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The analog data assimilation
(American Meteorological Society, 2017-10)
In light of growing interest in data-driven methods for oceanic, atmospheric, and climate sciences, this work focuses on the field of data assimilation and presents the analog data assimilation (AnDA). The proposed framework ...
Data Assimilation by Ensemblekalman filter With the Lorenz EquationsASSIMILAÇÃO DE DADOS VIA FILTRO DE KALMAN POR CONJUNTO COM O SISTEMA DE LORENZ
(Universidade Federal de Santa Maria, 2016)
Inference of stochastic parametrizations for model error treatment using nested ensemble Kalman filters
(John Wiley & Sons Ltd, 2019-04)
Stochastic parametrizations are increasingly used to represent the uncertainty associated with model errors in ensemble forecasting and data assimilation. One of the challenges associated with the use of these parametrizations ...
Model error covariance estimation in particle and ensemble kalman filters using an online expectation–maximization algorithm
(John Wiley & Sons Ltd, 2020-11)
The performance of ensemble-based data assimilation techniques that estimate the state of a dynamical system from partial observations depends crucially on the prescribed uncertainty of the model dynamics and of the ...
Stochastic parameterization identification using ensemble Kalman filtering combined with maximum likelihood methods
(Taylor & Francis, 2018-01)
For modelling geophysical systems, large-scale processes are described through a set of coarse-grained dynamical equations while small-scale processes are represented via parameterizations. This work proposes a method for ...
Estimating model-error covariances in nonlinear state-space models using Kalman smoothing and the expectation-maximization algorithm
(Wiley, 2017-04)
Specification and tuning of errors from dynamical models are important issues in data assimilation. In this work, we propose an iterative expectation-maximization (EM) algorithm to estimate the model-error covariances using ...
Estimation of the functional form of subgrid-scale schemes using ensemble-based data assimilation: a simple model experiment
(Wiley, 2016-10-02)
Oceanic and atmospheric global numerical models represent explicitly the large‐scale dynamics while the smaller‐scale processes are not resolved, so that their effects in the large‐scale dynamics are included through ...
Estimation of the functional form of subgrid-scale parametrizations using ensemble-based data assimilation : a simplemodel experiment
(Royal Meteorological Society, 2016)
Oceanic and atmospheric global numerical models represent explicitly the large-scale dynamics while the smaller-scale processes are not resolved, so that their effects in the large-scale dynamics are included through ...
Modelación hidrológica de largo plazo en la cuenca baja del Río Magdalena
(Corporación Universidad de la CostaIngeniería Civil, 2021)