The statistical prediction of East African rainfalls using quasi-biennial oscillation phases information

Hashim K. Ng’ongolo, Sergei P. Smyshlyaev

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DOI: 10.4236/ns.2010.212172                

Abstract

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.

Keywords

principal component analysis (PCA); Climatological Rainfall Zones; QBO-Index; SOI-Index; March to May Seasonal Rainfall in East Africa

Conflicts of Interest

The authors declare no conflicts of interest.

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