@article { author = {Fattahi, Ebrahim and Didevarasl, Ali and Salehi Pak, Tahmineh}, title = {Calculation of Probable Maximum Precipitation 24-h (PMP 24-h) through statistical and synoptic methods over the southwestern basins of Iran}, journal = {Journal of Climate Research}, volume = {1398}, number = {39}, pages = {1-14}, year = {2020}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Introduction Probable maximum precipitation (PMP) is a theoretical concept that is widely used by hydrologists to arrive at estimates for probable maximum flood (PMF) which is applicable to the risk evaluation of hydraulic structures such as dams and to review the adequacy of their spillway capacities. The PMP indicates the greatest amount of precipitation that is meteorologically possible for an area at a particular time with a given duration. There are the various methods to estimate PMP based on the different intended durations. Material and Methods In the present investigation using the annual maximum 24-h precipitation data series of 36 synoptic stations in 4 southwestern basins of Iran, the PMP values have been calculated based on the statistical (Hershfield-1 and Desa methods) and synoptical/physical methods. The derived results from both methods statistically are compared together and to the mean precipitation values as well as the observational maximum 24-h precipitation values. Furthermore, the values are considered spatially over the country to find out the geographic distribution of the PMP ranges. The Hershfield method is a statistical method for estimating the PMP for small areas that has been developed by Hershfield (1965) based on a general frequency equation given by Chow (1951).The method considers the annual rainfall series of a raingauge or an area and can be used at any place where there is sufficient rainfall data and in particular to make estimates when other meteorological data such as dew point, wind etc are lacking. In the present investigation the annual maximum 24-h precipitation data series of 36 synoptic stations through a period of 22 years (1989-2010) over the Southwestern basins, have been provided from IRIMO. The selection of the stations was based on their geographic position and complete time-length of their data series over the study period of 22 years. Then, all data series have been arranged into a database center in Excel and GIS software. As aforementioned, The PMP values have been calculated based on the Hershfield-1 and Desa methods. Results the results showed that the PMP values derived from Hershfield-1 method were extremely higher/deviated comparing to the long term mean values as well as the observational maximum 24-h precipitation. The ratio of PMP helshfield-1 to the long term mean values was up to 265%, and to the maximum 24-h precipitation has been estimated about 4.66, in the southern stations with low rainfall. Whiles the Desa method estimated the PMP values more closer to the recorded maximum precipitation data, as obtained ratio for PMP of Desa to the long term mean values was about 119% and to the maximum 24-h precipitation has been estimated about 2.19. By the way, the coefficients of variation and SKEW-test affirmed the highest variability of maximum 24-h precipitation in the southern stations, as therein the CVs and SKEW-test results were obtained more than 40% and 0.65 respectively. So the PMP values could be unreliable over such southern stations with low and irregular rainfall. Coefficient of variations derived from PMP values of Hershfield-1 and Desa illustrated also a range of 24-72% and 22-67% respectively. As it is found the PMP values of Hershfield-1 could have more variability comparing to the outputs of Desa method. This difference is originated from Km (frequency coefficient) calculations which are various for each of two PMP estimation methods, as in the Desa calculation method, the highest event of maximum 24-h precipitation is ignored, hence the Km equation resulted a lower coefficient in contrast to what derived from Km calculation in the Hershfield-1 method. In the Physical method the storm happened in 16-17 November 1994 is selected as an example. For this method we applied the humidity factor to maximize the precipitation. The derived PMP through physical method illustrated the lowest PMP values comparing to the statistical methods showing a PMP range from 24 to 134mm respectively at Ahvaz and Masjedsolyman stations. In the next step the maps of the estimated PMP by both two statistical methods, and the observed maximum 24-h precipitation data, have been drawn through ArcGIS software and using the Kriging interpolation method. The maps illustrated the highest ranges of PMP and maximum 24-h precipitation over the center of the Karoon basin and southern areas of Jarahi basin. But, the northern basins of Marzi-gharbi and Karkheh have showed the lowest ranges.}, keywords = {Probable Maximum Precipitation,Physical method,Statistical method,Hershfield and Desa methods,4 southwestern basins of Iran}, title_fa = {برآورد آماری و همدیدی بارش بیشینه محتمل در حوضه‌های جنوبغربی ایران}, abstract_fa = {در این تحقیق با استفاده از سری داده های سالانه بارش بیشینه 24 ساعته 36 ایستگاه سینوپتیک در چهار حوضه جنوبغربی کشور به محاسبه بارش بیشینه محتمل از طریق روش آماری (هرشفیلد و هرشفیلد- دسا) و روش همدیدی (فیزیکی) پرداخته شده است. نتایج به دست آمده از روش آماری هرشفیلد نشان می­دهد که بارش بیشینه محتمل نسبت به بارش بیشینه 24 ساعته خیلی بیشتر از مقدار مورد انتظار بوده است(3تا 4.66). اما در روش دسا مقادیر بارش بیشینه محتمل در مقایسه با روش هرشفیلد کاهش یافته)  48/1 تا 19/2(.  ضرایب تغییرپذیری و چولگی محاسبه شده نیز نشانگر تغییرپذیری بالای مقادیر بارش بیشینه 24 ساعته در ایستگاه­های کم­بارش­تر منطقه نسبت به نواحی کوهستانی و پربارش­تر است. این وضعیت برآورد بارش بیشینه محتمل در بخش­های جنوبی و کم­­بارش حوضه­های مورد مطالعه را غیرقابل اطمینان­تر می­نماید. نتایج بدست آمده در روش همدیدی که رخداد توفان 16-17 نوامبر 1994 را مورد بررسی قرار داده است با حداقل بارش بیشینه محتمل  حدود 24 میلیمتر در ایستگاه اهواز و حداکثر134 میلیمتر در ایستگاه مسجد سلیمان نسبت به هر دو روش آماری فوق از مقادیر کمتر و نزدیک به واقعیت برخوردار بوده است.   }, keywords_fa = {بارش بیشینه محتمل,روش همدیدی,روش آماری,حوضه‌های جنوب‌غرب ایران,روش هرشفیلد و دسا}, url = {https://clima.irimo.ir/article_113600.html}, eprint = {https://clima.irimo.ir/article_113600_657f08bc07ca5574adccb75db0cd42e9.pdf} } @article { author = {Azizi, Ghasem and Moradi, Mohammad and rezaei, hossein}, title = {The Source and spatial - temporal distribution of Cut-off Lows over IRAN}, journal = {Journal of Climate Research}, volume = {1398}, number = {39}, pages = {15-28}, year = {2020}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Introduction Cut-off low pressure systems are defined as closed lows in the upper troposphere that have become completely detached from the main westerly current.These systems are generally identifiable at mid and upper levels, by closed geopotential meters around the low center. Cut-off low systems are closed cyclonic eddies isolated from the main western stream. These lows are upper and midtropospheric features and consequently they do not need to have a corresponding low at the lower levels of the troposphere (Palmen and Newton, 1969). However, sometimes a Cut-off low may start as an upper-level trough extending to the surface after its development. Its intensity is higher in the upper troposphere, decreasing downward and being even possible to find anticyclonic circulation at the surface. They are defined as mid and upper tropospheric cold lows, which generate and develop in the westerlies. A split of the westerlies and a breaking of mid and upper level jet stream appear simultaneously with the generation of the closed low (e.g.Ndarana and Waugh 2010). Cut-off lows are upper-level low-pressure areas formed on the equatorward side of the maximum westerly winds in the polar or the subtropical jet stream. Traditionally, Cut-off lows have been recognized as depressions mostly located in mid latitudes, which are characterized by closed geopotential contours in isobaric maps (with a cold core) that have more or less concentric isotherms around the central core Because the jet stream corresponds to the boundary between two very different air masses, the air mass trapped