Abstract
Solar radiation is a crucial indicator of solar energy potential, agricultural productivity, hydrological cycles, and precipitation patterns. This study employed three traditional approaches (Linear Regression Analysis (LRA), Mann-Kendall (MK)/Modified Mann-Kendall (MMK) tests, and Spearman Rank Correlation (SRC)) alongside Innovative Trend Analysis (ITA), to detect seasonal and annual solar radiation trends across 15 stations in Bangladesh during 1983-2022. ITA revealed the highest annual increasing trend at Sitakunda (34.56 MJ/year) and the highest decreasing trend at Dhaka (-27.89 MJ/year). While traditional methods identified 61 significant (p < 0.05) trends, ITA surpassed them by detecting 70 significant (p < 0.05) trends out of 75 data series. Notably, nearly all significant trends identified by traditional methods were also captured by ITA (58 data series), demonstrating its effectiveness in uncovering hidden trends. The trends observed at most stations were likely influenced by variations in anthropogenic aerosol loadings and sunshine durations. A comprehensive comparison of ITA, LRA, SRC, and MK/MMK tests highlights their distinct advantages. The outcomes of this study are significant for advancing solar energy technologies, mitigating climate change impacts, and enhancing agricultural productivity. Moreover, they offer valuable insights for managing hydrological cycles and water resources, aiding policymakers and practitioners in developing sustainable strategies.
Published Version
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