Results 161 to 170 of about 116,536 (277)

A pilot variational coupled reanalysis based on the CESAM climate model

open access: yesQuarterly Journal of the Royal Meteorological Society, EarlyView.
Variational data assimilation of in‐situ and satellite ocean data and reanalysis atmospheric data into an intermediate complexity Earth system model is possible by adjusting the surface fluxes and internal model parameters. This pilot application requires nearly complete information on the atmospheric state for synchronization.
Armin Köhl   +6 more
wiley   +1 more source

A composite‐loss graph neural network for the multivariate post‐processing of ensemble weather forecasts

open access: yesQuarterly Journal of the Royal Meteorological Society, EarlyView.
The dual graph neural network (dualGNN), trained with a composite loss combining the energy score (ES) and variogram score (VS), consistently outperformed models optimized solely for ES or the continuous ranked probability score in the multivariate setting, as well as empirical copula approaches.
Mária Lakatos
wiley   +1 more source

Impact of data assimilation on Arctic sea‐ice thickness variability and its coupling with atmospheric forcing

open access: yesQuarterly Journal of the Royal Meteorological Society, EarlyView.
We document for the first time how the assimilation of CS2SMOS observations improves the model representation of Arctic sea‐ice thickness (SIT) and its variability: biases are reduced (top row), while excessive variability in the Beaufort Sea and lack of variability in the ice pack are both corrected (bottom row).
Jiping Xie   +3 more
wiley   +1 more source

Physics‐Informed Neural Networks for Battery Degradation Prediction Under Random Walk Operations

open access: yesQuality and Reliability Engineering International, EarlyView.
ABSTRACT This study addresses the challenge of predicting the state of health (SoH) and capacity degradation in Battery Energy Storage Systems (BESS) under highly variable conditions induced by frequent control adjustments. In environments where random walk behavior prevails due to stochastic control commands, conventional estimation methods often ...
Alaa Selim   +3 more
wiley   +1 more source

Measured‐State Conditioned Recursive Feasibility for Stochastic Model Predictive Control

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT In this paper, we address the problem of designing stochastic model predictive control (SMPC) schemes for linear systems affected by unbounded disturbances. The contribution of the paper is rooted in a measured‐state initialization strategy. First, due to the nonzero probability of violating chance‐constraints in the case of unbounded noise ...
Mirko Fiacchini   +2 more
wiley   +1 more source

The role of identification in data‐driven policy iteration: A system theoretic study

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
Abstract The goal of this article is to study fundamental mechanisms behind so‐called indirect and direct data‐driven control for unknown systems. Specifically, we consider policy iteration applied to the linear quadratic regulator problem. Two iterative procedures, where data collected from the system are repeatedly used to compute new estimates of ...
Bowen Song, Andrea Iannelli
wiley   +1 more source

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