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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.

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.

Regional climate models (RCMs) are widely used in regional assessment of climate change impacts. However, the reliability of individual models needs to be assessed before using their output for impact assessment. In this study, we evaluate the performance of RCMs from the Coordinated Regional Climate Downscaling Experiment program (CORDEX) to simulate minimum air temperature (TN), maximum air temperature (TX) and rainfall over Tanzania. Output from four RCMs driven by boundary conditions from three General Circulation Models (GCMs) and ERA-Interim data are evaluated against observed data from 22 weather stations. The evaluation is based on determining how well the RCMs reproduce climatological trends, interannual, and annual cycles of TN, TX and rainfall. Statistical measures of model performance that include the bias, root mean square error, correlation and trend analysis are used. It is found that RCMs capture the annual cycle of TN, TX and rainfall well, however underestimate and overestimate the amount of rainfall in March-April-May (MAM) and October-November-December (OND) seasons respectively. Most RCMs reproduce interannual variations of TN, TX and rainfall. The source of uncertainties can be analysed when the same RCM is driven by different GCMs and different RCMs driven by same GCM simulate TN, TX and rainfall differently. It is found that the biases and errors from the RCMs and driving GCMs contribute roughly equally. Overall, the evaluation finds reasonable (although variable) model skill in representing mean climate, interannual variability and temperature trends, suggesting the potential use of CORDEX RCMs in simulating TN, TX and rainfall over Tanzania.

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