模式气候吸引子信息约束下的动力协调初始化方法及其在ENSO预测中的应用

为了改善模式初始场质量,减少初值与模式不协调对ENSO预测的影响,针对国家气候中心NCCo海-气耦合模式原初始化方案动力小协调的问题,从利用模式长期耦合模拟资料中的模式气候吸引子信息的角度出发,发展了一种获取观测资料中与模式相协调分量的信息重构方法,提出了一种模式气候吸引子信息约束下的动力协调初始化方案.对该方案回报检验的结果表明:通过反演NCCo海-气耦合模式模拟资料中的模式气候吸引子信息,有助于获取观测资料中与模式相协调的信息分量特征,实现了初始化过程中动力模式与所同化观测资料间的协调.这种基于信息重构方法的动力协调初始化方案,既可以延续原初始化方案利用观测信息较多的优势,又克服了原方案中观测资料和动力模式不协调的缺陷.这种新的初始化方案,消除了观测资料和模式不协调在初始场中产生的小尺度高频噪声,突出了与NCCo模式动力特征相适应的ENSO尺度信息.进而抑制了初始场中高频噪声所引起的快变预报误差的增长,提高了模式的预测技巧.

A dynamically harmonic initialization method const rained by model climate attractor information of model and its Utilization in EN SO prediction.

In order to resolve the dynamically inharmonic problem between assimilated observational data and dynamic model in the original initialization scheme of the NCCo model, and improve its prediction skill on ENSO, a new initialization scheme called dynamically harmonic initialization scheme (DHI hereafter) based on a data reconstructed method was proposed. The main function of this data reconstructed method is to separate the model compatible part of observational information from the original observational data through inversing the information of model climate attractor contained in the long-term coupled simulations. To verify the capability of DHI, the prediction skill of DHI and its relative mechanism were also comprehensively analyzed. The results show that most of the model related ENSO scale noises in the intialfield caused by disharmony between the assimilated data and the model from the original initialization scheme have been squeezed out, while the model related ENSO scale signals in the intialfield have been well preserved. The corresponding fast prediction errors arisen from propagation of none ENSO scale noises are effectively halted. Thus, the prediction skill is improved greatly, and the harmony between the NCCo model and assimilated data is easily reached when it is initialized.