جستجوی مقالات مرتبط با کلیدواژه "extreme precipitation" در نشریات گروه "جغرافیا"

Climate change is likely to intensify hydrological cycles and affect the intensity and frequency of extreme rainfall.An increase in extreme rainfall in recent years has led to the assumption that climate change has made extreme rainfall non-stationary. Nonstationarity is defined as a change in the parameters of the probability distribution function due to the influence of time variables or other physical variables .The purpose of this study was to investigate the effect of temperature on the non-stationarity of extreme rainfall in Iran.The AIC value was calculated to determine whether the extreme rainfall follows the stationary or non-stationary model. The non-stationary GEV distribution was used to analyze the frequency of extreme rainfall. The return period of extreme rainfall was calculated based on the maximum temperature and the average annual temperature. It was observed that the intensity and frequency of extreme rainfall were non-stationarity due to an increase in the temperature and no spatially uniform pattern was observed in non-stationarity across the country. Related to the maximum temperature variable, the intensity of extreme rainfall was significantly decreased in 6 stations, including Hamedan, Shiraz, Shahr-e Kord, Zahedan, Iranshahr, and Shahroud. On the other hand, the trend of nonstationarity in Kerman has been significantly increasing with increasing maximum temperatures. Only two stations, Zahedan and Arak, were found to be significantly non-stationary concerning the annual mean temperature, and both stations showed a decreasing trend.

The position of Iran between extratropical and subtropical latitudes, the location of a major part of Iran on the desert belt of the world from North Africa to Central Asia, and the role of various geographical phenomena in Iran have caused all kinds of atmospheric hazards in this region. To have an accident (Alijani, 2018). Such risks are inherent in Iran's climate and have occurred regularly since the distant past, as the natural environment and human activities in different regions of Iran have adapted to these phenomena. As the behavior of these phenomena has been repeated somewhat regularly and the climatic changes and short-term atmospheric processes have been less. These phenomena include droughts and droughts, heavy rains and floods, floods and dust storms, frosts, heat and cold waves (Omidvar-Kamal 2013). But in recent decades, with the increase in the temperature of the earth after the industrial revolution (1850), and with the intensification and rapid trend of temperature in the recent decades from 1970 onwards, the atmospheric hazards in the world, including Iran, have become abnormal. Such heavy and short-term rains cause a lot of damage related to agriculture, severe soil erosion, and destruction of transportation infrastructure and flooding of cities and villages. In recent years, in connection with global warming and changes in the behavior and anomaly of rainfall in the world, the amount of rainfall has decreased in this region, but the rainfall has mainly changed its behavior to heavy and short-term rainfall. Therefore, knowing the patterns that lead to the occurrence of these precipitations will be useful in the first place for predicting and managing precipitations. The aim of this research is to identify and analyze the atmospheric circulation patterns leading to the occurrence of heavy rain and short-term flooding based on the data of the stability rain gauge in Khorasan.

in this study, the daily rainfall data and the rain logger of the stability station were used. Among the stations in the region, those that have a proper distribution in terms of spatial distribution and also have long-term statistics (1993-2017) were selected. The synoptic stations were chosen to cover all the regions of the province with different topography and climate diversity. In order to determine heavy rains, the 95th percentile index of daily rains in each station was used. In the following, days with heavy rainfall and more than 95th percentile were extracted in each of the stations using these indicators. The spatial distribution of these rainfalls in the whole province was determined by using the number of these rainfalls in the entire region. , heavy rain. In connection with the purpose of this study, determining the atmospheric patterns of heavy rainfall in Khorasan, after determining the days with heavy rainfall in the previous stage, the atmospheric patterns of rainfall were determined and synoptically analyzed. For this purpose, reanalyzed daily grid data with a resolution of 2.5 degrees were extracted from the National Center for Environmental Prediction and Atmospheric Research (NCEP/NCAR) for the above days. The selected window for receiving network data in this study is 15 to 70 degrees north and 15 to 80 degrees east, so that the patterns affecting Khorasan precipitation in this range can be identified.

