The Influence of Oceanic and Atmospheric Drivers on Djibouti’s Rainfall Variability
TadesseTerefeZeleke1,7
OmarAssoweDabar2
SintayehuAlemayehu1,3
JemalS.Ahmed1
SintayehuW.Dejene1
DejeneK.Mengistu5
AsaminewTeshome6,7
DegefieTibebe1
MoussaMahdiAhmed2
AniruddhaGhosh3
PedroA.Chilambe3
EvanGirvetz3
JulianRamirez-Villegas4
1International Center for Tropical AgricultureP.O. Box 5689Addis AbabaEthiopia
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Observatoire Régionale de Recherche sur l’Environnement et le Climat (ORREC), Centre d’Etudes et de Recherches de Djibouti (CERD)Route de L’aéroport, Djibouti-ville B.P. 486Djibouti3International Center for Tropical Agriculture (CIAT)P.O. Box 823-00621NairobiKenya
4International Center for Tropical Agriculture (CIAT)RomeItaly
5Bioversity InternationalP.O. Box 5689Addis AbabaEthiopia
6Ethiopian Meteorological InstituteAddis AbabaEthiopia
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Institute of Geophysics, Space Science and AstronomyAddis Ababa UniversityTadesse Terefe Zeleke*1,7, Omar Assowe Dabar2, Sintayehu Alemayehu1,3, Jemal S. Ahmed1, Sintayehu W. Dejene1, Dejene K. Mengistu5, Asaminew Teshome6,7, Degefie Tibebe1, Moussa Mahdi Ahmed2, Aniruddha Ghosh3, Pedro A. Chilambe3, Evan Girvetz3, Julian Ramirez-Villegas4
1International Center for Tropical Agriculture, P.O. Box 5689, Addis Ababa, Ethiopia
2Observatoire Régionale de Recherche sur l’Environnement et le Climat (ORREC), Centre d’Etudes et de Recherches de Djibouti (CERD), Route de L’aéroport, Djibouti-ville B.P. 486, Djibouti
3International Center for Tropical Agriculture (CIAT), Nairobi P.O. Box 823 − 00621, Kenya
4International Center for Tropical Agriculture (CIAT), Rome, Italy
5Bioversity International, P.O. Box 5689, Addis Ababa, Ethiopia
6Ethiopian Meteorological Institute, Addis Ababa, Ethiopia
7Institute of Geophysics, Space Science and Astronomy, Addis Ababa University
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Abstract
Rainfall variability presents a major challenge for climate-sensitive sectors in arid and semi-arid regions such as Djibouti, where livelihoods predominantly rely on rain-fed systems. This study provides a comprehensive assessment of seasonal and interannual variability in rainfall and temperature, emphasizing spatial patterns and the underlying oceanic and atmospheric drivers. Using station observations, satellite-based precipitation datasets (CHIRPS), and global reanalysis products, we characterize the seasonal climatology, dominant rainfall modes, and associated linkage with global and local drivers over the period 1981–2024. The climatological analysis reveals a bimodal rainfall regime, with primary peaks during July–September (JAS) and secondary peaks in March–May (MAM), reflecting the seasonal migration of the Intertropical Convergence Zone (ITCZ). JAS accounts for ~ 45.8% of annual rainfall and, in some regions, extends into November, contributing over 60% of the annual total. Rainfall exhibits a westward gradient, with the western highlands receiving the highest amounts, while temperature extremes peak in June–September, exceeding 40°C in lowlands, and decline moderately during December–February (DJF). Rotated Empirical Orthogonal Function (REOF) and Rotated Principal Component (RPC) analyses identify consistent spatial zones of rainfall variability across seasons. During MAM, northeastern, western, and central regions dominate variability, explaining 33.6%, 31.8%, and 26.7% of variance, respectively. In JAS, western Djibouti contributes 54.2% of variance, highlighting strong monsoonal influence. The ON season is highly fragmented, with the eastern tip accounting for 40.6% of variance, followed by the northwestern (32.8%) and south-central zones (17.6%), illustrating erratic rainfall patterns along coastal regions and extension of JAS in other areas. DJF rainfall is more spatially coherent, with the east-central (36.6%), western (28%), and central (25.8%) regions contributing most of the seasonal variance, shaped by extratropical troughs, the Red Sea Convergence Zone (RSCZ), and orographic lifting. Correlation analyses between seasonal RPCs and global Sea Surface Temperature (SST) anomalies reveal strong connections with the western Indian Ocean, Red Sea, and Gulf of Aden, which serve as key moisture sources. Large-scale climate modes, particularly the Indian Ocean Dipole (IOD) and El Niño–Southern Oscillation (ENSO), significantly influence rainfall seasonality. Positive IOD phases enhance ON rainfall via increased westerly moisture transport, while La Niña events tend to amplify JAS precipitation through displacement of the Walker circulation, which facilitates lifting of moisture-laden air entering the country. The findings underscore the complex interactions between ocean-atmosphere dynamics and local topography that govern spatiotemporal rainfall variability. Identifying dominant rainfall zones and their associated climate drivers provide critical insights for improving seasonal forecasting, early warning systems, climate-resilient planning, and targeted adaptation strategies in Djibouti and the broader Horn of Africa.
