Mechanisms associated with September to November (SON) rainfall over Uganda during the recent decades

Abstract

This study revisits teleconnections associated with the anomalous events of September to November (SON) rainfall over Uganda during 1981-2019, owing to the recent intensification of extreme events. Empirical Orthogonal Function (EOF), Composite and Correlation analysis are employed to examine the variability of SON rainfall over the study domain and associated circulations anomalies. The first EOF mode (dominant mode) displays a positive monopole pattern and explains 67.2% of the variance. The results revealed that SON rainfall is largely influenced by a Walker circulation mode over the Indian Ocean, whereby, wet events are associated with an ascending limb of the Walker circulation on the western part of the Indian Ocean characterized by convergence at low levels and divergence at upper level. The study showed that SON rainfall is positively (negatively) correlated with Indian Ocean (Atlantic Ocean) sea surface temperatures (SST). Furthermore, Indian Ocean Dipole (IOD) events have impact on SON rainfall with strong positive correlation, whereas Southern Oscillation Index (SOI) revealed negative correlation. The results also reveal that there is a lag in ENSO and IOD episodes during wet/dry events over the region. ENSO and IOD also tend to extend the rainfall season of SON and thus study of extreme events may not be well captured by studies focusing on SON. Future studies might consider the season of October to December or December to February. These phenomena need to be closely monitored and considered when making seasonal forecasts.

Comparison of CMIP6 and CMIP5 models in simulating mean and extreme precipitation over East Africa

“…The pronounced dry biases during MAM (Figures 2 and 3) could be a result of an observed reduction in seasonal precipitation (Funk et al ., 2008; Lyon and Dewitt, 2012; Liebmann et al ., 2014; Ongoma and Chen, 2017; Ayugi et al ., 2018). The exact causation of the dry patterns remains a challenge to accurately identify due to the weak correlation with large‐scale SST anomalies (Liebmann et al ., 2014; Ngoma et al ., 2021c). Summary results from most studies have narrowed to the impact of the west to central Pacific and the western Indian Ocean as the significant contributor to the observed decline (Williams and Funk, 2011; Liebmann et al ., 2014; Ayugi et al ., 2018; King et al ., 2021).…”

Investigation of the Historical Trends and Variability of Rainfall Patterns during the March–May Season in Rwanda

“…The EOF1 mode, in particular, highlights a predominant negative anomaly over much of Rwanda, except for localized areas of positive factor loading in the western corridor, alongside significant positive anomalies in the northeast and southwest. Such distribution indicates that EOF1 captures the primary mode of seasonal rainfall variability, potentially linked to large-scale atmospheric phenomena such as the East African monsoon system and its modulation by the intertropical convergence zone (ITCZ) [59,60]. The presence of positive loadings in the west and the stark contrasts observed across the EOF patterns could be indicative of orographic lifting effects, where elevated terrain in the west enhances convective activity, leading to increased precipitation, while eastern regions experience rain shadow effects.…”

Review of Deforestation in Ugandan Tropical Rainforest Reserves: A Threat to Natural Medicine

“…Agriculture is supported by deep fertile soils and therefore, highly productive (Minai, 2015). The country also has several open waters such as Lakes Victoria, Edward, Kyoga, George, and Albert with rivers like the Nile, Kafu, Kagera, and Rwizi (Ngoma et al, 2021). Data collection is a fundamental aspect of the course of any scientific research because it's the best choice of methods that give you better results and vice-versa (Rutten, 2015).…”