Statistical analysis of the relationship between rainfall and temperature in Gothalapani, Baitadi

Abstract

This study delves into the intricate relationship between temperature and rainfall in Gothalapani, a climatically diverse region in Baitadi, Nepal. Utilizing three years of monthly meteorological data (2022–2024) provided by the Department of Hydrology and Meteorology, we employed a comprehensive suite of statistical techniques, including descriptive statistics, correlation analysis (Pearson, Kendall, and Spearman), and copula-based modelling to capture both linear and non-linear dependencies. Results consistently show a moderate to strong positive correlation between rainfall and temperature, with higher rainfall occurring during warmer months, especially during monsoon periods. Notably, Gaussian copula analysis confirmed this dependence structure, demonstrating the utility of copulas for capturing non-linear climatic dependencies. The insights presented in this work hold practical significance for regional climate adaptation, sustainable agriculture, and water resource planning. Importantly, the limited 3-year dataset constrains our ability to infer long-term climatic trends, which is acknowledged as a key limitation.