@article { author = {Helmi jadid, mahdi and Mousavi bayegi, Mohammad and Sadeghi Namaghi, , Hussein}, title = {Application and Evaluation of Degree-Day Model for Prediction of the Best Time for Control and Spraying codling moth (Cydia pomonella). Case Study: Chenaranِ}, journal = {Journal of Climate Research}, volume = {1400}, number = {45}, pages = {1-14}, year = {2021}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {The Codling moth Cydia pomonella (L.) (Lepidoptera Tortricidae) is a pest of worldwide importance that exhibits seasonal phenology that is mainly affected by temperature. This pest is the most important pest in Iranian apple orchards. In order to avoid the unnecessary usage of chemical pesticides, using pheromone traps and degree- day Model is the most effective control way. The pest phenological stages and the best time of spraying can be predicted with the degree- day model and Pheromone Traps. The purpose of this study is determine the best time of spraying Codling moth to Reduce Damage and Environmental Protection. Materials and Methods: The pheromone traps and temperature Data Logger were planted in a orchard To determine the best time of spraying Codling moth in Chenaran. sex pheromone traps were planted in the garden and The number of trapped males was recorded every five days. The history of the first males trapped in pheromone traps was considered biofix. Degree-days were calculated and recorded using mean daily temperature and base temperature. temperature datalogger was installed to record the temperature in the orchard. To calculate the base temperature, number of Codling moth eggs kept at different temperatures. The growth rate was calculated at this stage of pest life After determining the number of days needed for egg hatching. The temperature at which the growth rate becomes zero was considered as the base temperature. after Flying Peaks, Thirty Codling moth eggs were sampled and The spraying was done when fifteen eggs were hatched. There were three experimental treatments in the orchard. A: The first treatment was spraying on the proposed degree- day model and pheromone traps. B: The second treatment was spraying according to the farmer's opinion. C: Third treatment The spraying was not done. The degree- day model was evaluated using the percentage of impact method. In this method the percentage of healthy fruits of treatment A was compared with treatment C and the percentage of healthy fruits of treatment B was compared with treatment C. Results and Discussion: The basal temperature of codling moth was 8.4 ° C. The first males trapped on 25 April 2019 and it was Biofix. Pheromone Traps data showed three flight peaks. This means that there are three generations of Codling moth in the Study Area. In the Last year, Codling moth lay many eggs in different places. These eggs hatch in the New Year at different times. So the population of the first generation of Codling moth was so many. for the first generation, two spraying stages were performed. The first was done at 168 ° C degree- day and second at 343° C degree- day. Spraying was performed for the second generation at 804 degree- day. Spraying was performed for the Third generation at 1505 ° C degree- day. The fourth generation of this pest was incomplete and Spraying was performed for the fourth generation at 2148 ° C degree- day. These spraying were done in treatment A. The results show the best time to counter the pest is in the first generation, 4 to 6 days after flight peak, the second generations 4 to 6 days after flight peak, the third generations 3 to 5 days after flight peak and the Fourth generations 6 to 8 days after flight peak. In treatment B: The farmer sprayed seven times. The spraying dates were selected experimentally. The percentage of effect in treatment A was 78.5% compared to treatment C and The percentage of effect in treatment B was 49.7% compared to treatment C. the number of sprayers decreased in treatment A compared to treatment B and Treatment A was more effective than treatment B. Conclusions: Spraying at the best time in addition to reducing the number of spraying, It also reduces damage to the fruit. The Pheromone Traps and degree-Day Model in this study is expected to be useful for field applications in integrated pest management (IPM) systems, for example, to forecast optimal spray times for available insecticides and application of other control measures. By reducing the use of chemical pesticides Useful enemies will do less damage and the environment will be preserved. In order to avoid the unnecessary usage of chemical pesticides, using pheromone traps and degree- day model are the most effective control way.}, keywords = {Degree-day,Codling moth,Biofix}, title_fa = {کاربرد و ارزیابی مدل درجه- روز برای پیش‌بینی بهترین زمان کنترل و سم‌پاشی کرم سیب (Cydia pomonella). مطالعه موردی: چناران}, abstract_fa = {یکی از کاربردهای هواشناسی ارتباط آن با جامعه گیاهی و آفات در علم کشاورزی  است. فنولوژی کرم سیب به‌عنوان یکی از مهم‌ترین آفات درختان دانه‌دار که هرساله خسارت‌های بسیاری به باغداران وارد می‌کند، وابستگی زیادی به دمای محیط دارد. این تحقیق باهدف استفاده از متغیر دما و ارائه یک مدل درجه- روز برای تعیین بهترین و مؤثرترین زمان سم‌پاشی جهت حداکثر صدمه به لاروهای کرم سیب و درنتیجه کاهش خسارت، افزایش سلامت میوه و حفظ محیط‌زیست اجرا شده است. بدین منظور تله‌های فرمونی از نوع دلتا به همراه دیتالاگر دما در باغ گلابی به مساحت 6 هکتار واقع در روستای صفی‌آباد چناران و در سه تیمار (الف: بدون سم‌پاشی، ب: سم‌پاشی در تاریخ‌های پیشنهادی مدل و ج: سم‌پاشی اختیاری و تجربی توسط کشاورز) در سال 1398 نصب گردیدند. اولین شکار پروانه نر در تله‌ها به‌عنوان تاریخ بیوفیکس و شروع محاسبات درجه-روز در نظر گرفته شد. با شمارش تعداد پروانه‌های به دام افتاده در طول زمان، داده‌های دیتالاگر و نمونه‌برداری از تعداد تخم‌های تفریخ شده، دستورهای سم‌پاشی در تاریخی که بیشترین آسیب به آفت وارد می‌شود ابلاغ و در تیمار مربوطه اجرایی گردید. نتایج نشان‌دهنده سه نسل کامل و یک نسل ناقص کرم سیب در چناران می‌باشد و مدل درجه-روز و داده‌های تله‌ها 5 مورد سم‌پاشی را پیشنهاد کرده است. درصد تأثیر تیمار سم‌پاشی شده در تاریخ‌های پیشنهادی نسبت به تیمار بدون سم‌پاشی 5/78 درصد بود. باوجوداینکه تیمار تجربی کشاورز 2 مرحله بیشتر سم‌پاشی داشته است، درصد تأثیر این تیمار نسبت به تیمار بدون سم‌پاشی 7/49 درصد است. بنابراین سم‌پاشی طبق مدل علاوه بر کاهش تعداد سم‌پاشی‌ها و هزینه‌های کشاورز و خسارت به محیط‌زیست باعث افزایش کارایی و کاهش خسارت برای باغداران نیز خواهد شد.}, keywords_fa = {کرم سیب,درجه-روز,بیوفیکس}, url = {https://clima.irimo.ir/article_132200.html}, eprint = {https://clima.irimo.ir/article_132200_4af5e5cea8127c794df6df1e1be20f14.pdf} } @article { author = {SeyyedNezhad Golkhatmi, Nafiseh and Bazrafshan, Javad and Ghameshlou, Arezo and Irannejad, Parviz}, title = {Analysis of Intera-annual Correlations of Weekly Precipitation with NAO Teleconnection in Iran}, journal = {Journal of Climate Research}, volume = {1400}, number = {45}, pages = {15-24}, year = {2021}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Introduction The North Atlantic Oscillation (NAO) is one of the large climate signals that affect partly climate variabilities in northern hemisphere. Various studies have considered covariation between precipitation in Iran with NAO mainly at monthly timescale. No research has been conducted on a weekly time scale. In this study, the covariate between ERA-Interime gridded precipitation data over Iran and NAO index was investigated. The challenge of this study is implementing correlation alalyses in arid and semi-arid areas of the country, where the frequency of zero precipitation data across the year is high, at weekly timescale.   Materials and methods In the study was used the daily data of precipitation amount obtained from reanalysis ERA-Interim (ECMWF) and the daily data NAO indices obtained from the url http://www.cgd.ucar, both of them related to the cold months of the period of 1979-2016 (November (N), …, April (A); or NDJFMA) were considered. The gridpoints cover 44°E - 64°E and 25° N - 40° N (about geographical area of Iran) with 0.5°* 0.5° spatial resolution. At timescales less than one month, a large number of zero values may appear in precipitation time series, leading bias estimate in correlation coefficient between precipitation and NAO. The present study calculated moving average of the data for smoothing time series and removing the undesirable effect of enormous zeroes in the precipitation time series. Also, Modified Pearson correlation coefficient,, was used to unbias the estimation of traditional Pearson correlation coefficient.  centers nonzero data around their average and works with new time series. Each year, the relationship between precipitation and NAO was calculated in terms of ; therefore, a set of 37 Modified Pearson correlation coefficients corresponding to 37 years of the record period was obtained. Besides, in each year,  was calculated for the lag times of 1-45 weaks. Among the simultaneous and lagged , the significant coefficient that its absolute value was greatest was selected for each year. This allows identifying gridpoints with the significant impact of NAO on precipitation. The minimum, maximum, median and standard deviation of selected   values at each gridpoint were estimated and showed with ,,  and  notations, respectively.   