Assessment of the Evolution and Socio-Economic Impacts of Extreme Rainfall Events in October 2019 over the East Africa

This study aimed at establishing and quantifying the evolution and socio-economic impacts of extreme rainfall events in October 2019. The study also focused on ascertaining the extent to which the Indian Ocean Dipole (IOD) and the El Ni?o Southern Oscillation (ENSO) influenced anomalous rainfall over East Africa (EA) in October 2019. It employed Singular Value Decomposition (SVD) methods to analyze inter-annual variability of EA rainfall and the Sea Surface Temperature Anomalies (SSTA) over the Indian and Pacific Ocean with a focus on October to December 2019 rainfall season. The SVD analysis enabled the exploration of the leading modes from the mean monthly rainfall and SSTs leading to the determination of the likely influence of the IOD and ENSO respectively. The first SVD coupled modes, which dominate the co-variability between the October rainfall over the EA domain, and SSTA over the Indian and Pacific Oceans based on 1981 to 2010 climatology indicate the monopole positive co-variability with rainfall over the entire EA domain. The corresponding spatial pattern for the SSTA over the Indian Ocean (IO) recaptures the positive IOD event while the central equatorial Pacific Ocean (i.e., over Ni?o 3.4 region) reveals a monopole positive loading, a typical signal for the warm phase of ENSO. The positive rainfall anomaly over the EA during October is found to be associated with either the IOD event or ENSO condition events independently or in phase. However, the inter-annual variability between October rainfall over EA and ENSO reveals a moderate relationship (r = 0.4212) while a robust association (r = 0.7084) is revealed with IOD. Comparatively, the October 2019 rainfall anomaly peaks the highest in history over the EA and was found to be coupled with highest positive IOD event in record. Unlikely, the 1997 October rainfall (which peaked the second in history), was associated with the co-occurrence of the positive phase of ENSO and IOD events. The findings of this study suggest that the positive IOD coupled mode had large impact on the distribution and variability of the October 2019 rainfall over the EA region.

Understanding the Evolution and Socio-Economic Impacts of the Extreme Rainfall Events in March-May 2017 to 2020 in East Africa

This study aimed at assessing the evolution, distribution and the socio-economic impacts of extreme rainfall over East Africa during the March, April and May (MAM) rainfall season focusing on assessing the trends and contribution of MAM rainfall in mean annual rainfall across the region. It employed Principal Component Analysis (PCA) methods to capture the patterns and variability of MAM rainfall. The PCA results indicated that the first Principal Component (PC) describe 17% of the total variance, while the first six PCs account only 53.5% of the total variance in MAM rainfall, underscoring the complexity of rainfall forcing factors in the region. It has been observed that MAM rainfall accounts about 30% - 60% of the mean annual rainfall in most parts of the region, signifying its importance in agriculture, water, energy and other socio-economic sectors. MAM has been characterized by increasing variability with varying trend patterns across the region. The MAM rainfall trend is not homogeneous across the region;some areas are experiencing a slight decreasing rainfall trend, while other areas are experiencing a slight increasing rainfall trend. The observed trend dynamics is consistent with the global trend patterns in precipitation as depicted in recent Intergovernmental Panel on Climate Change (IPCC) reports. Over the last five years MAM rainfall season have been characterized by record-breaking extremes. On 8th May 2017, Tanga and Mombasa meteorological stations recorded 316 mm and 235.1 mm of rainfall in 24 hours respectively, which are the highest amounts for these respective stations, since their establishment. Record highest 24 hours rainfall amounting to 134.9 mm and 119.4 mm were also observed at Buginyanya and Kawanda meteorological stations in Uganda on 18th March 2018 and 7th May 2020. On 6th May 2020, Byimana meteorological station in Rwanda, also observed 140.6 mm of rainfall in 24 hours, the highest since its establishment. These extremes have caused multiple losses of life and property, and severe damages to infrastructure. Unfortunately, the frequency and intensity of these extremes are projected to increase under a changing regional climate patterns. It is therefore important that more studies are carried out to enhance understanding about the evolution, dynamics and predictability of these extremes in East Africa region.

Rainfall Variability over Tanzania during October to December and Its Association with Sea Surface Temperature (SST)

The current study examines the interannual rainfall variability and its associated atmospheric circulation in Tanzania during October-December (OND) rainfall season based on 1974 to 2010 climatology. The Empirical Orthogonal Function (EOF), composite and correlation analysis were used in this study. Years with enhanced precipitation are found to be associated with the low level moist and unstable wind from Congo basin which organizes and forms a confluent zone, an inter tropical convergence zone (ITCZ) extending from Congo to northern sector of the country. It however, characterizes low-level westerly moisture flux transport sourced from Congo basin, ascending limb of the local Indian Ocean Walker circulation over East Africa which enhances convection for wetness condition. Wet years are also coupled with the positive Indian Ocean Dipole (IOD) and the warm phase of the El Nino Southern Oscillation (ENSO) condition. On the spatial scale, both the IOD and ENSO indices are well correlated with OND rains over the bimodal areas (Lake Victoria basin, North Eastern Highlands (NEH), and northern coast) with strong correlation being to the NEH. Strong temporal correlation is revealed between the OND rains and IOD (r = 0.6304) compared to ENSO (r = 0.5538) indicating that anomalous warming over the western Indian Ocean has a faster response to OND rains in Tanzania than the remote influence induced by anomalous warming from the central Pacific Ocean. The patterns associated with dry years are found to be linked with the low-level divergence accompanied by convergence in the upper level. This condition enhances continuous descending motion accompanied with suppression in rainfall activities. Dry years are also associated with negative IOD, cold phase of ENSO condition, descending limb of the Walker Circulation and significant reduction in the westerly moisture flux transport sourced from Congo basin towards the western sector and Lake Victoria basin.

Assessing the Variability of Heavy Rainfall during October to December Rainfall Season in Tanzania

Heavy rainfall is one of the primary causes of flood during rainy season in Tanzania leading to severe socio-economic impacts. The study aimed at assessing and characterizing the variability of Heavy Rainfall Events (HREs) using Empirical Orthogonal Function (EOF), Mann-Kendal (MK) trend test, Correlation and Composite analysis methods. Based on the daily-observed precipitation and reanalysis data sets for the October to December (OND) rainfall season of 35 years (1981-2015), the spatial and temporal characteristics of HREs in Tanzania are studied. The relationship between heavy rainfall (HR) and large-scale circulation anomalies including the Indian Ocean dipole (IOD) and El Ni?o southern oscillation (ENSO) indices was assessed. The study found that, approximately 590 HREs were concentrated over northern sector and coastal belt of Tanzania. The monthly variability indicates that HREs are more pronounced in December followed by November while October being the least affected. The occurrence of HREs over the Lake Victoria, Kigoma and Tabora is largely attributed to low-level convergence of westerlies and enhanced moisture from Congo basin accompanied by a pronounced rising limb of Indian Walker circulation cell. A time-series analysis of HRE exhibits an inter-annual variation characterized by a slightly increasing trend, though the computed trends were not statistically significant at 95% confidence level. In most part of Tanzania HREs were positively correlated with both ENSO and IOD indices, underscoring the critical role of ENSO and Indian Ocean dynamic in modulating rainfall variability over the region. In general, it has been found that most of the HREs are generally triggered or amplified by large-scale circulation patterns such as ENSO and IOD.