This study evaluates the ability of 10 regional climate models (RCMs) from the Coordinated Regional Climate Downscaling Experiment (CORDEX) in simulating the characteristics of rainfall patterns over eastern Africa. The seasonal climatology, annual rainfall cycles, and interannual variability of RCM output have been assessed over three homogeneous subregions against a number of observational datasets. The ability of the RCMs in simulating large-scale global climate forcing signals is further assessed by compositing the El Niño-Southern Oscillation (ENSO) and Indian Ocean dipole (IOD) events. It is found that most RCMs reasonably simulate the main features of the rainfall climatology over the three subregions and also reproduce the majority of the documented regional responses to ENSO and IOD forcings. At the same time the analysis shows significant biases in individual models depending on subregion and season; however, the ensemble mean has better agreement with observation than individual models. In general, the analysis herein demonstrates that the multimodel ensemble mean simulates eastern Africa rainfall adequately and can therefore be used for the assessment of future climate projections for the region.

No abstract

Luhunga et al. CCP-TZ in mid (2041-2070) and end (2070-2100) centuries respectively. Rainfall over parts of northeastern highlands and Coastal regions is projected to increase in the range of 0.5 to 1 mm/day and 0.25 to 0.5 mm/day under RCP 8.5 and RCP 4.5 emission scenarios respectively. However, the western regions, southwestern highlands and eastern side of Lake Nyasa are likely to experience decreased amount of rainfall in the range of 0.5 to 1mm/day under both RCP 8.5 and RCP 4.5 emission scenarios.

No abstract

Climate extreme indices in Tanzania for the period 1961-2015 are analyzed using quality controlled daily rainfall, maximum and minimum temperatures data. RClimdex and National Climate Monitoring Products (NCMP) software developed by the commission for climatology of the World Meteorological Organization (WMO) were used for the computation of the indices at the respective stations at monthly and annual time scales. The trends of the extreme indices averaged over the country were computed and tested for statistical significance. Results showed a widespread statistical significant increase in temperature extremes consistent with global warming patterns. On average, the annual timescale indicate that mean temperature anomaly has increased by 0.69˚C, mean percentage of warm days has increased by 9.37%, and mean percentage of warm nights has increased by 12.05%. Mean percentage of cold days and nights have decreased by 7.64% and 10.00% respectively. A non-statistical significance decreasing trends in rainfall is depicted in large parts of the country. Increasing trend in percentage of warm days and warm nights is mostly depicted over the eastern parts of the country including areas around Kilimanjaro, Dar-es-Salaam, Zanzibar, Mtwara, and Mbeya regions. Some parts of the Lake Victoria Basin are also characterized by increasing trend of warm days and warm nights. However, non-statistical significant decreasing trends in the percentage of warm days and warm nights are depicted in the western parts of the country including Tabora and Kigoma regions and western side of the lake Victoria. These results indicate a clear dipole pattern in temperature dynamics between the eastern side of the country mainly influenced by the Indian Ocean and the western side of the country largely influenced by the moist Congo air mass associated with westerly winds. The results also indicate that days and nights are both getting warmer, though, the warming trend is much faster in the minimum temperature than maximum temperature.

No abstract

This study aimed at assessing the evolution, distribution and the socioeconomic impacts of extreme rainfall over East Africa during the March, April and May (MAM) rainfall season focusing on assessing the trends and contribution of MAM rainfall in mean annual rainfall across the region. It employed Principal Component Analysis (PCA) methods to capture the patterns and variability of MAM rainfall. The PCA results indicated that the first Principal Component (PC) describe 17% of the total variance, while the first six PCs account only 53.5% of the total variance in MAM rainfall, underscoring the complexity of rainfall forcing factors in the region. It has been observed that MAM rainfall accounts about 30%-60% of the mean annual rainfall in most parts of the region, signifying its importance in agriculture, water, energy and other socioeconomic sectors. MAM has been characterized by increasing variability with varying trend patterns across the region. The MAM rainfall trend is not homogeneous across the region; some areas are experiencing a slight decreasing rainfall trend, while other areas are experiencing a slight increasing rainfall trend. The observed trend dynamics is consistent with the global trend patterns in precipitation as depicted in recent Intergovernmental Panel on Climate Change (IPCC) reports. Over the last five years MAM rainfall season have been characterized by record-breaking extremes. On 8 th May 2017, Tanga and Mombasa meteorological stations recorded 316 mm

Up to one thousand drowning deaths occur every year on Lake Victoria in East Africa. Nocturnal thunderstorms are one of the main culprits for the high winds and waves that cause fishing boats to capsize. The HIGHWAY project was established to develop an Early Warning System for Lake Victoria. Prior to HIGHWAY, weather forecasts for the lake were overly general and not trusted. Under the HIGHWAY project, forecasters from weather service offices in East Africa worked with leaders of fishing communities and Beach Management Units to develop marine forecasts and hazardous-weather warnings that were meaningful to fishermen and other stakeholders. Forecasters used high-resolution satellite, radar, and lightning observations collected during a HIGHWAY field campaign, along with guidance from numerical weather prediction models and a 4.4-km resolution Tropical Africa model, to produce specific forecasts and warnings for 10 zones over the lake. Forecasts were communicated to thousands of people by radio broadcasters, local intermediaries, and via smartphones using the WhatsApp application. Fishermen, ferry-boat operators, and lakeside communities used the new marine forecasts to plan their daytime and nighttime activities on the lake. A socio-economic benefits study conducted by HIGHWAY found that ~75% of the people are now using the forecasts to decide if and when to travel on the lake. Significantly, a 30% reduction in drowning fatalities on the lake is likely to have occurred, which when combined with the reduction in other weather-related losses, generates estimated socio-economic benefits of $44M/year due to the HIGHWAY project activities; the new marine forecasts and warnings are helping to save lives and property.