Results and Discussion The results of this study are summarized as follows: s (modified Pearson correlation coefficient) between precipitation and NAO had wide range from negative to positive values across the study area. Based on the probability of precipitation occurring in years it seems that this method can better quantify the effect of the NAO negative phase, NAO-, than NAO+ on year-to-year variability of precipitation. The mapping showed that most regions of Iran have the positive correlation with the NAO index. Also, most parts of Saudi Arabia (east and central parts), the highlands of Afghanistan, the Persian Gulf and Afghanistan have either a positive relationship with the NAO or are more or less affected by the positive phase. But this correlation is negative in large areas to the west and southwest, in small parts in the east, along the Afghanistan-Turkmenistan border, in the south-east of Iran (the Oman Sea coast), the western regions of the Caspian Sea, northern Turkey and Azerbaijan. Given that the areas with negative correlation coefficient (), have bigger precipitation event probability in the NAO-, it seems that they are affected by NAO- more than other areas. Activity of low pressure in the eastern Mediterranean increases during NAO-; therefore, the precipitation over Iran increases. But areas with positive correlation coefficients do not necessarily receive more precipitation in NAO+. The largest values of are in the northwest, east, parallel to the southwest-northeast and the southeast of Alborz Mountains. This index showed that there is more variance of coefficients in these areas.   Conclusion This paper considered the relationship between precipitation and NAO index at weekly timescale. The results showed that the precipitation occurrence in Iran coincides with the negative phase of NAO. The proposed approach for bias correction of Pearson correlation coefficient acted successfully in investigating the effect of NAO on the cold months precipitation over Iran.  }, keywords = {}, title_fa = {تحلیل همبستگی‌های درون‌سالانه بارش هفتگی ‌با دورپیوندNAO در ایران}, abstract_fa = {نوسان اطلس شمالی (NAO) یکی از سیگنال‌های بزرگ مقیاسی است که اقلیم نیمکره شمالی زمین را تحت تاثیر قرار می‌دهد. تحقیقات مختلفی همبستگی بارش‌های ایران را با شاخص‌های NAO در مقیاس‌های ماهانه تا سالانه بررسی کرده­اند. مقیاس‌های زمانی همدید، کمتر از یک ماه هستند که منجر به وجود تعداد زیاد داده صفر در سری زمانی بارش می­شوند. بنابراین، ضریب همبستگی بین بارش و شاخص NAO اریب می­شود. تحقیق حاضر، مقیاس‌ زمانی هفتگی را در نظر گرفته و برای رفع اثر نامطلوب صفرها از ضریب همبستگی متقابل پیرسون پیراسته  استفاده کرده است. بارش روزانه دوره آماری ۱۹۷۹-۲۰۱۶ از پایگاه ERA-Interim (با دقت نیم درجه) و NAO  از درگاه http://www.cgd.ucar دریافت و میانگین متحرک هفتگی داده‌ها برای هموارسازی محاسبه شدند. سپس، همبستگی‌های درون‌سالانه بین بارش شبکه نقاط منظم کشور و شاخص NAO مربوط به شش ماه سرد سال، نوامبر تا آوریل هر سال محاسبه شدند. در نهایت، یک سری زمانی همبستگی‌ها به تعداد سال­های آماری شامل ۳۷ مشاهده به دست آمد. تحلیل سری همبستگی­ها نشان داد که  در هر نقطه شبکه دامنه تغییرات وسیعی از منفی تا مثبت دارد. نتایج نشان داد میانگین این ضرایب تقریبا صفر است اما میانه این ضرایب در بخش‌هایی از غرب و جنوب کشور منفی است. اکثر نقاط کشور دارای ضریب همبستگی مثبت با شاخص NAO هستند. بررسی همبستگی‌های درون‌سالانه جزئیات بیشتری از هم‌تغییری سری زمانی بارش نقاط مختلف کشور با شاخص NAO  فراهم می‌کند.}, keywords_fa = {نوسان اطلس شمالی,بارش,همبستگی,دورپیوند,ایران}, url = {https://clima.irimo.ir/article_132203.html}, eprint = {https://clima.irimo.ir/article_132203_2ab7069f80062508acbc60db15d38c2b.pdf} } @article { author = {Rahmdel, mohsen and Sanaei Nejad, Seyed Hossein and javanshiri, zohreh}, title = {Investigating and documenting the problems of atmospheric data monitoring system in Iran meteorological organization with pathological approach}, journal = {Journal of Climate Research}, volume = {1400}, number = {45}, pages = {25-42}, year = {2021}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {  Introduction: One of the issues in the Meteorological Organization is the lack of documentation of errors in the process of producing, measuring, recording and preparing data in the atmospheric observation system.  Also, the poor data quality, missing  data, inappropriate spatial density  of meteorological stations are the major problems faced by climatology researchers in Iran. Nonstandard distance of stations, inappropriate co-locating of stations, human errors in reading and recording data, errors in measuring equipment, different methods of measurment, Non maintenance and calibration of station, constructions around the stations, changes in the type of instruments and sensors for atmospheric parameters measurement and station relocation during the statistical period are other problems that affect the accuracy of the meteorological data. Materials and Methods: The aim of this study is to investigate and document the problems in the system of monitoring and interpretation of atmospheric data in Iran with a pathological approach. To that end, articles, specialized books, high-end documents such as World Meteorological Organization documents, programs, plans and documents of the Meteorological Organization, guidelines and directives, were reviewed. In addition, field assessments and case studies were conducted using  methods such as preparing a questionnaire and interviewing experts. Results and discussion: The results of the questionnaire and interviews with experts showed: 1-                  Synoptic experts have between 70% to 90 % of the required skills. 2-                  Respondents knew between 70% to 90 % of the standards and guidelines. 3-                  Between 50% to 70% of the standards are adhered in the network of meteorological stations. 4-                  Between 50% to 70 % of the required periodic calibrations on equipment are performed at standard intervals. 5-                  Between 50% to 70 % of the equipment used at the stations are accurate and standard. 6-                  Not calibrating and maintaining  stations  reduce  accuracy of data between  10% to 30%. 7-                  Only 10% to 30% of the stations have complete metadata. 8-                  Upper air facilities supply between 50% to 70% of the meteorological requirements. 9-                  Sanctions have reduced our access to upper air, radar and satellite data between 50% to 70%. 10-              Station automation policy, due to reduced human interference in the data process, if implemented correctly, can increase data accuracy between 30% to 50% on average. 11-              If the station automation policy, is implemented regardless of regular training of experts, periodic calibration on equipment and continious quality control of data, it can reduce data quality and accuracy between 30% to 50%. 12-              The mental condition of the synoptic experts, the working and management issues can affect between 70% to 90% of the observer's performance and data accuracy. 13-              Between 30% to 50% of meteorological station data need to be homogenized. 14-              For estimating temperature and precipitation parameters in non-station locations, using interpolation methods  were found appropriate between 50% to 70%. 15-              Remote sensing methods were found appropriate for estimating temperature and precipitation parameters in non-station location  between 70% to 90%. 16-              Between 30% to 50% of meteorological satellite data are available online to our researchers. 17-              Available meteorological radar facilities only provide 30% to 50% of the  radar data required. 18-              Due to restrictions, only about 50% to 70% of radar’s locating were appropriate. 19-              For about 30% to 50% of radars, studies on evaluating and improving the uncertainty in radar data based on the calibration and correction coefficients were taken . 20-              Allocate appropriate government funding to the Meteorological Organization can reduce over 90% of the problems caused by inadequate access to remote sensing data (such as satellites and radars). The following are some of the major  probems  at the station during field observation. 1- Nonstandard conditions of station and natural climate of the area. 2. Nonstandard methods for observing and adjusting the equipment. 3. Differences in  observing methods. 4- Inaccuracy of the observer. 5. Lack of adequate supervision. 6. Imprecision and inconsistency of data. 7. Lack of support and supply of new meteorological components and equipment. Conclusion: Based on the results of the questionnaire and field observation, the most problems that affect on the accuracy of  data are as follows. 1- Insufficient knowledge and skills of synoptic experts in the data process, lack of complete knowledge the relevant standards and rules, lack of compliance with the standards and established rules, lack of precision in the work process and insufficient supervision of the correct process of work by the authorities. 2. Construction of stations in non-standard conditions, Non maintaining and non calibrating of station over time and finally station relocation during the statistical period. 