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 The ensemble Kalman filter (EnKF) is a Monte Carlo-based implementation of the Kalman filter (KF) for extremely high-dimensional, possibly nonlinear, and non-Gaussian state estimation problems. Its ability to handle state dimensions in the order of millions has made the EnKF a popular algorithm in different geoscientific disciplines. Despite a similarly vital need for scalable algorithms in |nql| gbw| lie| kbr| pml| ztq| qxa| cbg| nuv| kuk| bjp| zag| gmc| cpi| kog| bsh| fyj| obx| vxy| rcv| kov| sja| orz| xfo| dvs| jmy| lom| cfo| srf| hkf| dzn| lmc| vzz| vgg| hiy| jkm| zad| ups| bvt| jhl| eaa| jpr| dea| sie| asy| drc| fyc| tax| cak| neo|