Keywords:
Djibouti
climate variability
Sea Surface Temperature (SST)
Rotated Empirical Orthogonal Function (REOF)
El Niño–Southern Oscillation (ENSO)
Indian Ocean Dipole (IOD)
Horn of Africa
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1. Introduction
Arid and semi-arid regions (ASALs) are among the most climate-sensitive areas globally due to their inherent water scarcity, fragile ecosystems, and dependence on rain-fed livelihoods. These regions are increasingly experiencing warming trends that exceed the global average, with intensified hydrological extremes such as prolonged droughts and intense rainfall events (IPCC 2021; Funk et al. 2014; Camberlin 2018). The Horn of Africa (HoA) exemplifies this vulnerability. Its highly variable and often erratic rainfall, coupled with recurrent climate shocks and entrenched socio-economic fragilities, makes it one of the most exposed regions to climate-related risks (Nicholson 2017; FEWS NET 2020; Alasow et al. 2024; WMO 2025). Understanding climate variability in such regions is critical for advancing scientific knowledge while simultaneously supporting resilience-building, food security, early warning mechanisms, and informed, climate-resilient policy planning.
Djibouti, located at the southern entrance of the Red Sea, lies at the intersection of key climatic and oceanographic systems. Its topography consists of coastal plains, rugged volcanic mountains, and inland plateaus, with elevations ranging from sea level to over 1,750 meters in the Goda Mountains (Fig. 1) of Northwestern Djibouti, near the Gulf of Tadjoura, which serves as local water resources, forest preservation and livelihoods of nearby communities. This geographic complexity contributes to pronounced microclimatic variability. The country’s climate is classified as hyper-arid to semi-arid, receiving annual rainfall ranging from less than 100 mm in lowland areas to approximately 300 mm in the highlands (Assowe Dabar et al. 2021; Dabar et al. 2022). Rainfall is seasonal and highly localized, with two primary wet seasons: March–May and July–September (Palmer et al. 2023; Zeleke et al. 2017b; Souverijns et al. 2016). However, both the frequency and intensity of rainfall are influenced by large-scale climate drivers such as the Indian Ocean Dipole (IOD), El Niño–Southern Oscillation (ENSO), and regional sea surface temperature (SST) anomalies (Camberlin 2018; Waberi et al. 2023).
Fig. 1
) Study area of Djibouti showing (a) topography with surrounding ocean and land features, and (b) soil types based on FAO classification, including Luvisols, Calcaric Fluvisols, Calcaric Regosols, Eutric Regosols, Haplic Xerosols, Takyric Solonchaks, salt flats, and water bodies.
Djibouti’s socio-economic profile further accentuates its climate sensitivity. With limited freshwater resources, high reliance on food imports, and the predominance of climate-sensitive sectors like pastoralism, port-service and informal trade, the country is highly exposed to both slow-onset (drought) and rapid-onset (flash flood) climate hazards (UNDP 2024; FAO 2005). Despite its strategic geopolitical location and emerging development aspirations, Djibouti lacks robust climate information systems, which limits its capacity for adaptation planning and disaster risk management. Understanding the dynamics of climate variability and its drivers is thus a foundational step toward enhancing climate resilience and sustainable development.
From a theoretical perspective, the study of rainfall variability in ASALs is rooted in the analysis of large-scale atmospheric and oceanic interactions. ENSO and IOD, two dominant modes of interannual variability, have been shown to affect precipitation patterns across the tropics through shifts in convection zones, sea surface temperature anomalies, and regional wind patterns (Webster et al. 1999; Williams and Funk 2011). In East Africa, El Niño events are often associated with enhanced short rains (October–December), while positive IOD phases can intensify rainfall during the same season (Camberlin et al. 2002; Funk et al. 2014). However, the impacts of these teleconnections are often nonlinear, seasonally modulated, and spatially heterogeneous, particularly in data-sparse countries like Djibouti (Camberlin 2018; Waberi et al. 2023). Although foundational research by Camberlin et al. (2002) and Nicholson (2017) has illuminated the broad climatology of East Africa, focused studies on Djibouti remain limited. Recent works by Waberi et al. (2023), Assowe Dabar et al. (2021) and Dabar et al. (2022) have identified seasonal rainfall clusters and documented the influence of ENSO and IOD phases (Saji et al. 1999; Schott et al. 2009). However, these studies often lack high-resolution spatial analysis and do not fully explore the physical mechanisms through which global climate modes interact with Djibouti’s complex topography and localized weather systems. Moreover, the reliability of rainfall forecasts remains low due to lack of detail regional rainfall mechanisms and sparse observational coverage and limited use of integrated datasets.
The study investigates the influence of large-scale oceanic and atmospheric circulation patterns on the seasonal and interannual variability of regional rainfall in Djibouti, which delineate the spatiotemporal characteristics of rainfall across the country's diverse ecological and topographic settings. It quantifies the relationships between regional rainfall variability and key climate drivers such as the El Niño–Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), and regional sea surface temperature (SST) anomalies. Moreover, it examines the impact of orographic features and other localized climatic effects on sub-national rainfall patterns. Hence the research represents the first integrated diagnostic assessment of rainfall variability in Djibouti, combining ground-based nearby observations, satellite-derived precipitation products, and atmospheric reanalysis datasets. Through the application of robust advanced statistical methods, the study identifies the dominant modes of climate variability and their associated drivers. The findings contribute valuable insights to support national early warning systems, inform climate adaptation strategies, and guide planning in key climate-sensitive sectors such as water resource management, agriculture, and disaster risk reduction.
