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Understanding the spatial and temporal distribution of precipitation is important in agriculture, water management resources, and flood disaster management. The present study analyzed the changes in rainfall concentration over East Africa (EA). Three matrices—the precipitation concentration index (PCI), the precipitation concentration degree (PCD), and the precipitation concentration period (PCP)—were used to examine the changes in rainfall during 1981–2021. The changes in spatial variance annually and during two seasons, namely, "long rains" (March to May [MAM]) and "short rain" (October to December [OND]), were estimated using an empirical orthogonal function (EOF). The study employed the robust statistical metrics of the Theil–Sen estimator to detect the magnitude of change and modified Mann–Kendall (MMK) to examine possible changes in rainfall concentration. The localized variation of the power series within the series for PCI, PCD, and PCP variability was performed using the continuous wavelet transform. The findings showed that the concentration of rainfall patterns of EA occurred in four months of the total months in a year over most parts, with the western sides experiencing uniform rainfall events throughout the year. The EOF analysis revealed a homogeneous negative pattern during the MAM season over the whole region for PCD, PCI, and PCP for the first mode, which signified reduced rainfall events. Moreover, the MMK analysis showed evidence of declining trends in the PCD annually and during the MAM season, while the opposite tendency was noted for the OND season where an upward trend in the PCD was observed. Interestingly, areas adjacent to Lake Victoria in Uganda and Lake Tanganyika in Tanzania showed increasing trends in the PCD for annual and seasonal time scales. The analysis to characterize the rainfall cycle and possible return period, considering the indices of PCD, PCI, and PCP, showed higher variability during the year 2000, while much variability was presented in the PCP for the annual period. During the MAM and OND seasons, a 1-year band as a dominant period of variability was observed in all the indices. Overall, the findings of the present study are crucial in detecting the observed changes in rainfall concentration for avoiding the loss of life and property, as well as for coping with potential changes in water resources. [ABSTRACT FROM AUTHOR]

Extreme high temperature (EHT) events are the major indicator of global warming and their effect on natural ecosystems and agricultural production. The present study investigates the historical changes and projected trends of EHT events using Coupled Model Intercomparison Project phase 6 (CMIP6) Global Climate Models (GCMs) and observation data in East Africa. The distribution mapping (DM) approach effectively reduces the biases and improves the CMIP6 GCMs to match the observation data. This study considers the intensity of hot days (TXx) and hot nights (TNx) and two frequency indices estimated from the 90th percentile of the hot days (TX90p) and hot nights (TN90p) to evaluate the EHT events. The Mann-Kendall (MK) test and Sens's slope were used to estimate the trend of the EHT indices and significance level. Moreover, a regression approach was utilized to examine the relationship between EHT indices and meteorological conditions during the historical period (1990–2011). The results demonstrate that the recent period (2001−2010) experienced more frequent hot days (∼10–15%) and nights (∼12–20%) compared to the first decade (∼0–7%) (1990–2000) in most of the East Africa region. In addition, most stations across East Africa show a significant positive trend for the frequency of hot nights. The ensemble of the CMIP6 model simulation showed that the EHT events were projected to continue rising during the end of the 21st century (2071–2095). The intensity of hot days and nights is projected to escalate between 1.5 and 3 °C and 1–4 °C under SSP2–4.5 and SSP5–8.5 scenarios. Although, a high upsurge was detected in the frequency of hot nights (∼23–30%) during far future (2071–2095) compared to mid-future (2041–2070) under SSP5–8.5 and SSP2–4.5 scenarios. In addition, a strong correlation (R2 = ±0.8) was found between meteorological conditions and EHT indices, indicating the influence of atmospheric circulation on extreme temperature over East Africa. Our study provides valuable information regarding developing new policies and early warning systems for water resource managers and policymakers. • The historical and future changes in EHT events were assessed based on CMIP6 GCMs over East Africa. • The number of hot nights increased at higher rate than hot days over East Africa. • The frequency of hot nights upsurge during the recent decade (2001–2010) compared to 1st decade (1991–2000) in East Africa. • Kenya and Tanzania are projected to warm faster compared to Sudan and Ethiopia during the end (2071–2095) of the 21st century under SSP2–4.5. [ABSTRACT FROM AUTHOR]