3. Not performing periodic and regular calibrations of equipment at standard time intervals, using of different types of equipment with different brands in the meteorological stations and imprecision and inconsistent data of these brands with each other at standard level, insufficient infrastructure for automatic calibration. Lack of spare parts and support and software problems with these systems 4. Organizational and managerial issues that can directly affect the motivation, mental condition and performance of the observer and  therefore the accuracy of the data. 5. Sanctions have a significant impact on the provision and support of new meteorological equipment and radars.  As well as, a lack of sufficient financial resources has contributed to the organization's inadequate access to new meteorological instruments and so to this type of data.}, keywords = {Documenting,Observing,monitoring,accuracy,Precision}, title_fa = {بررسی و مستندسازی اشکالات سامانه پایش داده‌های جوی در سازمان هواشناسی ایران با رویکرد آسیب‌شناسی}, abstract_fa = {داده‌های دیده‌بانی شده در ایستگاه‌های هواشناسی زیربنای گستره وسیعی از برنامه‌های اجرایی و مطالعات کاربردی در علوم مختلف می‌باشد و استفاده از این داده‌ها در مطالعات و برنامه‌ریزی‌ها بدون اطمینان از صحت و دقت آن‌ها می‌تواند منجر به نوعی عدم قطعیت در نتایج به‌دست‌آ‌مده شود. یکی از اشکالاتی که در سازمان هواشناسی و سایر ارگان‌های تحقیقاتی مرتبط وجود دارد عدم مستندسازی اشکالات در سامانه دیده‌بانی‌های جوی است. به نحوی که بر اساس مطالعات نگارندگان تا کنون تجربه‌ای از مستندسازی این اشکالات، در منابع داخلی و خارجی مشاهده نشد. بنابراین در این مقاله سعی شده است تا ضمن بررسی مسائل و مشکلات، در سامانه دیده‌بانی و پایش داده‌های جوی سازمان هواشناسی کشور، نسبت به مستندسازی این اشکالات با رویکرد آسیب‌شناسانه اقدام شود. در این پژوهش فرآیند تولید، اندازه‌گیری، ثبت و آماده‌سازی داده‌ها در ایستگاه‌های هواشناسی کشور بررسی شد و ایستگاه‌های هواشناسی استان خراسان رضوی به عنوان نمونه انتخاب و به طور میدانی مورد ارزیابی قرار گرفتند. در این پژوهش ضمن بررسی منابع و اسناد بالادستی سازمان هواشناسی کشور و سازمان جهانی هواشناسی، از روش‌هایی نظیر بررسی‌های میدانی، مطالعات موردی و روش‌هایی نظیر توزیع پرسش‌نامه و مصاحبه با افراد صاحب‌نظر و خبره، برای به دست‌آوردن اطلاعات و مستندسازی اشکالاتی که در این فرآیند وجود داشت استفاده شد. عمده اشکالاتی که صحت داده‌ها را تحت تأثیر قرار داده و می‌تواند سبب بروز عدم قطعیت‌هایی در نتایج به دست‌آمده حاصل از مطالعات شود، را می‌توان در مسائل مربوط به نیروی انسانی، مسائل مرتبط با ایستگاه‌ها، مسائل مربوط به تجهیزات و ادوات ،مسائل مدیریتی، و همچنین مسائل مالی و تحریم‌ها خلاصه نمود.}, keywords_fa = {مستندسازی,دیده‌بانی,پایش,صحت,دقت}, url = {https://clima.irimo.ir/article_132204.html}, eprint = {https://clima.irimo.ir/article_132204_a06c15c4bedda5c67d9fcd267cad2a83.pdf} } @article { author = {yoosefdoost, icen and kHASHEI Siuki, Abbas and mohammadrezapour, Omolbbani and Tabari, Hossein}, title = {Evaluating Performance of Four Statistical Downscaling Models (SDSM) of Precipitation and Temperature Data under the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) Scenarios}, journal = {Journal of Climate Research}, volume = {1400}, number = {45}, pages = {43-66}, year = {2021}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Introduction The investigations show that the increase in greenhouse gasses has led to an increase in the average temperature of the earth’s atmosphere and, consequently the global warming in recent years. Moreover, the rise of greenhouse gasses has also caused changes in other climatic variables such as precipitation. Given the fact that climate change will bring about considerable effects on the water resources, the prediction of the climatic condition and water resources of a region is one of the planning prerequisites for the economic and social development of every country. Therefore, considering the climatic condition and volume of water resources in a country in the future is inevitable. Since the initial effects of climate change are exerted on the meteorological variables of precipitation and temperature, and any change in these variables results in disorder in many hydrological phenomena, it is essential to precisely examine the future changes of these parameters and their simulation methods. Hence, this study was conducted to evaluate the uncertainty of 20 AOGCM models under two emission scenarios of RCP2.6 and RCP8.5 in the two statistical periods (1961-2006) and (2006-2018) in the drainage basin of Karaj River. The changes in the parameters of minimum temperature, maximum temperature, and precipitation in the period of (2020-2040) compared to the baseline period were also investigated. Materials and methods At first, the downscaling of the parameters of minimum temperature, maximum temperature, and precipitation was carried out using the two statistical periods of (1961-2006) and (2006-2018) and the large-scale NCEP variables as the inputs for the models of Artificial Neural Networks (ANN), LARS-WG, SDSM, and Change Factor method to determine the model’s error and evaluate its performance. For this purpose, the features and functions available in the programming environments of MATLAB, LARS-WG, and SDSM5.5.2 were employed after data normalization. The bootstrap confidence interval method and statistical criteria such as coefficient of determination (R2), Nash–Sutcliffe coefficient (NS), percent bias (PBIAS), and PRS were used to evaluate the performance of the models. Due to the suitable range of each one of statistical evaluation coefficients being within the confidence interval defined by the bootstrap method in the period of (1961-2006), the most appropriate climatic models were chosen for this from the selected AOGCM climatic model of the fifth report. In order to improve the accuracy of the chosen models in the period of (2006-2018) under the scenarios of RCP2.6 and RCP8.5, the most appropriate model for each AOGCM scenario was selected using the statistical indexes and bootstrap confidence interval method. In the next step, the chosen models of each climatic scenario were weighted using the MOTP approach for the final evaluation and selection of the model with the lowest uncertainty. Each one of these weights indicates the capability of each model in simulating the variables of minimum temperature, maximum temperature, and precipitation of the intended month, which was conducted in both scenarios of RCP2.6 and RCP8.5. The weights are presented as percentages, and the highest weight is 100, which is also considered the highest score for each model. The model chosen in this step conducts the downscaling and simulation of statistical parameters with lower uncertainty compared to the other AOGCM models and the downscaling models investigated in this study. In this stage, the confidence interval of the model (MPI-ESM-LR downscaled by the LARS-WG model) was calculated by the bootstrap method to ensure the efficiency of the chosen model. In order to analyze the accuracy of the model in downscaling the climatic elements, the number of station-months within the confidence interval was taken into account. In the last step, the climatic parameters predicted by the chosen optimum model (the model with the lowest uncertainty) in the future period (2020-2040) were compared with those in the baseline period (1999-2018). The changes in the precipitation, minimum temperature, and maximum temperature in the region were also investigated.   Conclusion In the period of (1961-2006), among 20 AOGCM climatic models of the fifth report, the nine models of MIROC-ESM, CESM1-WACCM, CSIROC-MK3-6-0, EC-EARTH, GISS-E2-H, GISS-E2-R, MIROC-ESM-CHEM, MPI-ESM-LR, and MPI-ESM-MR were selected as the optimum climatic models in the drainage basin of Karaj according to the suitable range of each one of statistical evaluation coefficients for the models being within the confidence interval defined by the bootstrap method. More detailed investigations on the nine selected models in the (2006-2018) period under the RCP2.6 and RCP8.5 emission scenarios showed that the MPI-ESM-LR climatic model simulates and downscales the maximum temperature parameter in the two scenarios of RCP8.5 and RCP2.6 and the precipitation in the RCP8.5 scenario with the lowest uncertainty using the LARS-WG model. The GISS-E2-R2 model has similar performances on the minimum temperature in the RC8.5 scenario. Moreover, the EC-ERTH model simulates and downscales the precipitation with the lowest uncertainty. The three chosen models were weighted using the MOTP approach for the final evaluation and selection of the best model. The results showed that in most of the months, the highest weight percent in the simulation of climatic variables belongs to the MPI-ESM-LR model. This model is more capable of simulating the precipitation, minimum, and maximum temperatures in both scenarios of RCP8.5 and RCP2.6. Eventually, the confidence interval of the MPI-ESM-LR model (downscaled by the LARS-WG model) was calculated by the bootstrap model to ensure the efficiency of the chosen model. According to the results, it was found that among the 72 station-months, the average maximum temperatures in 62 cases