The statistical prediction of East African rainfalls using quasi-biennial oscillation phases information
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.
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.
Cite this paper
nullNg’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.
nullNg’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.
References
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[1] Mutai, C.C., Ward, M.N. and Coleman, A.W. (1998) Towards the prediction of the East Africa short rains based on sea-surface temperature-atmosphere coupling. International Journal of Climatology, 18, 975-997. [2] Nicholson, S.E. and Nyenzi, B.S. (1990) Temporal and spatial variability of SSTs in the tropical Atlantic and In-dian Oceans. Meteorology and Atmospheric Physics, 42, 1-17. [3] Ogallo, L.J., Janowiak, J.E. and Halpert, M.S. (1988) Teleconnection between seasonal rainfall over East Af-rica and Global seas surface temperature anomalies. Journal of the Meteorological Society of Japan, 66, 807- 822. [4] Beltrando, G. (1990) Space-time variability in April and October-November over East Africa during the period 1932-1983. International Journal of Climatology, 10, 691-702. [5] Ogallo, L.J. (1982) Quasi-periodic patterns in the East Africa rainfall records. Kenya Journal of Science and Technology, A3, 43-54. [6] Mukherjee, B.K., Indira, K., Reddy, R.S. and Ramana Murty, BH.V. (1985) Quasi-biennial oscillation in strato-spheric zonal winds and Indian summer monsson. Monthly Weather Review, 113, 1421-1424. [7] Nicholson, S.E. and Entekhabi, D. (1986) The quasi-periodic behavior of rainfall variability in Africa and its relationship to the Southern Oscillation. Archives for Meteorology, Geophysics, and Bioclimatology-Series A, 34, 311. [8] Holton, J.R. and Lindzen, R.S. (1972) An updated theory for the quasi-biennial cycle of the tropical stratosphere. Journal of the Atmospheric Sciences, 29, 1076-1080. [9] Holton, J.R. and Tan, H.C. (1980) The influence of equa-torial quasi-biennial oscillation on the global circulation at 50-mb. Journal of the Atmospheric Sciences, 37, 2200-2208. [10] Plumb, R.A. (1977) The interaction of two internal waves with the mean flow: Implications for the theory of the quasi-biennial oscillation. Journal of the Atmospheric Sciences, 34, 1847- 1858. [11] Lau, K., and Shoo, P.J. (1988) Annual cycle, Quasi-Biennial Oscillation and Southern Oscillation in global precipita-tion. Journal of Geophysical Research, 93, 10975-10988. [12] July, M.R., Mc Queen, C. and Levey, K. (1994) SOI and QBO signals in the African region. Theoretical and Ap-plied Climatology, 50, 103-115. [13] Mason, S.J. and Tyson, P.D. (1992) The modulation of sea surface temperature and rainfall associations over southern Africa with solar activity and Quasi-Biennial Oscillation. Journal of Geophysical Research, 97, 5847- 5856. [14] Ogallo, L.J. Okoola, R.E. and Wanjohi, D.N. (1994) Characteristics of Quasi-Biennial Oscillation over Kenya and their predictability potential for seasonal rainfall. Journal of the African Meteorological society, 45, 57-62. [15] Krishnamurti, T.N. and Ogallo, L.J. (1989) Recent Afri-can climate (1979-1984). Dept. of Meteorology, Florida State University, Tallahassee. [16] Nicholson, S.E. (1998) Historical fluctuations of Lake Victoria and other Lakes in the Northern Rift valley of East Africa, In: Lehman, J.T. Ed., Environmental Change and Response in East African Lakes, Kluwer Academic Publishers, Dordrecht, 7-35. [17] Wilks, D.S. (2006) Statistical methods in the atmospheric sciences, International Geophysics Series, 2nd Edition, Academic Press, New York. [18] Kaiser, H.F. (1959) Computer program for varimax rota-tion in factor analysis. Educational and Psychological Measurement, 19, 413-420. [19] Yevjevich, V., (1972) Probability statistics in hydrology. Water Resources Publication, Fort Collins. [20] Trenberth, K.E. (1997) The definition of El Ni?o. Bulle-tin of the American Meteorological Society, 78, 2771- 2777.