On February 17, 2017, in the geopotential height map of the middle surface of the atmosphere, a trough is drawn over the entire western half of Iran and the western coast of the Caspian Sea, and the center of this trough is a closed cell with a height of 5280 geopotential meters over the northeast of the Caspian Sea and Kazakhstan. This deep trough extends to Saudi Arabia and passes through the center of Saudi Arabia at a height of 5750 meters and shows the penetration of cold air in the upper atmosphere to the warm southern sea of Iran. At the same time, in the east of the Mediterranean Sea, there is a Rex-type blocking. These atmospheric conditions caused persistence and slow movement of the circulation system in the synoptic scale in Southwest Asia. At the same time, there is a low pressure center with a pressure of 1010 HP in front of the curved ship in the east of Iran. The east of this trough extends from the southwest and the western half along the southwest to the northeast direction of Iran, which caused instability in the northeast of Iran. On April 1, 2016, the arrangement of westerly winds in the entire Eurasia area shows a large anomaly in the westerly wind waves, naturally in late winter and early spring, due to the reduction of temperature and pressure differences in the northern hemisphere, westerly winds move meridian. And the number of long waves also increases hemispherical. In this map, there are two meridional patterns of westerly winds in the north and south, the first pattern in the north with a deep and curved channel with a west-east direction and closed with two equal heights, cut off low respectively over Western Russia and Kazakhstan respectively with There are 5280 and 5440 meters, That on the surface of the earth in these two areas, two low pressures with a pressure of 1003 and 1011 HP, respectively, indicate a strong rotation and instability in these areas.

Heavy rains and floods are one of the most important weather hazards that cause great damage to nature and humans every year. This type of precipitation, which is an inherent feature of arid and semi-arid climates, has increased significantly in recent years due to global warming and the increase in climate extremes.

Precipitation is one of the most important and variable elements of climate that has a lot of spatiotemporal variability, especially in arid and semi-arid regions. Adequate knowledge of precipitation variations is crucial for agricultural planning and water resource management in any region. For this purpose, in this study, using the daily data of Asfezari precipitation database during the period 1349 to 1394, the characteristics of precipitation and also the precipitation trends in Yazd province were investigated. The average coefficient of variation of the total annual rainfall of the province was 42.2 and varied from 32.9 to 68.4 in different cells. The highest coefficient of variation of precipitation on an annual scale was observed in the central and western regions of the province, which indicates the greater dispersion and risk of precipitation in these regions. The trend of precipitation was examined using nonparametric statistical tests of Mann-Kendall and Sen’s slope estimator. The spatiotemporal distribution of the trend of total annual Precipitation and total annual extreme Precipitation was similar and in both cases the general trend of the province was decreasing. The highest share of extreme Precipitation in total annual Precipitation was observed in the central regions of the province (Yazd-Ardakan plain). Therefore, in rainy years, these areas have favorable conditions for severe floods.

The statistical and spatial analysis of extreme rainfall is considered as one of the components of the management tool to prevent or control the risks caused by this phenomenon. The purpose of this research is to statistically investigate and spatially analyze the extreme precipitations in the Kashan Plain.The extreme rainfall of Kashan synoptic station were statistically analyzed in the period of 1971-2022 AD and the water year of 1350-1351 to 1401-1400 for a total of 18618 days.Then six cases of widespread extreme rainfall were selected and analyzed with the rainfall data of 13 synoptic stations and 11 rain gauge stations using geostatistics and spatial analysis methods.The extreme rainfall zonation maps of Kashan plain were prepared using by variogram models and kriging method.The results showed that the frequency of heavy and super heavy rains in winter and very heavy rains in spring is more than other seasons.The very high correlation of annual rainfall with the total and frequency of extreme rainfall shows that the volume of annual rainfall is more affected by the concentration of rainfall in short periods of a few days than by the distribution of rainfall throughout the year.Therefore, it was found that extreme precipitation plays an important role in the total precipitation and surface runoff, and as a result, the water balance of the region.The zoning maps showed that the rainfall of April 8, 2020, which is concentrated on the western belt and the heights of the basin, causes the erosion of the heights and causes floods in the foothills and low-lying areas of the plain. Also, rains such as the rains of March 8, 2019, which are most concentrated in the central areas, have a high potential to cause flooding.