within a COL maintains its polar characteristics. Materials and methods The characteristics of Cut-off Lows in Iran are studied for the period 1976–2015. To identify these systems, the Raul Nieto algorithm was used with automatic detection capabilities. The systematic identification of Cut-off Lows is realized by applying an original automated scheme using mean daily geopotential height, U wind and air temperature at 500 hPa NCEP Reanalysis data. Results and discussion According to the results the main regions of Cut-off lows formation affecting Iran in the east, west and south of Turkey, the eastern Mediterranean, and the Syrian and Jordanian countries. The origin of these systems was also reviewed seasonally. In this study, Iran was divided into four regions and the frequency of Cut-off low in these areas was investigated. The results showed that the most frequent occurrence of these systems occurred in A region (northwest quarter of Iran) and then in region C (northeastern quarter). Out of a total of 628 cut-off low that affected Iran over the course of 40 years, 552 cut-off low have affected region of A (northwest quarter of the country). After that, the area C (quarter northeast) is passing through 283 cut-off lows. The country's B region (quarter of southwest), with 162 cut-off lows, is ranked the next. Eventually, the D region (southeast quarter of the country) has the lowest abundance with 87 cut-off low during the 40-year period. In order to study more precisely the spatial distribution of cut-off low in the quadric areas, we analyze the spatial distribution of these systems Seasonally. In all four seasons, the region with the highest frequency of cut-off low is A (northwest quarter). This is due to the northwest quadrant on the main cut-off low including Turkey, the Black Sea and the Eastern Mediterranean. In areas B and D, the highest incidence of cut-off lows belongs to the winter season. Due to the fact that the western winds in the southern regions are too late in the middle of fall season and It also leaves the area very early in the spring, in the middle of the spring season, Therefore, the only season in which western winds are fully present is the winter. Therefore, the highest abundance of cut-off lows in these two regions is in winter. In areas A and C, most of the cut-off lows is in the spring and then there is a relatively small winter season. In total, in the A region, 552 cut-off low was identified during the 40 years period. Which is an average of 13.8 events per year. 1982, with 19 cut-off low incidents, and in 1992, 1996, and 2012, with 18 incidents, are most frequent in area A. The least frequent cases belonged to 2001 with the occurrence of 8 and 1978 and 1985 with event 9 in area A. Conclusion According to the results the main regions of Cut-off lows formation affecting Iran in the east, west and south of Turkey, the eastern Mediterranean, and the Syrian and Jordanian countries. In this study, Iran was divided into four regions and the frequency of Cut-off low in these areas was investigated. The results showed that the most frequent occurrence of these systems occurred in A region (northwest quarter of Iran) and then in region C (northeastern quarter). It was also found that in areas A and C, the largest Cut-off lows occurred in the spring and in the B areas (southwest quarter) and D (southeast quarter) in winter. The annual distribution of snow in the four regions of Iran was also examined. So, during the statistical period of 40 years, in 1982 in all four regions of Iran, the highest frequency of Cut-off low occurred.}, keywords = {Cut-off Low,Nieto,Robeita,Iran}, title_fa = {محل شکل گیری و توزیع فضایی- زمانی کم ارتفاع های بریده موثر بر ایران}, abstract_fa = {کم ارتفاع های بریده به عنوان یک کم ارتفاع بسته درورد سپهرمیانی و بالایی تعریف میشوند که به طور کامل از جریان اصلی بادهای غربی جدا شده اند. کم ارتفاع بریده یکی از پدیده های اثرگذار بر اقلیم ایران میباشد .هدف از این مقاله بررسی میزان این اثرگذاری در مناطق مختلف ایران در زمان های متفاوت میباشد .ویژگی های کم ارتفاع های بریده در ایران، برای دوره 2015-1976 مطالعه گردید. برای شناسایی این سیستم ها از الگوریتم رائولنییتو، با قابلیت شناسایی خودکار، استفاده گردید. این الگوریتم از داده های میانگین روزانه ارتفاع ژئوپتانسیل ترازهای ۵۰۰ و 600 هکتوپاسکال، باد مداری در تراز۵۰۰ هکتوپاسکال و دمای تراز۵۰۰ هکتوپاسکال ، از پایگاه دادههای مرکز ملی پژوهشهای جوی ایالات متحده استفاده میکند. نتایج نشان داد که اصلی ترین مناطق شکل گیری کم ارتفاع های بریده موثر بر ایران در شرق، غرب و جنوب ترکیه، شرق مدیترانه و کشورهای سوریه و اردن می باشند. در این مطالعه ایران به چهار منطقه تقسیم گردید و فراوانی رخداد کم ارتفاع های بریده در این مناطق بررسی گردید. نتایج نشان داد که بیشترین فراوانی وقوع این سیستم ها در منطقه A (ربع شمال غرب ایران) و سپس در منطقه C (ربع شمال شرق) رخ داده است. همچنین مشخص گردید که بیشترین رخداد کم ارتفاع های بریده در مناطق A و C، در فصل بهار و در مناطق B (ربع جنوب غرب) و D (ربع جنوب شرق)، در فصل زمستان بوده است. توزیع سالانه کم ارتفاع های بریده در مناطق چهار گانه ایران نیز بررسی گردید بطوریکه در طول دوره آماری 40 ساله،سال 1982 در هر چهار منطقه ایران، بیشترین فراوانی کم ارتفاع بریده رخ داده است.}, keywords_fa = {کم ارتفاع بریده,کم فشار بریده,سردچال,ایران}, url = {https://clima.irimo.ir/article_113601.html}, eprint = {https://clima.irimo.ir/article_113601_288adea1eda60e2ed1f206d047630f3d.pdf} } @article { author = {pakzad, zahra and ramesht, mohammad hosein and Gandomkar, Amir}, title = {The Tracks of Rainy Western Systems and Their Climatic Context. Case Study: Zagros Kaykhosravy Area}, journal = {Journal of Climate Research}, volume = {1398}, number = {39}, pages = {29-40}, year = {2020}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {The title of this article has two new meanings that are not commonly used in classical climatology, and this implies a particular issue. These two terms are the clima- context and the Kaykhosaravy Zagroos. The first word implies a concept borrowed from the theory of genet (1930), and in the language of climatology means that the places contain a clima- context and these are forming the behavior of the climatic systems. The second word (Kaykhosaravy Zagroos) is a space concept used for one of the two most prominent rainy core and means the Zagroos hat. This research is based on the Anthropocene theory (the human age in which man became the dominant force on the earth's system.) and choes theory (in this theory, it is believed that in all phenomena there are points where a slight change in them will make great changes and This principle is particularly true in atmospheric and climate models}, keywords = {}, title_fa = {مسیر سامانه‌های بارش غربی و پیش زمینه‌های متن اقلیمی (نگاره اقلیمی) آن‌ها مورد مطالعه: منطقه کیخسروی زاگرس}, abstract_fa = {مقاله دارای دو مفهوم جدید در ادبیات اقلیم­شناسی است. این دو واژه عبارتست از متن اقلیمی (نگاره اقلیمی) و کیخسروی زاگرس واژه اول وام گرفته از نظریه ژنت نظریه­پرداز ساختارگرااست که ترجمان آن به زبان اقلیم­شناسی بدین معنی است که مکان­ها دارای متن یا نگاره اقلیمی هستند واین نگاره­های اقلیمی هستند که رفتار سامانه­های اقلیمی را شکل می­دهند. واژه دوم، یک مفهوم مکانی است که در این مقاله برای یکی از دو کانون پربارش ایران یعنی زاگرس مرکزی بکاربرده شده­ است. مسئله مهم بررسی نقش نگاره­های اقلیمی ایران بر رفتار سامانه­های غربی است، روش کار بیشتر متکی به پدیدارشناسی است و لذا اگر چه از داده­های اقلیمی بهره برده شده ولی این داده­ها در چارچوبی تاویلی تحلیل شده است. برای دستیابی به اهداف پژوهش ابتدا نقشه نگاره اقلیمی در محدوده 50-10 درجه شمالی و 75-20 درجه شرقی تهیه و 5 عامل موثر در تحلیل متن یعنی فشار، دما، بارش، رطوبت نسبی، و تبخیر در سطح 500 هکتوپاسگال برای یک دوره آماری از (2015-1980) تحلیل شد. سپس گونه­شناسی سامانه­های ورودی از غرب در یک بازه(2017-1987) ساله صورت گرفت وکریدور عبورسامانه­های غربی مشخص گردید. این روش این امکان رافراهم آورد که بتوان براساس روش ماتریس تفاضل داده­های اقلیمی، نگاره­های اقلیمی ایران مشخص و رفتار سامانه­ها دربرابر نگاره­های اقلیمی ارزیابی شود. بررسی­های فوق نشان ­داد که : *ایران دارای سه نگاره اقلیمی است.*سامانه­هایی که از کیخسروی زاگرس می­گذرند در دو تیپ بارش­زا و غیر بارشی طبقه­بندی می­شوند و برای آنکه بتوانند زایش بارشی داشته باشند تنها کافی است در کوهرنگ به میزان 2/2درجه سلیسوس دمای آنها کاهش یابد.*تالاب بین­المللی هور العظیم در متن اقلیمی (نگاره اقلیمی) ایران می­تواند نقطه نظریه آشوب در بارش­های زاگرس مرکزی باشد.