The remainder of the manuscript is organized as follows: Section 2 describes the study area, data sources, and analytical methods employed to explore climate variability and its physical mechanisms. Section 3 presents the main findings, including the seasonal climatology, spatial and temporal variability of rainfall, and its linkages with ocean-atmosphere interactions. Section 4 offers a synthesis of the results, discusses their policy relevance, and provides recommendations for future research to strengthen climate resilience and early warning capabilities in Djibouti.
2. Methodology
2.1. Study Area
The Republic of Djibouti, covering approximately 23,200 km², is in the Horn of Africa at the southern gateway to the Red Sea, between 11° and 12.5°N latitude and 42° to 43.6°E longitude. It borders Eritrea to the north, Ethiopia to the west and south, Somalia to the southeast, and the Red Sea and Gulf of Aden to the east (Fig. 1). This strategic location at the convergence of major oceanic and atmospheric systems renders Djibouti highly sensitive to regional and global climate variability (Nicholson 2017; IPCC 2021). The country’s terrain is largely arid to semi-arid, featuring rugged mountains, plateaus, and low-lying coastal plains. Notable geographic features include the Danakil Depression and Lake Assal, Africa’s lowest point and one of the world’s saltiest lakes (FAO 2005). Rainfall is sparse, erratic, and spatially heterogeneous, with annual precipitation ranging from less than 100 mm in coastal regions to about 300 mm in highland areas (Assowe Dabar et al. 2021; Nicholson 2017; FEWS NET 2018). Djibouti experiences two primary rainy seasons: March–May (short rains) and July–September (main rains), both influenced by large-scale climate drivers such as the El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and regional SST anomalies (Souverijns et al. 2016; Zeleke et al. 2017a).
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With a population of approximately one million, mostly concentrated in Djibouti City, the country’s economy is service-oriented and heavily dependent on port-related activities (World Bank 2020; UNDP 2022). Agriculture is minimal and highly vulnerable to climatic stressors. Given its environmental sensitivity and developmental aspirations, understanding rainfall variability and its oceanic and atmospheric drivers is crucial for enhancing climate resilience, disaster preparedness, and sustainable resource management (Zeleke et al. 2013; IPCC 2021; UNDP 2022).2.2. Methodological Framework
The study employed suite statistical and diagnostic tools designed to capture the spatial and temporal characteristics of rainfall variability and its link to oceanic and atmospheric dynamics. Specifically, the study applied Rotated Empirical Orthogonal Function (REOF) analysis, non-linear correlation analyses with sea surface temperature (SST) anomalies, and trend detection techniques. This multi-method framework ensures a robust and nuanced understanding of rainfall patterns and their climatic drivers.
2.2.1. Data Sources
Rainfall data were obtained from the CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) dataset, which provides high-resolution gridded precipitation data from 1981 to present (Funk et al. 2015). Station rainfall records from nearby places of Ethiopia (have similar features Djibouti) were used to validate the CHIRPS dataset through spatial correlation and time series comparison. Additional climate variables, including temperature, were sourced from the CRU TS 4.09 dataset (Harris et al. 2020). SST data were derived from the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST), spanning the same period (Rayner et al. 2003), to examine the influence of large-scale oceanic conditions. Atmospheric circulation data, including wind vectors at multiple pressure levels, were obtained from the NCEP/NCAR Reanalysis Project (Kalnay et al. 1996), which provided essential context for understanding broader climatic dynamics.
2.2.2. Statistical and Diagnostic Methods
Seasonal patterns were identified using climatological averaging and seasonal index analysis, capturing long-term monthly (the study period) means to delineate major rainfall regimes (Wilks 2011; Hyndman & Athanasopoulos 2021). To analyze spatial and temporal variability, the study implemented Rotated Empirical Orthogonal Function (REOF) analysis. Compared to conventional Empirical Orthogonal Function (EOF), REOF (using varimax rotation) enhances the physical interpretability of spatial modes by producing more localized and orthogonal structures, making it particularly suitable for regional climate variability studies (Richman 1986; Navarra and Simoncini 2010; Zeleke et al. 2017a). The resulting principal components (PCs) were examined to identify dominant rainfall modes and assess their interannual behavior with its potential mechanisms. Trend analysis combined both parametric and non-parametric approaches. The Mann–Kendall test is used to detect monotonic trends due to its robustness against non-normal distributions and missing data (Kendall 1975; Weldegerima et al. 2018). Sen’s slope estimator quantified the magnitude of observed trends (Sen 1968; Yue & Wang 2004).
To explore teleconnections, we conducted correlation analyses between seasonal rainfall and SST anomalies using Pearson, Spearman, and Kendall coefficients. This comprehensive approach allowed for the detection of both linear and monotonic relationships, providing greater confidence in the identification of significant climate linkages (Wilks 2011). This integrative methodological approach enables a detailed assessment of the oceanic and atmospheric drivers of rainfall variability in Djibouti and provides a scientific foundation for enhancing early warning systems, adaptation planning, and climate-informed decision-making.