Climate extreme events have expanded and intensified during the 21st century. Extreme precipitation event annually leads to severe damage in agriculture, environment, infrastructures and even the human loss. Therefore, identification of the behavior of such events is one of the pivotal aspects of climatic change and the increase of information about extreme precipitation is tangibly necessary for the society especially with regard to those, living in the areas with high risk of flood. extreme precipitation events can be defined as significant deviations from the precipitation mean. As a result, to identify such precipitations, a criterion was needed to evaluate the rate of precipitation values’ deviation from mean. Importantly, given the different types of indicators and thresholds proposed for extracting extreme precipitation, choosing an appropriate threshold with climatology conditions of the study region which could also be capable of identifying extreme precipitation optimally in terms of amount and frequency, requires high precision. The present study aimed at identifying the extreme precipitation events in the west of Iran through introducing the appropriate threshold and spatial scale for the extraction and investigation of these events.

The west of Iran with the areaof 230760 square  kilometers includes about 14% of total area of Iran. Zagros Mountains, stretching from northwest to southeast, are the most important feature of the west of Iran. Two databases have been used in this study. The first database regardsthe precipitation data of 1129 synoptic stations, climatology and rain gauge in the west of Iran. The stations statistics have been checked in terms of existence of any outlier. Ultimately 823 stations out of 1129, were used for producing gridded data. The gridded data, are the results from the interpolation of daily precipitation observations since January 1st 1965 to December 31st 2016, using Kriging interpolation method and spatial separation of 6*6 kilometers. the final base, a matrix possessing the dimensions of18993*6410 (representing time on the rows and place on the columns) was developed. The second database referred to the Sea-level pressure patterns (Hectopascal).To identify such precipitations, in addition to the main threshold that includesthe mean of precipitation more than 75th percentile for each pixel per day of a year, a second threshold including the standard deviation of these precipitations (with the values of one, two, and three times more) has been also added to the mean. Accordingly, three groups of extreme precipitation were identified in the region which were separated according to the spatial zone that had been covered. Moreover, the sea-level pressure patterns were extracted with regard to these precipitations for each zone andthen classified using clustering analysis technique.

three groups of precipitations with different coverage zoneswere identified: 1- 83 days with equal to or more precipitation than the mean of precipitations more than 75th percentile plus one time standard deviation which cover more than 40% of the region. 2- 144 days with equal to or more precipitation than the mean of precipitations more than 75th percentile plus two times standard deviation which cover more than 20% of the region. 3- 82 days with equal to or more precipitation than the mean of precipitations more than 75th percentile plus three times standard deviation which cover more than 20%
The maps of 7 participation groups of the first type in comparison with 6 precipitation groups of the second and third type contain common and repetitive patterns. Each precipitation maps of the second and third types explains a type of patternand there is minimum overlapping in the maps. Therefore, the precipitations are obtained from the most particular and distinct atmospheric patterns. considering the three properties of 1- equality of precipitation groups of type two and three (both include 6 groups of atmospheric patterns). 2- repeating the atmospheric patterns of precipitation of type two prominently in the precipitations of type three. 3- the formation of the most optimum atmospheric modeling for the precipitations of both thresholds in the zones of 20% and higher, in the west of Iran, the extreme precipitations refer to those with higher means of recipitations more than 75th percentile plus two times standard deviations,have mostly occurred in the zone of 20% and higher of the region.

