Abstract

This study examines historical precipitation data from Lesotho, covering the period from 1901 to 2021, sourced from the Climatic Research Unit (CRU) at the University of East Anglia (UEA). The main objective is to evaluate stationarity and identify trends in the precipitation data to better understand long-term patterns and their implications for climate resilience.

To assess stationarity, the study applies the Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) Unit Root tests, which test for the presence of a unit root that suggests non-stationarity. Complementary to these, the Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test is used, which tests the null hypothesis of stationarity, providing a balanced perspective on the data’s stability.

Trend analysis is conducted using the Mann-Kendall test and Sen’s slope estimator. The Mann-Kendall test detects monotonic trends over time, while Sen’s slope quantifies the magnitude and direction of these trends. These methods together offer a robust analysis of temporal changes in precipitation.

Autocorrelation analysis is performed to identify any temporal dependencies and periodicities in the data, which are essential for understanding underlying correlation structures. Additionally, distributional properties are examined using the Jarque-Bera and Shapiro-Wilk tests to check for normality, ensuring the suitability of statistical modeling.

The results will enhance climate prediction capabilities, improve risk assessment for extreme weather events, and support effective water resource management. By providing a detailed understanding of historical precipitation trends and stationarity, this study contributes valuable insights for developing climate resilience and adaptation strategies in Lesotho. These insights are crucial for policymakers and stakeholders involved in climate adaptation planning and resource management.