<p>The Horn of Africa remains one of the world’s most climate-sensitive regions, with over half of its population affected by climate-induced disasters over the past two decades. Rising global temperatures have intensified extreme weather events including heatwaves, cyclones, prolonged droughts, and severe floods, posing significant threats to governments, businesses, and local communities. This study investigates shifts in rainfall patterns (variability, intensity, and depth) across monthly, and annual timeframes in the capital cities of Horn of Africa. Precipitation data from 1981 to 2022 were analysed using Mann–Kendall Test (MKT), Innovative Trend Analysis (ITA), and Intensity-Depth-Frequency (IDF) modeling with the Gumbel distribution. This study analyzes the interannual variability and trends of extreme rainfall across major capital cities in the Horn of Africa, Mogadishu, Djibouti, Nairobi, and Addis Ababa using the RX5day index, which represents the annual maximum consecutive 5-day rainfall during the March–May season from 1981 to 2022. MKT showed both positive and negative monthly trends in most of the months. The analysis showed predominantly increasing and statistically significant monthly rainfall trends in Mogadishu (e.g., April: Z = 1.81, May: Z = 2.61, August: Z = 3.04), while Djibouti exhibited positive trends in months like February (Z = 2.44) and May (Z = 2.14). Addis Ababa displayed mostly non-significant and weak trends with occasional slight increases (e.g., April: Z = 0.78), whereas Nairobi showed mixed patterns, including significant increases in November (Z = 2.14) and October (Z = 2.13), and slight declines in mid-year months. The IDF component assesses rainfall depth and intensity for durations ranging from 5 min to 24 h and return periods of 2 to 100 years. This study is grounded in the hypothesis that the capital cities of the Horn of Africa exhibit distinct spatiotemporal patterns of rainfall extremes driven by a combination of large-scale climate variability and local anthropogenic factors such as urbanization. To test this, we investigate shifts in rainfall patterns (variability, intensity, and depth) across daily, monthly, and annual timeframes in Mogadishu, Djibouti, Nairobi, and Addis Ababa. Results reveal considerable spatial and temporal differences in rainfall intensity. Nairobi exhibited the most pronounced recent extremes, particularly in 2019 and 2020, while Mogadishu and Djibouti experienced irregular but impactful peaks in 1992, 1990, and 2020. Addis Ababa showed a more stable pattern, with moderate to high RX5day values, indicating increased vulnerability to flash floods due to topographical features and rapid urbanization. These variations are influenced by large-scale climate drivers such as ENSO and the Indian Ocean Dipole, as well as local factors like urban expansion. The study underscores the utility of RX5day index in capturing rainfall extremes and highlights the urgent need for adaptive infrastructure, early warning systems, and climate-resilient urban planning to manage increasing flood risks. Results from the MKT and ITA reveal significant disparities in rainfall trends, with slope variations differing across cities and timescales. While the MKT detected declining annual rainfall trends in most capitals, Mogadishu exhibited an upward trend. The IDF analysis suggests that current rainfall variability has only a marginal impact on future rainfall depth across different return periods. The insights from this study offer valuable guidance for policymakers in designing adaptive strategies to address both water scarcity and extreme rainfall events across the region. Policy implications of these findings emphasize the importance of integrating localized hydrometeorological data into urban planning and disaster risk reduction strategies. Specifically, governments and development agencies should invest in city-specific flood risk management, upgrade drainage and water storage infrastructure, and enhance cross-border climate data sharing to strengthen regional resilience.</p> Graphical Abstract <p>The Horn of Africa is increasingly vulnerable to climate-induced extremes, including floods and droughts, driven by global warming and regional climate variability. This study focuses on the capital cities of Somalia, Ethiopia, Djibouti, and Kenya, analysing long-term shifts in rainfall intensity, depth, and frequency (IDF) from 1981 and 2022. Using daily precipitation data, the RX5day index was applied to identify extreme rainfall events during the March–May season. Statistical methods, including the Mann–Kendall Test (MKT), Innovative Trend Analysis (ITA), and IDF modeling using the Gumbel distribution, were employed to assess trends and changes across multiple timescales and return periods. Results reveal spatial disparities in rainfall extremes: Nairobi experienced intensified rainfall in recent years, while Mogadishu and Djibouti display irregular but impactful peaks. Addis Ababa displayed moderately increasing trends, likely influenced by topography and rapid urbanization. The IDF curves suggest marginal increases in rainfall depth and intensity at higher return periods. These findings underscore the influence the role of large-scale climate drivers such as ENSO and the Indian Ocean Dipole, alongside local urban pressures. The study underscores the urgent need for adaptive infrastructure, early warning systems, and climate-resilient urban planning to mitigate escalating flood risks in rapidly growing cities across the region.</p>

Spatiotemporal Trends in Rainfall Extremes: A Comprehensive Intensity–Duration–Frequency Analysis of Horn of Africa Capitals (1981–2022)