Recently, high extreme and frequency distribution of higher sequence of precipitation have been attended more. Through this, because of geographical characteristics of each area, diverse and different thresholds have been presented and utilized for the mentioned precipitation’s characteristics. Through the present research, for exploring and analyzing the extreme precipitation event in Tehran through the 1983-2016 statistical periods, some of the indexes presented by World Meteorological Organization Committee were utilized.
Data and

The extreme precipitation event distribution sequence behavior and frequency analyses and severity of the mentioned event were explored by using the Peak Over Threshold value model (POT). Selecting the suitable threshold for calculating the peaks higher than threshold using the 95 percentile methods, Mean of Remaining Life (MRL) and Model-Base Controlling (MBC) was done. Distribution parameters’ determining by maximum likelihood method and evaluating the occurrence and extreme events’ severity was investigated by using the Average Returning Intervals (ARLs).

The results accessed from Man-Kendal illustrated that in the studying stations, the significance process in the extreme indexes through the 1983-2016 was not met.

Exploring the development curves showed that through the 34-year-old statistical period (1983-2016), most of the observed extreme events in the stations had 1 to 10 years return. Q-Q exploring charts and χ2 statistics showed that POT model included the high quality for modeling the extreme events in the studying area

In this research, the frequency of the jet streams during extreme and pervasive precipitation have been analyzed using environmental to circulation approach. Therefore daily precipitation data of 11 synoptic stations have been extracted from January, 1st, 1951 to March, 20th,2013 (22725 days) from Iran meteorological organization. Then, by using two thresholds of extensiveness and intensity of precipitation occurrence( at least, half of the stations receive the precipitation and the average precipitation of stations will be more than 99th percentile average), 97 days had been recognized. Then, jet streams frequency and their locations and speed have been calculated on the frame of 0° to 120° E and 0° to 80° N for each pixel(1617) in levels 250, 300, 400 and 500 hPa ) at 00:00, 06:00, 12:00 and 18:00 UTC. The results indicate that jet streams over 300, 400 and 500 hPa levels and at 18:00 UTC observe over the study area. The highest frequency of jet streams is located in the north of Saudi Arabia. At the same time, the average speed maps of jet stream in conforming with the maximum frequency of jet stream on one hand and on the other hand is simultaneous with occurring the maximum speed of jet stream over study area that indicates the output axis of jet stream is toward the semi-western parts of Iran and east Azarbaijan is located on the left output part of jet streams where atmospheric divergence and instability occurred in all the observations. This can result in an expansion of air mass at the upper level or ascending vertical motion. Generally, the elongation of jet streams mostly until 500 hPa level at 18:00 indicates the thickness of the instability layer that can create the extreme and pervasiveprecipitation on east Azarbaijan.

Extreme precipitation is one of the climatic risky behaviors that are associated with abnormalities and environmental-human consequences. This study has investigated daily rainfall  of 20 rain gauge and synoptic stations over 30 years (1987-2016) in the West of Gilan province, to determine the trend of extreme precipitation changes. In this regard, non-parametric Mann-Kendall test, Senchr('39')s Estimator slope, Poisson distribution, and IDW interpolation have been applied, respectively, to determine the existence of trend, significance, to determine the probability of rainfall occurrence   and to identify spatial patterns of precipitation occurrence with different probabilities. The results suggested an increasing trend in Astaneh-ye Ashrafiyeh, Bandar-e Anzali, Masuleh, and Astara and an extreme decreasing trend in Bash Mahalleh due to the Mann-Kendall test. Studying the significance or insignificance of changes trend by Sen indicated that this trend has been significant in Mashin khaneh, Bash Mahalleh, and Punel Stations; and the null hypothesis, that is, the insignificance of change, was rejected. Senchr('39')s Method revealed that there were no significant changes in other stations, and their randomization will be confirmed. To this end, the spatial probability distribution of  to  indicate kernel probability displacement for different x.  The maximum probability to various occurrences has been at Masuleh station and Poisson distribution is a proper assessment of precipitation in this region.

