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This study revisits teleconnections associated with the anomalous events of September to November (SON) rainfall over Uganda during 1981-2019, owing to the recent intensification of extreme events. Empirical Orthogonal Function (EOF), Composite and Correlation analysis are employed to examine the variability of SON rainfall over the study domain and associated circulations anomalies. The first EOF mode (dominant mode) displays a positive monopole pattern and explains 67.2% of the variance. The results revealed that SON rainfall is largely influenced by a Walker circulation mode over the Indian Ocean, whereby, wet events are associated with an ascending limb of the Walker circulation on the western part of the Indian Ocean characterized by convergence at low levels and divergence at upper level. The study showed that SON rainfall is positively (negatively) correlated with Indian Ocean (Atlantic Ocean) sea surface temperatures (SST). Furthermore, Indian Ocean Dipole (IOD) events have impact on SON rainfall with strong positive correlation, whereas Southern Oscillation Index (SOI) revealed negative correlation. The results also reveal that there is a lag in ENSO and IOD episodes during wet/dry events over the region. ENSO and IOD also tend to extend the rainfall season of SON and thus study of extreme events may not be well captured by studies focusing on SON. Future studies might consider the season of October to December or December to February. These phenomena need to be closely monitored and considered when making seasonal forecasts.

The present study evaluates the performance of high‐resolution global climate models derived from Coupled Model Intercomparison Project Phase 6 (CMIP6 HighResMIP), in simulating rainfall characteristics over Madagascar on an annual and seasonal scales for the period 1981–2014. The models and their ensemble mean are assessed based on two observational datasets sourced from Climate Hazards Group Infrared Precipitation with Station data version 2 (CHIRPS v2.0) data and the European Centre for Medium‐Range Weather Forecasts (ECMWF) reanalysis fifth generation‐Land dataset (ERA5) as the references throughout the diverse analyses. A Taylor diagram, accompanied by the Taylor skill score (TSS), is used for the annual and seasonal model‐rankings and the overall performance of the models. The best‐performing models are EC‐Earth3P‐HR, ECMWF‐IFS‐HR, ECMWF‐IFS‐LR and HadGEM3‐GC31‐MM. The least‐recommended models with remarkable biases are BCC‐CSM2‐HR, CAMS‐CSM1‐0, FGOALS‐f3‐H, MPI‐ESM1‐2‐HR and MPI‐ESM1‐2‐XR. It is worth mentioning that FGOALS‐f3‐H tends to overestimate rainfall in most analyses, while MPI‐ESM1‐2‐HR and MPI‐ESM1‐2‐XR underestimate it. The findings of this study are of great importance to climatologists and present an opportunity for further investigation of underlying processes responsible for the observed wet/dry biases in order to improve the forecast skills in the models over the study area. [ABSTRACT FROM AUTHOR]

This study analyses the spatiotemporal variability of meteorological drought over Africa and its nine climate subregions from an ensemble of 19 multisource datasets (gauge-based, satellite-based and reanalysis) over the period 1983–2014. The standardized precipitation index (SPI) is used to represent drought on a 3-month scale. We analyse various drought characteristics (duration, events, frequency, intensity, and severity) for all drought months, and moderate, severe, and extreme drought conditions. The results show that drought occurs across the continent, with the equatorial regions displaying more negative SPI values, especially for moderate and severe droughts. On the other hand, Eastern Sahara and Western Southern Africa portray less negative SPI values. The study also reveals that extreme drought months have the largest interannual variability, followed by all drought months and severe drought months. The trend analysis of SPI shows a significantly increasing trend in drought episodes over most regions of Africa, especially tropical areas. Drought characteristics vary greatly across different regions of Africa, with some areas experiencing longer and more severe droughts than others. The equatorial region has the highest number of drought events, with longer durations for severe and extreme drought months. The Eastern Sahara region has a low number of drought events but with longer durations for moderate, severe, and extreme drought months, leading to an overall higher drought severity over the area. In contrast, Western Southern Africa and Madagascar display a consistently low drought severity for all categories. The study demonstrates the importance of conducting drought analysis for different drought levels instead of using all drought months. Drought management and adaptation strategies need to enhance community resilience to changing drought situations and consider drought variability in order to mitigate different impacts of drought across the continent. [ABSTRACT FROM AUTHOR]