
This study attempted to investigate the variability of extreme rainfall and temperature over Rwanda and the associated circulation anomalies forecasting on wet and dry rainfall events between 1961 and 2010. The datasets used to achieve the objectives includes Temperature, the rainfall dataset, wind vector, pressure vertical velocity (omega) and the Indian Ocean sea surface temperature (SST). The methods used include correlation analysis, Standardized anomaly, composite analysis, and Empirical Orthogonal Functions (EOF) analysis. The results show that the mean annual cycle depict two rainy Season in the courses of the year. The first rainy season runs from March – May (MAM) with the highest precipitation in April and second rainy season from September to November (SON), which has recorded the highest precipitation in November. The spatial distribution of monthly precipitation from January to December similarly show that the rainy season runs from March- May (MAM) received the highest precipitation in the region compared to September-November (SON). Results further show that the years with standardized deviation of +1 or more (wet years) including ,MAM and SON respectively, 1961,1963,1970,1981,1994,1998,2001,2004,2006 and 2009 whereas floods years. And for standardized deviation of -1 or less (dry years) includes 1979, 1984, 1993,2000,2001,2007 and 2010 considered as droughts years. The circulation anomalies associated with wet and dry years studied over these identified years revealed that in Rwanda, the equatorial wind climatology is deeply modified by the relief at a varied altitude.
Forecasters would make Rwanda climate more predictable. Strategies that integrate land and water management, and disaster risk reduction, within a framework of emerging climate change risks would bolster resilient development in the face of impacts of the new set of climate in Rwanda.
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Language(s): English
Format: Digital (Available online for logged-in users)
Tags: Extreme weather event ; Precipitation ; Extreme temperature ; Research ; Rwanda ; Thesis - WMO Fellowship Division ; Circulation anomaly pattern ; Wet and dry event ; Extreme Rainfall Add tag