Atmospheric circulation is important to determine the surface climate and environment, and affect regional climate and surface features. In this study, to quantify its effect, the classification system, developed by Lamb is applied to obtain circulation information for Ardabil, North West Province in Iran, on a daily basis, and is a method to classify synoptic weather for study area. For that purpose, daily mean sea-level pressure (MSLP) for extreme precipitation days from 1971 to 2007 is used to derive six circulation indices and to provide a circulation catalogue with 27 circulation types. The frequency of circulation types over different periods is computed and described. Five circulation types are most recognised in this study: E, SE, A, C and CSE. The catalogue and the associated indices provide a tool to interpret the regional climate and precipitation, and deal with the linkage between the mean extreme regional precipitations in north western of Iran and the large-scale circulation. Five circulation types E, A, SE, C and CSE are associated with high precipitation and rainy seasons (spring and September) but the most precipitation rate is resulted of cyclone family. Low pressure of north latitudes and central area of Iran with low pressure of gang from Pakistan and India.  SE is almost dominant circulation type over the years. The cold season started from august to march is characterized by frequent directional flows, especially E, SE, A, C and CSE whereas in  warm period (Apr–Aug) SE, NE, AE have  smaller role, especially in July, August and September more frequent flows dominated by SE and E.

Mesoscale Convective Systems (MCSs) are the convective precipitation structure that is most frequently associated with floods at mid-latitudes, mainly due to the high degree of organisation, which allows the structure to be maintained for a longer period of time and to become more extensive. Moreover, MCSs are an important link between atmospheric convection and larger-scale atmospheric circulation. Based on the results of previous studies, it can be claimed that Sudanese low pressure systems in many cases are the cause of the formation of MCSs, especially in southwestern Iran. Although many studies have been done in Iran on these systems and how they are formed, but the role of some environmental components of their formation and intensification, such as vertical wind shear, High and Low Level Jets (HLJ and LLJ) has received less attention. Therefore, the purpose of this study is to investigate the role of these factors in addition of the known factors that cause the formation of these systems. For this purpose, the flood of 24 and 25 march 2019 in the south and southwest of Iran has been selected as a case study. To track and investigate the spatial characteristics of MCSs in this study, IR channel of the second-generation Meteosat imagery (MSG) on March 24 and 25, 2019, with a spatial resolution of 3 km and a temporal resolution of 15 minutes from Eumetsat site was extracted. After calibration and georeference of the images, the brightness temperature was calculated. The exact choice of temperature threshold for the identification of convective systems is optional and depends on the spatial resolution and wavelength of imagery. The size distribution obtained from the 207 or 218 k thresholds are not very different, especially for larger convection systems. Therefore, in this study, a threshold of 218 degrees Kelvin was used. Also, there is no agreement among researchers on the criterion of minimum length or area in the definition of MCSs, and this criterion is mostly determined by the characteristics of the region and the selected temperature threshold. In this study we select a threshold of 10 thousand square kilometers. In other words, the system was identified as MCSs, which at some point in life had an area of more than 10,000 square kilometers. The daily precipitation data of GPCC database were used to investigate the scattering of precipitation produced by these systems. Also, to understand the synoptic and environmental conditions of occurrence of MCSs on studied days, first geopotential height data, zonal and meridional wind components, potential temperature, relative humidity, vertical velocity and CAPE from ECMWF database were extracted and then the required maps and diagrams were prepared to synoptic and environmental analyses. In general, the results of this study showed that three MCSs on March 24 and 25, 2019 affected different parts of Iran. The maximum area of ​​the cold core of the first system is about 73,000 square kilometers and has traveled from west to north of Iran. The second system, which affected Iran from the west to the northeast, had a maximum area of ​​about 660 thousand square kilometers. The cold core of the third quasi-stable system with a linear extension (northeast-southwest) and a maximum area of ​​about 440 thousand square kilometers, has moved slightly to the southeast. The synoptic conditions of the formation of these systems have been the same as the common pattern of the formation of Sudanese low pressure systems and MCSs. In this pattern, Azores high pressure can bring the cold air of the high latitudes to the middle latitudes and hot and humid air is injected by the high pressure over the Oman Sea and the Arabian Sea, which activates the Red Sea convergence zone along with the Mediterranean system. These conditions have led to the formation of the minimum potential temperature zone in the eastern Mediterranean with significant temperature and pressure differences compared to its environment, resulting in the formation of LLJ. This LLJ has been very effective in transferring hot and humid air to western Iran. So that in the peak hours of convective activity in the center of Iran, a potential temperature difference of about 30 degrees Kelvin with the environment has created that has played an effective role in the formation of convective storms. The transfer of hot and humid air by the LLJ has led to the formation and continuation of convection and the release of latent heat to enhance the convergence and longer life of convection systems. On the other hand, the coupling of LLJ and HLJ, by strengthening the MCSs in the western part of Iran and strengthening the divergent flow at higher levels, has strengthened the HLJ, which in turn has led to strengthening the convective system. Vertical wind shear probably also led to the formation of new convective cells in areas far from the origin of the primary convective cells. During the peak hours, unstable convective activity was observed over a large part of Iran, especially the southern and western parts, and its maximum was observed from the southern half of the Red Sea along the convergence zone to the west of Iran. Therefore, various components of the Sudanese low pressure system play an important role in the formation, continuity and development of mseoscale convective systems. It seems that low-level jet, vertical wind shear and its interaction with the Red Sea convergence zone and the outflow of primary convective cells have a very effective role in the occurrence of this phenomenon. Thus, more detailed studies of this issue using mesoscale numerical models will probably identify unknown aspects of Iranchr('39')s climate.

