تعیین روند زمانی و مکانی و نقطه تغییر بارش و دمای بیشینه تهران

ABSTRACT
This study aimed to analyze trends and assess the homogeneity of maximum temperature and precipitation during the cold seasons (autumn and winter) at four synoptic stations in Tehran over the period 1994–2023.The non-parametric Mann–Kendall test was employed to detect trends, and the Sen’s slope estimator was used to quantify the annual rate of change. To evaluate temporal homogeneity and identify potential structural shifts in the time series, four statistical tests—Pettitt, SNHT, Buishand, and Von Neumann—were applied. The results indicated that maximum temperature in both seasons exhibited a statistically significant increasing trend at most stations. In particular, in stations such as Shemiran and Geophysics, the average post-change temperature rose by more than 2°C. In contrast, autumn precipitation showed no significant trend, while winter precipitation at Mehrabad and Chitgar stations experienced a notable decreasing trend. The homogeneity tests also confirmed the occurrence of structural breaks in temperature data and, in some cases, in winter precipitation series. These findings reflect a clear pattern of seasonal warming, climate variability, and a relative decline in winter water resources in Tehran—issues that may have important implications for urban management, water resource planning, and climate adaptation strategies in the near future.
Extended Abstract
Introduction
In recent decades, climate change has become one of the major challenges for urban management in megacities such as Tehran. Rising temperatures, declining precipitation, temporal fluctuations in climatic patterns, and the expansion of urban heat islands are among the visible consequences of climate change at the urban scale. Tehran, because of its high population density, unique geographical location, and rapid physical development, is highly vulnerable to climatic variations. Particularly in the cold seasons, fluctuations in temperature and precipitation can significantly impact water resources, energy consumption, and service infrastructure.
Despite numerous global studies and some national research efforts, a precise and integrated examination of trends and homogeneity in Tehran’s climatic variables (especially at the seasonal scale) has received limited attention. Furthermore, analyzing trends and the statistical structure of these data can play a critical role in climate policy-making, drought management, and water resource planning.
This study aims to analyze trends and assess the homogeneity of maximum temperature and precipitation during the cold seasons (autumn and winter) at four synoptic stations in Tehran from 1994 to 2023. The main focus is to identify statistically significant trends and structural breakpoints in the time series of climatic variables to better understand the behavior of Tehran’s urban climate in recent decades.
Accordingly, the research addresses the following questions: Is there a statistically significant trend in maximum temperature and precipitation during autumn and winter in Tehran?Are the time series of these variables homogeneous, or have they experienced structural breaks over time? Which stations have undergone the most significant statistical changes, and what are the implications of these changes for Tehran’s climate management?
 
Methodology
This study employs an applied, quantitative, and analytical approach, utilizing daily maximum temperature and precipitation data from four synoptic stations Geophysics, Shemiran, Mehrabad, and Chitgar in Tehran. The data were collected for the autumn and winter seasons over a 30-year period (1994–2023). Following rigorous quality control procedures and removal of missing or erroneous data, the datasets were organized into seasonal time series. To analyze trends, the non-parametric Mann-Kendall test was applied, a widely accepted and robust method for detecting monotonic trends in climatic time series. Additionally, Sen’s slope estimator was used to quantify the annual rate of change, providing a reliable measure of trend magnitude.
To assess homogeneity and detect structural breaks in the time series, four statistical tests were employed: Pettitt, Standard Normal Homogeneity Test (SNHT), Buishand, and Von Neumann tests. Pettitt and Von Neumann tests are non-parametric tests capable of identifying sudden changes and non-random structures without requiring assumptions of normality. Conversely, SNHT and Buishand tests assume normality and are designed to detect shifts in the mean and variance. These methods were applied separately for each variable, season, and station.
 
Results and discussion
Statistical analysis of maximum temperature and precipitation in the cold seasons at synoptic stations in Tehran revealed significant climatic changes. In autumn, the Mann-Kendall test indicated a statistically significant increasing trend in maximum temperature at most stations, with Shemiran showing the highest Kendall’s tau (0.49) and Mehrabad the lowest (0.25). Sen’s slope ranged from 0.04 to 0.09 °C per year. During winter, all stations exhibited significant positive trends, with p-values mostly below 0.01, confirming high confidence in these trends.
Homogeneity tests, including Pettitt, SNHT, Buishand, and Von Neumann, detected structural breaks in maximum temperature data at Shemiran, Geophysics, and Chitgar. For instance, Shemiran’s mean temperature increased by 1.62 °C after the autumn breakpoint, and from 8.7 to 11.2 °C in winter, indicating a pronounced climatic shift in the 2000s (1380s SH). These increasing trends, particularly at Shemiran and Geophysics, are consistent with global warming patterns and are likely influenced by urbanization, enhanced heat islands, and changing energy consumption.
Regarding precipitation, autumn trends were largely non-significant, while winter precipitation decreased significantly at Chitgar and Mehrabad, with Sen’s slopes of -2.27 and -1.85 mm/year and negative Kendall’s tau values (-0.29 and -0.28). Chitgar also showed the highest winter precipitation inhomogeneity, with all tests confirming structural breaks (p < 0.05), potentially affecting snow storage, runoff, and water resources during dry periods.
These findings align with previous studies in Iran, including Bazgir et al. (2019) and Alipour & Malkian (2019), which reported inhomogeneity in temperature and precipitation. Overall, the simultaneous occurrence of increasing temperature trends, structural breaks, and declining winter precipitation demonstrates that Tehran is experiencing significant climate-related changes consistent with global trends.
 
Conclusion
This study analyzed trends and homogeneity of maximum temperature and precipitation during autumn and winter at four synoptic stations in Tehran from 1994 to 2023, identifying seasonal climate changes and structural breakpoints. Maximum temperatures showed significant increasing trends at most stations, particularly Shemiran and Geophysics, with winter averages rising over 2 °C after breakpoints. Homogeneity tests (Pettitt, SNHT, Buishand, Von Neumann) confirmed structural changes mainly in the 2000s. Autumn precipitation remained stable, while winter rainfall decreased significantly at Mehrabad and Chitgar. Given fixed station locations, uncertainty mainly arises from natural interannual variability. Overall, findings indicate warming during cold months, reduced winter precipitation, and structural changes, with implications for water, energy, public health, and urban resilience.
Funding
There is no funding support.
 
Authors’ Contribution
All of the authors approved thecontent of the manuscript and agreed on all aspects of the work.
 
Conflict of Interest
Authors declared no conflict of interest.
 
Acknowledgments
We are grateful to all the scientific consultants of this paper.