3. Results and Discussion
3.1. Climatology of Rainfall and Temperature
A monthly and seasonal climatological assessment of rainfall and temperature in Djibouti reveals pronounced spatiotemporal variability, particularly in precipitation distribution across the country. Despite its small geographical size, Djibouti exhibits distinct regional rainfall regimes, influenced by topography, proximity to the sea, and orographic effects. The monthly rainfall climatology (Fig. 2) highlights that the western and central parts of the country receive the bulk of their annual rainfall during the July–September (JAS) season, corresponding with the northern extension of the East African monsoon. The JAS season accounts for approximately 45.8% of annual rainfall, extending in some regions to November, increasing its contribution to over 60% of the yearly total. Rainfall intensity exhibits a clear east–west gradient, with the western highlands receiving the highest totals, while the eastern coastal zones experience relatively greater precipitation during the March–May (MAM) season, which is more uniform across the country. A secondary, less intense rainy period occurs during October–December (OND) in the eastern region. These patterns suggest that orographic lifting and sea breezes from the Gulf of Aden play significant roles in modulating local precipitation (Palmer et al. 2023; Omay et al. 2023; Nicholson 2017; Gamoyo et al. 2015).
Fig. 2
) Spatial distribution of mean monthly rainfall (a–l) and national mean annual cycle (m) for Djibouti, 1981–2024.
Extreme events occasionally punctuate the climatology. For instance, Cyclone Sagar on May 2018, originating from the Arabian Sea, brought intense rainfall to Djibouti City over two days, causing urban flooding and infrastructure damage (Camberlin et al. 2024; Thomas & Lekshmy 2022).
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The annual rainfall cycle further emphasizes seasonal asymmetry, with August as the peak month (~ 22% of annual total), followed by September (~ 12.6%), July (~ 11.6%), April (~ 11%), and March (~ 10.9%). June is consistently the driest month, contributing less than 1% of the annual total, a decline associated with the intensification of the southerly Somali Jet, enhancing wind divergence and vertical wind shear (Omay et al. 2023; Nicholson 2017; Wainwright 2016). These seasonal transitions underscore the critical role of JAS rainfall for water availability in western interior regions, while MAM rains support pastoral livelihoods, particularly along coastal zones. In Djibouti, some areas receive up to 300 mm of rainfall annually, while the national rainfall amount over the past 44 years was approximately 3.8 billion mm/year (Fig. 2). Given the spatial and temporal distribution of rainfall, integrated water management strategies are essential. In urban settings, nature-based solutions such as rooftop rainwater harvesting, permeable pavements, and smart drainage systems can enhance water capture and reuse. In rural and pastoral zones, community-managed micro-dams and sand dams can retain MAM and JAS rainfall for livestock and irrigation. When combined with real-time climate monitoring and AI-enabled hydrological forecasting, these interventions can establish climate-resilient water infrastructure tailored to Djibouti’s arid and variable climate (UNEP 2020; FAO 2021; WMO 2022).Djibouti’s thermal regime is characterized by marked seasonal extremes and pronounced spatial variability, strongly influenced by its unique topography and geographic setting (Fig. 3). The annual temperature cycle reaches its peak during June–September (JJAS), when daytime maximum temperatures frequently exceed 40°C and even minimum nighttime values often remain above 30°C. These conditions typify the hyper-arid and semi-arid environments of the region, amplifying heat stress and intensifying evapotranspiration losses. Conversely, during the December–February (DJF) season, temperatures decline modestly, offering relatively milder conditions; however, even in this period, thermal levels remain high compared to temperate climates worldwide, underscoring the persistent heat load that characterizes Djibouti’s environment. Spatially, clear thermal contrasts emerge across the landscape. The central highlands and mountainous regions develop cooler microclimates due to orographic elevation and enhanced convective activity, whereas the eastern and western low-lying coastal zones, along with inland depressions, experience amplified heating. This spatial dichotomy mirrors the broader climatological dynamics of the Horn of Africa, where elevation gradients serve as dominant control on local temperature regimes (Baxter et al. 2023; Billi 2022; Liebmann et al. 2014; Zeleke et al. 2017b; Gebrechorkos et al. 2019; Zeleke et al. 2024).
Fig. 3
) Monthly climatology of minimum (night-time) temperatures and the national mean annual cycle in Djibouti (1981–2024); panels (a–l) show the spatial distribution of monthly mean minimum temperatures, while panel (m) depicts the countrywide average annual cycle.
The persistence of elevated temperatures in lowland environments is not only a function of geographic setting but also of atmospheric processes. Subsidence associated with regional circulation systems, combined with limited cloud cover and strong land–atmosphere coupling, contributes to the amplification of surface heating (Mora Castro & Sergio, 2010). Such mechanisms align with observations across comparable arid and semi-arid landscapes in East Africa and beyond (Dinku et al. 2014; McSweeney et al. 2010). These persistent high temperatures, coupled with minimal seasonal relief, place lowland populations and ecosystems under considerable thermal stress. The implications are multifaceted: increased risks of heat-related health impacts, accelerated water demand, and heightened vulnerability of rainfed agricultural systems and pastoral livelihoods. Furthermore, the superimposition of projected global warming (IPCC 2021) suggests that current extremes may represent only a baseline, with future scenarios pointing toward more intense and prolonged heat events. In this context, Djibouti’s spatially diverse temperature patterns underscore both the moderating role of elevation and the heightened susceptibility of coastal and inland lowlands, highlighting the urgent need for adaptive measures tailored to physiographic and climatological realities.
