ارزیابی مدل‌ها و سناریوهای گزارش پنجم تغییراقلیم در برآورد دما و بارش ایستگاه بیرجند

افزایش میزان غلظت گازهای گلخانه ای می تواند منجر به گرم شدن جهانی شود و این امر آب و هوا را تحت تاثیر قرار داده و  منجر به وقوع پدیده تغییراقلیم شود. در این تحقیق سعی شد روند تغییرات بارش، دمای کمینه و دمای بیشینه ایستگاه سینوپتیک بیرجند در طی دوره های زمانی مختلف از سال 2010 تا سال 2100 میلادی با استفاده از داده های گزارش پنجم تغییراقلیم مورد بررسی قرار گیرد. مدل های csiromk3.6،  gfdlesm2m، gisse2r، ipslcm5amr و mirocesm به همراه سناریوهای انتشار rcp2.6, rcp4.5, rcp6, rcp8.5ارزیابی تغییرات بارش، دمای کمینه و دمای بیشینه را در دوره زمانی های مختلف آینده نسبت به دوره زمانی پایه برای ایستگاه سینوپتیک بیرجند انجام دادند. برای اطمینان از نتایج مدل ها، ابتدا مقایسه ای بین داده های متغییرهای هواشناسی حاصل از مدل ها با ایستگاه سینوپتیک در دوره زمانی پایه انجام شد. نتایج تحقیق مشخص کرد مدل های gfdlesm2m و gisse2r از دقت بیشتری در برآورد متغییرهای هواشناسی در دوره زمانی پایه و آتی برخوردارند. همچنین روند تغییرات بارش از سال 2010 تا 2100 میلادی برای مدل ها و سناریوهای مختلف متغییر خواهد بود. با این وجود، مدل های gfdlesm2m و mirocesm در بین مدل ها و سناریو rcp8.5 در بین سناریوها کاهش بارش بیشتری را برآورد می کنند. از مقایسه سناریوها در همه مدل ها نیز مشخص شد که دمای بیشینه در سناریو rcp8.5و rcp2.6 به ترتیب بیشترین و کمترین افزایش را در طی دوره های آتی خواهد داشت. همچنین این تحقیق مشخص کرد مدل های مختلف gcm و سناریوهای انتشار برآورد متفاوتی از متغییرهای هواشناسی خواهند داشت و باید در انتخاب مدل و سناریو برای هر منطقه دقت بیشتری انجام داد.

Evaluation models and scenarios of the climate change Fifth Report in estimation temperature and precipitation of Birjand Station

Introduction According to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, the atmospheric concentrations of the greenhouse gases, i.e., carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), have increased to unprecedented levels in the last 800 000 years. An increase in the levels of GHGs (greenhouse gases) can lead to greater warming, which, in turn, can influence the world’s climate that leading to the phenomenon climate change. It is predicted that climate change induced weather extremes, extreme heat, severe drought and heavy precipitation that will have significant impacts on agriculture. In support of the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), the fifth phase of the Coupled Model Intercomparison Project 5 (CMIP5) provides a new suite of coordinated climate model experiments focusing on major gaps in understanding of historical and future climate changes. Most of the present day CMIP5 models show good performances in reproducing the present climatology, climate variability and climate extremes. In this research, the trend of rainfall changes, minimum temperature and maximum temperature of the synoptic station of Birjand during the decades and different periods from 2010 to 2100 years was studied using the data of CMIP5. Materials and Methods This research was conducted to determine climate changes  condition in Birjand Synoptic Station located at longitude between 59˚ 7’ N and latitude between 32˚ 52’E, Iran. AR5 Global Climate Models of CSIROMK3.6, GFDLESM2M, GISSE2R, IPSLCM5AMR and MIROCESM with RCP2.6, RCP4.5, RCP6 and RCP8.5 Emission scenarios performed precipitation, minimum temperature and maximum temperature in the coming decades for the Birjand Synoptic Station.  Also, the process of changes in meteorological variables in the two form of decadesdecades from 2010 to 2100 and between the next three periods of 20402010, 20702070, and 20702100 were taken. The changes in meteorological variables of the future periods were investigated to the base period (19702000) of station. Results and Discussion The results of the study indicated that GFDLESM2M and GISSE2R models have a more accurate estimation of meteorological variables over the base and future time periods. Also The trend of precipitation from 2010 to 2100 year for various models and scenarios in different decades. However, the GFDLESM2M and MIROCESM models estimate a further decrease in rainfall between models and RCP8.5 among scenarios. Also Comparison of scenarios in all models showed that the maximum temperature in the RCP8.5 and RCP2.6 respectively with the highest and the least increase in the coming years. This increase in temperature for the scenario is RCP8.5 and the two MIROCESM and IPSLCM5AMR models will be more than 6 degrees Celsius in 2100 year in compared to 2010 year. The maximum and minimum temperatures Changes unlike precipitation are steadily increasing  and except in the near future  period (20402010), in the next two periods, the models estimate the trend of temperature rise in the future relative to the base period. The MIROCESM and IPSLCM5AMR models and the MIROCESM and GFDLESM2M models estimate the highest maximum temperature and minimum temperature increase in the future compared to the base period. In Comparing periods, the far future (20702100) and midterm (20402070) period estimated a higher increase in temperature and precipitation, respectively. The GISSE2R model estimates the minimum maximum and maximum temperature rise for the three periods. Conclusions The research has determined that models are uncertain in the estimation of weather variables, which makes it difficult to select the appropriate model for use in research. Changes in scenarios are also different and the 8.5 scenario estimates higherrisk conditions that including higher temperature increases and further reductions for the future. Also, in comparison to periods, highest rainfall and temperature increase was estimated in the 2055 period and 2085 period respectively. The use of climate change Fifth Report data and the study of variations in meteorological variables over the next three periods can determinate what will happen in the future in accordance with the climate change scenarios. Also, the results of this research can be helpful in considering future weather variables in planning for management of different sectors of agriculture, water resources and environment in the future.