On Ensemble Kalman Filter and Smoother
نویسندگان
چکیده
منابع مشابه
The Analog Ensemble Kalman Filter and Smoother
In classical data assimilation using sequential Monte Carlo methods, a physical model is run at each time steps to simulate members corresponding to different forecast scenarios. In this paper, we propose to use statistical analogs provided by observational or model-simulated data to emulate the dynamical model and generate relevant forecast members. This new methodology is called AnEnKF/AnEnFS...
متن کاملAn Ensemble Kalman Filter and Smoother for Satellite Data Assimilation
This paper proposes a methodology for combining satellite images with advection-diffusion models for interpolation and prediction of environmental processes. We propose a dynamic state-space model and an ensemble Kalman filter and smoothing algorithm for on-line and retrospective state estimation. Our approach addresses the high dimensionality, measurement bias, and nonlinearities inherent in s...
متن کاملAn Ensemble Kalman Smoother for Nonlinear Dynamics
It is formally proved that the general smoother for nonlinear dynamics can be formulated as a sequential method, that is, observations can be assimilated sequentially during a forward integration. The general filter can be derived from the smoother and it is shown that the general smoother and filter solutions at the final time become identical, as is expected from linear theory. Then, a new sm...
متن کاملTutorial on the Ensemble Kalman Filter ∗
The ensemble Kalman filter (EnKF) is a recursive filter suitable for problems with a large number of variables, such as discretizations of partial differential equations in geophysical models. The EnKF originated as a version of the Kalman filter for large problems (essentially, the covariance matrix is replaced by the sample covariance), and it is now an important data assimilation component o...
متن کاملHybrid Levenberg–Marquardt and weak-constraint ensemble Kalman smoother method
The ensemble Kalman smoother (EnKS) is used as a linear least-squares solver in the Gauss–Newton method for the large nonlinear least-squares system in incremental 4DVAR. The ensemble approach is naturally parallel over the ensemble members and no tangent or adjoint operators are needed. Furthermore, adding a regularization term results in replacing the Gauss–Newton method, which may diverge, b...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications
سال: 2018
ISSN: 2188-4730,2188-4749
DOI: 10.5687/sss.2018.15