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The self-organizing map, a new approach to apprehend the Madden–Julian Oscillation influence on the intraseasonal variability of rainfall in the southern African region

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Abstract

The Madden–Julian Oscillation (MJO) is the major mode of intraseasonal variability (30–60 days) in the tropics, having large rainfall impacts globally, and possibly on southern Africa. However, the latter impact is not well understood and needs to be further explored. The life cycle of the MJO, known to be asymmetric, has been nevertheless analyzed usually through methods constrained by both linearity and orthogonality, such as empirical orthogonal function analysis. Here we explore a non-linear classification method, the self-organizing map (SOM), a type of artificial neural network used to produce a low-dimensional representation of high-dimensional datasets, to capture more accurately the life cycle of the MJO and its global impacts. The classification is applied on intraseasonal anomalies of outgoing longwave radiation within the tropical region over the 1980–2009 period. Using the SOM to describe the MJO is a new approach, complimentary to the usual real-time multivariate MJO index. It efficiently captures this propagative phenomenon and its seasonality, and is shown to provide additional temporal and spatial information on MJO activity. For each node, the subtropical convection is analyzed, with a particular focus on the southern Africa region. Results show that the convection activity over the central tropical Indian Ocean is a key factor influencing the intraseasonal convective activity over the southern African region. Enhanced (suppressed) convection over the central Indian Ocean tends to suppress (enhance) convection over the southern African region with a 10-day lag by modulating the moisture transport.

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Acknowledgments

The present research is supported by the Japan Science and Technology Agency (JST)/Japan International Cooperation Agency (JICA) through the Science and Technology Research Partnership for Sustainable Development (SATREPS). NCEP/DOE 2 Reanalysis, Interpolated OLR and NOAA High Resolution SST data are provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their Web site at http://www.esrl.noaa.gov/psd/. The SOM is performed using the SOM_PAK software (www.cis.hut.fi/research/som_pak). Other calculations, as well as graphics, are made using the R project for statistical computing (http://www.r-project.org). The authors would like to thank two anonymous reviewers for their helpful comments.

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Authors and Affiliations

  1. Department of Earth and Planetary Science, Graduate School of Science, The University of Tokyo, Tokyo, Japan

    Pascal Oettli & Tomoki Tozuka

  2. IRD, LOCEAN, Paris, France

    Takeshi Izumo

  3. CSIR Natural Resources and the Environment, Climate Studies, Modelling and Environmental Health, Pretoria, South Africa

    Francois A. Engelbrecht

  4. Application Laboratory, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama, Japan

    Toshio Yamagata

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  1. Pascal Oettli
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  2. Tomoki Tozuka
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  3. Takeshi Izumo
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  4. Francois A. Engelbrecht
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  5. Toshio Yamagata
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Correspondence to Pascal Oettli.

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Dr Takeshi Izumo was formerly at the University of Tokyo.

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Oettli, P., Tozuka, T., Izumo, T. et al. The self-organizing map, a new approach to apprehend the Madden–Julian Oscillation influence on the intraseasonal variability of rainfall in the southern African region. Clim Dyn 43, 1557–1573 (2014). https://doi.org/10.1007/s00382-013-1985-4

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