}, keywords_fa = {متن اقلیمی (نگاره اقلیمی) “کیخسروی زاگرس “فضا و مثلث نیچ”,“ نظریه آشوب}, url = {https://clima.irimo.ir/article_113602.html}, eprint = {https://clima.irimo.ir/article_113602_bf9dfe930c383a035a48845a67b00076.pdf} } @article { author = {Hanafi, Ali}, title = {Identification of areas and precipitation regimes of the Republic of Azerbaijan with using cluster analysis}, journal = {Journal of Climate Research}, volume = {1398}, number = {39}, pages = {41-59}, year = {2020}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {IntroductionOne of the most interesting research areas of the scientific community in recent years is the study of the behavior and regimes of rainfall at the local, regional and global levels. At the proposal of the Intergovernmental Panel on Climate Change, rainfall changes should be comprehensively addressed in all areas (IPCC, 2007). The zoning and recognition of homogeneous climatic regions is one of the basic needs of planning. Climatic zoning is often based on the use of different climate variables in order to take into account the role of all variables in determining the climate of the regions. The main feature of rainfall in Iran is that the annual precipitation in the country is significant both in spatial and temporal terms. This spatial and temporal distribution of rainfall in Iran is affected by the distribution of global circulation systems, which has the slightest change in its pattern, causing extreme weather abnormalities. Therefore, spatial and temporal abnormalities of rainfall and severe changes in rainfall intensity and rainfall difference are the most important characteristics of rainfall in Iran (Babaei and Farajzadeh, 2002: 52). The temporal and spatial distribution of rainfall in Azerbaijan is also important due to its impact on Iranian water resources. In this study, it has been tried to analyze the cluster statistical methods to identify the zoning and zoning regime in Azerbaijan. To be Cluster analysis is a statistical method that clustering a set of individuals in terms of their similarity. Therefore, each cluster is a group whose constituents have the most similarity. There have been a lot of rainfall related to the parameters that can be mentioned.Masoudian (2005) determined the cluster analysis method for Iran rainfall and concluded that Iran has three main regimes: first winter precipitation regime, second winter / spring precipitation regime and third winter weather regime. Mohammadi (2011) investigated Iranian precipitation trend using data from 1437 stations of synoptic, climatic and barometric stations during a 40-year period and concluded that in the time series of Iran's precipitation and pixel average, there was a significant increase or decrease in the confidence level is 95 percent (Mohammadi, 2011). In an exploratory study, Younesi (2014) explores the climate of the Republic of Azerbaijan and concludes that the maximum rainfall of Azerbaijan occurs in the northern parts (highlands of Shah dagh and Bazarzdozo), southeast (Lankaran region) and western (Khan Kandi area). Masterzard (2014) study of the terrestrial climate in Afghanistan based on the daily rainfall data of the Aphrodite database. The results of this study have shown that the average rainfall in Afghanistan is 256 mm. The area has a maximum of two parts in the eastern region with 800 mm in terms of rainfall, and another in the northeast with 450 mm. Mefakheri et al. (2017) investigated the time and uniformity of precipitation in Iran. In this research, cluster analysis method for climatic zoning and to estimate the spatial and temporal dispersion of rainfall and spatial data, the coefficient of variation and uniformity of statistics have been used in three decades, years, and seasonal periods. Van et al. (2011) conducted a research entitled Spacecraft spatial trends in the Les Cheson plateau. The results showed that based on the non-parametric Mann-Kendall test, there are no significant changes in the precipitation trend of this region. Theodoro et al. (2016) studied the temporal and spatial variations of monthly rainfall in the Brazilian Mato Grosso region using a cluster analysis. Rao et al. (2017) evaluated the precipitation trend in the central and southern regions of Peru during the statistical period from 1965 to 2010. Using cluster and component analysis, they identified four areas of rainfall and examined the trend of rainfall changes in these areas.The country of Azerbaijan is important due to its neighbors with our country and because of its historical, cultural, ethnic and natural ties with Iran. Identifying its climate features is also one of the areas that can be of interest to Iranian researchers. This research has been done for this reason.Materials and methodsThe South Caucasus region includes the countries of Azerbaijan, Armenia and Georgia. Azerbaijan is located in the south of the Caucasus Mountains and north of the Aras River, near the Caspian Sea. In this study, the daily rainfall data of the Aphrodite database, which has a spatial resolution of 0.25 * 0.25 degrees, has been used in a statistical period of 60 years (1951-1951) to identify the rainfall regions of Azerbaijan. At first, rainfall data of 263 locations (pixels) located in the territory of Azerbaijan and adjacent regions were prepared from the base of Aphrodite, and then the average daily precipitation was calculated for these points and a 365 × 263 matrix was formed. This matrix was the basis for judging the peripheral regions and perihelion regimes of Azerbaijan. In order to identify the terrestrial and rainy regions of the country, the cluster analysis of the basin was used by integrating into MATLAB software.Results and discussionThe average annual rainfall of Azerbaijan is 397 mm. The maximum rainfall of Azerbaijan is observed at the northern altitudes of Shah Dagh and Bazarduzu, and low-lying areas in Lankaran with values 600 mm and a minimum rainfall in the central regions of Shirvan and Baku with values  300 mm. As the north and west of the region progress to the central and southern parts, the annual precipitation is also reduced. In Nakhchivan, the maximum rainfall of about 450 mm corresponds to the mountainous areas of the northeast and as far as the south and west of the Nakhchivan area advance, annual rainfall decreases.Precipitation is a climate whose amount changes continuously. By analyzing the cluster on the average annual rainfall in Azerbaijan, this country is divided into six districts. These areas are different in terms of precipitation and annual distribution. In general, the country of Azerbaijan is divided into two high rainfall (the Lankaran and high Caucasian) and low rainfall (coastal area and Baku). However, each of the high and low rainfall regions was divided into smaller areas and finally six areas were identified in Azerbaijan.In order to identify the regime of the country of Azerbaijan, a matrix with a size of 363 × 363 was formed, which represented 263 places per day in terms of percentage per day. On this basis, the first Euclidean distance of all spatial precipitation is measured every day. After measuring the Euclidean distance, a cluster analysis was performed by integration method on the interval matrix and 263 points were clustered in accordance with the degree of similarity. In general, the diet regime in Azerbaijan is divided into two types of rainy regimes: spring rainfall regime, which includes three sub-diet regimes (Nakhchivan regime, Northwest regime and central regime), and the most annual rainfall occurs during the spring and the autumn regime - Spring with two regimes (Lankaran regime and East Azarbaijan and Baku regime), in which the share of precipitation falls from the first year of precipitation and the spring precipitation is in the second place.The seasonal distribution of precipitation in Azerbaijan is as follows: in the west of the country and Nakhchivan, the regions receive the highest percentages of their annual precipitation in the spring, in which more than 38 percent of the annual precipitation falls this season. The regions in the eastern part of Azerbaijan, such as the cities of Baku and Lankaran, receive their most annual precipitation in the fall so that more than 35 percent of the