Ensemble Kalman methods: a mean field perspective
This paper provides a unifying mean field based framework for the derivation and analysis of
ensemble Kalman methods. Both state estimation and parameter estimation problems are …
ensemble Kalman methods. Both state estimation and parameter estimation problems are …
Arctic sea ice data assimilation combining an ensemble Kalman filter with a novel Lagrangian sea ice model for the winter 2019–2020
Advanced data assimilation (DA) methods, widely used in geophysical and climate studies
to merge observations with numerical models, can improve state estimates and consequent …
to merge observations with numerical models, can improve state estimates and consequent …
[HTML][HTML] Ensemble Kalman filter for GAN-ConvLSTM based long lead-time forecasting
Data-driven machine learning techniques have been increasingly utilized for accelerating
nonlinear dynamic system prediction. However, machine learning-based models for long …
nonlinear dynamic system prediction. However, machine learning-based models for long …
Ensemble-based flow field estimation using the dynamic wind farm model floridyn
Wind farm control methods allow for a more flexible use of wind power plants over the
baseline operation. They can be used to increase the power generated, to track a reference …
baseline operation. They can be used to increase the power generated, to track a reference …
Multivariate state and parameter estimation with data assimilation applied to sea-ice models using a Maxwell elasto-brittle rheology
In this study, we investigate the fully multivariate state and parameter estimation through
idealised simulations of a dynamics-only model that uses the novel Maxwell elasto-brittle …
idealised simulations of a dynamics-only model that uses the novel Maxwell elasto-brittle …
Probabilistic forecasts of sea ice trajectories in the Arctic: impact of uncertainties in surface wind and ice cohesion
We study the response of the Lagrangian sea ice model neXtSIM to the uncertainty in sea
surface wind and sea ice cohesion. The ice mechanics in neXtSIM are based on a brittle-like …
surface wind and sea ice cohesion. The ice mechanics in neXtSIM are based on a brittle-like …
Multivariate state and parameter estimation with data assimilation on sea-ice models using a Maxwell-Elasto-Brittle rheology
In this study, we investigate the fully multivariate state and parameter estimation through
idealised simulations of a dynamic-only model that uses the novel Maxwell-Elasto-Brittle …
idealised simulations of a dynamic-only model that uses the novel Maxwell-Elasto-Brittle …
Tailoring data assimilation to discontinuous Galerkin models
In recent years discontinuous Galerkin (DG) methods have received increased interest from
the geophysical community. In these methods the solution in each grid cell is approximated …
the geophysical community. In these methods the solution in each grid cell is approximated …
An adaptive hierarchical ensemble Kalman filter with reduced basis models
The use of model order reduction techniques in combination with ensemble-based methods
for estimating the state of systems described by nonlinear partial differential equations has …
for estimating the state of systems described by nonlinear partial differential equations has …
Desarrollo del sistema de pronóstico del Río de la Plata y su Frente Marítimo: PronUy_RPFM
D Balparda, L Sellanes, D Silva, M Jackson, P Ezzatti… - Ribagua, 2022 - Taylor & Francis
En este trabajo se presentan las características del sistema global de pronóstico
desarrollado para el Río de la Plata y Frente Marítimo, denominado PronUy_RPFM, y en …
desarrollado para el Río de la Plata y Frente Marítimo, denominado PronUy_RPFM, y en …