Quantifying predictability of Indian summer monsoon intraseasonal oscillations using nonlinear time series analysis

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The chaotic time series analysis is used to estimate the predictability of the Indian summer monsoon intraseasonal oscillations (ISOs). An index of the ISO is constructed using the daily gridded high-resolution (0.25 x 0.25 ) Indian summer monsoon rainfall dataset during 1951–2007. A low-dimensional chaotic attractor for the monsoon ISO with a correlation dimension of 3.8 is identified for a saturation embedding dimension of 5. The correlation dimension gives the minimum number of variables, whereas, the saturation embedding dimension gives the maximum number of variables needed to describe the state of the system. Thus, a minimum of 4 variables and a maximum of 5 variables should be able to simulate the ISO. The largest Lyapunov exponent of the ISO index time series is 0.05. The limit of predictability of the monsoon ISO is nearly 3 weeks.

Document Type: Research Article

DOI: http://dx.doi.org/10.1127/0941-2948/2012/0350

Publication date: August 1, 2012

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  • Meteorologische Zeitschrift (originally founded in 1866) is the joint periodical of the meteorological societies of Austria, Germany and Switzerland. It accepts high-quality peer-reviewed manuscripts on all aspects of observational, theoretical and computational research out of the entire field of meteorology, including climatology. Meteorologische Zeitschrift represents a natural forum for the meteorological community of Central Europe and worldwide.
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