annual rainfall in this season falls. Due to extreme cold weather in the winter season in the region of Azerbaijan and the Caucasus does not drop much, so that an average of 20 percent of the annual precipitation in the region occurs this season. The highest percentage of the country's winter rainfall is located in the east and the inshore peninsula, which is also located in Baku.Conclusion In this research, we have tried to investigate the cluster analysis of the regions and rainfall regimes in Azerbaijan. In order to study the regions and slopes of the Republic of Azerbaijan, the daily precipitation data of the Aphrodite database, which has a spatial resolution of 0.25 * 0.25 degrees, has been used for a period of 60 years (1951-2010). In order to identify the terrestrial and rainy regions of the country, the cluster analysis of the basin was used by integrating into MATLAB software. The average precipitation of Azerbaijan is about 397 mm. It is divided into two high and low rainfall regions. The high area is seen in two parts, one in the Lankaran area and one in the mountainous regions of the Caucasus and the small Caucasus in the northeastern and southwest of the country. The average annual rainfall in the low rainfall region (central areas) is about 290 mm, and the average rainfall in high-rise areas (Lankaran and Caucasus heights) is about 565 mm. The low rainfall area also includes central regions and Nakhchivan. In Azerbaijan, the country is divided into two types of rainy regimes: spring rainfall regime, which includes three sub-diet regimes (Nakhchivan regime, Northwest and central regime), and the most annual rainfall in these areas occurs in the spring and autumn diet with two sub-diet regimes (Lankaran regime and East Azarbaijan and Baku regimes), in which the share of precipitation falls from the first year of precipitation and the second in spring.}, keywords = {Precipitation regime,Cluster analysis,Ward methodology,Azerbaijan}, title_fa = {شناسایی نواحی و رژیم‌های بارشی کشور جمهوری آذربایجان با استفاده از تحلیل خوشه ای}, abstract_fa = {به منظور ارزیابی بارش و شناسایی نواحی و رژیم ها بارشی کشور جمهوری آذربایجان از داده های بارش روزانه پایگاه داده آفرودایت[1] با تفکیک مکانی 25/0 در 25/0 درجه قوسی، برای یک دوره 60 ساله ( 2010- 1951) استفاده شده است. ابتدا داده‌های بارش مربوط به 263 مکان ( پیکسل) که در محدوده کشور آذربایجان و مناطق مجاور قرار داشتند از پایگاه آفرودیت تهیه گردید و سپس میانگین بارش روزانه مربوط به این نقاط محاسبه گردیده و یک ماتریس 263*365 تشکیل گردید. در ادامه به منظور شناسایی نواحی بارشی و نیز رژیم‌های بارشی کشور آذربایجان از تحلیل خوشه ای پایگانی به روش ادغام وارد در نرم افزار متلب[2] استفاده گردید. نتایج حاصل نشان داد که میانگین بارش کشور آذربایجان در حدود 397 میلی متر می باشد که در مرتبه اول به دو ناحیه پربارش و کم بارش تقسیم می گردد. در مقیاس پایین تر هر یک از نواحی پربارش و کم بارش به نواحی کوچک‌تری تقسیم گردیده و در نهایت شش ناحیه بارشی در کشور آذربایجان شناسایی گردید. منطقه پربارش شامل قفقاز بزرگ ( ارتفاعات شاه داغ و بازاردوزو)، قفقاز کوچک ( منطقه قره باغ) و منطقه جنوب شرقی لنکران می باشد و منطقه کم بارش شامل بخش مرکزی جلگه کورا و آران و منطقه ساحلی آبشوران می باشد. میانگین بارش سالانه در ناحیه کم بارش ( بخش مرکزی و آبشوران) در حدود 290 میلی متر و میانگین بارش در نواحی پربارش ( ناحیه لنکران و ارتفاعات قفقاز بزرگ و کوچک) در حدود 565 میلی متر می باشد. از لحاظ رژیم بارشی نیز در حالت کلی کشور آذربایجان به دو رژیم بارشی تقسیم می‌گردد که عبارت‌اند از: رژیم بارش بهاره که شامل سه رژیم بارش فرعی (رژیم نخجوانی، رژیم شمال غرب و رژیم مرکزی) است و بیشترین بارش سالانه در این مناطق در فصل بهار اتفاق می‌افتد و رژیم پاییزه – بهاره با دو رژیم بارش فرعی (رژیم لنکرانی و رژیم شرق آذربایجان و باکو) است که در آن سهم بارش‌های پاییزه از بارش سالانه در رتبه اول و بارش‌های بهاره در رتبه دوم قرار دارد.}, keywords_fa = {رژیم بارش,تحلیل خوشه ای,روش وارد,جمهوری آذربایجان}, url = {https://clima.irimo.ir/article_113687.html}, eprint = {https://clima.irimo.ir/article_113687_fb74f8cb6e4c147f7c91c87e17dc2b09.pdf} } @article { author = {Zare, Hossein and Bannayan, Mohammad and Nasiri mahalatti, Mehdi and sanaei nejad, Hossein and Eshtrak, Tiloo}, title = {Introducing and evaluating a robust statistical model to estimate wheat LAI from satellite data in different climatological locations}, journal = {Journal of Climate Research}, volume = {1398}, number = {39}, pages = {61-74}, year = {2020}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {}, keywords = {}, title_fa = {معرفی و ارزیابی مدلی پایدار برای تخمین شاخص سطح برگ گندم بوسیله تصاویر ماهواره‌ای در شرایط اقلیمی متفاوت}, abstract_fa = {تخمین دقیق شاخص سطح برگ به عنوان یکی از متغیرهای کلیدی اکوسیستم دارای اهمیت فراوانی می‌باشد. هدف از این تحقیق معرفی مدلی مناسب جهت برآورد شاخص سطح برگ گندم بوسیله NDVI محاسبه شده از تصاویر لندست و مقایسه دقت آن با مدل‌های رایج آماری می‌باشد. در این راستا، داده‌های چندساله در دو منطقه در جنوب غرب آلمان برای واسنجی و اعتبارسنجی مدل‌های تجربی، نیمه تجربی و مدل معرفی شده در این مقاله با نام NPLE مورد استفاده قرار گرفت. سپس مقادیر بهینه پارامترهای هر مدل برای ارزیابی در مزارع آستان قدس مشهد استفاده شد. مدل‌های مورد ارزیابی عبارتند از: 1- وینا (مدل تجربی سه پارامتری). 2- لیو (مدل نیمه‌تجربی با دو پارامتر تجربی و یک پارامتر مربوط به ضریب خاموشی). 3- چادوری (مدل نیمه تجربی با پارامتر ضریب خاموشی) و 4- NPLE (مدل تجربی بدون پارامتر) و 5- نسخه اصلاح شده‌ی NPLE که در آن بجای NDVI از درصد پوشش گیاهی استفاده شده است. نتایج نشان داد که مدل‌های NPLE و وینا دارای خطای بیشتری نسبت به بقیه مدل‌ها بودند. مدل لیو، چادوری و NPLE اصلاح شده دارای خطای قابل قبولی در واسنجی و اعتبارسنجی بودند (RMSE~0.30). در مرحله ارزیابی مدل‌ها در مشهد، مدل NPLE اصلاح شده و چادوری بهترین نتیجه را داشتند، در حالی که مدل‌های دیگر دارای خطای سیستماتیک بالایی بودند، این مطلب نشان می‌دهد که مقادیر بهینه بدست آمده برای پارامترهای مدل‌های لیو و وینا با تغییر مکان آزمایش (مشهد) معتبر نمی‌باشند. بدلیل کمتر بودن و همچنین غیر سیستماتیک بودن خطای پیش بینی در مدل NPLE اصلاح شده، پیشنهاد می‌شود که خروجی این مدل در مطالعات واسنجی مدل‌های زراعی مورد استفاده قرار گیرد}, keywords_fa = {تخمین سطح برگ,مدل آماری,سنجش از دور,شاخص گیاهی}, url = {https://clima.irimo.ir/article_113688.html}, eprint = {https://clima.irimo.ir/article_113688_5a4ffa25b357409f93de4396f7a5e72e.pdf} } @article { author = {amiri, shervin and Najafi, Fahimeh and Mohammadi, Leila}, title = {Assessment of utilizing the ground-based radio occultation for monitoring the relative humidity and lower atmosphere layers pressure by using the GPS signals in Iran}, journal = {Journal of Climate Research}, volume = {1398}, number = {39}, pages = {75-88}, year = {2020}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Introduction The typical method in meteorology organizations for derivate the profiles of atmospheric parameters variations, is the meteorology balloon equipped with radiosondes. In each its ascent and in 2 hours period of flight, it can derivate the different heights data from the earth surface to 30 km from the sea level. Considering the high costs of radiosonde transmitters, meteorology stations are able to just one or maximum two launches per day, generally. Therefore, this limitation causes to reduction of the time accuracy of the atmospheric variations forecasts in heights, specifically the relative humidity. Consequently, it decreases the prediction of atmospheric conditions in seasons like spring that the conditions even vary hourly. Materials and Methods   Utilizing the complementary methods, covering these disadvantages and making it possible to assess the atmospheric conditions more times throughout the day, is too considered by the world meteorology research centers.Nowadays, new applications of navigation satellites systems like GPS and GLONASS are considered in the field of meteorology. According to preliminary tests conducted in China, it was found that by inserting a GPS receiver with a 360 degree field of view on a 5-km-high mountain, 80 to 100 latency events are detectable.The same coefficient of refraction can be calculated on a daily basis. This information, which can be converted to atmospheric parameters, is located around the receiver's location. The results obtained from this method and its comparison with the data extracted from the radiosonde indicate that it is reliable. This is the method. In order to provide the necessary conditions for conducting