Selected Publications

(See my CV for a full list of publications and see "Research" page for detailed descriptions)

(See in here for a list of publications in chronological order)

Articles (* indicates the corresponding author)

I. Efficient statistically accurate algorithms for solving high dimensional Fokker-Planck equation

• Nan Chen* and Andrew J. Majda, Beating the Curse of Dimension with Accurate Statistics for the Fokker-Planck Equation in Complex Turbulent Systems, Proc. Natl. Acad. Sci, 2017: 201717017. [PDF]
• Nan Chen*, Andrew J. Majda and Xin Tong, Rigorous Analysis for Efficient Statistically Accurate Algorithms for the Fokker-Planck Equation in Large Dimensions, SIAM/ASA Journal on Uncertainty Quantification, Accepted. [PDF]
• Nan Chen* and Andrew J. Majda, Efficient Statistically Accurate Algorithms for the Fokker-Planck Equation in Large Dimensions, Journal of Computational Physics, 354 (2018): 242-268. [PDF]

II. Simple stochastic dynamical models for the El Nino Southern Oscillation (ENSO)

• Sulian Thual, Andrew J. Majda and Nan Chen*, A Tropical Stochastic Skeleton Model for the MJO, El Nino and Dynamic Walker Circulation: A Simplied GCM, 2018, Submitted.[PDF]
• Sulian Thual, Andrew J. Majda, Nan Chen*, Mechanisms of the 2014-2016 Delayed Super El Nino Capturing by Simple Dynamical Models, Climate Dynamics, Accepted, 2018. [PDF]
• Sulian Thual*, Andrew J. Majda, Nan Chen, Seasonal Synchronization of a Simple Stochastic Dynamical Model Capturing El Nino Diversity, Journal of Climate, 30.24 (2017): 10047-10066.[Link]
• Nan Chen*, Andrew J. Majda and Sulian Thual, Observations and Mechanisms of a Simple Stochastic Dynamical Model Capturing El Nino Diversity, Journal of Climate, 2018, 31.1 (2018): 449-471.[PDF]
• Nan Chen* and Andrew J. Majda, A Simple Stochastic Dynamical Model Capturing the Statistical Diversity of El Nino Southern Oscillation, Proc. Natl. Acad. Sci., 114(7), pp. 1468-1473, 2017. [PDF]
• Nan Chen* and Andrew J. Majda, A Simple Dynamical Model Capturing the Key Features of the Central Pacific El Nino, Proc. Natl. Acad. Sci., 113(42), pp. 11732-11737, 2016. [PDF]
• Sulian Thual, Andrew J. Majda, Nan Chen* and Sam Stechmann, A Simple Stochastic Model for El Nino with Westerly Wind Bursts, Proc. Natl. Acad. Sci., 113(37), pp. 10245-10250, 2016. [PDF]

III. Predicting the MJO and monsoon intraseasonal time series through nonlinear low-order stochastic models

• Nan Chen*, Andrew J. Majda, C. T. Sabeerali and Ajayamohan S. Ravindran, Predicting Monsoon Intraseasonal Precipitation using a Low-Order Nonlinear Stochastic Model, Journal of Climate, 2018, 31.11 (2018): 4403-4427.[Link]
• Nan Chen* and Andrew J. Majda, Predicting the Cloud Patterns for the Boreal Summer Intraseasonal Oscillation through a Low-Order Nonlinear Stochastic Model, Mathematics of Climate and Weather Forecasting, 1(1), pp. 1-20, 2015. [PDF]
• Nan Chen* and Andrew J. Majda, Predicting the Real-time Multivariate Index for the Madden-Julian Oscillation through a Low-Order Nonlinear Stochastic Model, Monthly Weather Review, 143(6), pp. 2148-2169, 2015. [PDF]
• Nan Chen*, Andrew J. Majda, and Dimitris Giannakis, Predicting the Cloud Patterns for the Madden-Julian Oscillation through a Low-Order Nonlinear Stochastic Model, Geophysical Research Letters, 41(15), pp. 5612-5619, 2014. [PDF] [Supp] [Movie]