期刊论文
发表日期：

2025年10月29日

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Abdirahman Ismail Dhaqane,
Mohamad Fared Murshed,
Irfan Ur Rashid,
Saddam Hussain,
Mansour Almazroui,
Riaz Ali

摘要

The Horn of Africa remains one of the world’s most climate-sensitive regions, with over half of its population affected by climate-induced disasters over the past two decades. Rising global temperatures have intensified extreme weather events including heatwaves, cyclones, prolonged droughts, and severe floods, posing significant threats to governments, businesses, and local communities. This study investigates shifts in rainfall patterns (variability, intensity, and depth) across monthly, and annual timeframes in the capital cities of Horn of Africa. Precipitation data from 1981 to 2022 were analysed using Mann–Kendall Test (MKT), Innovative Trend Analysis (ITA), and Intensity-Depth-Frequency (IDF) modeling with the Gumbel distribution. This study analyzes the interannual variability and trends of extreme rainfall across major capital cities in the Horn of Africa, Mogadishu, Djibouti, Nairobi, and Addis Ababa using the RX5day index, which represents the annual maximum consecutive 5-day rainfall during the March–May season from 1981 to 2022. MKT showed both positive and negative monthly trends in most of the months. The analysis showed predominantly increasing and statistically significant monthly rainfall trends in Mogadishu (e.g., April: Z = 1.81, May: Z = 2.61, August: Z = 3.04), while Djibouti exhibited positive trends in months like February (Z = 2.44) and May (Z = 2.14). Addis Ababa displayed mostly non-significant and weak trends with occasional slight increases (e.g., April: Z = 0.78), whereas Nairobi showed mixed patterns, including significant increases in November (Z = 2.14) and October (Z = 2.13), and slight declines in mid-year months. The IDF component assesses rainfall depth and intensity for durations ranging from 5 min to 24 h and return periods of 2 to 100 years. This study is grounded in the hypothesis that the capital cities of the Horn of Africa exhibit distinct spatiotemporal patterns of rainfall extremes driven by a combination of large-scale climate variability and local anthropogenic factors such as urbanization. To test this, we investigate shifts in rainfall patterns (variability, intensity, and depth) across daily, monthly, and annual timeframes in Mogadishu, Djibouti, Nairobi, and Addis Ababa. Results reveal considerable spatial and temporal differences in rainfall intensity. Nairobi exhibited the most pronounced recent extremes, particularly in 2019 and 2020, while Mogadishu and Djibouti experienced irregular but impactful peaks in 1992, 1990, and 2020. Addis Ababa showed a more stable pattern, with moderate to high RX5day values, indicating increased vulnerability to flash floods due to topographical features and rapid urbanization. These variations are influenced by large-scale climate drivers such as ENSO and the Indian Ocean Dipole, as well as local factors like urban expansion. The study underscores the utility of RX5day index in capturing rainfall extremes and highlights the urgent need for adaptive infrastructure, early warning systems, and climate-resilient urban planning to manage increasing flood risks. Results from the MKT and ITA reveal significant disparities in rainfall trends, with slope variations differing across cities and timescales. While the MKT detected declining annual rainfall trends in most capitals, Mogadishu exhibited an upward trend. The IDF analysis suggests that current rainfall variability has only a marginal impact on future rainfall depth across different return periods. The insights from this study offer valuable guidance for policymakers in designing adaptive strategies to address both water scarcity and extreme rainfall events across the region. Policy implications of these findings emphasize the importance of integrating localized hydrometeorological data into urban planning and disaster risk reduction strategies. Specifically, governments and development agencies should invest in city-specific flood risk management, upgrade drainage and water storage infrastructure, and enhance cross-border climate data sharing to strengthen regional resilience.

Graphical Abstract

The Horn of Africa is increasingly vulnerable to climate-induced extremes, including floods and droughts, driven by global warming and regional climate variability. This study focuses on the capital cities of Somalia, Ethiopia, Djibouti, and Kenya, analysing long-term shifts in rainfall intensity, depth, and frequency (IDF) from 1981 and 2022. Using daily precipitation data, the RX5day index was applied to identify extreme rainfall events during the March–May season. Statistical methods, including the Mann–Kendall Test (MKT), Innovative Trend Analysis (ITA), and IDF modeling using the Gumbel distribution, were employed to assess trends and changes across multiple timescales and return periods. Results reveal spatial disparities in rainfall extremes: Nairobi experienced intensified rainfall in recent years, while Mogadishu and Djibouti display irregular but impactful peaks. Addis Ababa displayed moderately increasing trends, likely influenced by topography and rapid urbanization. The IDF curves suggest marginal increases in rainfall depth and intensity at higher return periods. These findings underscore the influence the role of large-scale climate drivers such as ENSO and the Indian Ocean Dipole, alongside local urban pressures. The study underscores the urgent need for adaptive infrastructure, early warning systems, and climate-resilient urban planning to mitigate escalating flood risks in rapidly growing cities across the region.