围隔资料同化的有效措施
Effective Actions for Ensemble Data Assimilation
摘要：
Enhancement数据同化是确定观测动力系统模型的最可能相空间轨迹的问题，因为它接收来自将信息传递到模型的测量的输入。本文利用统计物理学中的方法，给出了当动力学模型有误差、初始状态有不确定性和接收测量信息时，与动力学模型时间发展相关的平均轨道的有效作用量和运动方程。如果测量中的误差之间存在相关性，则它们自然包括在该方法中。
英文摘要：
Ensemble data assimilation is a problem in determining the most likely phase space trajectory of a model of an observed dynamical sys- tem as it receives inputs from measurements passing information to the model. Using methods developed in statistical physics, we present effective actions and equations of motion for the mean orbits associ- ated with the temporal development of a dynamical model when it has errors, there is uncertainty in its initial state, and it receives informa- tion from measurements. If there are correlations among errors in the measurements they are naturally included in this approach.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