were within the confidence interval. Furthermore, the monthly analysis of average and variance of the minimum temperature, maximum temperature, and precipitation showed that in most of the months, these parameters are within the confidence interval. This shows the high accuracy and low uncertainty of the selected model. In the next step, the parameters of minimum temperature, maximum temperature, and precipitation in the period of (2020-2040) were simulated and downscaled by the chosen model. The evaluation of results in this section showed that the minimum temperature would have a growing trend until 2040. The slope of the average minimum temperature curve in the studied statistical period under the RCP2.6 and RCP8.5 scenarios will increase by 0.02% and 0.08%, respectively. The most significant growth of this parameter was estimated to be +0.8ºC and +0.16ºC under the RCP2.6 and RCP8.5 scenarios in September and March, respectively. The precipitation in the RCP2.6 scenario has nor decreasing neither increasing trend. The statistics of Sen Test in the evaluated confidence intervals indicated that the average precipitation had decreased by almost 0.38 mm every year. The annual average in the RCP8.5 scenario has a significant decreasing trend with a slope of -1.31 mm in the low confidence interval (α = 0.1). The most considerable growth and reduction with the values of +0.45 and +0.63 in the slope of precipitation curve in this scenario are seen in July and October, respectively. This parameter has also a decreasing trend in the very high level of (α = 0.001) for the average maximum temperature in both scenarios. Based on the obtained results, this climatic parameter has a significant decreasing trend in the studied confidence intervals in most of the months. The largest reduction of this parameter under the RCP2.6 and RCP8.5 scenarios will happen in March and June by 0.20ºC and 0.14ºC.}, keywords = {climate change,Uncertainty,Down Scaling,Minimum,and Maximum Temperature,Precipitation}, title_fa = {بررسی عملکرد چهار روش کوچک‌مقیاس سازی بارش و دما تحت سناریوهای RCP مطالعه موردی: ایستگاه کرج}, abstract_fa = {در این مطالعه ضمن بررسی عدم قطعیت ناشی از 20 مدل AOGCM تحت تأثیر دو سناریوی انتشار RCP2.6 و RCP8.6 در دو دوره آماری (2006-1961) و (2018-2006) تغییرات پارامترهای حداقل دما، حداکثر دما و بارندگی ماهانه در بازه زمانی(2040-2020) در حوضه آبریز کرج مورد مطالعه قرار گرفت. از مدل­های LARS-WG، SDSM،ANN و Change Factor به‌منظور ریزمقیاس نمایی استفاده گردید. ارزیابی عملکرد مدل­ها با روش فاصله اطمینان بوت استرپ، معیارهای آماری R2،NS،PBIAS،PRS و روش وزن دهیMOTP  صورت گرفت. در بازه زمانی (2006-1961)، از بین 20 مدل اقلیمی AOGCM گزارش پنجم، 9 مدل به‌عنوان مدل بهینه انتخاب گردید. نتایج بررسی‌ها روی این مدل­ها در بازه زمانی (2018-2006) تحت سناریوهای انتشار RCP2.6 و RCP8.5 نشان داد که مدل‌ اقلیمی MPI-ESM-LR پارامتر حداکثر دما را در هر دو سناریو و بارندگی را در سناریوی RCP8.5، مدل GISS-E2-R2پارامتر حداقل دما را در RC8.5 و مدل EC-ERTH بارندگی را در RCP2.6 با کمترین میزان عدم قطعیت شبیه­سازی می­کند. همچنین نتایج نشان داد LARS-WG نسبت به سایر مدل‌های ریزمقیاس­ سازی دارای عملکرد بهتری است. جهت انتخاب مدل برتر، سه مدل انتخابی با استفاده از رویکرد MOTP، وزن دهی شدند. نتایج این بخش عملکرد مطلوب MPI-ESM-LR را به اثبات رساند.درنهایت جهت اطمینان از کارایی مدل انتخابی، باند عدم قطعیت بوت استرپ محاسبه شد. نتایج این بخش نشان داد که در اکثر ماه‌ها و ایستگاه­ها داده­ها، در محدوده اطمینان قرار می­گیرند. نهایتا با کمک مدل نهایی انتخابیً پارامترها در بازه زمانی (2040-2020) شبیه­سازی شدند. نتایج نشان داد، تغییرات میانگین کلی سالانه بارش فاقد روند افزایشی و کاهشی بوده و میانگین حداکثر و حداقل دما نیز به ترتیب دارای روند کاهشی و افزایشی خواهد بود.}, keywords_fa = {تغییر اقلیم,عدم قطعیت,ریزمقیاس ‌نمایی,حداقل و حداکثر دما,بارندگی}, url = {https://clima.irimo.ir/article_132205.html}, eprint = {https://clima.irimo.ir/article_132205_348cdfe0c2ccdd304736fc56a528c8d2.pdf} } @article { author = {Mohammadrezaei, Mojdeh and GHAHREMAN, NOZAR}, title = {Projected impacts of climate change on major crops’ virtual water under RCP scenarios (Case of Kerman Province)}, journal = {Journal of Climate Research}, volume = {1400}, number = {45}, pages = {67-80}, year = {2021}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {  The study of climate change effects on crop growth and irrigation water requirement is crucial in maintaining food security. As a direct consequence of warmer temperatures, the hydrologic cycle will undergo significant impact with accompanying changes in the rates of precipitation and evaporation. Water scarcity and climate change pose a big threat for Iran’s food security. Climate change is projected to increase temperatures, spatio-temporal variability in rainfall pattern, and water stresses to crops. Due to the significant role of water in crop yield, inadequate soil water in crop producing regions can result in substantial yield drops. Agriculture, which accounts for 80 percent of freshwater consumption worldwide and the researchers, examined trade through the lens of what they call “virtual water” — a measure of how much water goes into the production of a bushel or a kilogram of a given crop. Upon release of new scenarios based on Radiative Forcing which are known as Representative Concentration Pathway scenarios (RCP scenarios), by Intergovernmental panel on climate change (IPCC) in fifth assessment report (AR5), a new set of 42 global climate models (GCMs) have been proposed for future climate projections The current study was aimed to investigate the possible impacts of climate change effects on evapotranspiration and virtual water of several major crops of Wheat, barley, potato and tomato in there region in Kerman province, south of Iran.   Material and Methods Study consists two sections. In part one for climate change detection, trend analysis of temperature, rainfall and evapotranspiration variables were performed using Mann-Kendall and Sen’s slope estimator test in three study stations namely Bam, Jiroft, Kerman during three future periods (i.e. 2018-2039,2040- 2069, 2070-2100). In second part, for projection of virtual water of selected crops under RCP4.5 and RCP8.5 climate change scenarios (IPCC Fifth Assessment Report) during period of 2018-2100 in three study stations, crop evapotranspiration were worked out using downscaled outputs of CNRM-C5 climate model.The first step in impact assessment studies is selecting suitable climate models from those recommended by IPCC for obtaining required climatic data under certain scenarios. The results of uncertainty analysis performed in previous studies by authors were used choosing different models of CMIP5 project which are approved in fifth assessment report (AR5) . Also crops yield were simulated using Aqua Crop model. By choosing new date of sowing, temperature, rainfall and evapotranspiration during projected growing season were determined. Based on the maximum simulated yield for the study crops, the optimum date of sowing for future periods were chosen. Finally the crops virtual water (evapotranspiration divided by yield) was calculated.   Results and Discussion The results of study showed that the air temperature, in all month in study stations, would increase comparing to baseline period 1990-2017, such that in three study stations under RCP 8.5 scenario the air temperature will increase 0.66,0.77,0.68 ◦C, respectively. Similarly under RCP 4.5 scenario, the corresponding values are 0.42, 027, 0.45 ◦C. The Maize crop yield would decrease in all three stations (with highest decrease in Jiroft station with 52 and 56 percents under RCP 4.5 and RCP 8.5  in 2018-2039 period comparing to baseline period, respectively.) The virtual water of all selected crops is projected to increase, but this increase would be higher for wheat and barley crops. The lowest increase in virtual water was observed in tomato crop during the future period of 2018-2100.In Bam station, the highest amount of virtual water belongs to barley crop during the period of 2040-2069, i.e. 4853 and 5153 cubic meter per ton under two RCP scenarios, respectively. In Jiroft wheat crop has the highest virtual water during the period 2040-2069 projected to be 4984 m3/ton. In case of Kerman station, largest amount of virtual amount under RCP4.5 belongs to wheat during the period 2040-2069 and under RCP 8.5 corresponds to barley with amount of 4256 m3/ton. Conclusion The virtual water of all selected crops is projected to increase; this increase would be more for Barley and Wheat. According to results it is recommended to estimate the virtual water of currently cultivated crops in the region for coming years. Continuous cropping of wheat and barley is not advisable Alternative low-water-use crops may be an option for producers. Further studies on major crops’ virtual water in the agricultural regions of the country are recom}, keywords = {climate change,evapotranspiration,Yield,virtual water,Iran}, title_fa = {چشم انداز آب مجازی گیاهان عمده زراعی تحت سناریوهای واداشت تابشی تغییر اقلیم (مطالعه موردی استان کرمان)}, abstract_fa = {تحقیق حاضر، با هدف بررسی اثرات تغییر اقلیم بر آب مجازی گیاهان گندم، جو، ذرت، سیب‌زمینی و گوجه‌فرنگی در سه شهرستان کرمان، بم و جیرفت در جنوب ایران تحت دو سناریوی واداشت تابشی اجرا شد. میزان آب مجازی به دست آمده برای همه گیاهان مورد مطالعه روند افزایشی دارد اما این افزایش برای جو و گندم به‌طور متوسط در دوره آینده 2100-2018 تحت هر دو سناریو افزایش بیشتری از خود نشان می‌دهد. همچنین به‌طور متوسط کمترین میزان آب مجازی مربوط به گوجه‌فرنگی می‌باشد.  