پیش‌نگری تغییرات دما و بارندگی تحت سناریوهای CMIP6 در استان سیستان و بلوچستان

نوع مقاله : مقالات پژوهشی

نویسندگان

• سمیه میرشکاری ¹
• فاطمه یعقوبی ²
• سید ابوالفضل هاشمی ³

¹ گروه زراعت، پژوهشکده کشاورزی، پژوهشگاه زابل، زابل، ایران

² گروه اگروتکنولوژی، دانشکده کشاورزی، دانشگاه فردوسی مشهد، مشهد، ایران

³ پژوهشکده تالاب بین‌المللی هامون، پژوهشگاه زابل، زابل، ایران

10.22067/jsw.2024.89164.1422

چکیده

تغییر اقلیم به‌دلیل تأثیرات مخرب زیست‌محیطی و اجتماعی-اقتصادی آن به مهم‌ترین چالش در قرن بیست و یکم تبدیل شده‌ است. در این مطالعه، 10 مدل گردش عمومی از ششمین گزارش IPCC جهت پیش‌نگری تغییرات بارندگی و دما در سه منطقه ایرانشهر، زابل و زاهدان در استان سیستان و بلوچستان مورد ارزیابی قرار گرفتند. سپس روش‌های مختلف تصحیح اریبی در CMhyd ارزیابی شدند و با استفاده از روشی که از کارایی بالاتری نسبت به سایر روش‌ها برخوردار بود، بارندگی و دمای حداکثر و حداقل مدل‌های منتخب برای سه دوره زمانی در آینده (2050-2026، 2075-2051 و 2100-2076) تحت دو سناریو SSP2-4.5 و SSP5-8.5 تصحیح گردیدند. داده‌های تصحیح اریبی‌شده مدل‌های منتخب میانگین‌گیری شده و سپس تغییرات آن‌ها در دو مقیاس ماهانه و سالانه در سه دوره آینده نسبت به دوره پایه (2014-1994) موردارزیابی قرار گرفت. نتایج نشان داد که از 10 مدل مورد مطالعه، 8 مدل از کارایی خوبی (R² < 40/0، 02/12 < RMSE < 23/4 درجه‌سانتی‌گراد، 74/0 < NSE < 12/0، 59/9 < MAE < 36/3 درجه‌سانتی‌گراد) در شبیه‌سازی دمای حداقل و حداکثر روزانه برخوردار بودند. بااین‌حال، کارایی تمامی مدل‌ها در شبیه‌سازی‌شده بارندگی روزانه ضعیف بود (R² ˃ 19/0، 70/3 < RMSE < 24/1 میلی‌متر، 57/0- < NSE < 41/7-، 85/0 < MAE < 23/0 میلی‌متر). از بین روش‌های مختلف تصحیح اریبیِ دما و بارندگی موجود در CMhyd، روش نقشه‌برداری توزیع دما و بارشبهترین عملکرد را داشتند و سبب بهبود کارایی خروجی‌های مدل‌های اقلیمی گردیدند. به‌طور میانگین در همه مکان‌ها، دمای حداکثر سالانه در دوره‌های پیش‌بینی‌شده نزدیک، میانه و دور به‌ترتیب 3/1، 1/2، و 8/2 درجه‌سانتی‌گراد تحت SSP2-4.5 و 6/1، 1/3، و 1/5 درجه‌سانتی‌گراد تحت SSP5-8.5 افزایش نشان خواهد داد. درحالی‌که برای دمای حداقل، میزان افزایش 6/1، 6/2، و 4/3 درجه‌سانتی‌گراد برای SSP2-4.5 و 9/1، 9/3، و 3/6 درجه‌سانتی‌گراد برای SSP5-8.5 خواهد بود. بارندگی سالانه در تمامی مکان‌ها بین 22/58- تا 33/49 درصد نسبت به دوره پایه تحت سناریوی SSP5-8.5 به‌ترتیب در دوره‌های آینده نزدیک و دور در زابل و ایرانشهر متغیر خواهد بود. افزایش سالانه در میانگین دمای حداکثر و حداقل عمدتاً ناشی از افزایش دمای هوا درماه‌های ژانویه، فوریه، آگوست، سپتامبر، اکتبر، نوامبر و دسامبر خواهد بود. کاهش سالانه بارندگی نیز عمدتاً از کاهش بارندگی درماه‌های ژانویه، فوریه، مارچ، نوامبر و دسامبر و افزایش سالانه بارندگی از افزایش قابل‌توجه بارندگی در ماه‌های می و اکتبر نسبت به دوره پایه ناشی خواهد شد. نتایج مطالعه حاضر می‌تواند به بهبود درک ما از اثرات تغییر اقلیم بر منطقه موردمطالعه کمک کند و برنامه‌ریزان و ذینفعان را تشویق کند تا راهبردهای بهینه برای کاهش اثرات منفیِ آن را شناسایی کنند.

