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Variability in rainfall and temperature results in different impacts on agricultural practices. Assessesment of variability and trend of rainfall and temperature for the district of Musanze in Rwanda was conducted using six meteorological stations for a period of 37 years, ranging from 1981 to 2018, and data were obtained from Rwanda Meteorology Agency. Musanze district is located in highland areas of Rwanda, understanding the variability and trend in rainfall and temperature is paramount to increase the uptake of climate information and support strategic orientation. The Mann–Kendall nonparametric test and modified Mann–Kendall were used to assess the trend in rainfall and temperature, whereas Sen's slope estimator was used to assess the magnitude of change. The results from both methods showed much similarity and consistency. The assessment of variability and trend in rainfall and temperature in Musanza district indicated that increasing temperature and decreasing rainfall trends gave an indication of changes in variability and trend in rainfall and temperature. The annual pattern revealed a substantial downward tendency of −25.7% for Nyange, the only station with constant decreasing trend over all seasons, DJF, −61.4%, SON, −12.2%, JJA, −40.3%, and MAM, −4.35. Temperature analysis for both maximum and minimum indicated increasing trend which was signal for constant warming up in the area. The results from coefficient of variation indicated a high disparity in rainfall variation from June to August which ranged between 51 and 74%, and other seasons changes were moderate. [ABSTRACT FROM AUTHOR]

ABSTRACT Recent special reports on climate extremes have shown evidences of changes in the patterns of climate extremes at global, regional and local scales. Understanding the characteristics of climate extremes at regional and local levels is critical not only for the development of preparedness and early warning systems, but is also fundamental in the development of any adaptation strategies. There is still very limited knowledge regarding the past, present and future patterns of climate extremes in the Greater Horn of Africa (GHA). This study, which was supported by the World Bank Global Facility for Disaster Reduction and Recovery (WB-GFDRR) and implemented by the World Meteorological Organization, was organized in terms of three workshops with three main objectives; (1) analysis of daily rainfall and temperature extremes for ten countries in the GHA region using observed in situ data running from 1971 to 2006, (2) assessing whether the United Kingdom Met-office and Hadley centre Providing REgional Climates for Impact Studies (UK-PRECIS) modelling system can provide realistic representation of the past and present climate extremes as observed by available in situ data, and (3) studying the future regional climate extremes under different scenarios to further assess the expected changes in climate extremes. This paper, therefore, uses the outputs of these workshops and also includes post-workshop analyses to assess the changes of climate extremes within the GHA. The results showed a significant decrease in total precipitation in wet days greater than 1 mm and increasing warm extremes, particularly at night, while cold extremes are decreasing. Considering a combination of geophysical models and satellite gravimetry observations from the Gravity Recovery and Climate Experiment (GRACE) mission in the frame of GRACE daily Kalman-smoothing models, for the years 2002 to 2010, we explored a decline in total water storage variations over the GHA. [ABSTRACT FROM AUTHOR]

Linkages between dominant spatio-temporal decadal rainfall variability modes and the global sea surface temperature (SST) modes are investigated over East Africa region for the period 1950-2008. Singular value decomposition (SVD) and canonical correlation analysis (CCA) techniques are employed to examine potential linkages and predictability of decadal rainfall variability over the region. When the ten-year periodicity is filtered out from the observed monthly rainfall data, distinct decadal rainfall regimes are exhibited in the time series of mean seasonal rainfall anomalies. Spectral density analysis of rainfall time series showed dominance of a ten-year periodicity, significant at 95% confidence level. The Principal Component Analysis (PCA) results yielded nine and seven homogeneous decadal rainfall zones for long rains; March-May (MAM), and the short rains: October-December (OND) seasons, respectively. The third season of June-August (JJA) which is mainly experienced in western and coastal sub-regions had eight homogenous zones delineated. Results show that the leading three SVD-coupled modes explain greater than 75% of the squared covariance between the two fields. The first SVD mode for Indian, Atlantic and Pacific Oceans contributed to 50, 43 and 38% of the total square covariance for MAM season, respectively. The same mode accounted for 65, 48 and 40% for OND rainfall season, respectively. For the JJA season, mode one contributed to about 61, 39 and 42% of the variance. The study showed that forcing of decadal rainfall over the region is associated with El Niño mode that is prominent over the Pacific Ocean, while Indian Ocean dipole is the leading mode over the Indian Ocean basin. An inter-hemispheric dipole mode that is common during ENSO was a prominent feature in the Atlantic Ocean forcing regional decadal rainfall. The high variability of these modes highlighted the significant roles of all the global oceans in forcing decadal rainfall variability over the region. In addition, results from multiple linear regression model showed substantial variation of the model prediction skill of the decadal rainfall variability modes within various homogenous zones and for different seasons. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]