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

  • Hamida Ngoma Nanjing University of Information Science and Technology https://orcid.org/0000-0002-3690-244X
  • Wang Wen Nanjing University of Information Science and Technology
  • Brian Ayugi Nanjing University of Information Science and Technology
  • Rizwan Karim Nanjing University of Information Science and Technology
  • Exavery Kisesa Makula Nanjing University of Information Science and Technology
Keywords: Rainfall; Extreme; Circulation; Uganda; East Africa

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. Thefirst 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.

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Published
2021/03/31
Section
Original Research