کلیدواژه‌ها

• تصحیح اریبی
• تغییر اقلیم
• دمای حداقل
• دمای حداکثر
• CMhyd

موضوعات

• هواشناسی کشاورزی

عنوان مقاله [English]

Projections of Temperature and Precipitation Changes under CMIP6 Scenarios in Sistan-va-Baluchestan Province

نویسندگان [English]

• S. Mirshekari ¹
• F. Yaghoubi ²
• S.A. Hashemi ³

¹ Agriculture Institute, Research Institute of Zabol, Zabol, Iran

² Department of Agrotechnology, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran

³ Hamoun International Wetland Institute, Research Institute of Zabol, Zabol, Iran

چکیده [English]

Introduction
The 21st century is witnessing the increase of climate change as an important challenge due to its destructive environmental and socio-economic effects. Extreme climatic conditions have become frequent and more intense in recent decades as a result of human activities. Iran, as one of the countries in the Middle East with a different climate in each region of the country, has suffered significant adverse effects of climate change. Considering the importance of the climate change, it is important to investigate the changes in climate variables to know the future conditions and make management decisions. In the field of climate research, global climate models are useful tools that are often used to investigate the global climate system, including historical and projected periods. Since the use of the CMIP6 dataset provides improved clarity and accuracy for predicting future climate forecasts, the main objective of the present study is to predict the temperature and precipitation changes in the near, mid, and far future in Sistan-va-Baluchestan province.
 
Materials and Methods
The minimum temperature, maximum temperature, and precipitation data of 10 general circulation models (GCMs) of the 6th IPCC report for the baseline (1990-2014) were downloaded from the Global Climate Research Program database (https://esgf-node.llnl.gov). Then GCMs were including ACCESS-CM2, CMCC-ESM2, CNRM-CM6-1-HR, CNRM-ESM2-1, EC-Earth3-CC, EC-Earth3-Veg-LR, INM-CM4-8, INM-CM5-0, MIROC6, and NorESM2-MM. Four statistical indicators including correlation coefficient (R²), RMSE, Nash-Sutcliffe efficiency (NSE), and mean absolute error (MAE) were used to evaluate the performance of 10 GCMs. Based on the results obtained from the these indicators, the models that had higher performance in predicting the temperature and precipitation data were selected as the best models for forecasting in the future. The ensemble of these models under two SSP2-4.5 and SSP5-8.5 scenarios for the near, middle, and far future (2026-2050, 2051-2075, and 2076-2100) were extracted from the World Climate Research Program database.
CMhyd (Climate Model data for hydrologic modeling) tool was used to bias correction climate data of the selected models. In order to choose the best bias correction method, the R², RMSE, NSE, and MAE were estimated.
After bias correction, the climate data of selected models were ensembled and then the changes in precipitation and maximum and minimum temperature in three future periods compared to the baseline was estimated.
 
Results and Discussion
The results showed that out of 10 GCMs, seven models had good performance (R² > 0.40, 4.23 < RMSE < 12.02°C, 0.12 < NSE < 0.74, and 3.36 < MAE < 9.59°C) in simulating daily minimum and maximum temperature. However, the performance of all models in simulated daily precipitation was poor (R² > 0.19, 1.24 < RMSE < 3.70 mm, -7.41 < NSE < -0.57, and 0.23 < MAE < 0.85 mm).
Among the different bias correction methods of temperature and precipitation available in CMhyd, the distribution mapping method had the best performance.
In all three regions, compared to the baseline, the average annual minimum and maximum temperature under two scenarios will increase in the future periods and precipitation will decrease in most periods and scenarios. These changes will be mainly in the SSP5-8.5 scenario compared to SSP2-4.5 and also in the far future period compared to the middle and near future. Averaged across all locations, annual maximum temperature showed increases in near, middle, and far projected periods of 1.3, 2.1, and 2.8°C under SSP2-4.5 and 1.6, 3.1, and 5.1°C under SSP5-8.5, respectively (Fig. 2), while for minimum temperature, the increases will be of 1.6, 2.6, and 3.4°C for SSP2-4.5 and 1.9, 3.9, and 6.3°C for SSP5-8.5. The range of annual precipitation among all sites was from –58.22 to 49.33% under SSP5-8.5 in the near and far future periods in Zabol and Iranshahr, respectively.
The annual increase in the average maximum and minimum temperature will be mainly due to the increase in air temperature in the months of January, February, August, September, October, November and December. The annual decrease in precipitation will mainly result from the decrease in precipitation in January, February, March, November, and December, and the annual increase in precipitation will result from the significant increase in precipitation in May and October compared to the baseline.
 
Conclusion
The results showed that under different scenarios of climate change, the maximum and minimum temperatures in the near, middle, and far future periods will face an increase compared to the baseline. However, the precipitation changes in the future time periods are not the same as compared to the baseline, and in some periods the precipitation will decrease and in others it will increase. But in general, the decrease in precipitation will be more than its increase. Therefore, it is very important to formulate and implement appropriate management programs for the needs of each region, in order to properly manage water resources and adapt to extreme temperatures and their consequences.

کلیدواژه‌ها [English]

• Bias correction
• Climate change
• CMhyd
• Maximum temperature
• Minimum temperature

©2024 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).

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