Nonlinear Madden-julian Oscillation Indices Using Kernel Methods

نویسندگان

  • Eniko Székely
  • Dimitrios Giannakis
  • Andrew J. Majda
چکیده

We investigate in this paper the dominant intraseasonal signals in both convection and circulation data using the nonlinear Laplacian spectral analysis (NLSA) method. Three Madden-Julian oscillation (MJO) indices are constructed based on temporal modes extracted from pure cloudiness, lowerand upper-level zonal wind anomalies. All three indices reveal strong intermittency and capture well – through the use of kernel-based similarity methods from machine learning – the inherent nonlinear nature of both convection and circulation in the tropics.

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تاریخ انتشار 2015