preprint
An analysis of decadal climate data from Dar es Salaam spanning January 2014 to October 2024 reveals subtle but statistically significant shifts in seasonal patterns. Using meteorological records and non-parametric statistical tests across five distinct seasons, the study assessed trends in rainfall, temperature, and relative humidity. The results show unexpected shifts that contrast with conventional expectations for coastal weather patterns. Rainfall slightly increased during the long dry season, accompanied by a decline in daytime temperatures during the same period. Additionally, nighttime temperatures during the short dry season demonstrated a measurable decrease. In contrast, relative humidity showed only minor and statistically insignificant fluctuations across the entire decade. While the absolute scale of these changes remains small, their statistical consistency suggests early-stage climatic shifts that could influence the coastal city over longer periods.
Coastal cities face compounding challenges from climate variability, including urban flooding and changing heat patterns. By identifying measurable, counter-intuitive shifts such as increased rain and cooling during traditionally dry periods, this analysis provides an evidence base to inform adaptive infrastructure strategies and long-term urban planning.
This work represents early-stage baseline research without a direct commercial product. The data and insights could eventually inform urban planners, climate adaptation consultants, and civil engineering organisations designing local flood and thermal management strategies, though the abstract does not indicate an immediate commercialisation pathway.
AI-generated from the published abstract. Always read the original work before citing.
Background: Coastal cities like Dar es Salaam face an increasing vulnerability to the adverse impacts of climate variability, including urban flooding, heat stress, and altered water availability. Examining the temporal evolution of key climatic variables is critical to informing adaptive strategies and promoting sustainable urban development. Methods: Decadal seasonal trends in rainfall, daytime and nighttime temperatures, and relative humidity were analyzed using monthly data from January 2014 to October 2024, sourced from the Tanzania Meteorological Authority. We applied the non-parametric Mann-Kendall trend test and Sen’s slope estimator to detect and quantify monotonic trends across five defined seasons. Results: We observed statistically significant trends across several seasons. Rainfall during the long dry season (JJA) had a slight increase, with a Sen’s slope of +0.39097 mm/year and a p-value of 0.00457, suggesting a slight deviation from typical seasonal dryness. Daytime temperatures during JJA declined (Sen’s slope = –0.03675°C/year; p = 0.00121), and nighttime temperatures during the short dry season (JF) also showed a significant decrease (Sen’s slope = –0.04000°C/year; p = 0.04445). Relative humidity demonstrated only minor, statistically insignificant fluctuations across all seasons, with the highest z-value recorded in OND. Conclusion: The findings highlight shifting climatic patterns in Dar es Salaam that diverge from conventional expectations, including increased precipitation during dry periods and seasonal cooling. Although the detected trends are modest in absolute magnitude, their statistical significance is noteworthy because consistent directional changes, however small, accumulate over time and may signal early-stage climatic shifts that warrant monitoring.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.31223/x5qf25
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