such tests in Iran, high points were selected for placing MBRO receivers. Recent years, derivation of the atmospheric parameters by using the radio occultation, has become a practical method. Ground-based radio occultation is a novel technique for exploring the lower atmosphere parameters. In this research, a simulation of ground-based radio occultation has been carried out, on Damavand Mountain, Sabalan Mountain in the northwest region, and Bazman Mountain in the southwest of Iran and the atmospheric parameters derivation program based on this method has been implemented. Also for verification, Atmospheric parameters derived by MBRO such as relative humidity and water vapor pressure, on Damavand mountain in two different days are compared to radiosondes data of Mehrabad region and the result shows that curves of ground-based radio occultation has fine confirmation with radiosondes curves. As experiments in other countries, MBRO is an affordable method for exploring the variation of lower atmosphere and a complementary method of radiosondes for gathering the lower atmosphere data. Resutls In this paper, the concept and function of the Mountain based radio occultation (MBRO) method are presented and the results are evaluated by simulation and comparison method. The simulation results show that with the placement of MBRO receivers in different mountains of Iran, a suitable coverage of tangent points can be obtained. The amount of this coverage and the number of occultation phenomena and the length depend on the geographic location of the receiver's placement and its height. The maximum duration of the satellite's exposure to the occultation in Iran is about 20 minutes. By obtaining these tangential points in the desired areas and determining the bending strength of each received signal, and using partial bending which is obtained due to reception of a positive and negative upward angle signal in the receiver, we can obtain the refractive index of the barley At high altitudes below the receiver's location and therefore atmospheric parameters reached low altitudes, and due to the large amount of latency information in the range of several hundred kilometers of high points in Iran at a low cost, measurements performed by radiosonde in shorter time intervals were completed. Improve weather forecasts and short-term forecasts. We simulate the simulation on the mountains (Damavand, Sabalan, Bazman). At the end of the comparison between the results of the application of Layer Radio latency on Mount Damavand in two different seasons with Radiosonde information located at Mehrabad Airport and its results are presented. When receiver combined with receivers that can receive other signals from satellite navigation satellites such as Glonass and Galileo, the available data volume and accuracy of results will increase significantly. The evaluation shows that the use of ground-based radio occultation method due to increased extraction of atmospheric data, especially at low altitudes, has a significant effect on raising the accuracy and speed of meteorological forecasts and increasing its efficiency in warning at the time and reducing the damage caused by phenomena such as flood.}, keywords = {Mountain Based Radio Occultation,Atmospheric parameters,Radiosonde}, title_fa = {ارزیابی بکارگیری نهفتگی رادیویی زمینپایه جهت رصد تغییرات رطوبت نسبی و فشار لایههای جو پایین در کشور}, abstract_fa = {امروزه کاربردهای نوینی از سیستم ماهواره‌های ناوبری مانند GPSدر زمینه­های هواشناسی مطرح شده است. استخراج پارامترهای جوی با استفاده از روش نهفتگی رادیویی با توجه به قرارگیری ماهواره‌های ناوبری GPSدر مدار زمین، در سال­های اخیر به یک روش کاربردی تبدیل شده است. نهفتگی رادیویی زمین‌پایه یک تکنیک نو برای کاوش جو پایین می‌باشد. در این پژوهش شبیه‌سازی ای از نهفتگی رادیویی زمین‌پایه­ بر روی کوه دماوند، کوه سبلان در منطقه شمال غربی و کوه بزمان در جنوب غربی ایران انجام شده و برنامه استخراج داده­های جوی با استفاده از این روش پیاده­سازی شده است. اعتبار داده­های بدست آمده از پدیده نهفتگی رادیویی زمین‌پایه بر روی قله دماوند در دو روز متفاوت مورد بررسی قرارگرفته است. پارامترهای جوی بدست آمده از این روش با داده‌های رادیوسوند واقع در منطقه مهرآباد مورد ارزیابی قرارگرفته و نتیجه نشان می‌دهدکه نمودارهای بدست آمده از روش نهفتگی رادیویی زمین‌پایه مطابقت خوبی با نمودارهای رادیوسوند در منطقه دارد. همانطور که در کشورهای دیگر نیز آزمایش شده، روش نهفتگی رادیویی زمین‌پایه به عنوان یک تکنیک نو و اقتصادی برای کاوش تغییرات جو پایین و روش مکمل رادیوسوند برای جمع‌آوری داده‌های مربوط به جو پایین است که از اهمیت به سزایی برخوردار می­باشد و موجب بالا بردن دقت پیش‌بینی­های هواشناسی در کشور می­شود.}, keywords_fa = {نهفتگی رادیویی زمین‌پایه,پارامترهای جوی,رادیوسوند}, url = {https://clima.irimo.ir/article_113689.html}, eprint = {https://clima.irimo.ir/article_113689_657cb51538a96dd40090a13a0dc791fc.pdf} } @article { author = {Bararkhanpour, Sedighe and Ghorbani, Khalil and Salari Jazi, Meysam and Rezaei Ghaleh, Laleh}, title = {Study of Seasonal and Annual Rainfall Changes with Quantile regression method (Case Study: Gorgan Hashem-Abad Station}, journal = {Journal of Climate Research}, volume = {1398}, number = {39}, pages = {89-104}, year = {2020}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Abstract Introduction: Precipitation is an important meteorological variable throughout time and place, and affects many phenomena and events in the contexts of agriculture, environment, natural resources, human activities, and etc. The study of variations in precipitation at different time scales is of great importance. Investigating precipitation’s seasonal time scale can be indicative of the variation pattern of this variable within a year, and its interpretation is beneficial in understanding both the patterns of wet and dry periods within a year and also seasonal hydrological components, while the investigation of annual time scale in a region can significantly be effective in better understanding the changes in the hydrological cycle in the studied area. Therefore, understanding the variability of hydrological processes and their associated statistics is essential for better water resource management.  Also, the changes in when the precipitation begins, can cause variations in the length of wet and dry periods. According to the impacts climate variables have on human and environment, it is necessary to review any changes in these variables over time. The use of the non-parametric Mann-Kendall test to examine the trend in the data series is a common method, which the analysis derived from it can lead to an initial understanding to find out whether the data is random (with no trend) or a trend exists within the data series being studied, but to better understand changes in a variable over time, it is better to examine the changes in different quantiles. The data series consists of events of varying intensities and quantities, and it is therefore necessary to study the deciles or percentiles of the series in order to investigate the aligned or non-aligned probability change. For this purpose, a quantile regression is suggested. In this study seasonal and annual precipitation of the Hashem Abad station in Gorgan was studied. Materials and Methods: The study area is the synoptic meteorological station of Hashem Abad, Gorgan, with an average annual rainfall of 550 mm and an average temperature of 18 ° C, which has a Mediterranean climate. At this station, weather data have been collected since the year 1984. In this study, precipitation data was used by the end of year 2017. After the establishment of seasonal and annual time series, non-parametric Mann-Kendall tests, Sen slope and quantile regression tests were performed and the results were compared.  