The statistical prediction of East African rainfalls using quasi-biennial oscillation phases information
Hashim K. Ng’ongolo, Sergei P. Smyshlyaev
DOI: 10.4236/ns.2010.212172   PDF   HTML     6,409 Downloads   11,930 Views   Citations


A simple correlation method and a quasi-biennial oscillation (QBO)/rainfall composite analysis were used to examine the teleconnections be-tween the seasonal rainfall anomalies of March through May (long-rains) over East Africa and the different QBO phases in the stratospheric zonal winds, and also explore the predictive potential of the long rainy season using infor-mation about the phases of the QBO for the pe-riod 1979-2003. We study the spatial correlation patterns statistically to understand the climatic associations between the equatorial strato-spheric zonal wind and regional rainfall at the interannual time scale. The aim of this analysis is to establish whether this global signal can be employed as predictor variable in the long-range forecasts. Principal component analysis (PCA) is employed in the first instance to reduce the large dimensionality of the predictant (monthly rainfall data), to retain the time series of the principal components (PCs) and to delineate the rain gauge network of East Africa into homo-geneous zones. Spatial patterns of the factor loading were used to delineate East Africa into 11 homogeneous zones.

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Ng’ongolo, H. and Smyshlyaev, S. (2010) The statistical prediction of East African rainfalls using quasi-biennial oscillation phases information. Natural Science, 2, 1407-1416. doi: 10.4236/ns.2010.212172.

Conflicts of Interest

The authors declare no conflicts of interest.


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