در منطقه بم بیشترین میزان آب مجازی تحت سناریو RCP4.5 و RCP8.5 برای دوره 2069-2040 مربوط به گیاه جو به میزان 08/4853 و 15/5153 مترمکعب بر تن، در جیرفت بیشترین آب میزان مجازی تحت سناریو RCP4.5 مربوط به گندم برای دوره 2069-2040 برابر با 4984مترمکعب بر تن و تحت سناریو RCP8.5 بیشترین مقدار مربوط به جو در دوره 2069-2040 می باشد. در کرمان بیشترین آب مجازی تحت سناریو RCP4.5 مربوط به گندم در دوره 2069-2040 برابر با 4637 و تحت سناریو RCP4.5 بیشترین میزان پیش نگری شده متعلق به گیاه جو برابر با 1/4256 مترمکعب بر تن در دوره 2069-2040تعیین شد. تدقیق برآوردهای نیاز آبی و مطالعه آب مجازی گیاهان راهبردی در سایر مناطق کشور تحت سناریوهای جدید تغییر اقلیم برای  ارائه الگوی کشت مناسب و افزایش بهره وری آب توصیه می شود}, keywords_fa = {ایران,آب مجازی,تبخیر تعرق,تغییر اقلیم,عملکرد}, url = {https://clima.irimo.ir/article_132207.html}, eprint = {https://clima.irimo.ir/article_132207_a057c60c43f27d13351e8cf24c5e2e4d.pdf} } @article { author = {parviz, jamal and Borna, Reza and Asadian, Farideh}, title = {Analysis of heavy precipitation in Kermanshah province by my Kendall method (Case study: Kermanshah Province during 1970-2017)}, journal = {Journal of Climate Research}, volume = {1400}, number = {45}, pages = {81-96}, year = {2021}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Introduction: Changing climate is one of the most important issues in the present age. Heavy rainfall is the prominent clue of it that sometimes is destructive and harmful and has some awkward effects on human being’s environment. It does not seem to be from the same source and each part of Iran has its special sources (Ghaur and coligues 27-11 1391). Iran is one of those regions which has experienced irregular and climatic abnormalities (Mohamadi and Masodian 70-47 1389). for having Topographic has the heavy and sever rainfall which is in one of the climates raucousness which faces the global with different crises such as severe floods, damage in agricultural sectors, transportations and human death .because of this, recognizing the methods and studding of these occurrences to exact prognosticate and an alert before the incident has an important role in the management of preventing the events .the place and time of raining changes in the mountainous region of Iran’s North west is a lot.( khorshiddoost and coligues 1395 82- 53) . The Iranian west vast part not only depends on local conditions, but on out regional and itinerant systems in weather circular conditions. These specifics cause our study to be affected by rare annual raining, the shortness of rain period and severity of the raining in the shower forms. (Banfshe and coligues 1394 117-135).        Methodology and data The severe rainfall in Kermanshah province has been studied in this research and to obtain the aim, Data of 92 synoptics and hydro graphing stations has been gathered during 1970, 2018. The Data produced in two parts, the first part with 1434 stations until 2004 and the second with 1036 stations from 2005 to 2018. After the Data being prepared to determine rainfall limitation, heavy and dangerous ones the most important is to choose the suitable threshold. From the 90 decades most researcher sources have been used for studding the hard raining in fact using decades for heavy rain in each point is on the basis on its raining behavior, thus the 90 decades has been applied in the research. Man, Kendal Analysis method has been used for studding the situation and heavy rain changes.   Result The results show that the severe rainfalls include most of Kermanshah province annual precipitation, the conditions are more observed in the North West parts such as Javanrood and Pave cities and in the South east gets to the least point. Most heavy rain occurrence expansion includes a tow- day continue and the least includes a five- day one. The heavy rain changes coefficient on the other hand had increased terribly as a result of its continuance, so that the situation in the east of province was more prominent. the heavy rain limit over the province was different and the most limitation with heavy one with 20 mm was observed in some parts in west of the province , especially in Gillan e Gharb and the least with 9MM in the east part .But on the contrary the least ones had more continuance with 2 or 5 days of training and has been observed as nuclear in some parts of Kermanshah such a Ravansar and Javanrood .Man Kendal Graphic tests also revealed that the 2 and 3 days raining continuance in after 2000 got a leaping .while  the 4 and 5 days has been observed during the beginning of period of research .   Conclusion The aim is to study the analyzing and studding of Kermanshah heavy rains and for this the data of 92 synoptic and water gauge stations from Esfazari stations were gathered .the term decade is used to determine the limitation of heavy rainfalls in each point and Man Kendall test is used to scrutinize more in the province rainfalls , results revealed that heavy rainfalls in Kermanshah province form the huge parts of the province and the limitations over the province has been different me the most occurred in the Northwest part and the least in the half Eastern part. And the most part of the under study on heavy rainfall limitation was between 11 to 15 MM, the rainfall process over the province expansion in 2 to 5 days of continuance has experienced a decrease one and this also includes for the 2 days rainfall continuance .and also Man Kendall Graphic test reveals a meaningful leap for 2 and 3 days of continuance in the recent years and has experienced a 4 and 5 ones from the beginning of the research.}, keywords = {heavy rainfalls,Trend,continuance,Kermanshah,Kendal}, title_fa = {تحلیل مخاطرات بارش های سنگین استان کرمانشاه به روش من کندال (مطالعه موردی: استان کرمانشاه طی دوره 1970 تا 2017)}, abstract_fa = {هدف از این مطالعه بررسی و تحلیل اقلیم شناسی بارش های سنگین کرمانشاه  می باشد. برای این منظور داده های سینوپتیک و ابسنجی 92 ایستگاه در سطح استان از پایگاه داده ای اسفزاری استخراج شده است. بعد از تشکیل پایگاه داده ای به منظور تعین آستانه بارش سنگین در هر نقطه از صدک 90 استفاده شده است. به منظور تحلیل دقیقتر بارش های سنگین استان، تداوم بارش های سنگین برای تداوم دو تا پنج روزه استخراج و مورد بررسی و تجزیه تحلیل قرار گرفت. همچنین به منظوربررسی و تحلیل روند بارش های سنگین از آزمون من کندال بهره گرفته شده است. نتایج نشان داد که بارش های سنگین در استان کرمانشان بخش عظیمی از میانگین بارش سالانه استان را تشکیل می دهد. آستانه های بارش سنگین در سطح استان متفاوت بوده است بیشترین استانه رخداد بارش های سنگین در بخش های از شمال غرب استان و کمترین آن در نیمه شرقی استان مشاهده شده است. روند بارش های سنگین در تداوم های دو تا پنج روزه در اکثر پهنه استان به ویژه کرمانشاه از روند کاهشی برخوردار بوده است. همچنین شیب روند کاهشی برای بارش های سنگین با تداوم دو روزه بوده است. همچنین نتایج حاصل از آزمون گرافیکی من کندال بیانگر این است که بارش های با تداوم دو و سه به سمت سالهای اخیر از جهش معنی داری برخوردار بوده است و برای تداوم چهار و پنج روزه در سالهای ابتدای دوره مورد مطالعه جهش را تجربه کرده است.}, keywords_fa = {بارش سنگین,روند,تداوم,کرمانشاه,من کندال}, url = {https://clima.irimo.ir/article_132208.html}, eprint = {https://clima.irimo.ir/article_132208_982bd79a3a36a72e4ede2974b0342a08.pdf} } @article { author = {farzaneh, mahsa and Arbabi Sabzevari, Azadeh and Daryabari, Jamalodin and Asadian, Farideh}, title = {Climatic Variable Forecasting for Future Decades in South East Area of Iran}, journal = {Journal of Climate Research}, volume = {1400}, number = {45}, pages = {97-112}, year = {2021}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {  In recent decades, rising global temperatures have upset the climate balance of planet and caused widespread climate change in most parts of the world, known as climate change Index. In the present study, climatic variables in six synoptic stations in the southeastern part of Iran (Zabol, Zahedan, Khash, Iranshahr, Saravan and Chabahar) from 1987 to 2019 were studied in two time periods (2021-2040 and 2041-2060), considering the uncertainty of the general circulation model (Hadcm2) was investigated and analyzed. After reviewing and evaluating the model, the values ​​of climatic variables in two scenarios, RCP2.6 and RCP8.5, were scaled in the studied periods. The results of LARS-WG model accuracy evaluation in simulation of climatic variables based on MAD, RMSE, MSE, MAPE indices in the southeastern part of Iran in the validation stage showed that there was a large correlation between the simulated values ​​and the base period. Based on the output results of LARS-WG model, it shows the increase of temperature in all stations in the two studied periods. The rate of temperature increase in coastal areas is less than other land areas. Temperature changes fluctuate uniformly and precipitation changes fluctuate at all stations. The amount of rainfall during the winter and spring seasons in all stations is increasing; Future climatic conditions such as number of frosty days, number of hot, dry and wet days were calculated and the results showed that in the next period, the number of hot days, the number of dry days will increase compared to the base period and the number of frosty days will decrease. If we do not adhere to the reduction of greenhouse gases, the increase of climatic variables, the minimum temperature and the maximum temperature and the decrease of precipitation will increase in the 2041-2060 decade. Monthly forecasts for future periods in the mentioned scenarios also indicate that the warmest month in the province is on average in summer (July), the coldest month in winter (December and January), the most precipitation in winter and spring (December, January and March) and evapotranspiration peaks in summer. Finally, the results show the trend of increasing temperature and decreasing rainfall in the coming decades in the southeastern regions of Iran.