[1] Stefano Pierini, Henk A. Dijkstra, Mu Mu, 2014: Intrinsic low-frequency variability and predictability of the Kuroshio Current and of its extension. Advances in Oceanography and Limnology, DOI: 10.1080/19475721.2014.962091
[2] Rong Feng, Mu Mu, Wansuo Duan, 2014: Study on the “winter persistence barrier” of Indian Ocean dipole events using observation data and CMIP5 model outputs. Theoretical and Applied Climatology, DOI: 10.1007/s00704-013-1083-x
[3] Mu Mu, Yanshan Yu, Hui Xu, Tingting Gong, 2014: Similarities between optimal precursors for ENSO events and optimally growing initial errors in El Niño predictions. Theoretical and Applied Climatology, 115, 461-469.
[4] Mu Mu, 2013: Methods, current status, and prospect of targeted observation. Science China (Earth Sciences), 56, 1997-2005.
[5] Wang, Q., M. Mu, and H. A. Dijkstra, 2013: Effects of nonlinear physical processes on optimal error growth in predictability experiments of the Kuroshio Large Meander. J. Geophys. Res., 118, 6425-6436.
[6] Wang, Q., M. Mu, and H. A. Dijkstra, 2013: The similarity between optimal precursor and optimally growing initial error in prediction of Kuroshio large meander and its application to targeted observation. J. Geophys. Res., 118(2), 869-884.
[7] Yu, Y., M. Mu, W. Duan, and T. Gong, 2012: Contribution of the location and spatial pattern of initial error to uncertainties in El Niño predictions. J. Geophys. Res., 117,doi:10.1029/2011JC007758
[8] Yu, Y., Mu M.,and W. Duan,2012: Does Model Parameter Error Cause a Significant “Spring Predictability Barrier” for El Niño Events in the Zebiak–Cane Model?,J.Climate,25,1263-1277.
[9] Mu, Mu, Zhina Jiang, 2011: Similarities between Optimal Precursors that Trigger the Onset of Blocking Events and Optimally Growing Initial Errors in Onset Prediction. J. Atmos. Sci., 68, 2860-2877.
[10] Mu, M., W. Duan, Q. Wang, and R. Zhang, 2010: An extension of conditional nonlinear optimal perturbation approach and its applications. Nonlin. Processes Geophys., 17, 211-220.
[11]Mu, M., F. F. Zhou, and H. L. Wang, 2009: A Method for Identifying the Sensitive Areas in Targeted Observations for Tropical Cyclone Prediction: Conditional Nonlinear Optimal Perturbation. Mon. Wea. Rev., 137, 1623-1639.
[12] Mu, M., and Z. N. Jiang, 2008: A method to find perturbations that trigger blocking onset: Conditional nonlinear optimal perturbations. J. Atmos. Sci., 65, 3935-3946.
[13] Mu, M., and Z. N. Jiang, 2008: A new approach to the generation of initial perturbations for ensemble prediction: Conditional nonlinear optimal perturbation. Chinese Science Bulletin, 53, 2062-2068.
[14] Mu, M., H. Xu, and W. S. Duan,2007: A kind of initial errors related to "spring predictability barrier" for El Nino events in Zebiak-Cane model,Geophysics Research Letters,34, L03709, doi:10.1029/2006GL027412.
[15] Mu, M. and B. Wang, 2007: Nonlinear instability and sensitivity of a theoretical grassland ecosystem to finite-amplitude perturbations, Nonlin. Processes Geophys., 14, 409-423.
[16] Mu, M., and Z. Y. Zhang, 2006: Conditional nonlinear optimal perturbations of a two-dimensional quasigeostrophic model,J.Atmos.Sci.,63, 1587-1604.
[17] Mu, M. and Q. Zheng, 2005: Zigzag Oscillations in Variational Data Assimilation with Physical "On-Off" Processes, Month Weather Review, 133, 2711-2720.
[18] Mu, M., L. Sun and H. A. Dijkstra,2004: The sensitivity and stability of thermohaline circulation of ocean to finite amplitude perturbations. Journal of Physical Oceanography,34,2305-2315.
[19]Mu, M., and J. F. Wang,2003: A method to adjoint variational data assimilation with physical "on-off" processes,J.Atmos.Sci.,60,2010-2018.
[20] Mu, M., W. S. Duan, and B. Wang, 2003: Conditional nonlinear optimal perturbation and its applications,Nonlinear Processes in Geophysics, 10, 493-501.