Area of research
Atmospheric Science · Global and Planetary Change
Research interest
Research focused on Dynamical systems theory and Turbulence, with related work in Statistical physics, Nonlinear system, Data assimilation. Notable publications include 'Filtering Complex Turbulent Systems', 'Physics constrained nonlinear regression models for time series', and 'Using machine learning to predict extreme events in complex systems'.
Predicting observed and hidden extreme events in complex nonlinear dynamical systems with partial observations and short training time series
Efficient nonlinear optimal smoothing and sampling algorithms for complex turbulent nonlinear dynamical systems with partial observations
Using machine learning to predict extreme events in complex systems
Statistical dynamical model to predict extreme events and anomalous features in shallow water waves with abrupt depth change
Linear and nonlinear statistical response theories with prototype applications to sensitivity analysis and statistical control of complex turbulent dynamical systems
Model Error, Information Barriers, State Estimation and Prediction in Complex Multiscale Systems
Conditional Gaussian Systems for Multiscale Nonlinear Stochastic Systems: Prediction, State Estimation and Uncertainty Quantification
A flux-balanced fluid model for collisional plasma edge turbulence: Model derivation and basic physical features
Beating the curse of dimension with accurate statistics for the Fokker–Planck equation in complex turbulent systems
Improving synoptic and intraseasonal variability in CFSv2 via stochastic representation of organized convection
Efficient statistically accurate algorithms for the Fokker–Planck equation in large dimensions
Simple stochastic dynamical models capturing the statistical diversity of El Niño Southern Oscillation
Implementation and calibration of a stochastic multicloud convective parameterization in the NCEP <scp>C</scp>limate <scp>F</scp>orecast <scp>S</scp>ystem (CFSv2)
Nonlinear stability and ergodicity of ensemble based Kalman filters
Introduction to Turbulent Dynamical Systems in Complex Systems
Simple stochastic model for El Niño with westerly wind bursts
Filtering Nonlinear Turbulent Dynamical Systems through Conditional Gaussian Statistics
Low-Dimensional Reduced-Order Models for Statistical Response and Uncertainty Quantification: Two-Layer Baroclinic Turbulence
State estimation and prediction using clustered particle filters
Data-driven prediction strategies for low-frequency patterns of North Pacific climate variability
Role of stratiform heating on the organization of convection over the monsoon trough
Simple dynamical models capturing the key features of the Central Pacific El Niño
Concrete ensemble Kalman filters with rigorous catastrophic filter divergence
Arctic Sea Ice Reemergence: The Role of Large-Scale Oceanic and Atmospheric Variability*
A Multiscale Model for the Intraseasonal Impact of the Diurnal Cycle over the Maritime Continent on the Madden–Julian Oscillation
Noisy Lagrangian Tracers for Filtering Random Rotating Compressible Flows
Numerical Schemes for Stochastic Backscatter in the Inverse Cascade of Quasigeostrophic Turbulence
Statistical energy conservation principle for inhomogeneous turbulent dynamical systems
Predicting the Real-Time Multivariate Madden–Julian Oscillation Index through a Low-Order Nonlinear Stochastic Model
Predicting the Cloud Patterns for the Boreal Summer Intraseasonal Oscillation Through a Low-Order Stochastic Model