QPCA-EnDCF is a deterministic ensemble data assimilation method that replaces stochastic observation perturbations with a spectrally regularized rank-κ update on whitened residuals, yielding better spread-skill and rank-histogram reliability than stochastic EnKF on Lorenz-96 in undersampled regimes.
The Ensemble Kalman filter: a signal processing perspective
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A data-driven stochastic differential equation for tropical cyclone intensification is inferred from IBTrACS and ERA5 data, producing synthetic storms whose statistics and nonlinear dynamics match observations and a leading physics-based model.
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A Data-Consistent Approach to Ensemble Filtering
QPCA-EnDCF is a deterministic ensemble data assimilation method that replaces stochastic observation perturbations with a spectrally regularized rank-κ update on whitened residuals, yielding better spread-skill and rank-histogram reliability than stochastic EnKF on Lorenz-96 in undersampled regimes.
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Learning a Stochastic Differential Equation Model of Tropical Cyclone Intensification from Reanalysis and Observational Data
A data-driven stochastic differential equation for tropical cyclone intensification is inferred from IBTrACS and ERA5 data, producing synthetic storms whose statistics and nonlinear dynamics match observations and a leading physics-based model.