Inter-annual Variability of March to May Rainfall over Tanzania and Its association with Atmospheric circulation anomalies.

Philemon Henry King’uza; Paul Tilwebwa Shelleph Limbu

doi:10.5937/gp23-22430

Philemon Henry King’uza Nanjing University of Information Science and Technology
Paul Tilwebwa Shelleph Limbu Nanjing University of Information Science and Technology

DOI: https://doi.org/10.5937/gp23-22430

Keywords: Tanzania, Inter-annual Variability, Rainfall, EOF, MAM,

Abstract

This study used Empirical Orthogonal Function (EOF), student t test composite and correlation analysis techniques to investigate the inter-annual variability of March to May rainy season over Tanzania and its association atmospheric circulation anomalies. The EOF results showed that the rainfall over the country during MAM season does not vary too much with the first dominant mode (EOF1) showing the variance of 22.4% of the total rainfall and that much of the rainfall being concentrated over the coast, northeastern and southern regions. It was found that during wet years, the study area was dominated by convergence at the lower level which is associated with enough moisture advected by south easterlies from Indian Ocean due to the relaxation of Mascarene high (MH) over the region and westerlies from Congo basin. The rising motion at lower level was enhanced with the presence of ascending limb of Walker circulation cell over the western Indian Ocean (WIO) and the coast region. Central Pacific and east coast of Atlantic Oceans are relatively warm during wet years. Furthermore, significantly negative correlation observed between southeast Indian Ocean (SEIO) region and MAM rainfall over Tanzania at the 95% confidence level portrays that much of the regions receives high sufficient amount of rainfall when the western Indian Ocean (WIO) is relatively warmer than the SEIO. The results show that Nino 3.4 and Tropical North Atlantic (TNA) indices are strongly positive correlated with MAM rainfall over the east coast region. This study will help to improve seasonal forecasts over Tanzania.

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