Due to the nation’s highly varied topography and East Africa’s complex meteorology, there is considerable spatial heterogeneity in rainfall. This paper explores the temperature and rainfall climatology of Rwanda using this new dataset, subdividing the year into two rainy seasons (March-May and September-December), a moderate season (January-February) and a dry season (June-August). Understanding climatology, systematic change and predictability of the climate system are of critical importance for Rwanda, in which over 80% of the total population are engaged in (mostly rain-fed) agriculture and thus face considerable exposure to climate related risks. The sector meets 90% of the national food needs and generates more than 70% of the country’s export revenues.
Climatologies and summary statistics, including the mean, variance, and trend for the abovementioned temperature and rainfall variables are analyzed at the seasonal and annual time scales. Daily-derived statistics including rainy day frequency and 5-day dry spell risk are also explored in the same way. Additionally, onset date and rainy season cessation date are studied and historical climatologies are presented.
Temperature and rainfall within Rwanda are both heavily influenced by elevation. Temperature trends are positive (warming) throughout the country during the ENACTS (1983-present) and particularly strongly so in the lowland eastern region. While this observation is consistent with the narrative of anthropogenic climate change and other regional observations of warming, more research is needed to assess the relatively contributions of anthropogenic forcing and regional variability. Trends in rainfall, rainy day frequency and dry spell frequency are more spatially and temporally heterogeneous.
Seasonal forecasts of rainfall for the MAM and SOND rainy seasons are also explored and forecast information is presented in a probability of exceedance format. Forecast rainfall anomalies are found to be dependent on the state of ENSO, the Indian Ocean Dipole and the broader modeled East African rainfall. Seasonal forecasts of daily derived statistics are also developed in an exploratory way.