Arid and semi-arid regions, including northeastern Iran, are highly vulnerable to climate change due to limited water resources and strong dependence on agricultural activities. Therefore, a rigorous assessment of hydroclimatic trends and their linkage to global drivers such as rising atmospheric CO₂ concentrations is essential for developing effective adaptation strategies and sustainable resource management. This study aims to analyze temperature and precipitation trends and to investigate their relationship with global CO₂ concentrations over a 30-year period (1995–2024) in northeastern Iran.
Monthly, seasonal, and annual data from 16 synoptic meteorological stations were analyzed. Trend detection was conducted using the non-parametric Mann–Kendall test, Sen’s slope estimator, and linear regression analysis, while paired t-tests were applied for comparative assessment. Homogeneity of time series was evaluated using Pettitt, SNHT, and Buishand tests. Spatial patterns of trends were mapped using the Inverse Distance Weighting (IDW) interpolation method in ArcGIS. Additionally, hierarchical cluster analysis based on four climatic variables was performed to identify distinct regional climate regimes.
Results indicate that 15 out of 16 stations (93.75%) exhibit a statistically significant warming trend at the 0.05 significance level. The highest warming rates were observed at Qaen, Tabas, Torbat-e Jam, and Sarakhs stations, whereas Quchan was the only station showing a non-significant cooling trend. Annual precipitation demonstrated a predominantly decreasing pattern, with statistically significant declines at selected stations. A positive and significant relationship was identified between regional temperature and global CO₂ concentrations. Cluster analysis classified the stations into three distinct climatic groups. The integrated analytical framework applied in this study provides a robust basis for identifying vulnerable areas and supporting climate adaptation planning in northeastern Iran.