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In this paper, we analyze the space-time structures of the 10–25 day intraseasonal variability of rainfall over Central Africa (CA) using 1DD GPCP rainfall product for the period 1996–2009, with an emphasis on the comparison between the western Central Africa (WCA) and the eastern Central Africa (ECA) with different climate features. The results of Empirical Orthogonal Functions (EOFs) analysis have shown that the amount of variance explained by the leading EOFs is greater in ECA than WCA (40.6% and 48.1%, for WCA and ECA, resp.). For the two subregions, the power spectra of the principal components (PCs) peak around 15 days, indicating a biweekly signal. The lagged cross-correlations computed between WCA and ECA PCs time series showed that most of the WCA PCs lead ECA PCs time series with a time scale of 5–8 days. The variations of Intraseasonal Oscillations (ISO) activity are weak in WCA, when compared with ECA where the signal exhibits large annual and interannual variations. Globally, the correlation coefficients computed between ECA and WCA annual mean ISO power time series are weak, revealing that the processes driving the interannual modulation of ISO signal should be different in nature or magnitude in the two subregions.

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The interannual variations in the intraseasonal oscillations (ISO) activity have long been investigated in different geographical areas around the world. However, Central Africa (CA) remains a serious gap in climate variability studies, especially at intraseasonal timescales because very few of these studies focused on this region. In this paper, we investigated the interannual variations in the amplitude of intraseasonal oscillations (ISO) in CA, using an ISO index (ISOI), extracted from the wavelet transform on the 25-70-day filtered daily Outgoing Longwave Radiation (OLR) data. Results showed that the ISOI in CA undergoes large interannual variations with some years of high as 1985 and 1990, and years of very low ISO as 1981 and 2001. The composite analysis revealed that the warm El Niño Southern Oscillation (ENSO) years are characterized by negative ISOI in most part of CA, while cold ENSO years are dominated by positive ISOIs. The lagged correlations computed between ISOIs and Niño3.4 index showed that the relationship ISOI-ENSO varies much spatially, but the correlation coefficients are globally low, with maxima around ± 0.5. The empirical orthogonal function (EOF) analysis applied on monthly ISOI revealed that two main spatial structures characterize ISOI variability, which explain 15.7% and 8.4% of the total variance, respectively. The first is marked by mostly positive loadings, crossing CA from northwest to southeast, and the second

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