**PAPERS** · CV · RESEARCH SUMMARY

Data-driven spectral decomposition and forecasting of ergodic dynamical systems

D. Giannakis (2017), *Appl. Comput. Harmon. Anal.*, in press

Delay-coordinate maps and the spectra of Koopman operators

S. Das, D. Giannakis (2017), *Nonlinearity*, in review

Extraction and prediction of coherent patterns in incompressible flows through space-time Koopman analysis

D. Giannakis, S. Das (2017), *Phys. D*, in review

Predicting regional and pan-Arctic sea ice anomalies with kernel analog forecasting

D. Comeau, D. Giannakis, Z. Zhao, A. J. Majda (2017), *Climate Dyn.*, in revision

Indo-Pacific variability on seasonal to multidecadal timescales. Part II: Multiscale atmosphere-ocean linkages

D. Giannakis & J. Slawinska (2017), *J. Climate*, in press

Indo-Pacific variability on seasonal to multidecadal timescales. Part I: Intrinsic SST modes in models and observations

J. Slawinska & D. Giannakis (2017), *J. Climate*, 30, 5265-5294

The seasonality and interannual variability of Arctic sea-ice reemergence

M. Bushuk & D. Giannakis (2017), *J. Climate*, 30, 4657-4676

Extraction and prediction of indices for monsoon intraseasonal oscillations: An approach based on nonlinear Laplacian spectral analysis

C. T. Sabeerali, R. S. Ajayamohan, D. Giannakis, A. J. Majda (2017), *Climate Dyn.*, doi:10.1007/s00382-016-3491-y

Kernel analog forecasting of tropical intraseasonal oscillations

R. Alexander, Z. Zhao, E. Szekely, D. Giannakis (2017), *J. Atmos. Sci*, 74, 1321-1342

Spatiotemporal pattern extraction with data-driven Koopman operators for convectively coupled equatorial waves

J. Slawinska & D. Giannakis (2016), *Proceedings of the 6th International Workshop on Climate Informatics: CI 2016*

Analog forecasting with dynamics-adapted kernels

Z. Zhao & D. Giannakis (2016), *Nonlinearity*, 29(9), 2888-2939

Initiation and termination of intraseasonal oscillations in nonlinear Laplacian spectral analysis-based indices

E. Szekely, D. Giannakis & A. J. Majda (2016), *Math. Wea. Climate Forecasting*, 2(1), 1-25

Data-driven prediction strategies for low-frequency patterns of North Pacific climate variability

D. Comeau, Z. Zhao, D. Giannakis & A. J. Majda (2016), *Climate Dyn.*, in press

Spatiotemporal feature extraction with data-driven Koopman operators

D. Giannakis, J. Slawinska & Z. Zhao (2015), *J. Mach. Learn. Res. Proceedings*, 44, 103-115

Nonlinear Laplacian spectral analysis of Rayleigh-Bénard convection

N. D. Brenowitz, D. Giannakis & A. J. Majda (2015), *J. Comput. Phys*, 315, 536-553

Sea-ice reemergence in a model hierarchy

M. Bushuk, D. Giannakis (2015), *Geophys. Res. Lett.*, 42(13), 5337–5345

Preprint; Supporting information; Movie 1

Nonparametric forecasting of low-dimensional dynamical systems

T. Berry, D. Giannakis & J. Harlim (2015), *Phys. Rev. E*, 91, 032915

Movie 1, 2, 3

Dynamics-adapted cone kernels

D. Giannakis (2015), *SIAM J. Appl. Dyn. Syst.*, 14(2), 566

Arctic sea ice reemergence: The role of large-scale oceanic and atmospheric variability

M. Bushuk, D. Giannakis & A. J. Majda (2015), *J. Climate*, 28, 5477-5509

Movie 1, 2, 3, 4, 5, 6, 7

Extraction and predictability of coherent intraseasonal signals in infrared brightness temperature data

E. Szekely, D. Giannakis & A. J. Majda (2014),* Climate Dyn.*, 46(5), 1473-1502

Movie 1, 2

Predicting the cloud patterns of the Madden-Julian Oscillation through a low-order nonlinear stochastic model

