EnSF-LR combines nonlinear score-based analysis on observed components with EnKF-style linear regression on unobserved components via ensemble covariance, achieving lower full-state RMSE than EnSF and EnKF in nonlinear-observation tests on Lorenz-63 and Lorenz-96.
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A deep learning method amortizes probabilistic XCO2 retrieval from OCO-2 spectra via Laplace approximations and normalizing flows, trained on simulations with model errors to achieve faster inference and better-calibrated uncertainties than operational solvers.
An autoregressive Gaussian process transport-map construction factors spatio-temporal joint densities into conditional distributions with data-dependent sparsity to enable scalable generative modeling of non-Gaussian fields.
A derivative-free ensemble Kalman-Bucy smoother is developed for continuous-time data assimilation that supports Bayesian causal inference and iterative model structure identification with small ensemble sizes under partial observations.
A tornado outbreak with simultaneous tornadic supercells occurred in the Philippines within an easterly severe weather regime, documented as the first known instance there.
This is an introductory review of the linear algebraic subproblems and contemporary solvers in variational data assimilation for geophysical applications.
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A Two-Step Ensemble Score Filter for Data Assimilation in Partially Observed Systems
EnSF-LR combines nonlinear score-based analysis on observed components with EnKF-style linear regression on unobserved components via ensemble covariance, achieving lower full-state RMSE than EnSF and EnKF in nonlinear-observation tests on Lorenz-63 and Lorenz-96.
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Amortized Probabilistic Retrieval of Atmospheric CO2 from OCO-2 Spectra Using Deep Learning with Laplace Approximations and Normalizing Flows
A deep learning method amortizes probabilistic XCO2 retrieval from OCO-2 spectra via Laplace approximations and normalizing flows, trained on simulations with model errors to achieve faster inference and better-calibrated uncertainties than operational solvers.
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Scalable generative modeling of non-Gaussian spatio-temporal fields via autoregressive Gaussian processes
An autoregressive Gaussian process transport-map construction factors spatio-temporal joint densities into conditional distributions with data-dependent sparsity to enable scalable generative modeling of non-Gaussian fields.
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A Continuous-Time Ensemble Kalman-Bucy Smoother for Causal Inference and Model Discovery
A derivative-free ensemble Kalman-Bucy smoother is developed for continuous-time data assimilation that supports Bayesian causal inference and iterative model structure identification with small ensemble sizes under partial observations.
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Localized Tornado Outbreak at the Upstream of a Tropical Easterly Wave in Camarines Norte, Philippines (13 September 2025)
A tornado outbreak with simultaneous tornadic supercells occurred in the Philippines within an easterly severe weather regime, documented as the first known instance there.
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An Introduction to Solving the Least-Squares Problem in Variational Data Assimilation
This is an introductory review of the linear algebraic subproblems and contemporary solvers in variational data assimilation for geophysical applications.