In current study, we underlined the trends of annual precipitation over Iran in relation with changes in high and low extremes and normal values of precipitation from spatial analysis point of view. To this end, the third version of Asfazzari national database with 10 10 km spatial resolution and daily temporal resolution for 46 years (1970/3/21 to 2016/3/19) is adopted. Trend analysis depicted that in the major parts of the country (approximately 80.9%) the annual precipitation has experienced decreasing trends which tend to reducing about 1.5 billions cubic meters of input water in the hydrologic system of the country. Our finding showed that the decreasing trends of precipitation prompted by large scale and global systems. However, the local factors (longitude, latitude, elevation, slop) are culprits for changing the effects of abovementioned factors. These factors cause the decreasing trends to be statistically significant solely in a part of 33.53% of Iran territory (northeast, parts of eastern of Iran, parts of inner slops of Zagros mountain chain, an area from Kerman to Isfahan, Charmahal-o-Bakhtiari, Kohgiloyeh-oBoyerAhmad, from west of Shiraz, and north of Bushehr to Sanandaj in the west of Iran). Furthermore, the results of our study illustrated that the decreasing trends are due to decreasing in high values of precipitation, particularly decreasing in the 75th percentiles and above of precipitation values. The areas which include increasing trends covered spatially spread areas of about 2.93% of the country. This area has not been able to compensate for the lack of precipitation due to decreasing trends in the area associated with statistically significant decrease in precipitation.