Djibouti’s consistently high solar irradiance and elevated temperatures present significant opportunities for renewable energy deployment and climate-resilient technological solutions. Among the most promising strategies is the adoption of Concentrated Solar Power (CSP) systems integrated with thermal energy storage, which utilize mirrors to focus sunlight and store heat in molten salts, enabling continuous electricity generation even during non-sunlight hours (IRENA 2020). Complementary approaches include solar-assisted cooling technologies, such as absorption and adsorption chillers, which align peak cooling demand with peak solar availability, offering sustainable alternatives to conventional air conditioning (IEA 2022). In the built environment, passive thermal design integrated with Phase Change Materials (PCMs) can regulate indoor temperatures by absorbing and releasing latent heat, thereby reducing reliance on energy-intensive cooling systems (Zalba et al. 2003; Cabeza et al. 2010). Additionally, solar desalination technologies, including multi-effect distillation and solar stills, leverage abundant solar energy to provide decentralized potable water supplies, addressing chronic freshwater scarcity in coastal and inland areas (Ghaffour et al. 2013). Remote or off-grid regions can benefit from Thermoelectric Generators (TEGs), which convert thermal gradients into electricity to power small-scale health, communication, or environmental monitoring devices (Zhenhua et al. 2022; Xie et al. 2022; Yuming et al. 2023). Furthermore, Djibouti’s geothermal potential provides a foundation for hybrid solar–geothermal systems, combining surface and subsurface energy to enhance power plant efficiency and ensure year-round energy reliability (DiPippo 2012; World Bank 2016). Collectively, these technologies offer a pathway to transform the country’s extreme thermal environment into a driver of sustainable energy, water security, and climate resilience.
The broader climatological context underscores the critical influence of climate variability on Djibouti’s socio-economic sectors, particularly agriculture, water resources, and urban infrastructure. Deviations from average conditions, whether in the form of excessive rainfall or prolonged dry spells, pose substantial risks to livelihoods and development. For instance, anomalously high rainfall in 2018 triggered widespread flooding, disrupting infrastructure, agriculture, and human settlements, while below-average seasonal precipitation has been closely linked to droughts and water scarcity (Zeleke et al. 2017a; Zeleke et al. 2017b; Gebrechorkos et al. 2019). The combined analysis of rainfall and temperature climatology highlights the vulnerability of lowland regions to both thermal extremes and hydrological variability. Consequently, climate-informed adaptation strategies: including resilient energy systems, water management innovations, and infrastructure planning, are essential to safeguard economic stability, enhance food security, and build long-term resilience to the projected intensification of climate extremes in Djibouti (IPCC 2021).
3.2. Spatiotemporal Variability and Trends of Rainfall
Building upon the climatological assessment presented in the above, Djibouti’s March–May (MAM) and July–September (JAS) rainfall seasons exhibit pronounced spatiotemporal variability, strongly shaped by regional atmospheric dynamics, topographic features, and ocean-atmosphere interactions. To quantify these patterns, Rotated Empirical Orthogonal Function (REOF) analysis was applied, revealing three primary modes of rainfall variability for each season (Fig. 4).
Fig. 4
) MAM and JAS seasons three dominant variability patterns with the corresponding time component (1981–2024).
During the MAM season, the northeastern region emerges as the most dominant contributor, explaining 33.6% of the total variance (Fig. 4a). The western and central regions follow, accounting for 31.8% and 26.7%, respectively (Figs. 4b–c). The associated principal component time series (Fig. 4d) display substantial interannual fluctuations, consistent with broader Horn of Africa patterns where MAM rainfall is influenced by large-scale climate drivers such as the Indian Ocean Dipole (IOD) and El Niño–Southern Oscillation (ENSO) (Dinku et al. 2014; Nicholson 2017). Spatial heterogeneity during this minor rainfall season reflects the interplay of orographic uplift, moisture advection from the Indian Ocean, and localized convection, patterns also documented in Ethiopia and Somalia (Gebrechorkos et al. 2018; 2019; Segele & Lamb 2005).
In contrast, JAS rainfall variability is dominated by the western region, which explains 54.2% of total variance (Fig. 4e), followed by the north-central and northeastern regions contributing 19.5% and 16.7%, respectively (Figs. 4f–g). Temporal patterns (Fig. 4h) indicate stronger interannual coherence and higher coefficients of determination relative to MAM, reflecting the influence of monsoonal circulation and teleconnections with the Atlantic Ocean (Zaroug et al. 2014). The dominance of the western sector during JAS highlights the role of African monsoon dynamics and Red Sea moisture convergence, a mechanism similarly observed in Yemen and southwestern Saudi Arabia (Camberlin 2018). Collectively, these results indicate that MAM rainfall is spatially fragmented and sensitive to competing oceanic and topographic forcings, whereas JAS rainfall exhibits spatial consolidation under dominant monsoonal control.
Extending this analysis to the October–November (ON) season, three dominant zones of variability emerge (Fig. 5): the eastern coastal strip contributes 40.6% of the seasonal variance, followed by the northwestern (32.8%) and south-central (17.2%) regions. Principal component analyses reveal highly volatile but weakly predictable rainfall patterns, consistent with the erratic nature of short rains across the Horn of Africa (Nicholson 2017). The heightened sensitivity of the eastern tip reflects proximity to the Red Sea, facilitating episodic moisture surges, while the northwestern variability mirrors Ethiopia’s arid lowlands, where terrain and localized convection dominate (Viste & Sorteberg 2013; Zeleke et al. 2017a). The limited predictability of ON rainfall highlights challenges for early warning and emphasizes the need for adaptive, decentralized water management strategies.
Fig. 5
) ON and DJF seasons three dominant variability patterns with the corresponding time component (1981–2024).
