Hydrology and Land Surface Studies

Nonlinear statistics reveals stronger ties between ENSO and the tropical hydrological cycle

  1. Shiraj Khan1,2,
  2. Auroop R. Ganguly1,
  3. Sharba Bandyopadhyay3,
  4. Sunil Saigal2,
  5. David J. Erickson III4,
  6. Vladimir Protopopescu1,
  7. George Ostrouchov4

Article first published online: 20 DEC 2006

DOI: 10.1029/2006GL027941

Issue

Geophysical Research Letters

Geophysical Research Letters

Additional Information

How to Cite

Khan, S., A. R. Ganguly, S. Bandyopadhyay, S. Saigal, D. J. Erickson III, V. Protopopescu, and G. Ostrouchov (2006), Nonlinear statistics reveals stronger ties between ENSO and the tropical hydrological cycle, Geophys. Res. Lett., 33, L24402, doi:10.1029/2006GL027941.

Author Information

  1. 1

    Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA

  2. 2

    Department of Civil and Environmental Engineering, University of South Florida, Tampa, Florida, USA

  3. 3

    Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA

  4. 4

    Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA

Publication History

  1. Issue published online: 20 DEC 2006
  2. Article first published online: 20 DEC 2006
  3. Manuscript Accepted: 6 NOV 2006
  4. Manuscript Revised: 27 OCT 2006
  5. Manuscript Received: 12 SEP 2006

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Keywords:

  • nonlinear statistics;
  • El Niño–Southern Oscillation;
  • tropical rivers

[1] Cross-spectrum analysis based on linear correlations in the time domain suggested a coupling between large river flows and the El Niño-Southern Oscillation (ENSO) cycle. A nonlinear measure based on mutual information (MI) reveals extrabasinal connections between ENSO and river flows in the tropics and subtropics, that are 20–70% higher than those suggested so far by linear correlations. The enhanced dependence observed for the Nile, Amazon, Congo, Paraná, and Ganges rivers, which affect large, densely populated regions of the world, has significant impacts on inter-annual river flow predictabilities and, hence, on water resources and agricultural planning.

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