Multi-index ensemble Kalman filtering
نویسندگان
چکیده
In this work we combine ideas from multi-index Monte Carlo and ensemble Kalman filtering (EnKF) to produce a highly efficient method called EnKF (MIEnKF). MIEnKF is based on independent samples of four-coupled estimators hierarchy resolution levels, it may be viewed as an extension the multilevel (MLEnKF) developed by same authors in 2020. Multi-index here refers two-index method, consisting that are coupled two degrees freedom: time discretization size. Under certain assumptions, when strong coupling between solutions neighboring numerical resolutions attainable, proven more tractable than MLEnKF. Said efficiency gains also verified numerically series test problems.
منابع مشابه
Variance Reduced Ensemble Kalman Filtering
A number of algorithms to solve large-scale Kalman filtering problems have been introduced recently. The ensemble Kalman filter represents the probability density of the state estimate by a finite number of randomly generated system states. Another algorithm uses a singular value decomposition to select the leading eigenvectors of the covariance matrix of the state estimate and to approximate t...
متن کاملFour-dimensional ensemble Kalman filtering
Ensemble Kalman filtering was developed as a way to assimilate observed data to track the current state in a computational model. In this paper we show that the ensemble approach makes possible an additional benefit: the timing of observations, whether they occur at the assimilation time or at some earlier or later time, can be effectively accounted for at low computational expense. In the case...
متن کاملEnsemble Kalman Filtering with Shrinkage Regression Techniques
The classical Ensemble Kalman Filter (EnKF) is known to underestimate the prediction uncertainty resulting from model overfitting and estimation error. This can potentially lead to low forecast precision and an ensemble collapsing into a single realisation. In this paper we present alternative EnKF updating schemes based on shrinkage methods known from multivariate linear regression. These meth...
متن کاملOptimization-based Sampling in Ensemble Kalman Filtering
In the ensemble Kalman filter (EnKF), uncertainty in the state of a dynamical model is represented as samples of the state vector. The samples are propagated forward using the evolution model, and the forecast (prior) mean and covariance matrix are estimated from the ensemble. Data assimilation is carried out by using these estimates in the Kalman filter formulas. The prior is given in the subs...
متن کاملSome Ideas for Ensemble Kalman Filtering
In this seminar we show clean comparisons between EnKF and 4D-Var made in Environment Canada, briefly describe the Local Ensemble Transform Kalman Filter (LETKF) as a representative prototype of Ensemble Kalman Filter, and give several examples of how advanced properties and applications that have been developed and explored for 4D-Var can be adapted to the LETKF without requiring an adjoint mo...
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: Journal of Computational Physics
سال: 2022
ISSN: ['1090-2716', '0021-9991']
DOI: https://doi.org/10.1016/j.jcp.2022.111561