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<p>This study employs spatial econometric techniques, specifically the Spatial Autoregressive Model (SAR), to analyze rainfall variability in Somalia over a 120-year period (1901–2021) using high-resolution gridded precipitation data from the Climate Research Unit Time-Series (CRU TS) dataset. The analysis reveals significant temporal and spatial patterns, with annual rainfall ranging from 150&#xa0;mm to 400&#xa0;mm (coefficient of variation ranging from 5% in the 2000s to 32% in the 1950s) and no clear linear trend but marked interannual variability. Decadal analysis highlights extreme fluctuations, including the lowest mean rainfall of 213.22&#xa0;mm in the 1940s and the highest of 315.51&#xa0;mm in the 1960s, representing a 48% difference between wettest and driest decades, followed by a trend toward more stable patterns in recent decades, with variance decreasing to 193.80 in the 2000s and 411.37 in the 2020s. Spatial analysis demonstrates strong spatial autocorrelation, with Moran’s I values ranging from 0.29 to 0.35 across different spatial weight specifications, indicating statistically significant clustering at <i>p</i> &lt; 0.001. The SAR model outperformed traditional OLS regression, with distance-based spatial weights achieving the highest explanatory power (R² = 0.45), followed by K-Nearest Neighbors (R² = 0.42) and contiguity-based weights (R² = 0.40), representing a 12.5% improvement over OLS baseline (R² = 0.40). Temperature analysis revealed a warming trend of 0.004&#xa0;°C per year (<i>p</i> &lt; 0.05), with a weak negative correlation with rainfall (<i>r</i> = -0.15, <i>p</i> &lt; 0.05). These findings underscore the importance of spatial dependencies in understanding rainfall variability and highlight the utility of spatial econometric methods for climatological studies.</p> Graphical Abstract <p>This visualization captures the key findings from our 120-year climate trend analysis in Somalia (1901–2021), showing rainfall variability patterns across time and space. The central map illustrates the strong spatial autocorrelation of precipitation (Moran’s I values: 0.29–0.35), with color gradients indicating rainfall clustering across regions. Time series charts highlight the remarkable decadal fluctuations, particularly the driest period in the 1940s (213.22&#xa0;mm) and wettest in the 1960s (315.51&#xa0;mm), followed by increasingly stable patterns in recent decades. The comparative model performance section demonstrates how our Spatial Autoregressive Model (SAR) outperformed traditional approaches, with distance-based spatial weights achieving R² = 0.45. The correlation plot reveals the weak negative relationship between temperature and rainfall, a critical finding for agricultural planning. This research advances understanding of Somalia’s climate dynamics, providing essential insights for developing regional coordination strategies and flexible approaches to enhance resilience in this climatically vulnerable region.</p> <p></p>

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Climate Rhythms in a Fragile Region: Decoding Somalia’s 120-Year Rainfall Patterns Through Spatial Econometrics

  • 期刊论文

  • 发表日期：

    2025年8月2日

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  • Ahmed Abdiaziz Alasow,
  • Abdifatah Ahmed Hersi,
  • Saralees Nadarajah

摘要

This study employs spatial econometric techniques, specifically the Spatial Autoregressive Model (SAR), to analyze rainfall variability in Somalia over a 120-year period (1901–2021) using high-resolution gridded precipitation data from the Climate Research Unit Time-Series (CRU TS) dataset. The analysis reveals significant temporal and spatial patterns, with annual rainfall ranging from 150 mm to 400 mm (coefficient of variation ranging from 5% in the 2000s to 32% in the 1950s) and no clear linear trend but marked interannual variability. Decadal analysis highlights extreme fluctuations, including the lowest mean rainfall of 213.22 mm in the 1940s and the highest of 315.51 mm in the 1960s, representing a 48% difference between wettest and driest decades, followed by a trend toward more stable patterns in recent decades, with variance decreasing to 193.80 in the 2000s and 411.37 in the 2020s. Spatial analysis demonstrates strong spatial autocorrelation, with Moran’s I values ranging from 0.29 to 0.35 across different spatial weight specifications, indicating statistically significant clustering at p < 0.001. The SAR model outperformed traditional OLS regression, with distance-based spatial weights achieving the highest explanatory power (R² = 0.45), followed by K-Nearest Neighbors (R² = 0.42) and contiguity-based weights (R² = 0.40), representing a 12.5% improvement over OLS baseline (R² = 0.40). Temperature analysis revealed a warming trend of 0.004 °C per year (p < 0.05), with a weak negative correlation with rainfall (r = -0.15, p < 0.05). These findings underscore the importance of spatial dependencies in understanding rainfall variability and highlight the utility of spatial econometric methods for climatological studies.

Graphical Abstract

This visualization captures the key findings from our 120-year climate trend analysis in Somalia (1901–2021), showing rainfall variability patterns across time and space. The central map illustrates the strong spatial autocorrelation of precipitation (Moran’s I values: 0.29–0.35), with color gradients indicating rainfall clustering across regions. Time series charts highlight the remarkable decadal fluctuations, particularly the driest period in the 1940s (213.22 mm) and wettest in the 1960s (315.51 mm), followed by increasingly stable patterns in recent decades. The comparative model performance section demonstrates how our Spatial Autoregressive Model (SAR) outperformed traditional approaches, with distance-based spatial weights achieving R² = 0.45. The correlation plot reveals the weak negative relationship between temperature and rainfall, a critical finding for agricultural planning. This research advances understanding of Somalia’s climate dynamics, providing essential insights for developing regional coordination strategies and flexible approaches to enhance resilience in this climatically vulnerable region.