The use of indigenous knowledge in weather and climate prediction in Mahenge and Ismani wards, Tanzania

This paper discusses the role of indigenous knowledge (IK) in weather and climate prediction in Mahenge and Ismani wards focusing on Safari Road and Mahenge Mjini villages in Mahenge; and Uhominyi and Ismani Tarafani villages in Ismani. The perception of local communities about climate change is assessed. Local environmental and astronomical indicators used by local communities in weather and climate prediction are identified and documented. A team of five IK experts in both Mahenge and Ismani was identified and assigned the task of making continuous observations of the IK indicators and producing seasonal rainfall forecast for the purpose of testing the accuracy and reliability of IK. Key informant interviews and Focus Group Discussions (FGDs) approaches were used in data collection regarding existing IK in weather forecast. A total of 120 respondents were interviewed in study Mahenge and Ismani wards respectively. A Statistical Package for Social Science (SPSS) was used for data analysis. More than 83% of the respondents were found to be aware of climate change. Plant phenology, particularly that of mango trees was found to be the most used indicator in both wards. An assessment of the forecasted and observed 2011/2012 seasonal rainfall indicates comparable results.This article is also published in a Proceedings of the first Climate Change Impacts, Mitigation and Adaptation Programme Scientific Conference, 2012Royal Norwegian Governmen

Spatial and Temporal Analysis of Rainfall and Temperature Extreme Indices in Tanzania

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.The paper is publishedThe authors wish to thank The Tanzania Meteorological Agency for providing data used in this study and WMO for providing guidance in the analysis of climate extreme in climate time series