Document Type : Research Paper

Authors

• Reza Norooz-Valashedi ¹
• Sedigheh Bararkhanpour ahmadi ²
• hadigheh bahrami pichaghchi ²
• Sara Mazloom Babanari ²

¹ Assistant Professor of Agrometeorology, Department of Water Engineering, Sari Agricultural Sciences and Natural Resources University, Sari, Iran

² PhD Student of Agrometeorology, Department of Water Engineering, Sari Agricultural Sciences and Natural Resources University, Sari, Iran

Abstract

Introduction
Climate is one of the environmental factors whose changes cause extensive alterations in different parts of the ecosystem and pose a significant threat to sustainable development. Temperature, a main element of climate, can affect the climate structure of any region through sudden, short-term, and long-term changes. In recent decades, the Earth has faced global warming, evidenced by climatic changes worldwide. One important consequence of global warming is the increase in extreme weather phenomena, such as sudden temperature changes, excessive heat, abnormal cold, heavy rains and floods, drought, and dust storms caused by the drying of wetlands. Climate extreme indices not only play an important role in investigating climate events on regional and global scales but also assist in climate modeling and decision-making for various sectors.
 
Materials and methods
In this research, temperature data from the MRI-ESM-2 model under three scenarios—optimistic (SSP1-2.6), average (SSP2-4.5), and pessimistic (SSP5-8.5)—for two periods, the near future (2021-2060) and the distant future (2061-2100), were used. First, historical data for the base period and scenario data for the future period (until 2100) for the studied climate model were obtained from the ESGF database. Then, using the R programming language, the time series of historical data and scenarios were extracted from the model for each desired station, and the statistical downscaling of the data was performed using the bilinear interpolation method at the level of the studied stations. The data were grouped based on the three scenarios in all studied stations, and RClimDex software was used to extract indices based on minimum and maximum daily temperatures. In this research, 16 extreme temperature indices for the studied area were calculated on annual and monthly scales, and trends and breakpoints in these indices were investigated using the Mann-Kendall trend detection test, Sen’s Slope test, and Pettitt mutation detection test.
 
Results and discussion
The results show a decrease in extreme hot events based on the SSP1-2.6 scenario, a decrease in indices related to cold and freezing days, and an increase in extreme warm indices based on the SSP5-8.5 scenario, observed in most areas of the province. Generally, the indices for the number of summer days (with a slope of 40-70%), tropical nights (45-65%), the length of the heat period (30-50%), and the length of the growing season (40-60%) showed significant increases. Conversely, the indices for the number of frost days (-20 to -80), ice days (-10 to -40), and the length of the cold period (-10 to -70) significantly decreased. The results of Pettitt's test indicated change points for increasing and decreasing trends in hot and cold extreme indices, respectively, in the 2040s (near future) and 2080s (far future). Therefore, to control extreme temperatures and their adverse effects on various aspects of human life, especially agriculture and water resources, strategies should be developed and implemented according to the needs of each region.
 
Conclusions
The results indicated more frequent sudden changes in temperature indices under the pessimistic scenario compared to the other two scenarios, affecting broader areas of Mazandaran province. There is a likelihood of sudden increases in hot extreme indices and decreases in cold and freezing days both in the near future (2030s, 2040s, and 2050s) and far future (2070s and 2080s). Overall, significant changes in temperature extreme indices were observed during the future statistical periods studied, with Mazandaran province expected to experience higher air temperatures and more frequent extreme heat events. These findings align with regional and global studies. The rise in temperature, particularly during hot months when precipitation decreases naturally, significantly impacts agriculture in this region, which is a major area for rice production in the country. These changes also affect the hydrological cycle downstream of the Haraz basin. Additionally, temperature fluctuations during winter and cold months can influence the timing of snow melting in the basin, thereby affecting peak flood flows downstream. Given these factors and the necessity of such research in understanding human activities, water resource management, food security, and human health, it is crucial to investigate the impacts of extreme climate events driven by temperature in future policy-making. Human societies must adapt and adjust based on these anticipated conditions. Therefore, studying the intensity, frequency, and timing of extreme events and raising awareness about them can effectively address environmental challenges and enable rational planning to mitigate and reduce these events.
 

Keywords

• Climate Change
• Drainage Basin
• Downscaling
• Growing Season
• Spatio-Temporal