Impacts of Assimilation Frequency on Ensemble Kalman Filter Data Assimilation and Imbalances

Impacts of Model Error and Ensemble Initiation on Mesoscale Data Assimilation with an Ensemble Kalman Filter

An 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...

SPE 109808 An Iterative Ensemble Kalman Filter for Data Assimilation

The ensemble Kalman filter (EnKF) is a subject of intensive investigation for use as a reservoir management tool. For strongly nonlinear problems, however, EnKF can fail to achieve an acceptable data match at certain times in the assimilation process. Here, we provide iterative EnKF procedures to remedy this deficiency and explore the validity of these iterative methods compared to standard EnK...

An Ensemble Adjustment Kalman Filter for Data Assimilation

A theory for estimating the probability distribution of the state of a model given a set of observations exists. This nonlinear filtering theory unifies the data assimilation and ensemble generation problem that have been key foci of prediction and predictability research for numerical weather and ocean prediction applications. A new algorithm, referred to as an ensemble adjustment Kalman filte...

Snow Data Assimilation via an Ensemble Kalman Filter

A snow data assimilation study was undertaken in which real data were used to update a conceptual model, SNOW-17. The aim of this study is to improve the model’s estimate of snow water equivalent (SWE) by merging the uncertainties associated with meteorological forcing data and SWE observations within the model. This is done with a view to aiding the estimation of snowpack initial conditions fo...