Results and Discussion: The results of the Mann-Kendall test and ordinary linear regression showed that the precipitation has a significant decreasing trend only in spring, and the remaining seasons as well as the annual precipitation are of no trend. But the quantile regression shows a number of different results, so that not all the quantiles do follow the same slope in a time series, and even in a series, some of the quantiles have an increasing slope while others have a decreasing slope. In the spring, the mid-range quantiles have a significant decreasing slope, but in the rest of quantiles, there is a decreasing and non-significant slope. In the summer, the upper quantiles are of increasing slope while lower and mid-range quantiles have decreasing slope, and these slopes confirm the existence of a significant increasing statistical trend in only extreme upper quantiles. In the autumn, in many quantiles, there is an increasing positive slope, and only in the extreme lower and upper quantiles a decreasing and negative slope is visible. These slopes show a significant decreasing trend in the extreme lower quantiles. In the winter, in the upper quantiles, show an increasing and positive slope, but in the mid-range and lower quantiles, demonstrate a decreasing and negative slope. These slopes are statistically significant in many quantiles. On an annual scale, like the winter, the upper quantiles are of increasing slope and the lower and mid-range quantiles are of decreasing slope. These slopes are non-significant in many cases, and only in extreme lower quantiles a significant decreasing trend exists.  Comparison of the existing significant trends using different regression methods suggests that the quantile regression method is considered to be useful in estimating extreme precipitations trend that cannot be evaluated by the Mann-Kendall and ordinary linear regression methods.  Final conclusion: A comparative study of the results of the Mann-Kendall and ordinary linear regression methods shows that both methods depict the similar variations, but the magnitude of the variations in the Mann-Kendall method is estimated more than linear regression. Also, the results of this study indicate that changes in different quantiles of data may have a significant difference in direction and quantity with the changes in the mean or average of data, and therefore, it is necessary to study and analyze the quantile regression method in order to properly understand the changes in time series of seasonal and annual precipitation data.}, keywords = {Precipitation,quantile regression,Mann-Kendall,Ordinary linear regression}, title_fa = {مطالعه روند تغییرات فصلی و سالانه بارش با روش رگرسیون چندک (مطالعه موردی: ایستگاه هاشم‌آباد گرگان)}, abstract_fa = {بارش یکی از متغیرهای هواشناسی است که مقدار آن در زمان و مکان از تغییرات زیادی برخوردار است و بر بسیاری از پدیده‌ها و رویدادها در زمینه‌های کشاورزی، محیط‌زیست، منابع ‌طبیعی، فعالیت‌های بشری  مؤثر است. لذا با توجه به تأثیرپذیری انسان و محیط‌زیست از بارش، می‌بایست هرگونه تغییر در این عوامل در طول زمان مورد بررسی قرار گیرد. از روش‌های مرسوم جهت بررسی روند در سری داده‌ها، استفاده از آزمون من‌کندال می‌باشد. در صورتی‌که سری داده‌ها متشکل از وقایعی با شدت‌ها و مقادیر مختلف می‌باشد،  لازم است تا دهک‌ها یا صدک‌های سری به منظور تغییر احتمالی مورد بررسی قرارگیرد. بنابراین در این پژوهش، در کنار آزمون من‌کندال و رگرسیون خطی معمولی، از روش رگرسیون چندک نیز  برای بررسی روند فصلی و سالانه بارش در ایستگاه سینوپتیک هاشم‌آباد گرگان در طول سال‌های ۱۳۹۶-۱۳۶۳ (۲۰۱۷-۱۹۸۴ میلادی) استفاده گردید. نتایج آزمون من‌کندال حاکی از وجود روند کاهشی معنی‌دار بارش تنها در فصل بهار می‌باشد. بررسی مقایسه‌ای نتایج روش‌های من-کندال و رگرسیون خطی معمولی نشان می‌دهد که هر دو روش جهت تغییرات را به طور مشابه نشان می‌دهند اما بزرگی تغییرات در روش من-کندال بیشتر از روش رگرسیون خطی می‌باشد.  نتایج رگرسیون چندک نشان می‌دهد که تمام چندک‌ها در یک سری زمانی، از شیب یکسانی تبعیت نمی‌کند و حتی ممکن است در یک سری، برخی چندک‌ها دارای شیب افزایشی و برخی دارای شیب کاهشی باشند. همچنین نتایج نشان داد که از نظر معنی‌داری شیب، در فصل بهار، چندک‌های میانی شیب کاهشی ولی در فصل‌ تابستان، چندک‌های بالایی شیب افزایشی دارند. در فصل پاییز چندک‌های پایینی دارای روند کاهشی و در فصل زمستان چندک‌های میانی روند کاهشی، اما چندک‌های بالایی روند افزایشی  دارند و همچنین در سری سالانه بارش، چندک‌های پایینی دارای شیب کاهشی بارش می‌باشند که به طور کلی می‌توان اظهار داشت که بر ترسالی‌های شدید و خشکسالی‌های شدید افزوده شده است.}, keywords_fa = {بارش,رگرسیون چندک,من-کندال,رگرسیون خطی معمول}, url = {https://clima.irimo.ir/article_113692.html}, eprint = {https://clima.irimo.ir/article_113692_74c802783684d74b7f658fef43671e75.pdf} } @article { author = {MousaPour, Mostafa and Feizizadeh, Bakhtiar and Hosseini, Syed Akbar and Kerchi, Hasan and Azadeh, Seifi}, title = {Comparison performance of artificial neural network, support vector machine and object-oriented model for monitoring snow cover surface changes using Landsat multi temporal images (Case study: Alvand mountain)}, journal = {Journal of Climate Research}, volume = {1398}, number = {39}, pages = {105-121}, year = {2020}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Expanded abstract:  snow is one of the most important forms of precipitation in hydrology cycle in mountainous basin which plays an important role on agricultural and domestic water supply resources as delayed flows in high flow seasons and minimal flow in low flow seasons and energy production. today, the use of remote sensing data is applied at obtaining the area of accurate snow cover data in the efficient management of water resources. The purpose of this study is to determine the changes in snow cover in alvand mountains of hamedan using of remote sensing. The research method is using of artificial neural network classification, support vector machine, and object oriented model, that with using of the most appropriate method among them has been calculated, the amount of snow cover area variations in different time series. Alvand mountain in hamadan province is located between hamedan, tuyserkan, asadabad and bahar. Its highest mountaintop, called alvand, is located 18 kilometers south of hamadan city and is 3584 meters above sea level. The direction of this mountain is drawn from the northwest to the southeast and the hamedan province divides into two northern and southern halves. The data used in this study include sensor images MSS, TM, ETM +, and OLI Landsat satellite in the time series of 1975, 1986, 1993, 2001, 2008, and 2018. To prepare a map of changes the snow cover area, was carried out processing operations on satellite images in three stages: preprocessing, processing, and post processing. Similar spectral separation and division of the class which has the same spectral behavior are called satellite information classification. The main purpose of classification of digital images is to create subject maps. In recent years, new approaches have been proposed to concurrent with the advancement of image computer processing technology, for example, the use of neural networks, tree decisions, and methods derived from fuzzy logic theory, the use of secondary information such as texture, background and ground effects are the most important of these methods. An artificial neural network algorithm is a method in the field of machine learning and artificial intelligence that eventuates from the human nervous system to analyze complex nonlinear models and parallel computing systems. One of the advantages of artificial neural networks is that they are independent of the assumption of statistical distribution. Neural networks are nonlinear and can transform the input data into a desired output as a complex mathematical function. Support vector machine is a sample classification method that first time was introduced by Vladimir vapnik. This method is a non-parametric supervised statistical method to classify the classes in the training data, super surface practice on them. The support vector machine is one of the supervised classification algorithms that predict every sample stand in which class or group. This algorithm has less sensitive to the phenomena of multidimensional space, for this reason, it is a suitable method for the classification of multi-spectral and hyperspectral data. One of the advantages of a support vector machine algorithm is to provide a good classified image resolution with small training samples. In recent years, many research has been carried out on the applications of fuzzy logic in remote sensing, have largely been based on object oriented methods, in addition to numerical values, is used the data of texture, shape and tone color, in classification process. The ability to classify the base pixels method is limited when different ground objects are recorded with the same numeric values on a digital image. The object oriented classification method has been proposed to solve this problem. One of the clearest difference between the basic image pixel processing and object oriented image processing are in processing of object oriented image, the processing basic units are image objects or segments, not single pixels, the other difference is that the classification in object-oriented image processing is soft classification, which is based on fuzzy logic. After operation preprocessing on satellite images, maps of classification the snow cover area was provided of this three mentioned method from alvand mountain. Then the validity of these methods was evaluated. This research specified that object oriented model, support vector machines and artificial neural network have the highest accuracy respectively and thus changes of snow cover area were calculated in different time series using the object-oriented method. The snow cover area obtained using of the object-oriented model were 630, 611, 414, 151, 242, 154 square kilometers in 1975, 1986, 1993, 2001 ,2008 and 2018 respectively, indicating the area of the snow cover have diminished significantly from 1975 to 2018 in the alvand mountains.