455 citations · 2.1k across the 56 of their papers we have counts for
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Data-driven Spatio-temporal Prediction of High-dimensional Geophysical Turbulence using Koopman Operator Approximation
M. A. Khodkar, Athanasios C. Antoulas, Pedram Hassanzadeh
We show the skills of a data-driven low-dimensional linear model in predicting the spatio-temporal evolution of turbulent Rayleigh-Bénard convection. The model is based on dynamic…
A test case for application of convolutional neural networks to spatio-temporal climate data: Re-identifying clustered weather patterns
Ashesh Chattopadhyay, Pedram Hassanzadeh, Saba Pasha
Convolutional neural networks (CNNs) can potentially provide powerful tools for classifying and identifying patterns in climate and environmental data. However, because of the inhe…
Quantifying the annular mode dynamics in an idealized atmosphere
Pedram Hassanzadeh, Zhiming Kuang
The linear response function (LRF) of an idealized GCM, the dry dynamical core with Held-Suarez physics, is used to accurately compute how eddy momentum and heat fluxes change in r…
Data-driven reduced modelling of turbulent Rayleigh-Benard convection using DMD-enhanced Fluctuation-Dissipation Theorem
M. A. Khodkar, Pedram Hassanzadeh
A data-driven, model-free framework is introduced for calculating Reduced-Order Models (ROMs) capable of accurately predicting time-mean responses to external forcings, or forcings…
Reduced-order modeling of fully turbulent buoyancy-driven flows using the Green's function method
M. A. Khodkar, Pedram Hassanzadeh, Saleh Nabi +1
A One-Dimensional (1D) Reduced-Order Model (ROM) has been developed for a 3D Rayleigh-Bénard convection system in the turbulent regime with Rayleigh number . The…