[Figure 6]
The spatio-temporal variability of rainfall using the PCA technique was
based on climatological classification similar to Fig. 4. Based on the
Bartlett’s test statistics (e.g., Snedecor and Cochran, 1989) more than
five significant modes explaining non-random variations in rainfall at
95% confidence level were identified. But for purposes of physical
interpretability, we focus on three of those rainfall modes. Leading
rainfall modes in the Congo basin are characterised by annual,
multi-annual and short-term seasonal signals (Figs. 5a-b and 6a-b).
There is a strong dipole patterns in dominant mode where strong spatial
patterns of rainfall on the opposite side of the equator are notable
(EOF-1, Figs. 5a-b and 6a-b). These spatial patterns show the different
wet seasons in the basin. From the time series associated with these
spatial patterns, the wet season (positive phase) in northern section
coincides with the dry season (negative phase) of the southern region
(EOF-1/PC-1, Figs. 5a-b and 6a-b). The multi-annual signal, which
corresponds to the bimodal rainfall patterns and short-term seasonal
signals are relatively stronger on the West and in regions encompassing
Congo, Equatorial Guinea, and Gabon (EOF-2 and EOF-3, Figs. 5a-b and
6a-b). Generally, there is significant difference in the observed
spatial loadings (averaged spatial distribution) of the first orthogonal
mode of rainfall over different climatology (EOF-1, Figs. 5a-b and 6a-b)
and confirms the extensive impacts of extreme and severe droughts, which
affected more than 50% of the basin between 1901 and 1930 (Ndehedehe et
al., 2019). The total variability of the leading modes (annual
variations) of rainfall increased during the 1931- 1960 (56.3%)
and 1961- 1990 (57.3%) periods compared to the 1901- 1930
baseline period (51.3%). It varied less between 1991 and 2014 (55.4%)
as opposed to the two climatological periods between 1931 and 1990.
Furthermore, the total variability in the multi-annual rainfall signals
declined from 16.5% at the start of the century (1901- 1930) to
13.6% in the 1991- 2014 period while the total variability
accounted for by other short-term meteorological signals oscillated
between 4.0% and 2.7% during the entire period.