}, keywords = {Remote Sensing,Artificial Neural Network,Support Vector Machine,object base,alvand mountain}, title_fa = {مقایسه عملکرد شبکه عصبی مصنوعی، ماشین بردار پشتیبان و مدل شیءگرا در پایش تغییرات سطح پوشش برف با استفاده از تصاویر چند زمانه لندست (مطالعه موردی: کوهستان الوند)}, abstract_fa = {پوشش برف و تغییرات زمانی آن، از پارامترهای اساسی در بررسی­های هیدرولوژیکی و اقلیم شناسی می­باشند. امروزه با استفاده از تصاویر ماهواره­ای می­توان به ارزیابی تغییرات سطح پوشش برف در سری­های زمانی مختلف پرداخت. پژوهش حاضر با هدف پایش تغییرات سطح پوشش برف در کوهستان الوند همدان با استفاده از داده­های رقومی ماهواره لندست در سری­های زمانی سال­های 1975، 1986، 1993، 2001، 2008 و 2018 انجام گرفته است. روش تحقیق در این پژوهش، استفاده از طبقه­بندی شبکه عصبی مصنوعی، ماشین بردار پشتیبان و مدل شیء گرا جهت برآورد سطح پوشش برف بوده است که پس از انجام عملیات پیش پردازش بر روی تصاویر ماهواره­ای، نقشه­های طبقه­بندی سطح پوشش برف کوهستان الوند از روش­های شبکه عصبی، ماشین بردار پشتیبان و مدل شیءگرا تهیه گردید. سپس صحّت این روش­ها مورد ارزیابی قرار گرفت. پژوهش حاضر نشان داد به ترتیب، مدل شیءگرا، ماشین بردار پشتیبان و شبکه عصبی مصنوعی دارای بالاترین میزان دقت بودند، لذا تغییرات مساحت سطح پوشش برف در سری­های زمانی مختلف، با استفاده از روش شیءگرا محاسبه گردید. مساحت بدست آمده برای سطح پوشش برف در کوهستان الوند با استفاده از مدل شیءگرا به ترتیب عبارت بودند از، سال 1975 برابر با 630 کیلومتر مربع، سال 1986 برابر با 611 کیلومتر مربع، سال 1993 برابر با 414 کیلومتر مربع، سال 2001 برابر با 151 کیلومتر مربع، سال 2008 برابر با 242 کیلومتر مربع و سال 2018 برابر با 154 کیلومتر مربع که نشانگر کاهش چشمگیر سطح پوشش برف از سال 1975 تا سال 2018 در کوهستان الوند می­باشد. }, keywords_fa = {سنجش از دور,شبکه عصبی مصنوعی,ماشین بردار پشتیبان,مدل شی گرا,کوهستان الوند}, url = {https://clima.irimo.ir/article_113695.html}, eprint = {https://clima.irimo.ir/article_113695_407f293f995ffa636aa8223d38da65e8.pdf} } @article { author = {Sobhani, Behroz and safarian, Vahid and seddignia, Abbasali}, title = {Agro- Climate zonation of grapevine cultivation in Qare-Sou watershed using novel multi-criteria methods}, journal = {Journal of Climate Research}, volume = {1398}, number = {39}, pages = {123-138}, year = {2020}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Introduction The growth and development of plants depends on the genetic structure and the environment and water conditions (Creasy, 2009: 24). One of the basic ways for agricultural development is optimal land use, in accordance with climatic conditions. Essentially, it is necessary to recognize different factors, such as stability factors (elevation, soil, slope) and unstable factors (climate factors). Grapes are grown throughout the world and used alone in a variety of products. Grape cultivation is one of the major horticultural industries, with its cultivated area in the world of 7.9 million hectares (Mohammadi, 2013: 58). In general, the aim of this study was to find new areas for grape cultivation in Qare-Sou basin, considering the water conditions and vegetative needs of the grapevine, and, by investigating and identifying the positive and negative factors, the spread of cultivation Grapes or limiting it around the study area. Materials and methods Calculate the degree of growth day index Plant growth, like all biological phenomena, depends on the thermal power of the environment. The growth of each plant begins at a certain temperature threshold. For example, the grape threshold is 10 degrees centigrade. In this research, Equation 1 was used to calculate GDD (Mousavi, 1393: 117). GDD = (Tmax +Tmin )/2-Tbase In this equation, TMAX is the maximum temperature, Tmin is the minimum temperature and Tbase is the threshold temperature or plant's base temperature. If the day is zero or negative, then that day will not affect growth. So, we can calculate the GDD index for each station with the average temperature of each month and convert it to the average daily temperature and base temperature (for grapes 10) (Mousavi, 1393: 117). Average temperature during growth (T) For its calculation, Equation 2 is used, which means the average temperature of the plant growth moths that has been accumulated since the onset of the growth of the plant, which begins with germination and ends with the arrival of the grape fruit, and computes the average(Mousavi, 1393: 117). Techniques used in this research 1. Saw SAW method 2- Multimora Results and discussion First, by drawing maps in the GIS environment, we conclude that east of the river is not suitable for the cultivation of grapes, and as the west moves up, the preference for cultivating grapes increases, this priority in the northern part of Meshkin shar has reached the right place and again, as we go north stream, the priority of grape cultivation has been reduced, however, this reduction is not as high as the east mound, and the Mashiran area is considered medium for cultivation, as in the Lahrud region, but the boundary partially differs in different methods. In addition, in all methods around Kaleybar, the most suitable and best area for grape cultivation was obtained. Secondly, by interpreting the graphs and maps from the potential evapotranspiration calculations, we conclude that as we go from east to the westside of the river, the water requirement of the region increases due to high evapotranspiration and negative balance of water. Conclusion Investigations carried out with five different methods in Chapter 4, it can be concluded that most of the Qare-Sou and surrounding areas are suitable for grapevine cultivation. Grapes have a little need for water in relation to the currently cultivated crops, as well as a diverse and diverse nutritional value, high pharmaceutical value, high health and treatment, and the glacial effect due to the delay in the beginning of grape germination and water diversity And the region's airspace and the existence of the river are less than the surrounding area. Therefore, with better management, it is possible to prevent waste of water in the area and, at a lower cost, produce a valuable, nutritious and profitable product. By using five different methods, it can be concluded that most of Qarhosu and its surrounding areas are suitable for grapevine cultivation. Grapes have a little need for water in relation to the currently cultivated crops, as well as a diverse and diverse nutritional value, high pharmaceutical value and high health and treatment, as well as glacial effects due to the delay in the beginning of grape germination and water diversity. And the region's airspace and the existence of the river are less than the surrounding area. Therefore, with better management, it is possible to prevent waste of water in the area and, at a lower cost, produce a valuable, nutritious and profitable product.}, keywords = {}, title_fa = {پهنه‌بندی آگروکلیماتیک کشت انگور در حوضه آبخیز قره سو با استفاده از روش‌های نوین چند معیاره}, abstract_fa = {هدف از این پژوهش،‌ شناسایی نواحی مستعد برای کشت انگور در حوضه آبخیز قره­سو با توجه به شرایط آبو هوایی منطقه مورد مطاله است.