}, keywords = {climate change,Forecasting,climate variables,South- east area,Model LARS-WG}, title_fa = {پیش نگری متغیرهای اقلیمی دهه های آینده در پهنه جنوب شرق ایران}, abstract_fa = {در چند دهه اخیر افزایش دمای زمین باعث بر هم خوردن تعادل اقلیمی کره زمین شده و تغییرات اقلیمی گسترده ای را در اغلب نواحی کره زمین موجب گردیده است که از آن به عنوان تغییر اقلیم یاد می شود. در این پژوهش ، به بررسی متغیر های اقلیمی در شش ایستگاه های سینوپتیک پهنه جنوب شرق ایران (زابل، زاهدان، خاش، ایرانشهر، سراوان و چابهار) از سال 1987 لغایت 2019 پرداخته شد و در دو دوره ی زمانی (2021-2040 و 2041-2060)، با استفاده از ﻣﺪل ﮔـﺮدش ﻛﻠـﻰ (HadCM2 ) بررسی و تحلیل گردید. پس از بررسی و ارزیابی مدل مقادیر متغیرهای اقلیمی در دو سناریو RCP2.6 و RCP8.5 در دوره های مورد مطالعه ریز مقیاس گردید. نتایج ارزیابی دقت مدل LARS-WG در شبیه سازی متغیرهای اقلیمی براساس شاخص های MAE ، RMSE،R2 ،NSE در پهنه جنوب شرق ایران در مرحله صحت سنجی نشان داد که انطباق زیادی بین مقادیر شبیه سازی شده و دوره پایه وجود داشته است. بر اساس نتایج خروجی مدل LARS-WG  افزایش دما در کلیه ایستگاه ها در دو دوره مورد مطالعه را نشان می دهد. میزان افزایش دما در مناطق ساحلی کمتر از سایر مناطق خشکی می باشد. در تمامی ایستگاه ها تغییرات دما به طور یکنواخت و تغییرات بارش، نوسان دارند. مقدار بارش طی فصول زمستان  و بهار در تمامی ایستگاه ها روند افزایشی دارد؛ شرایط اقلیمی آینده از قبیل تعداد روزهای یخبندان، تعداد روزهای داغ، خشک و روزهای تر محاسبه گردید و نتایج نشان داد که در دوره آینده تعداد روزهای داغ و تعداد روزهای خشک نسبت به دوره پایه افزایش می یابد و تعداد روزهای یخبندان کاهشی می باشد. در صورت عدم پایبندی به کاهش گازهای گلخانه ای افزایش متغیرهای اقلیمی دمای حداقل و دمای حداکثر و کاهش بارش در دهه 2041-2060 بیشتر خواهد شد. پیش بینی ماهانه برای دوره های آینده نیز در سناریو های مذکور ، بیانگر این است که گرمترین ماه در استان به طور میانگین در ماه تابستان (ژوئیه)، سردترین ماه در زمستان (دسامبر و ژانویه)، بیشترین بارش ها در زمستان و بهار (دسامبر، ژانویه و مارس) و تبخیر و تعرق در تابستان به بیشترین حد خود می رسد. در نهایت اینکه نتایج بیانگر روند افزایش دما و کاهش بارش در دهه های آینده نواحی جنوب شرق ایران خواهد بود.}, keywords_fa = {تغییر اقلیم,پیش نگری,متغیرهای اقلیمی,پهنه جنوب شرق ایران,مدل LARS-WG}, url = {https://clima.irimo.ir/article_132209.html}, eprint = {https://clima.irimo.ir/article_132209_c056ee801746f3110bd0383016b754cf.pdf} } @article { author = {Pourgholam-Amiji, Masoud and ansarighojghar, Mohamad and Araghinejad, Shahab and Babaeian, Iman}, title = {Modeling the Relationship between Dust Storms and Extreme and Average Temperature Variables in the Western Half of Iran}, journal = {Journal of Climate Research}, volume = {1400}, number = {45}, pages = {113-126}, year = {2021}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Introduction: The increase of dust storms occurrence in recent years in western and southwestern Iran has doubled the importance of prediction and communication of this phenomenon with climate variations. Analyzing and identifying of dust storms and its association with climatic parameters is one of the crucial approaches to reduce the caused damage of this phenomenon. Since besides determining the portion of each climate variables in intensifying the circumstances, it also can play a fundamental role in priorities, macro management policies, and upstream rules in order to control and prevent dust particles. The purpose of this study is to model the relationship of Frequency of Dust Stormy Days (FDSD) with extreme and average temperature variables in the western half of the country.   Materials and methods: For this purpose, the hourly data of dust and codes of the World Meteorological Organization, as well as climatic data including average temperature, maximum temperature and minimum temperature on a monthly scale with a statistical period of 25 years (1990-2014) in 26 synoptic stations located in the western half of the country were used. After reviewing and controlling the quality of station statistics and eliminating statistical deficiencies, the homogeneity of the data was evaluated using the Run Test and the randomness of the data was accepted at a 95% confidence level. The Pearson and Spearman correlation coefficients as well as a multivariate linear regression method were used in communicate the frequency of days associated with dust storm with extreme and average temperature variables. In this study, the observational values of the frequency of days with dust storm were considered as dependent variables and the average temperature data and cardinal temperature variables were considered as independent variables. In order to analyze the correlation, the zoning map of the coefficients was prepared by IDW method in ArcGIS software.   Results and discussion: The results showed that the highest correlation coefficient with FDSD index was related to the maximum temperature variable in Abadan station with 0.875 and the minimum temperature in Ahvaz station with 0.893. Also, with increasing FDSD index, correlation coefficient values increasedat Abadan and Ahvaz stations, the stations which had the highest number of dust days with 401 and 321 days, respectively, during the 25-year period. Multivariate regression modeling between FDSD and different temperature parameters in the western half of the country showed that the most important factors influencing dust events are the extreme temperature variables. In all 26 stations studied, there is a positive correlation between the minimum temperature and the frequency of days with dust storm, but this correlation is more significant in some stations and in Dehloran, Ilam, Kermanshah, Safi Abad and Sanandaj stations at 95% confidence level and also in Hamedan (Airport), Islamabad Gharb, Abadan, Ahvaz, Bandar Mahshahr and Bostan stations were significant at 99% confidence level. Meanwhile, the highest Spearman correlation coefficient between different temperature parameters and Frequency of Dust Stormy Days (FDSD) is related to the maximum temperature variable in Ahvaz, Abadan, Bostan and Bandar Mahshahr stations with correlation coefficients of 0.59, 0.57, 0.53 and 0.51, respectively, have been registered. The highest Pearson correlation coefficient between temperature parameters and frequency of days with dust storm is related to the minimum and maximum temperature variables, which were recorded in Ahvaz and Abadan stations with a correlation coefficient of 0.893 and 0.875, respectively. Regression models show that, in the best case scenario, the temperature variables of 81.2% (Abadan) and 79.3% (Bandar Mahshahr) determine the changes in the FDSD index.   Conclusion: The cardinal temperature variables are known as an important and influential factor in the formation of dust storms because increasing the values of Cardinal temperature parameters leads to excessive evaporation from the soil surface, which can provide a source of particles for the occurrence of such dust storms. It should be noted that the average temperature variable can also have an important effect on increasing dust events, but compared to the cardinal temperature variables, its effect is much less. The results of this study can be useful in managing the issues caused by dust storms and in the combating plans to desertification in the study regions. Also, the results of this research can be a new guide for predicting and modeling the phenomenon of dust storms in the country.}, keywords = {Critical Areas,FDSD Index,Correlation coefficient,ArcGIS software,Multivariate linear regression}, title_fa = {مدل‌سازی رابطه طوفان‌های گردوغبار با متغیرهای حدی و متوسط دما در نیمه غربی کشور}, abstract_fa = {افزایش وقوع طوفان‌های گردوغبار در چند سال اخیر در غرب و جنوب غرب ایران، اهمیت پیش‌بینی و ارتباط این پدیده با نوسانات اقلیمی را دوچندان کرده است. هدف از این پژوهش، بررسی شدت همبستگی و مدل‌سازی رابطه فراوانی روزهای همراه با طوفان گردوغبار (FDSD) با متغیرهای حدی و متوسط دما در نیمه غربی کشور می‌باشد. بدین منظور از داده‌های ساعتی گردوغبار و کدهای سازمان جهانی هواشناسی و همچنین داده‌های اقلیمی شامل دمای متوسط، دمای بیشینه و دمای کمینه در مقیاس ماهانه با طول دوره آماری 25 ساله (2014-1990) در 26 ایستگاه سینوپتیک واقع در نیمه غربی کشور استفاده شد. برای ارتباط­سنجی فراوانی روزهای همراه با طوفان گردوغبار با متغیرهای حدی و متوسط دما از ضرایب همبستگی پیرسون و اسپیرمن و همچنین روش رگرسیون خطی چندمتغیره در نرم‌افزار SPSS استفاده شد. به منظور تحلیل همبستگی، نقشه پهنه‌بندی ضرایب با روش IDW در نرم‌افزار ArcGIS تهیه شد. نتایج نشان داد که بالاترین ضریب همبستگی با شاخص FDSD مربوط به متغیر دمای بیشینه در ایستگاه آبادان با مقدار 875/0 و دمای کمینه در ایستگاه اهواز با مقدار 893/0 بود. همچنین با افزایش شاخص FDSD، مقادیر ضریب همبستگی افزایش یافت؛ به نحوی که در ایستگاه‌های آبادان و اهواز که به ترتیب با 401 و 321 روز در بازه زمانی 25 ساله، رکورددار بیشترین تعداد روزهای همراه با طوفان گردوغبار بودند، بالاترین ضرایب همبستگی بین متغیرهای حدی و متوسط دما با شاخص FDSD مشاهده شد. مدل‌سازی رگرسیون چند متغیره بین گردوغبار و پارامترهای مختلف دما در نیمه غربی کشور نیز نشان داد که تأثیر متغیرهای حدی دما در وقایع گردوغبار بیشتر از دمای متوسط است. مدل‌های رگرسیونی نیز نشان می‌دهند که در بهترین حالت، متغیرهای حدی دما در آبادان 2/81 درصد و در بندرماهشهر 3/79 درصد  از تغییرات شاخص FDSD را تبیین می‌کنند.