Abstract: he main goal of this work is to present a new square root ensemble generation technique that is consistent with a recently developed extension of Kalman-based linear regression algorithms such that they may perform nonlinear ...

Abstract: A widely used observation space covariance localization method is shown to adversely affect satellite radiance assimilation in ensemble Kalman filters (EnKFs) when compared to model space covariance localization. The two ...

Abstract: nsemble-based Kalman filter (EBKF) algorithms are known to produce posterior ensembles whose variance is incorrect for a variety of reasons (e.g., nonlinearity and sampling error). It is shown here that the presence of ...

Abstract: This article discusses a practical problem faced in operational atmospheric forecasting and data assimilation, and efforts to improve forecast quality through the choice of quality control parameters. The need to utilize ...

Abstract: ppropriate specification of the error statistics for both observational data and short-term forecasts is necessary to produce an optimal analysis. Observation error stems from instrument error, forward model error, and ...

Abstract: AbstractIt is well known that the ensemble-based variants of the Kalman filter may be thought of as producing a state estimate that is consistent with linear regression. Here, it is shown how quadratic polynomial regression ...