مراحل پژوهش حاضر عبارتند از: مرحله اول جمع­آوری داده­های اقلیمی از ایستگاه­های هواشناسی اردبیل، ‌اصلاندوز، اهر، سرعین، فرودگاه، کلیبر، ‌مشکین­شهر مشیران، و نمین. مرحله دوم محاسبه و مشخص کردن شاخص­های فنولوژیکی که برای رشد انگور از جمله، بارش­های سالانه و فصلی، میانگین دما در طول دوره رشد، درجه روز رشد، رطوبت نسبی و ساعت آفتابی در بازه زمانی 20 ساله (2017-1998). مرحله سوم استفاده از روش‌های سلسله مراتبی، مولتی مورا و ساو برای تصمیم گیری بهتر و تعیین ارجحیت کشت انگور می‌باشد.نتایج حاصل از تحلیل نقشه­ها نشان دادکه نواحی شرقی حوضه قره سو از قبیل ایستگاه های اردبیل، نیر و نمین با توجه به شرایط دمایی و طول روز نامناسب، نواحی مرکزی و غربی از قبیل ایستگاه های مشکین شهر، مشیران، دوست بیگلو و لاهرود با توجه به شرایط دمایی، درجه روز و بارش مناسب و نواحی جنوبی حوضه در ایستگاه کلیبر به علت شرایط مطلوب اقلیمی خیلی مناسب برای کشت انگور می باشد.  هم‌چنین نمودارها و نقشه‌های حاصل از محاسبات تبخیر و تعرق پتانسیل نشان می‌دهد که در نواحی مرکزی، غربی و جنوب حوضه قره سو نیاز آبی منطقه، به خاطر تبخیر و تعرق زیاد و بیلان منفی آب، افزایش می­یابد.}, keywords_fa = {آب و هواشناسی کشاورزی,حوضه قره سو,روش‌های چند معیاره,ArcGIS}, url = {https://clima.irimo.ir/article_113698.html}, eprint = {https://clima.irimo.ir/article_113698_8a1aa839f99feb00e4e9044b2b68933d.pdf} } @article { author = {Keykhosravi, Ghasem and Yahyavi, Ameneh}, title = {A New Approach in Determining the Location of the Sea Breeze Front on the Caspian Sea Coast}, journal = {Journal of Climate Research}, volume = {1398}, number = {39}, pages = {139-153}, year = {2020}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Introduction:Sea breeze is atmospheric and intermediate Ocean phenomenon that depends on the temperature difference between sea surface and drought and is generally formed under conditions of clear sky. When the sea breeze penetrates dry, its impact on temperature, humidity, clouds and rainfall can be very clear. The sea breeze is usually associated with lowering the temperature and increasing the moisture content of the atmosphere. The initiation of a sea breeze sometimes is characterized by a sudden discontinuous region, called the "sea breeze". The occurrence of this front is connected to the relatively dense, cool, and stable sea of indoor air, which makes the warm and volatile air mass rise near the sea breeze. Due to the wind's convergence near the front, the accumulated air often mixes together and forms clouds. Therefore, the presence of the sea breeze front can often be deduced from the appearance of a line of coulomb clouds parallel to the shore that is under the pressure of the sea breeze (Smith 1976; Simpson 1994).Methodology:In this study, in order to determine the sea breeze front in the study area, first, during the statistical period (2015-2011), using the wind directions at different hours in the days when at each of the stations, the wind direction from the coast was drought To determine the occurrence of the sea breeze. The time of the beginning of the sea breeze at each of the seasons was determined by the stations, and then the product of the Earth's surface temperature was measured on days when the satellite images were not cloudy. Afterwards, in the Envi software environment, you are plotting the cross-sectional temperature profile from the coast to the land at each station. The location of the sea breeze was determined by the sudden change of temperature in descending order, and then the amount of distance that the sea breeze was moving forward in dry times was calculated in any given day.Discussion:The periods of formation of the sea breeze vary according to the amount of sunshine, and the periods of warming and drying in different months. Beginning in the months of December, January and November at 12 GMT, in the months of October, November, March, April and May, at 9:00 and in June, July, August and September, from 6:00 GMT, the Sea of Aziz To be formed. The rate of advance of the sea breeze depends on various factors such as latitude, local winds, distances and proximity to heights, etc., can affect the progress of the sea breeze to land. The Caspian Sea, due to its small size and depth compared to the oceans and the small differences in temperature between oceanic and oceanic environments, its daily climatic characteristics have caused the maximum advance of the sea breeze to land over long distances. At Anzali Station, on average, in all seasons, the maximum take-off reaches 5 kilometers. At the Babolsar station, the autumn season has a further advance (4.9 km) compared to other seasons. At the KishaShahr station, the sea breeze penetrates more than other stations, reaching an average of 6.5 km in the spring, summer and autumn seasons. At the station of Noshahr, the spring season has the smallest advance to land (3.5 km). Therefore, the difference in sea water temperature and dryness in the southern margin of the Caspian Sea caused different depths and sea breeze levels in different seasons, so that the maximum pace of the sea breeze among the study samples reaches 13 km at the station of Kianeshahr.Conclusion:According to the studies carried out in this study, the results indicate that the sea breeze is a clear phenomenon on the southern shores of the Caspian Sea. The formation of the sea breeze is different in different months depending on the temperature difference between land and sea. As the greatest difference in temperature between land and sea occurs in the evenings, a more powerful condensation environment is created at these times, As in most of the study samples, the first days of the sea breeze in the months of December, January and November at 12:00 GMT, in the months of October, November, March, March, and May from 9:00 and in June, July, August and September It's at 6 o'clock in Greenwich. The maximum spread of the sea breeze at a distance of 13 kilometers is observed, and in all the study samples of the region, the convergence of the Sea of Breeze front was less than 13 kilometers inland. In most study samples, at a time when there is no temperature difference between the coast and the temperature of the sea breeze, the depth of the sea breeze and its distance are less, and at times when the temperature difference is greater, the depth of the sea breeze and its progression in the higher land Gets.}, keywords = {Southern coast of the Caspian Sea,sea breeze,surface temperature,sea breeze front}, title_fa = {رویکردی نوین در شناسایی میزان محل قرار گیری جبهه نسیم دریا در سواحل دریای خزر}, abstract_fa = {نسیم دریا از جمله پدیده های میان مقیاس جوی، ویژه مناطق ساحلی است. هدف این مطالعه بررسی ساعات شروع نسیم دریا در هر کدام از فصول سال، میزان پیشروی نسیم دریا به سمت خشکی و شناسایی جبهه نسیم دریا می باشد. بدین منظور ابتدا آمار ساعتی جهات باد از ایستگاه های مورد مطالعه در فاصله زمانی(2015-2011) از سازمان هواشناسی دریافت گردید، سپس روزهایی که جهت باد در ایستگاه ها از سمت ساحل به سمت خشکی بودند، استخراج گردید. برای تعیین میزان تفاوت های دمایی از خط ساحلی تا خشکی از محصول دمای سطح زمین(LST) سنجنده مادیس با توان تفکیک مکانی 1000 متر در روزهای غیر ابری استفاده گردید. نتایج بیانگر آن است که نسیم دریا پدیده بارز در سواحل جنوبی خزر می باشد، ساعات شکل گیری نسیم دریا با توجه به اختلاف دما بین خشکی و دریا در ماههای مختلف متفاوت است. از آنجائیکه بیشترین اختلاف دما بین خشکی و دریا در عصرها رخ می دهد، محیط چگال گرای قوی تر نیز در این ساعات ایجاد می شود،بگونه ای که در اکثر نمونه های مطالعاتی ساعات شروع نسیم دریا در ماههای دی، بهمن و آذر در ساعت 12 به وقت گرینویچ، در ماههای مهر، آبان، اسفند، فروردین و اردیبهشت از ساعت 9 و در ماههای خرداد، تیر، مرداد و شهریور در ساعت 6 به وقت گرینویچ می باشد. دریاچه خزر با توجه به وسعت و عمق کمتر نسبت به اقیانوس ها و تفاوت های دمای اندک نسبت به محیط های اقیانوسی، مشخصه های آب و هواشناختی روزانه آن باعث شده که حداکثر پیشروی نسیم دریا به سمت خشکی در مسافت های طولانی انجام نگیرد. حداکثر گسترش نسیم دریا در خشکی تا مسافت 13 کیلومتری مشاهده می شود و در تمامی نمونه های مطالعاتی منطقه همگرایی جبهه نسیم دریا کمتر از 13 کیلومتر در داخل خشکی پیشروی داشتند. در بیشتر نمونه های مطالعاتی، در زمان هایی که اختلاف دمایی بین ساحل و دمای جبهه نسیم دریا مشاهده نمی شود، عمق نسیم دریا و مسافت آن کمتر و در زمان هایی که اختلاف دمایی زیادتر می شود عمق نسیم دریا و پیشروی آن در داخل خشکی زیادتر می شود.}, keywords_fa = {سواحل جنوبی دریای خزر,نسیم دریا,دمای سطح زمین,جبهه نسیم دریا}, url = {https://clima.irimo.ir/article_113701.html}, eprint = {https://clima.irimo.ir/article_113701_5c15cb22d3fec29632a9944243bb9163.pdf} }