Microclimatic Temperature Variability and Trends in Bengkulu Province: ANOVA and Regression-Based Analysis

Siti Hairunnisa Norfahmi; Rida Samdara; Supiyati Supiyati; Wina Ayu Lestari

doi:10.37905/jjom.v7i2.33376

Microclimatic Temperature Variability and Trends in Bengkulu Province: ANOVA and Regression-Based Analysis

Siti Hairunnisa Norfahmi, Rida Samdara, Supiyati Supiyati, Wina Ayu Lestari

Abstract

This study investigates the microclimatic variability and trends of air temperature across three meteorological stations—Fatmawati, Bengkulu, and Kepahiang—in Bengkulu Province, Indonesia. Using five years of daily data (June 2020 to May 2025), minimum (Tmin), maximum (Tmax), and average (Tavg) temperatures were analyzed to understand both spatial patterns and temporal changes in surface air temperature. One-way ANOVA was conducted to assess whether mean temperatures differed significantly across stations, followed by Tukey post hoc test for pairwise comparisons. The analysis revealed a consistent and statistically significant difference in all temperature variables (p < 0.05), particularly between the inland highland station (Kepahiang) and the two coastal stations. In addition, monthly averages of Tavg were analyzed using simple linear regression, with significance tested via regression-based ANOVA. All three stations exhibited statistically significant warming trends (p < 0.005), with slopes ranging from +0.0152 to +0.0213 °C/month (~0.18–0.26 °C/year), despite relatively modest coefficients of determination (R² = 0.14–0.24). These results highlight a dual climatic dynamic in the region: strong seasonal and spatial variability, overlaid with emerging baseline warming. The study underscores the importance of localized climate analysis for adaptation planning, particularly in topographically diverse tropical regions facing increased exposure to climate variability and change.

Keywords

Microclimate; Temperature Trends; ANOVA; Regression

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DOI: https://doi.org/10.37905/jjom.v7i2.33376