Document Type : Complete scientific research article
Authors
1
Ph.D Student of Agrometeorology, Water Engineering Department, Sari Agricultural sciences and Natural Resources University, Sari, Iran.
2
Assistant Professor, Water Engineering Department, Sari Agricultural sciences and Natural Resources University, Sari, Iran.
3
Ph.D. Student of Agrometeorology, Water Engineering Department, Sari Agricultural sciences and Natural Resources University, Sari, Iran.
4
Ph.D Student of Biology, Microbiology Department, South Dakota state University, South Dakota, USA.
10.22069/jwsc.2023.21185.3635
Abstract
Abstract
Background and objectives: Global warming cause changes in temperature variables and consequently increase in the occurrence of extreme events like as floods and droughts, result from extreme weather in most cases; Therefore, it is important to study and investigate the future changes of extreme values of meteorological and hydrological parameters, including temperature, more than the average or median value. Therefore, the purpose of this research is to investigate the effects of climate change on the trend of seasonal changes in extreme temperatures (very high and very low values) in coastal stations of Mazandaran province based on CMIP6 models and quantile regression method.
Materials and methods: In this research, in order to investigate the trend of extreme values of temperature in Mazandaran province for the future periods, the output of the sixth generation of climate change models (Coupled Model Intercomparison Project phase 6, CMIP6) was used. For this purpose, minimum and maximum temperature of 4 main synoptic stations of the province, including Babolsar, Qarakhil, Ramsar and Nowshahr, and also the output of the NorESM2-MM climate model from the CMIP6 in near future (2026-2055) and far future (2071-2100) at three optimistic (SSP126), moderate (SSP245) and pessimistic (SSP585) scenarios was used. In order to downscaling climate model data at the studied meteorological stations, various methods in the CMhyd downscaling software were used, and the Temperature data output for the method that had higher accuracy, was selected to analysis of trend. In the next step, the quantile regression method was used to investigate the seasonal trend of temperature extreme values and the results were analyzed.
Results: The results of downscaling using different methods have shown that the Variance Scaling method has the best performance among the available methods in CMhyd. In general, the results show a positive temperature anomaly (annual temperature increase compared to the base period in SSP126=1.3, SSP245=2.56, SSP585=3.2 oC) in Mazandaran province in all months of the year until the end of the 21st century. The intensity of the anomalies is higher in the warm months than in the cold ones. Under the optimistic scenario, the extreme values of the temperature variables in the spring and autumn seasons will decrease by a maximum of 1 degree per decade in the distant future. However, the average minimum temperature is increasing in all scenarios (including the optimistic scenario) and the decrease is only predicted for extreme values. But under the average and pessimistic scenarios, there will be an increase in the temperature extreme values in all seasons, so that its intensity will be greater for the pessimistic scenario and in the spring season (0.15 oC per year).
Conclusion: According to the results, it concluded that the significant increase in extreme temperature during the day and night, especially in the warm months of the year, will increase evapotranspiration, and along with the decrease in rainfall in the hot months, it will cause a decrease in water resources in different parts of Mazandaran province and pressure on the groundwater. Therefore, it is very important to formulate and implement appropriate management programs according to the needs of each region, in order to adapt to extreme temperatures and their adverse consequences.
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