Preliminary test of a data assimilation system with a regional high-resolution atmosphere-ocean coupled model based on an ensemble Kalman filter
Preliminary test of a data assimilation system with a regional high-resolution atmosphere-ocean coupled model based on an ensemble Kalman filter
复制标题
基于集合卡尔曼滤波器的区域高分辨率大气-海洋耦合模型资料同化系统的初步测试
DOI：
10.1175/mwr-d-16-0068.1
复制
发表时间：
2017
影响因子：
3.2
通讯作者：
and A. Wada
中科院分区：
文献类型：
--
作者：
Kunii;M.;K. Ito;and A. Wada
利用区域中尺度海-气耦合模式的集合卡尔曼滤波（EnKF）方法，初步研究了在集合资料同化中如何提供符合实际的海表温度（SST）估计值，并反映SST的不确定性。2014年7月至8月期间，通过一个月的数据同化周期实验对该系统进行了评估，在此期间发生了热带气旋（TC）和强降雨事件。结果表明，即使不同化SST和海表盐度观测值，耦合模式的资料同化循环也能真实地再现SST的分布，提供给海洋模式的大气变量对海洋变量具有一定的物理控制作用。在EnKF与耦合模式计算的预测误差协方差显示依赖于海洋垂直混合的近地面大气变量，由于大气和海洋之间的变化以及SST变化对大气边界层的影响的差异。与非耦合大气模式相比，耦合模式的EnKF更真实地再现了台风Halong（2014）在成熟阶段的强度变化，尽管SST估计值仍有下降，特别是在黑潮区域周围。这表明，应开发一个能够实际控制大气和海洋变量的大气-海洋耦合数据同化系统。
An ensemble Kalman filter (EnKF) that uses a regional mesoscale atmosphere–ocean coupled model was preliminarily examined to provide realistic sea surface temperature (SST) estimates and to represent the uncertainties of SST in ensemble data assimilation strategies. The system was evaluated through data assimilation cycle experiments over a one-month period from July to August 2014, during which time a tropical cyclone (TC) as well as severe rainfall events occurred. The results showed that the data assimilation cycle with the coupled model reproduced SST distributions realistically even without assimilating SST and sea surface salinity observations, and atmospheric variables provided to ocean models can, therefore, control oceanic variables physically to some extent. The forecast error covariance calculated in the EnKF with the coupled model showed dependency on oceanic vertical mixing for near-surface atmospheric variables due to the difference of variability between the atmosphere and the ocean as well as the influence of SST variations on the atmospheric boundary layer. The EnKF with the coupled model reproduced the intensity change of Typhoon Halong (2014) during the mature phase more realistically than with an uncoupled atmosphere model, although there remained a degradation of the SST estimate, particularly around the Kuroshio region. This suggests that an atmosphere–ocean coupled data assimilation system should be developed that is able to physically control both atmospheric and oceanic variables.