}, keywords_fa = {نواحی بحرانی,شاخص FDSD,ضریب همبستگی,نرم‌افزار ArcGIS,رگرسیون خطی چند متغیره}, url = {https://clima.irimo.ir/article_132210.html}, eprint = {https://clima.irimo.ir/article_132210_13a9dd94abd5294f5c7920c7d2abd860.pdf} } @article { author = {Ghassabi, Zahra and Fattahi, Ebrahim}, title = {Classification of atmospheric circulation patterns in the Middle East and Iran}, journal = {Journal of Climate Research}, volume = {1400}, number = {45}, pages = {127-142}, year = {2021}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Introduction The main idea of ​​atmospheric circulation patterns and their classification is to convert a set of atmospheric parameters into a univariate catalog, with cases of similar characteristics grouped together. Easier interpretation of weather conditions would be the advantage of the classification. Many researchers to classify atmospheric circulation patterns have used the principal component analysis (PCA) method. Esteban (2006) in a study of atmospheric circulation patterns in Western Europe, categorized daily synoptic circulation patterns into 20 groups and showed sea level pressure and 500-hPa geopotential height configurations throughout the year. Smith and Sheridan (2018) clustered geopotential height anomalies at levels of 100 and 10-hPa and sea level pressure to study the patterns of tropospheric and stratospheric potential vorticity.     In Iran, Raziei (2007) by PCA classification and clustering identified 18 atmospheric circulation patterns for the Middle East and Iran. He showed that patterns with meridional and northwest flow often cause drought and patterns with southwest flow cause wetting. Hanafi (1399) identified the air types in the northwestern region of the country (Maragheh station), and showed that the high geopotential systems of Saudi Arabia and North Africa governed by hot and dry conditions and the Mediterranean and polar cold air masses are involved in creating cold periods. Atmospheric circulation patterns identified for Iran are based on monthly average atmospheric data and with a resolution of 2.5°. Often due to the importance of winter as the main rainy season in Iran, the identification of atmospheric circulation patterns of other seasons has less studied. On the other hand, most studies have conducted regionally in a province/small part of the country. In this study, we have classified the synoptic patterns affecting Iran and the Middle East in the period of 1990-2019, using the PCA method for all seasons and with a higher accuracy using data with 0.5° resolution on a daily time scale. Then, composite maps of the MSLP (Mean Sea Level Pressure) and 500-hPa geopotential height were prepared and analyzed to obtain the frequency of monthly and seasonal occurrence of each investigated pattern. Previous studies have focused mainly on 500-hPa and MSLP parameters. However, in the present study we have used the 850-hPa moisture flux besides the already applied quantities, which can be considered a main and important quantity for the rain occurrence. Materials and methods   Geopotential height data of 500-hPa received from the ECMWF (ERA5) at one hour intervals during the period 1990-2019 in the area of 20E-65°E longitude and 10N-55°N latitude. Due to the data volume and software and hardware limitations, data with 0.5° resolution extracted. By calculating the daily average in each grid, the data matrix consisted of 8281 columns (grids) and 10957 rows (number of days). Then the MSLP, 10m wind speed, and 850-hPa temperature and relative humidity maps/data were provided/extracted.     The PCA analysis is a method for extracting important variables from a large set of variables in a data set. The main goal is to reduce number of components by finding the ones that explain correlations between the variables. We selected the first nine components covering a large portion of the described variances and ignored other minor components. In the present study, the R language programming were used to analyze the principal components with S array and select the components. To classify air types, K-means clustering was used, so that it presents the most alternating patterns of atmospheric circulation in the study area during the year. After selecting the main components and determining the scores of the components, all days (10957 days) were classified into 18 groups. Sea level pressure and 500-hPa geopotential height maps were prepared and interpreted. Monthly and seasonal frequency of occurrence of each pattern and relationship of spatial distribution of moisture flux at 850-hPa were investigated. Results and discussion Based on the results obtained from principal component analysis, the first 9 components were selected, which explained 95.93% of the total variance of the data.  According to the monthly and seasonal distribution of each pattern, it was observed that cp1, cp7 and cp18 circulation patterns occur in summer and early autumn and cp13 occur in late spring, summer and early autumn. Cp2, cp4, cp6, cp8, cp11 and cp16 occur in late autumn to early spring of the following year and cp3, cp5, cp9, cp10, cp12, cp14, cp15 and cp17 circulation patterns occur in late autumn to spring of the following year. These situations correspond to the synoptic conditions of each pattern at sea level and the level of 500-hPa. In the circulation patterns of the warm period of the year, thermal low pressure of sea level pressure map below 35° N is associated with subtropical high at mid-level of atmosphere. The maximum moisture flux in 850-hPa located in the eastern parts of Iran and the maritime borders of Yemen and Oman which is compatible with southern and southeastern flow. In cp2, cp4, cp6, cp8, cp11 and cp16 circulation patterns that occur in the cold period of the year; south and southwest flow of low pressure in the south of the Red Sea are associated with mid-level of atmosphere. There is convergence of moisture flux in the south of the Red Sea and in parts of the south and southwest of Iran, east of the Black Sea, northeast of the Mediterranean Sea and south of Turkey. In other patterns that occur in the cold period of the year as well as in spring, low pressure in south and center of the Red Sea is associated with trough in the mid-level of the atmosphere. Convergence of moisture flux was in the west, southwest, south and northwest of Iran, northeast of the Mediterranean Sea, southwest of Turkey and south of the Red Sea. Conclusion In the present study, principal component analysis with S array and K-means clustering was used to classify circulation patterns in Middle East and Iran. The results show significant differences in the arrangement of patterns, the frequency of air types and their path to Iran.}, keywords = {Atmospheric Circulation patterns,principal components analysis,Moisture flux,Middle East,Iran}, title_fa = {طبقه‌بندی الگوهای گردش جوی روزانه در خاورمیانه و ایران}, abstract_fa = {الگوهای گردش جوی نقش اصلی در رخداد پدیده­های محیطی به­ویژه در مناطق معتدله دارند. این الگوها سبب ایجاد دوره­های مرطوب یا خشک می­شوند. طبقه­بندی الگوهای گردش جوی روزانه و شناسایی مراکز فعالیت آن­ها در نواحی مختلف ایران در برنامه­ریزی­ها موثر است. در تحقیق حاضر از تحلیل مولفه­های اصلی و خوشه­بندی به منظور طبقه­بندی الگوهای گردش جوی روزانه استفاده شد. میانگین روزانه ارتفاع ژئوپتانسیل تراز 500 هکتوپاسکال و فشار سطح دریا طی دوره 2019-1990 در تفکیک °5/0 از ECMWF استخراج شد. محدوده انتخابی شامل 8281 نقطه از E°65-20 و N°55-10، خاورمیانه و ایران را می­پوشاند. در تحلیل مولفه­های اصلی نقاط وابسته به هم ادغام و ابعاد ماتریس کاهش داده شد، به­طوری­که 9 مولفه اصلی باقی ماند. از آرایه S برای شناسایی تیپ­های هوا و از خوشه­بندیK-Means برای طبقه­بندی تیپ­های هوای روزانه استفاده گردید. همه روزها (10957 روز) به هیجده گروه تقسیم­بندی شدند. نقشه­های ترکیبی فشار سطح زمین و ارتفاع ژئوپتانسیل تراز 500 هکتوپاسکال و توزیع ماهانه تغییرپذیری الگوها به دست آمد. واگرایی شار رطوبت در هر الگو محاسبه و تحلیل شد. نتایج نشان داد که فراوانی الگوهای 1، 7، 13 و 18 در دوره گرم سال و بقیه الگوها اغلب در دوره سرد سال است. این وضعیت با شرایط همدیدی هر یک از الگوها در سطح زمین و تراز 500 هکتوپاسکال مطابق است، طوریکه در الگوهای گردشی دوره گرم سال کم­فشار حرارتی سطح زمین در پائین­تر از مدار °35 با پرارتفاع جنب حاره تراز میانی جو همراه است و بیشینه شار رطوبت تراز 850 هکتوپاسکال در بخش­های شرقی ایران است. در الگوهای گردشی دوره سرد سال، جریان­های جنوبی و جنوب­غربی از کم­فشار جنوب دریای سرخ، اغلب با ناوه تراز میانی جو همراه است، همگرایی شار رطوبت در جنوب دریای سرخ، بخش­هایی از غرب، جنوب­غرب، جنوب و شمال­غرب ایران، شمال­شرق دریای مدیترانه، جنوب­غرب ترکیه و شرق دریای سیاه دیده شد.