Biblio
Filtre: Forfatter er Mohamad El Gharamti [Slett Alle Filtre]
Estimation of Ocean Biogeochemical Parameters in an Earth System Model Using the Dual One Step Ahead Smoother: A Twin Experiment. Frontiers in Marine Science 9, (2022).
Assimilation of semi-qualitative sea ice thickness data with the EnKF-SQ: a twin experiment. Tellus A: Dynamic Meteorology and Oceanography 72, (2019). Abstract
Assimilation of semi-qualitative observations with a stochasticensemble Kalman filter. Quarterly Journal of the Royal Meteorological Society 144, (2018). Abstract
Ensemble data assimilation for ocean biogeochemical state and parameter estimation at different sites. Ocean Modelling 112, (2017).
Online tuning of ocean biogeochemical model parameters using ensemble estimation techniques: Application to a one-dimensional model in the North Atlantic. Journal of Marine Systems 168, (2017). Abstract
Assessing clustering strategies for Gaussian mixture filtering a subsurface contaminant model. Journal of Hydrology 535, (2016). Abstract
A Bayesian consistent dual ensemble Kalman filter for state-parameter estimation in subsurface hydrology. Hydrology and Earth System Sciences (HESS) 20, (2016). Abstract
On the efficiency of the hybrid and the exact second-order sampling formulations of the EnKF: A reality-inspired 3D test case for estimating biodegradation rates of chlorinated hydrocarbons at the port of Rotterdam. Hydrology and Earth System Sciences (HESS) 20, (2016). Abstract
A Greedy Approach for Placement of Subsurface Aquifer Wells in an Ensemble Filtering Framework. Lecture Notes in Computer Science (LNCS) 8964, (2015). Abstract
An iterative ensemble Kalman filter with one-step-ahead smoothing for state-parameters estimation of contaminant transport models. Journal of Hydrology 527, (2015). Abstract
Mitigating Observation Perturbation Sampling Errors in the Stochastic EnKF. Monthly Weather Review 143, (2015). Abstract
A One-Step-Ahead Smoothing-Based Joint Ensemble Kalman Filter for State-Parameter Estimation of Hydrological Models. Lecture Notes in Computer Science (LNCS) 8964, (2015). Abstract
