Patterns of Dekadal Rainfall Variation Over a Selected Region in Lake Victoria Basin, Uganda

Abstract

Understanding variations in rainfall in tropical regions is important due to its impacts on water resources, health and agriculture. This study assessed the dekadal rainfall patterns and rain days to determine intra-seasonal rainfall variability during the March-May season using the Mann-Kendall (MK) trend test and simple linear regression (SLR) over the period 2000-2015. Results showed an increasing trend of both dekadal rainfall amount and rain days (third and seventh dekads). The light rain days (SLR = 0.181; MK = 0.350) and wet days (SLR = 0.092; MK = 0.118) also depict an increasing trend. The rate of increase of light rain days and wet days during the third dekad (light rain days: SLR = 0.020; MK = 0.279 and wet days: SLR = 0.146; MK = 0.376) was slightly greater than during the seventh dekad (light rain days: SLR = 0.014; MK = 0.018 and wet days: SLR = 0.061; MK = 0.315) dekad. Seventy-four percent accounted for 2-4 consecutive dry days, but no significant trend was detected. The extreme rainfall was increasing over the third (MK = 0.363) and seventh (MK = 0.429) dekads. The rainfall amount and rain days were highly correlated (r: 0.43-0.72).

Assessing Weather Research and Forecasting (WRF) Model Parameterization Schemes Skill to Simulate Extreme Rainfall Events over Dar es Salaam on 21 December 2011

“…as described by Mugume et al [38] and the Pearson moment product correlation to analyze the association between observed and simulated rainfall. Yang et al [39] defined the bias, MAE, RMSE and CORR in (Equations (4)- (6) i is the ith data point and N is the total number of corresponding paired data points of predicted (P) and observed (O).…”

Improving Quantitative Rainfall Prediction Using Ensemble Analogues in the Tropics: Case study of Uganda

“…The rainfall data were obtained from the Uganda National Meteorological Authority (UNMA) and quality controlled by checking it for completeness. The missing gaps in some stations were filled using normal ratio method described by Mugume et al [8].…”

“…March-May and September-November). The March-May (MAM) seasonal rainfall over Uganda is generally influenced by the Inter-Tropical Convergence Zone [2,8]; the monsoon winds of East Africa [32,33]; the Indian ocean dipole [2,7]; the humid Congo airmass [6]; the tropical cyclones, semi-permanent subtropical anticyclones and easterly waves [7,8]; the complex topography [33], vegetation and inland water bodies which modulate local rainfall [8,34]. The Inter-Tropical Convergence Zone migrates north and southwards over the equator two times a year, which brings two rainfall seasons in the region i.e.…”

“…Over Eastern Africa, the rainfall distribution and quantity is influenced by many factors such as the Inter-Tropical Convergence Zone, El Niño/La Niña episodes, Indian Ocean Dipole and extra-tropical weather systems [7,8]. The spatial and temporal variability of rainfall makes its quantitative prediction a challenge [8,9].…”

“…Some of the scientific ways of predicting rainfall quantitatively have been suggested such as: the use of radar [8] and the use of Numerical Weather Prediction (NWP) models [6]. The use of radar is considered superior at short-range forecasts due to better spatial representation and assimilation…”