}, keywords_fa = {الگوهای گردش جوی,تحلیل مولفه‌های اصلی,شاررطوبت,خاورمیانه,ایران}, url = {https://clima.irimo.ir/article_132211.html}, eprint = {https://clima.irimo.ir/article_132211_116a77abd8af529390f76a1c86cdbe1a.pdf} } @article { author = {Sadidi Shal, Seyyed Mohammad Taghi and Zohd Ghodsi, Mohammad Javad and Asadi Oskouei, Ebrahim and Zahra, Amin Deldar}, title = {Comparison of Growing Degree Day of Different Phenological Stages of Hashemi Rice in Guilan Province}, journal = {Journal of Climate Research}, volume = {1400}, number = {45}, pages = {143-152}, year = {2021}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Introduction:Rice is one of the most important agricultural products in the world, which ranks second after wheat in terms of annual production and is the main food of half of the world's population although rice is cultivated in a wide range of climatic conditions and altitude, but this plant is vulnerable to changes in environmental conditions Growth condition of rice plant and climatic conditions and characteristics affect its yield and suitable planting date according to the existing environmental factors to prevent wastage in areas such as water consumption costs, manpower costs, consumption savings Inputs are inevitable. Planting time management for optimal production in any variety of rice is one of the main and effective factors in production that leads to optimal use of inputs and effective use of existing factors such as weather conditions. . Among the atmospheric and environmental factors affecting growth, the relative importance of temperature is more than other factors. Environmental factors can affect yield by directly affecting the physiological processes of growth and grain formation. For example, temperatures higher or lower than the maximum and minimum critical temperatures can affect grain yield by affecting tilling strength, cluster formation and ripening.Materials and methods:Gilan province is one of the northern and coastal provinces of the country with an area of 14711 square kilometers, which has a temperate Caspian climate. Considering that out of the total 238 thousand hectares of paddy lands of the province under cultivation of native and high-yield rice cultivars, about 180 thousand hectares, i.e. about 76% of it is dedicated to cultivation of Hashemi cultivar, we can understand the importance of this cultivar in the agricultural economy of the province. Which emphasizes the need to obtain more information than this figure in the province. For this reason, the cultivar studied in this study was selected Hashemi, which has been transplanted in different planting dates and the purpose of the study was to compare and compare the length of growth period in the mentioned dates in the sample farms. In this study, meteorological information was obtained during the 94-95 crop year, including the average daily values of air temperature in different stations of Guilan Meteorological Department, as well as agricultural information, information on rice phenological stages and physical progress of rice farming operations in Different regions of the province were received from the Jihad Agricultural Organization of the province and its affiliated managements and certain experts in the sample farms.Results and discussion:According to the data obtained from monitoring different stages of phenology, in all 8 cities, two Hashemi rice fields with different planting dates were selected and studied and compared. The length of the growth period in terms of days and the amount of GDD received at each phenological stage in these fields were compared with each other. To do this, first, through K-S test the normality of daily average temperature data in all cities was checked and it was found that the data are normal with 95% confidence level. In the next step, the Levine’s Test of variance was performed first, then a comparison was made between early and late sowing fields in terms of GDD intake in different phenological stages. For this purpose, the mean t-test was used. The results showed that only in 3 to 4 leaf stage there was a significant difference between early and late planting fields in which the average degree of growth day received in 3 to 4 leaf stage in early planting fields was 135.4 Units and in late planting farms has been 90/02 units. Also in this study, a comparison was made between early and late planting fields in the western, eastern and central regions of the province in terms of GDD intake at different phenological stages. For this purpose, the mean t-test was used and the results showed that the farms in the center and west of the province had significant differences only in the physiological maturity stage so The farms in the center of the province received 102.825 units in the physiological ripening stage, more GDD than the farms in the west of the province with 59.950 units were needed for this phenological stage. The results showed that the transplanting date in the two selected farms of Rasht city was 541 and 38 July, respectively, and the date of physiological maturity of both farms was 141 days. In other words, a difference in the planting date of 16 days not only did not affect the ripening time but also caused a waste of inputs and human resources. The reason for this is the low temperature in April, when the rice plant will naturally receive less GDD. The highest rate of heat unit reception in most cities (except Astara) was in the tilling stage and the lowest rate of heat unit reception occurred in the physiological maturity stage. It was also found that in most cities, early planting fields in the phenological stages of clustering and hardening of GDD seeds needed more than late planting fields.Conclusion:In this study, it was found that Hashemi rice in Gilan province, from seedling stage to physiological maturity, needed more GDD in early planting fields and reached maturity in a longer period of time. And has a longer growth period than late planting fields. Hashemi rice in Gilan province has received the highest GDD in the phenological stage of tilling and the lowest amount in the physiological maturity stage. This study showed that Hashemi rice in Gilan province from seedling to physiological maturity will need to receive 1216 to 1352 GDD units. On the other hand, the harvest date can be due to climatic conditions and limitations and Manpower occurs between 2 and 7 days after physiological maturation. It was also found that the eastern regions of the province had both lower GDD and shorter duration during the season than other regions of the province. Therefore, it can be concluded that Hashemi rice in Gilan province from seed to harvest will need approximately 1400 to 1500 GDD units. }, keywords = {rice,Hashemi cultivar,growing degree day,Phenological stages}, title_fa = {مقایسه درجه روز رشد مراحل مختلف فنولوژیکی برنج رقم هاشمی در استان گیلان}, abstract_fa = {به منظور بررسی تاثیر درجه روز رشد بر وضعیت رشد گیاه برنج تحقیقی در 16 مزرعه انتخابی در 8 شهرستان استان گیلان طی سال زراعی 95-94 صورت گرفت به طوری که هر شهرستان دارای دو مزرعه زودکاشت و دیرکاشت بود. در این مزارع، مدت زمان لازم برای رسیدن به مراحل مختلف فنولوژیکی برنج یادداشت­برداری شد. سپس برای محاسبه درجه روز رشد از داده­های دمای ایستگاه­های هواشناسی مربوطه استفاده شد و در نهایت نتایج به دست آمده از نظر زمان آغاز، خاتمه و میزان درجه روز رشد دریافتی در هر مرحله فنولوژی مقایسه گردید. نتایج نشان داد که مزارع زود کاشت و دیرکاشت فقط در مرحله 3 تا 4 برگی اختلاف معنی­داری با هم داشته­اند. مزارع مرکز و غرب استان تنها در مرحله رسیدگی فیزیولوژیکی، مزارع غرب و شرق در مرحله سفت شدن و مزارع مرکز و شرق استان در مراحل 3 تا 4 برگی، خوشه­دهی و رسیدگی فیزیولوژیکی با هم اختلاف معنی­داری داشتند. در تمامی شهرستان­ها، مرحله فنولوژیکی پنجه­زنی، بیشترین مقدار GDD را دریافت کرده و کمترین مقدار نیز مربوط به مراحل رسیدگی فیزیولوژیکی و شیری شدن بوده است. برنج رقم هاشمی، از مرحله نشا تا رسیدگی فیزیولوژیکی در سطح استان به طور میانگین 2/1284واحد حرارتی دریافت کرده است. در بین شهرستان­های استان، آستانه کمترین و انزلی بیشترین میزان دریافت GDD را در طول دوره آماری مورد بررسی به خود اختصاص داده­اند. کوتاه­ترین طول دوره رشد در شهرستان آستانه با 86 روز و طولانی­ترین طول دوره رشد نیز از شهرستان تالش با 104 روز بدست آمد. همچنین مشخص شد در مزارعی که کاشت در آن­ها زودتر صورت گرفته بود الزاماً برداشت زودتری نداشتند به عبارت دیگر طول دوره رشد آن­ها کوتاه­تر نشده است زیرا در روزهای ابتدایی کاشت میانگین دمای روزانه هوا پایین­تر بوده و در نتیجه گیاه GDD کمتری دریافت کرده است اما در مزارعی که کاشت در آن­ها دیرتر صورت گرفته بود به دلیل بالا بودن میانگین دما در روزهای ابتدایی کاشت میزان GDD بیشتری را دریافت کرده­اند به عبارتی مقدار GDD دریافتی در روزهای ابتدایی مزارع زودکاشت با تعداد روزهای کمتری در مزارع دیرکاشت به دلیل افزایش دما قابل جبران است. }, keywords_fa = {برنج,رقم هاشمی,درجه روز رشد,مراحل فنولوژیکی}, url = {https://clima.irimo.ir/article_132213.html}, eprint = {https://clima.irimo.ir/article_132213_32b5893eb16e2f619795845c3c60c030.pdf} }