collaborators

9 papers

physics.ao-ph2026

Statistical Response of ENSO Complexity to Initial Condition and Model Parameter Perturbations

Marios Andreou, Nan Chen

Studying the response of a climate system to perturbations has practical significance. Standard methods in computing the trajectory-wise deviation caused by perturbations may suffe…

eess.SY2026

An Adaptive Online Smoother with Closed-Form Solutions and Information-Theoretic Lag Selection for Conditional Gaussian Nonlinear Systems

Marios Andreou, Nan Chen, Yingda Li

Data assimilation (DA) combines partial observations with dynamical models to improve state estimation. Filter-based DA uses only past and present data and is the prerequisite for…

math.DS2026

A Martingale-Free Introduction to Conditional Gaussian Nonlinear Systems

Marios Andreou, Nan Chen

The conditional Gaussian nonlinear system (CGNS) is a broad class of nonlinear stochastic dynamical systems. Given the trajectories for a subset of state variables, the remaining f…

physics.ao-ph2026

TianJi-Environ: An Autonomous AI Scientist for Atmospheric Environmental Research

Haoluo Zhao, Hongchun Zhang, Nan Li +6

As atmospheric environmental prediction continues to improve, interpretable validation of pollution mechanisms and feedback processes has become a main challenge in atmospheric che…

math.DS2026

Mechanisms and Pathways of Extreme Events in Partially-Observed Stochastic Dynamical Systems

Charlotte Moser, Nan Chen, Marios Andreou

Extreme events occur across the natural, engineering, and socioeconomic sciences, where rare but high-impact episodes can lead to disproportionate consequences that pose major chal…

math.NA2026

A Continuous-Time Ensemble Kalman-Bucy Smoother for Causal Inference and Model Discovery

Zhang Jiang, Marios Andreou, Sebastian Reich +1

Data assimilation (DA) integrates observational information with model predictions to improve state estimation in complex systems. While filtering provides the basis for online for…