During the December–February (DJF) season, rainfall variability shifts towards the east-central (36.6%), western (28.0%), and central (25.8%) regions (Fig. 5). Although DJF precipitation is lower in magnitude than ON, interannual variability remains significant. Unlike the convectively driven ON rains, DJF rainfall is largely governed by extratropical atmospheric dynamics, including the southward extension of the Arabian Peninsula winter trough, and modulated by local orographic effects, particularly in elevated interior zones (Camberlin 2018). Similar spatial patterns have been observed in Eritrea and Yemen, where winter rainfall is shaped by coastal convection and highland uplift (Zaroug et al. 2014; Nicholson 2017).
The contrast between ON and DJF rainfall highlights two key challenges for climate risk management in Djibouti: ON’s spatially fragmented, flood-prone patterns versus DJF’s organized but drier regime. These dynamics underscore the sensitivity of Djibouti’s rainfall to both oceanic drivers (IOD, ENSO) and continental atmospheric processes, consistent with broader observations across arid and semi-arid East Africa (Funk et al. 2018; IPCC 2021). Effective adaptation for agro-pastoral communities requires integrating high-resolution diagnostics of these drivers into forecasting systems, enhancing predictive skill for short rains (ON) and winter precipitation (DJF) alike (Gebrechorkos et al. 2019; Segele & Lamb 2005; World Bank 2020).
Figures 4 and 5 collectively demonstrate that Djibouti’s seasonal rainfall variability is both regionally heterogeneous and temporally dynamic, with dominant modes of variance varying by season. Understanding these spatiotemporal patterns is critical for climate-informed water resource planning, agricultural scheduling, and disaster risk reduction, providing a foundation for resilience strategies tailored to the country’s arid and highly variable climate.
3.3. Mechanisms of Spatiotemporal Rainfall Variability
Djibouti’s rainfall exhibits pronounced spatiotemporal variability, shaped by a complex interplay of oceanic, atmospheric, and topographic factors. Analysis of seasonal dominant rainfall modes using Rotated Principal Components (RPCs) reveals strong teleconnections with sea surface temperature (SST) anomalies across multiple oceanic basins (Figs. 6 and 7). The standardized anomaly analysis demonstrates that rainfall distribution is closely modulated by regional and global SST variability, highlighting the critical role of adjacent oceans, including the Red Sea, Gulf of Aden, western Indian Ocean, and select equatorial Atlantic regions, in shaping both seasonal and interannual precipitation regimes.
Fig. 6
) Significant (p < 0.05) correlations between seasonal dominant rainfall RPCs and corresponding SST anomalies for MAM (panels a–c) and subsequent seasons (rows 2–4), illustrating dominant RPC–SST relationships.
Fig. 7
) Significant correlations between seasonal areal mean rainfall anomalies and corresponding SST anomalies (panels a, c, e, g) and the corresponding climatological rainfall patterns (panels b, d, f, h) for MAM, JJA, ON, and DJF seasons during 1981–2024.
Seasonal rainfall variability in Djibouti is strongly influenced by SST fluctuations, with distinct spatial and temporal correlations emerging from different oceanic regions. Warm SST anomalies in the Red Sea and western Indian Ocean enhance evaporation and moisture transport, fueling convective activity and precipitation over Djibouti (Figs. 6 and 7). This mechanism is consistent with observations across the Horn of Africa, where Indian Ocean SSTs are pivotal in regulating regional rainfall and monsoonal intensity (Funk et al. 2014; Nicholson 2017). The Gulf of Aden further modulates coastal precipitation through moisture advection, which is amplified by orographic lifting along escarpments and highlands (Viste & Sorteberg 2013; Zeleke et al. 2017a; Zeleke et al. 2017b).
The seasonal modulation of rainfall mechanisms reflects the shifting dominance of SST regions and associated wind circulation patterns. During months with anomalously warm SSTs in the Red Sea and western Indian Ocean, enhanced moisture availability promotes convection and precipitation, particularly in coastal and highland zones (Viste & Sorteberg 2013). These patterns align with prior studies demonstrating the western Indian Ocean’s influence on East African monsoon dynamics and moisture flux (Funk et al. 2014). The Indian Ocean Dipole (IOD) and El Niño–Southern Oscillation (ENSO) emerge as primary large-scale drivers of Djibouti’s rainfall variability. Positive IOD phases are typically associated with enhanced rainfall due to strengthened moisture transport from the Indian Ocean and increased convective activity (Camberlin 2018). Conversely, El Niño events suppress rainfall by altering circulation patterns, including an eastward shift of the Walker circulation, producing subsidence over the Horn of Africa during JAS (Williams & Funk 2011; Figs. 6 and 7). In contrast, La Niña conditions during MAM, ON, and DJF are associated with reduced moisture transport and below-average rainfall (Figs. 6–7), corroborating earlier findings on ENSO’s dual seasonal influence (Camberlin et al. 2002).
Importantly, favorable rainfall conditions across all seasons depend on the combined state of ENSO and adjacent climate oscillations, emphasizing the multi-driver complexity of Djibouti’s hydroclimate.
Djibouti’s elevated terrain, particularly the Goda Mountains, interacts with moisture-laden winds to produce localized rainfall via orographic lifting. This process amplifies spatial variability, especially during periods of enhanced SST-driven moisture convergence (Nicholson 2017). The resulting rainfall distribution reflects the synergy between regional oceanic conditions and local physiography, producing the heterogeneous precipitation patterns observed across the country (Figs. 7b, d, f, h).