Extreme precipitation plays a fundamental role in the formation of some hazards that could have severe social-economic consequences. Studying and determining the factors that lead to the occurrence of such extreme events in the city of Tehran as the capital of the country is important. In this study, precipitation in twenty-four hours that were equal or higher than the 95th percentile of precipitation during 1976-2005, considered as an extreme event. The data required for the selected cases was taken from the NCEP/NCAR archive. Among the identified cases, two 8th of November 2005 with 15mm and 1st of February 1994 with 39mm of precipitation in 24 hours have been adapted for a detailed study. To better understand the atmospheric circulation leading to the events, synoptic conditions 48 hours before and 24 hours after the precipitation were examined by means of surface, 500-hPa and 250-hPa weather charts. Consequently, two different circulation patterns were recognized. In the first one, a center of high pressure over the Caspian Sea that extends toward the Black Sea and occasionally tongues toward central part of the country was observed. In the second pattern, there were two high pressures, one over the North West of the Mediterranean Sea and the other over the central Asia. At the same time, a trough from the Red Sea extended toward the east of the Mediterranean Sea and combined with a dynamic low-pressure system that accompanied with a trough in the middle of the troposphere. It has also been realized that the sub tropic jet stream axis passes over the Tehran and a meridional branch of polar jet stream forms over the Mediterranean Sea have a significant role in increasing precipitation. The study also revealed that if the Red Sea trough reaches higher latitudes, the precipitation over Tehran would be heavier.

Atmospheric rivers (ARs) are long-narrow, concentrated structures of water vapour flux associated with extreme rainfall and floods. Accordingly, the arid and semi-arid regions are more vulnerable to this phenomenon. Therefore, this study identifies and introduces the highest precipitation occurred during the presence of ARs from November to April (2007-2018). The study also attempted to demonstrate the importance of ARs in extreme precipitation, influenced areas and identifies the effective synoptic factors. To this end, integrated water vapour transport data were used to identify ARs, and documented thresholds applied. AR event dates were investigated by their daily precipitation, and eventually, ten of the highest precipitation events (equivalent to the 95th percentile of maximum precipitation) associated with ARs were introduced and analyzed. The results showed that most ARs associated with extreme precipitation directly or indirectly originated from the southern warm seas. So the Red Sea, the Gulf of Aden and the Horn of Africa were the major source of ARs at the time of maximum IVT occurred. Synoptically, seven AR events formed from the low-pressure Sudanese system and three events from integration systems. The subtropical jet was the dominant dynamic of the upper troposphere, which helped to develop and constant of ARs. Moreover, the predominant structure of jets had a meridional tendency in Sudanese systems, while it was a zonal orientation in integration systems. The intense convective flows have caused extreme precipitation due to the dominance of strong upstream flow besides having the highest moisture flux. The station had the highest precipitation has been located in the eastern and northwestern region of the negative omega field or upstream flows.

Precipitation is considered as one of the most important climate elements affecting different environmental aspects.. Precipitation extremes follow a geographical pattern like all other climate elements. Recognition of such patterns, specifically in those areas where people’s lives depend on precipitations, can determined the amount of success in environmental management as well as in resources planning. High extreme precipitation in Iranian coastal region of Caspian Sea, especially eastern parts, the recognition of spatial auto-correlation of such a phenomenon can facilitate environmental planning and also increasing adaptability with such a disaster. Therefore, in order to analyze auto-correlation of the sum frequency of monthly extreme precipitations of under investigation region, the 99 percentile of precipitation for each pixel of the map is considered. 385 stations were studied during the time period covering 1966 to 2016. We have used spatial statistics techniques to analyze spatial auto-correlation features. Results of the present study showed that the dominant behavior in sum frequency of monthly extreme precipitation under study region followed cluster pattern. The areas with positive auto-correlations were mostly found in internal areas and far from the coastal line over most months. Positive auto -correlated clusters were spread in eastern and western regions and some parts in central areas. G* test approved the frequency of clusters with high and low values. The comparison of our findings with previous studies showed that the geographical location of under investigation region, and also synoptic systems affecting the region have affected the spatial auto-correlation frequency pattern of extreme precipitation occurrence.

