DEnVar同化方案,开展批量循环同化及其预报试验和台风预报试验,并与4DVar方案对比。批量预报试验表明,四维集合预报误差的引入改善了分析场,显著提高了同化系统的全球预报能力;台风预报试验表明,H-4DEnVar中随流型演变的背景误差是台风路径预报误差减小的主要原因;与4DVar对比发现,考虑集合预报误差IO成本情况下,H-4DEnVar以4DVar 26%计算成本表现出基本相当的预报能力。H-4DEnVar同化方案在规避切线性和伴随模式的同时表现出了良好的同化预报效果,为在不使用切线性和伴随模式情况下实现四维同化提供了参考。The flow-dependent background error covariance between variables is important,yet traditional climatic background errors in variational systems are difficult to characterize such kind of information.Although 4DVar can implicitly evolve the initial background error covariance by tangent linear and adjoint models,it suffers from complex development,maintenance,and expensive computational costs,which are particularly prominent in high-precision scalable global atmospheric models.To avoid the tangent linear and adjoint models,the four-dimensional ensemble forecast error is introduced into the CMA global data assimilation system,and the H-4DEnVar assimilation scheme is developed.The batch cycling forecast experiments and typhoon forecast experiments are conducted and compared with the 4DVar scheme.Batch forecast experiments indicate that the introduction of the four-dimensional ensemble forecast error improves the analysis and significantly improves the global forecast performance;typhoon forecast experiments show that the flow-dependent background error in H-4DEnVar is the main reason for the reduction in typhoon track forecast error;the comparison with 4DVar reveals that H-4DEnVar exhibits essentially comparable forecast capability at 26% of the computational cost of 4DVar when the IO cost of the ensemble forecast error is considered.The H-4DEnVar assimilation scheme shows good analysis and forecast effects while avoiding the tangent linear and adjoint models,and provides a reference for achieving four-dimensional assimilation scheme without the tangent linear and adjoint models.

关 键 词：切线性和伴随模式 背景误差协方差 4DVAR 集合预报误差 H-4DEnVar 

分 类 号：P456.7[天文地球—大气科学及气象学]