Composite analyses of lower-level (1000–850 hPa), mid-level (600–500 hPa), and upper-level (300–100 hPa) winds further illustrate the dynamical mechanisms underlying rainfall variability (Fig. 8). During wet years, anomalous low-level winds enhance moisture flux from the Red Sea and Gulf of Aden into the western and central regions, while mid- and upper-level circulations reinforce convective activity. Conversely, dry years are characterized by weaker or divergent wind patterns, reducing moisture convergence and suppressing rainfall. Seasonal composites highlight that these processes are modulated differently across MAM, JAS, ON, and DJF, reflecting shifts in ocean-atmosphere coupling and monsoonal circulation strength.
Fig. 8
) Seasonal composites of SST, wind at lower (1000–850 hPa), mid (600–500 hPa), and upper (300–100 hPa) levels for wet versus dry rainfall anomaly years during 1981–2024.
Overall, Djibouti’s spatiotemporal rainfall variability arises from the interconnected influence of SST anomalies, wind circulation patterns, topography, and large-scale climate drivers such as IOD and ENSO. This complex interplay produces the distinct seasonal and geographic disparities observed across the country. A comprehensive understanding of these mechanisms is essential for improving seasonal forecasting, early warning systems, and adaptive climate strategies, particularly in regions exposed to hydroclimatic extremes. Incorporating high-resolution diagnostics of SST-driven teleconnections and wind dynamics into national climate models can enhance predictive skill and inform water resource management, agricultural planning, and disaster risk reduction, strengthening resilience in Djibouti’s arid environment (Funk et al. 2014; Camberlin 2018; Viste & Sorteberg 2013).
4. Summary and Conclusions
This study provides a comprehensive assessment of Djibouti’s rainfall and temperature climatology, spatiotemporal variability, and the underlying mechanisms driving precipitation patterns, spanning the period 1981–2024. The findings reveal the highly dynamic nature of the country’s climate, shaped by complex interactions between topography, atmospheric circulation, and oceanic forcing, with significant implications for water resources, agriculture, and climate resilience planning.
The climatological analysis highlights distinct seasonal rainfall regimes in Djibouti. The March–May (MAM) season provides moderate but spatially uniform precipitation, primarily supporting pastoral and smallholder agricultural activities, particularly along the eastern coastal zones. In contrast, the July–September (JAS) season constitutes the main rainy period, contributing over 45% of the annual rainfall. This season is characterized by an east-to-west gradient in rainfall intensity, with the western interior regions receiving the highest totals due to orographic uplift and moisture convergence from the African monsoon system. The secondary rainfall period extending into October–November further accentuates the spatial heterogeneity of precipitation, especially in the western and central regions. The annual rainfall cycle emphasizes August as the peak month, with 30–70 mm of rainfall depending on topographic elevation. June is consistently the driest month, reflecting the influence of southerly winds and the Somali Jet, which enhance divergence and vertical wind shear across the country. These findings underscore the critical role of the JAS season in national water availability and the importance of MAM rains in sustaining pastoral livelihoods, particularly in lowland and coastal zones.
Temperature patterns in Djibouti exhibit strong seasonal and spatial variability. Minimum temperatures during June–September frequently exceed 30°C, while maximum temperatures surpass 40°C, reflecting the country’s arid and semi-arid climate. Elevated regions such as the Goda and Mabla mountains maintain cooler microclimates due to altitudinal moderation, whereas low-lying coastal zones experience amplified thermal intensity. The persistence of elevated temperatures across lowland regions highlights the vulnerability of human and ecological systems to heat stress, while also presenting opportunities for solar energy harnessing, including concentrated solar power (CSP), solar-assisted cooling, and solar desalination technologies. Such interventions can transform climatic challenges into sustainable development solutions for energy, water, and food security.
Extreme rainfall deviations, whether excessive or insufficient, have profound socio-economic implications. High rainfall events, such as those associated with Cyclone Sagar in 2018, triggered widespread flooding, infrastructure damage, and disruption of livelihoods, while below-average rainfall events contribute to drought, threatening agricultural output and water availability. Climatological assessment reinforces the need for integrated water management systems, early warning frameworks, and community-level adaptation strategies to mitigate these hazards.
The analysis of seasonal and interannual rainfall variability reveals marked spatial heterogeneity, shaped by regional atmospheric dynamics and topographic influences. Rotated Empirical Orthogonal Function (REOF) analyses identify three dominant modes of variability per season, elucidating the spatial focus and temporal evolution of rainfall anomalies. During MAM, the northeastern region explains 33.6% of variance, followed by western (31.8%) and central (26.7%) regions. Principal component analyses demonstrate strong interannual fluctuations, highlighting the influence of Indian Ocean Dipole (IOD) and ENSO teleconnections. Variability is spatially fragmented, reflecting competing forcings from the Indian Ocean, local orography, and episodic convection. In the JAS season, the western region dominates, contributing 54.2% of variance, while north-central and northeastern regions contribute 19.5% and 16.7%, respectively. Temporal analyses indicate higher predictability, suggesting that monsoonal circulation and Red Sea moisture convergence play a more consistent role in modulating rainfall. These spatial and temporal patterns align with observations from Sudan, Eritrea, and Yemen, emphasizing the regional coherence of monsoonal-driven rainfall variability.
