Add to ORKGWe investigate a method to substantially reduce the analysis computations within the Local Ensemble Transform Kalman Filter (LETKF) framework. Instead of computing the LETKF analysis at every model grid point, we compute the analysis on a very coarse grid and interpolate onto a high-resolution grid by interpolating the analysis weights of the ensemble forecast members derived from the LETKF. Because the weights vary on larger scales than the analysis fields or analysis increments, there is little degradation in the quality of the weight-interpolated analyses compared to the analyses derived with the high-resolution grid, and the results from the weight-interpolated analyses are more accurate than the ones derived by interpolating the analys...
In this paper, we propose an efficient and practical implementation of the ensemble Kalman filter vi...
We introduce a new formulation of the ensemble forecast sensitivity developed by Liu and Kalnay with...
This paper outlines the basic concept and mathe-matical formulation of the Local Ensemble Kalman Fil...
AbstractLocal ensemble transform Kalman filters (LETKFs) allow explicit calculation of the Kalman ga...
(LETKF) (Hunt et al. 2006) is an efficient data assimilation scheme of the square root ensembl
The main goal of my research is to improve the performance of the EnKF in assimilating real observat...
A local ensemble transform Kalman filter (LETKF) is developed and assessed with the AGCM for the Ear...
We modify the local ensemble Kalman filter (LEKF) to incorporate the effect of forecast model bias. ...
A B S T R A C T We present a four-dimensional ensemble Kalman filter (4D-LETKF) that approximately a...
The most widely used methods of data assimilation in large-scale oceanography, such as the Simple Oc...
Ensemble Kalman filters (EnKF) based on a small ensemble tend to provide collapse of the ensemble ov...
The ensemble Kalman filter (EnKF) takes an advantage of the ensemble prediction technique to estimat...
The ensemble Kalman filter (EnKF) is a 4-dimensional data-assimilation method that uses a Monte-Carl...
A square root approach is considered for the problem of accounting for model noise in the forecast s...
The main goal of my research is to improve the performance of the EnKF in assimilating real observat...
In this paper, we propose an efficient and practical implementation of the ensemble Kalman filter vi...
We introduce a new formulation of the ensemble forecast sensitivity developed by Liu and Kalnay with...
This paper outlines the basic concept and mathe-matical formulation of the Local Ensemble Kalman Fil...
AbstractLocal ensemble transform Kalman filters (LETKFs) allow explicit calculation of the Kalman ga...
(LETKF) (Hunt et al. 2006) is an efficient data assimilation scheme of the square root ensembl
The main goal of my research is to improve the performance of the EnKF in assimilating real observat...
A local ensemble transform Kalman filter (LETKF) is developed and assessed with the AGCM for the Ear...
We modify the local ensemble Kalman filter (LEKF) to incorporate the effect of forecast model bias. ...
A B S T R A C T We present a four-dimensional ensemble Kalman filter (4D-LETKF) that approximately a...
The most widely used methods of data assimilation in large-scale oceanography, such as the Simple Oc...
Ensemble Kalman filters (EnKF) based on a small ensemble tend to provide collapse of the ensemble ov...
The ensemble Kalman filter (EnKF) takes an advantage of the ensemble prediction technique to estimat...
The ensemble Kalman filter (EnKF) is a 4-dimensional data-assimilation method that uses a Monte-Carl...
A square root approach is considered for the problem of accounting for model noise in the forecast s...
The main goal of my research is to improve the performance of the EnKF in assimilating real observat...
In this paper, we propose an efficient and practical implementation of the ensemble Kalman filter vi...
We introduce a new formulation of the ensemble forecast sensitivity developed by Liu and Kalnay with...
This paper outlines the basic concept and mathe-matical formulation of the Local Ensemble Kalman Fil...