IV. Filtering, state estimation and predicting conditional Gaussian systems with model error (dyad model, triad model, parameter estimation and noisy Lagrangian tracers)

• Nan Chen* and Andrew J. Majda, Conditional Gaussian Systems for Multiscale Nonlinear Stochastic Systems: Prediction, State Estimation and Uncertainty Quantification, Entropy, 2018, 20(7), 509.[PDF]
• Andrew J. Majda and Nan Chen*, Model Error, Information Barriers, State Estimation and Prediction in Complex Multiscale Systems, 2018, Submitted. [PDF]
• Nan Chen* and Andrew J. Majda, Filtering Nonlinear Turbulent Dynamical Systems through Conditional Gaussian Statistics, Monthly Weather Review, 144(12), pp. 4885-4917, 2016. [PDF]
• Nan Chen* and Andrew J. Majda, Model Error in Filtering Random Compressible Flows Using Noisy Lagrangian Tracers,, Monthly Weather Review, 144(11), pp. 4037-4061, 2016. [PDF]
• Nan Chen, Andrew J. Majda and Xin Tong*, Noisy Lagrangian Tracers for Filtering Random Rotating Compressible Flows, Journal of Nonlinear Science, 25(3), pp. 451-488, 2015. [PDF]
• Nan Chen, Andrew J. Majda and Xin Tong*, Information Barriers for Noisy Lagrangian Tracers in Filtering Random Incompressible Flows, Nonlinearity, 27(9), pp. 2133-2163, 2014. [PDF]

V. Filtering the spatial-extended stochastic systems with model error

• Nan Chen* and Andrew J. Majda, Filtering the Stochastic Skeleton Model for the Madden-Julian Oscillation, Monthly Weather Review, 144(2), pp. 501-527, 2016. [PDF]

VI. MCMC algorithm for parameter estimation with hidden instability

• Nan Chen*, Dimitris Giannakis, Radu Herbei and Andrew J. Majda, An MCMC Algorithm for Parameter Estimation of Signals with Hidden Intermittent Instability, SIAM/ASA Journal of Uncertainty Quantification, 2(1), pp. 647-669, 2014. [PDF]

VII. Test models for prediction and state estimation with model errors

• Michal Branicki*, Nan Chen, and Andrew Majda, Non-Gaussian Test Models for Prediction and State Estimation with Model Errors, Chinese Annals of Mathematics, Series B, Volume 34 (Special volumn in honor of the scientific heritage of Jacques-Louis Lions), Issue 1, pp. 29-64, 2013. [PDF]

VIII. Ground water system

• Nan Chen, Max Gunzburger, Bill Hu, Xiaoming Wang*, and Celestine Woodruff, Calibrating the exchange coefficient in the modified coupled continuum pipe-flow model for flows in karst aquifers, Journal of Hydrology, 414-415, pp. 294-301, 2012. [PDF]
• Shuai Lu*, Nan Chen, Bang Hu and Jin Cheng, On the Inverse Problems for the Coupled Continuum Pipe Flow model for flows in karst aquifer, Inverse Problems, 28, pp. 065003, 2012. [Link]
• Nan Chen*, Max Gunzburger, and Xiaoming Wang, Asymptotic Analysis of the Differences between the Stokes-Darcy System with Different Interface Conditions and the Stokes-Brinkman System, J. Math. Anal. Appl., 368,(2), pp. 658-676, 2010.[PDF]

IX. Gevrey regularity

• Nan Chen, Cheng Wang*, and Steven Wise, Global in time Gevrey regularity solution for a class of bistable gradient flows, Discrete and Continuous Dynamical Systems-Series B, 21(6), 1689-1711, 2016. [PDF]

Translated Books

• Nan Chen, Xiaoming Wang, Jin Cheng, and Yu Jiang, Introduction to PDEs and Waves for the Atmosphere and Ocean (written by Prof. A. Majda), Translated Chinese version, Science Press, Oct 2009. [Link]

Book chapters

• Michal Branicki, Nan Chen and Andrew Majda, Page 99-138. P. G. Ciarlet, T. Li and Y. Maday, Partial Differential Equations: Theory, Control and Approximation. Springer, 2014. [Link]

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