N. Chen, A. J. Majda & D. Giannakis (2014), *Geophys. Res. Lett.*, 41(15), 5612

An MCMC algorithm for parameter estimation in signals with hidden intermittent instability

N. Chen, D. Giannakis, R. Herbei & A. J. Majda (2014), *SIAM/ASA J. Uncertainty Quantification*, 2(1), 647

Symmetric and antisymmetric signals in MJO deep convection. Part I: Basic modes in infrared brightness temperature

Tung, W.-w., D. Giannakis & A. J. Majda (2014), *J. Atmos. Sci.*, 71, 3302

Symmetric and antisymmetric signals in MJO deep convection. Part II: Kinematics and thermodynamics

Tung, W.-w., D. Giannakis & A. J. Majda (2014), *J. Atmos. Sci.*, submitted

Reemergence mechanisms for North Pacific sea ice revealed through nonlinear Laplacian spectral analysis

M. Bushuk, D. Giannakis & A. J. Majda (2014), *J. Climate*, 27, 6265

Limits of predictability in the North Pacific sector of a comprehensive climate model

D. Giannakis & A. J. Majda (2012), *Geophys. Res. Lett.*, 39, L24602

Auxiliary material

Nonlinear Laplacian spectral analysis: Capturing intermittent and low-frequency spatiotemporal patterns in high-dimensional data

D. Giannakis & A. J. Majda (2012), *Stat. Anal. and Data Min.*, 6(3), 180

Movie

Hierarchical structure of the Madden-Julian Oscillation in infrared brightness temperature data revealed through nonlinear Laplacian spectral analysis

D. Giannakis, W.-w. Tung & A. J. Majda, *Conference on Intelligent Data Understanding (CIDU) 2012*, Boulder, Colorado, October 24-26, 2012

Information theory, model error, and predictive skill of stochastic models for complex nonlinear systems

D. Giannakis, A. J. Majda & I. Horenko (2012), *Physica D*, 241, 1735

Comparing low-frequency and intermittent variability in comprehensive climate models through nonlinear Laplacian spectral analysis

D. Giannakis & A. J. Majda (2012), *Geophys. Res. Lett.*, 39, L10710

Supporting information; Movie 1, 2, 3

The symmetries of image formation by scattering. I. Theoretical framework

D. Giannakis, P. Schwander & A. Ourmazd (2012), *Optics Express*, 20(12), 12799

Movie

The symmetries of image formation by scattering. II. Applications

P. Schwander, C. H. Yoon, A. Ourmazd & D. Giannakis (2012), *Optics Express*, 20(12), 12827

Movie 1, 2, 3, 4

Quantifying the predictive skill in long-range forecasting. Part I: Coarse-grained predictions in a simple ocean model

D. Giannakis & A. J. Majda (2012), *J. Climate*, 25(6), 1793

Quantifying the predictive skill in long-range forecasting. Part II: Model error in coarse-grained Markov models with application to ocean-circulation regimes

D. Giannakis & A. J. Majda (2012), *J. Climate*, 25(6), 1814

Nonlinear Laplacian spectral analysis for time series with intermittency and low-frequency variability

D. Giannakis & A. J. Majda (2012), *Proc. Natl. Acad. Sci.*, 109(7), 2222

Supplementary information 1 (pseudocode), 2; Movie S1, S2

Time series reconstruction via machine learning: Revealing decadal variability and intermittency in the North Pacific sector of a coupled climate model

D. Giannakis & A. J. Majda, *Conference on Intelligent Data Understanding (CIDU) 2011*, Mountain View, California, October 19-21, 2011

Instabilities in free-surface Hartmann flow at low magnetic Prandtl numbers

D. Giannakis, R. Rosner & P. F. Fischer (2009), *J. Fluid Mech.*, 636, 217

A spectral Galerkin method for the coupled Orr-Sommerfeld and induction equations in free-surface MHD

D. Giannakis, P. F. Fischer & R. Rosner (2009), *J. Comput. Phys.*, 228(4), 1188

Challenges for the kinetic unified dark matter model

D. Giannakis & W. Hu (2005), *Phys. Rev. D*, 72, 063502

Benchmarking and incentive regulation of quality of service: An application to the UK electricity distribution networks

D. Giannakis, T. Jamasb & M. Pollitt, *Energ. Policy*, 33(17), 2256 (2005)