The October–November (ON) short rains exhibit high spatial heterogeneity, with the eastern coastal strip contributing 40.6% of variance. Principal component analyses indicate low predictability, reflecting the erratic nature of ON rainfall across the Horn of Africa, where variability is strongly influenced by ITCZ progression, IOD-induced moisture transport, and episodic convective events. In contrast, DJF rainfall is more spatially coherent, shifting toward east-central, western, and central regions. Although overall precipitation is lower than in ON, interannual variability remains significant, driven largely by extratropical circulation and orographic uplift. The juxtaposition of ON’s fragmented, flood-prone regime against DJF’s organized but drier pattern underscores the dual challenges of acute hydro-meteorological hazards and chronic water scarcity, demanding adaptive strategies that address both short- and long-term risks.
A core finding of this study is the influence of ocean-atmosphere interactions on Djibouti’s rainfall patterns, mediated through SST anomalies, wind circulation, and large-scale climate oscillations (Figs. 6–8). Sea Surface Temperature (SST) anomalies in the Red Sea, Gulf of Aden, western Indian Ocean, and equatorial Atlantic correlate strongly with seasonal and interannual rainfall variability. Warm SST anomalies enhance evaporation and moisture transport, promoting convection along coastal and highland zones, consistent with patterns observed across the Horn of Africa (Funk et al. 2014; Nicholson 2017). Composite analyses demonstrate that wet years are associated with enhanced low- to upper-level wind convergence, whereas dry years display divergent or weakened circulation patterns.
Indian Ocean Dipole (IOD), positive phases enhance eastern Horn rainfall via strengthened moisture transport, particularly affecting MAM and ON seasons. El Niño–Southern Oscillation (ENSO), suppresses rainfall during JAS through altered Walker circulation and subsidence, while La Niña reduces precipitation during MAM, ON, and DJF. The interplay between IOD and ENSO modulates both seasonal intensity and interannual predictability. Topography further amplifies rainfall heterogeneity, with mountainous regions inducing orographic lifting that enhances local precipitation. The synergy between SST anomalies, atmospheric circulation, orography, and large-scale climate drivers explains the observed seasonal and spatial disparities, providing a mechanistic understanding of Djibouti’s hydroclimate.
The findings of this study have direct implications for water resource management, agricultural planning, and climate adaptation in Djibouti. The combination of highly variable rainfall patterns and limited freshwater availability highlights the need for context-specific, adaptive strategies. For water resources, interventions such as micro-dams, sand dams, rooftop rainwater harvesting, and smart drainage systems can enhance water capture and storage, while integrating real-time climate monitoring and AI-enabled hydrological forecasting can optimize the use of scarce water supplies. In agriculture, seasonal diagnostics provide essential guidance for crop selection, irrigation scheduling, and pastoral management, particularly during the ON and JAS periods when rainfall variability is most pronounced; the adoption of drought-tolerant crops and supplemental irrigation can further mitigate climate-related risks. Climate adaptation can be strengthened by incorporating mechanistic insights into forecasting and early warning systems to better prepare for extreme rainfall events and prolonged dry periods, while solar-based technologies, including Concentrated Solar Power (CSP) and desalination, offer sustainable solutions for energy and water security in regions prone to heat stress and water scarcity. At the policy level, the evidence generated by this study informs national climate resilience strategies, disaster risk reduction frameworks, and regional adaptation initiatives, thereby supporting broader objectives such as the African Union Climate Resilience Framework and the UN Sustainable Development Goals.
Overall, the study demonstrates that Djibouti’s climate is marked by pronounced spatiotemporal variability, shaped by the complex interplay of oceanic, atmospheric, and topographic factors. Seasonal rainfall regimes are highly asymmetric, with the JAS rains dominating the annual cycle and MAM precipitation playing a critical role in sustaining coastal and pastoral livelihoods. Spatial variability is also notable, with the western interior receiving the bulk of JAS rainfall, while eastern coastal areas experience higher ON precipitation. Oceanic forcing through SST anomalies in the Red Sea, Gulf of Aden, and western Indian Ocean strongly influences moisture availability and rainfall patterns, while large-scale climate oscillations such as the Indian Ocean Dipole (IOD) and El Niño–Southern Oscillation (ENSO) modulate both rainfall intensity and interannual predictability. Topography further amplifies local variability, creating microclimatic contrasts that are critical for water resource distribution and agricultural planning. These insights underscore the importance of integrated water and energy management strategies, informed by seasonal and interannual climate diagnostics, to enhance resilience in a region exposed to hydroclimatic extremes. The findings advance the understanding of Djibouti’s rainfall dynamics, providing a robust foundation for improved forecasting, resource management, and climate adaptation. Elucidating both climatological patterns and mechanistic drivers, this research offers actionable guidance for policymakers, practitioners, and the scientific community, ensuring that climate resilience initiatives are grounded in a comprehensive understanding of local and regional hydroclimatic processes.
Electronic Supplementary Material
Below is the link to the electronic supplementary material
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Author Contribution
Authors’ contributions: Tadesse Terefe Zeleke, Omar Assowe Dabar, Jemal S. Ahmed, and Dejene K. Mengistu drafted the main manuscript text. Sintayehu Alemayehu, Sintayehu W. Dejene, and Asaminew Teshome contributed to the study conceptualization and prepared Figure 1. Degefie Tibebe, Moussa Mahdi Ahmed, Aniruddha Ghosh, Pedro A. Chilambe, Evan Girvetz, and Julian Ramirez-Villegas contributed to the methodological development and overall conceptual framework. All authors critically reviewed and approved the final version of the manuscript.
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Data Availability
In the Data source section of the methodology of the draft paper, it clearly indicated and acknowledged all data sources.
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