Long-term Climate Change Trends: 43-Year Analysis of Climatic Data in Gangotri National Park, Western Himalaya

Understanding long-term climatic patterns is essential for assessing climate change impacts and informing adaptation strategies. This study aims to examine the temporal variations in climate from 1981 to 2023 in Gangotri National Park, Western Himalaya. Using NASA’s Modern-Era Retrospective analysis for Research and Applications (MERRA-2), we analysed daily, monthly, and annual agroclimatology data for maximum (T _max ) and minimum (T _min ) temperatures (°C), corrected precipitation (mm/day), and relative humidity (RH, %) at 2 meters. The datasets were processed using R statistical software (version 4.4.1), and seasonal trends were evaluated with linear regression models to quantify the rate of change and statistical significance (p < 0.05). The analysis revealed that T _max significantly decreased during the monsoon season, with an average decline of 0.01°C per year (p < 0.005), while T _min increased during both the monsoon and post-monsoon seasons by 0.04°C per year and by 0.02°C per year in summer (p < 0.05). Precipitation trends indicated a substantial rise during the monsoon (0.057 mm per year) and winter (0.016 mm per year), indicating more intense rainfall. RH also increased across all seasons, with the higher rises in summer (0.31% per year) and post-monsoon (0.30% per year). These findings suggest that the observed shifts in these parameters may have a substantial influence on park's distinctive ecosystems. Validation using HOBO fine-scale microclimate loggers confirmed consistent seasonal trends between observational data and NASA POWER estimates, with no significant differences in trendlines (p > 0.05), demonstrating the reliability of NASA POWER for long-term climate studies in this region.