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Mitigating Observation Perturbation Sampling Errors in the Stochastic EnKF
AbstractThe stochastic ensemble Kalman filter (EnKF) updates its ensemble members with observations perturbed with noise sampled from the distribution of the observational errors. This was shown to
Enhanced Adaptive Inflation Algorithm for Ensemble Filters
AbstractSpatially and temporally varying adaptive inflation algorithms have been developed to combat the loss of variance during the forecast due to various model and sampling errors. The adaptive
A Bayesian Consistent Dual Ensemble Kalman Filter for State-Parameter Estimation in Subsurface Hydrology
This paper reverse the order of the forecast-update steps following the one-step-ahead (OSA) smoothing formulation of the Bayesian filtering problem, based on which a new dual EnKF scheme, the Dual-EnKF, is proposed, which is able to successfully recover both the hydraulic head and the aquifer conductivity.
Constraining a compositional flow model with flow‐chemical data using an ensemble‐based Kalman filter
This work considers the problem of estimating reservoir permeability using information about phase pressure as well as the chemical properties of fluid components and indicates that including chemical composition data significantly enhances the accuracy of the permeability estimates.
An Extended SEIR Model with Vaccination for Forecasting the COVID-19 Pandemic in Saudi Arabia Using an Ensemble Kalman Filter
An extended SEIR model with a vaccination compartment is proposed to simulate the novel coronavirus disease (COVID-19) spread in Saudi Arabia and the capability of the proposed model in achieving accurate prediction of the epidemic development up to two-week time scales is demonstrated.