In all weather maps, without exception belt or wind tape at high speed are seen to have drawn very long distances. As defined by the World Meteorological Organization, whenever the tape speed is faster than 30 meters per second, the jet stream is created (Alijani and Kavyani, 1379: 291). However, according to the definition in the dictionary of weather and climate extreme horizontal winds with speeds of over 50 knots, or about 26 meters per second, above the planetary winds blow, refers jet stream (Hitch, 1961). In fact, the jet stream, the core of which are fast moving and in the context of long and short waves, as they are areas of convergence and divergence (Alijani, 1381: 82). The core of the jet stream speed is also reduced from the core center around which this reduction to the poles to the equator volubility or positive, or negative anti cyclone.
Experimental basic research with an inductive approach. Geographical zones studied western regions of Iran. The data base that environmental to circulation approach involves two variables. The daily precipitation data of 69 synoptic stations and climate West of Iran (Hamedan, Kurdistan, Kermanshah, Lorestan and Ilam) in the interval from 2010 to 1961 as the database environment event was received from the National Weather Service. The second group of variables including wind component-oriented data and meridional wind component in order to draw jet streams at levels 250, 300, 400 and 500 hp were taken from the website of Noaa , data extraction was performed using the software Grds. According to the event database environment, enjoying updated daily rainfall 18624 West Iran interpolation method was Kriging. or this purpose, an interpolation of rainfall per day, the study area the size of 2.5 × 2.5 km in 1367 became cells, resulting in the formation of an array of daily precipitation database with dimensions of 1367 × 18624 West was Iran. Selected. Perform calculations on the data, was conducted using MATLAB software. The resulting calculation is presented in the form of maps. Maps arches were used for mapping software The number of rainy days inclusive extreme studied stations cover 30% of the 119 days that were analyzed. One of the most common parameters in spatial analysis in relation to the distribution points around the center Average used, the standard deviation ellipse. Since the situation may be occurring phenomena, has deviated directional arrow and oval standard deviation of the probability distribution may well show (Asgari, 1390: 89), as well as in-order to display the deviation of the distribution points, the standard oval used. Standard oval on the frequency jet stream was applied in each pixel.
Frequency jet stream at 250 hPa level spatial analysis showed that the most frequent jet stream is from the Southern Red Sea to the south of the Mediterranean, in other words more than 70% of the formation, establishment and cross Jetstream’s West's influence on rainfall in this area is, which is the main route from the Red Sea, which leads to water injection system precipitation from the Red Sea to the West Iran.% of the formation and establishment of the jet stream. Frequency jet stream at 400 hPa level spatial analysis showed that during the study period was the most common jet streams northeastern extension of the Red Sea to the west over Irans. The actual zones in this area in more than 50% of the formation and establishment of the jet stream. By reducing the height of the territory of jet streams and their influence has waned. Spatial analysis showed that the frequency jet stream at 500 hPa level jet stream during the study period was the most common variety of the northeastern Red Sea to the west of Iran in the covers. The actual zones in this area in more than 50% of the formation and establishment of the jet stream. The results of the standard oval jet stream in the range of activities on Iran's western regions, respectively. Given that, the event shows the dispersion ellipse fitting, oval shows the pattern of the jet stream of high activity in the West of Iran.
The results show that the jet stream at 250 hPa level, show a high frequency. Maps of average speed jet stream jet stream and on the other hand, in accordance with the highest frequency of occurrence coinciding with the maximum speed jet streams in the study area, and reflects the core jet stream wrapping the second quarter (by increasing positive vortices and upper level divergence and low levels of the atmosphere is mobile convergence) on the West Iran.

Extreme precipitations at each point are those irregular precipitations which are situated in the trail and away from the focus point of the precipitation frequency distribution of that point. Recently, the thresholds and upward trails of precipitation frequency distribution have been greatly regarded. In this regard, and proportionate to the geographical properties of each zone, various and numerous thresholds have been introduced and applied for this precipitation property. One of the frequently-used indices of daily precipitation is based on generalized distribution of extreme values. In this research, extreme precipitations’ threshold of western Iran have been determined using extreme values generalized distribution statistical methods, extreme precipitations of the region have been recognized, and their spatial distribution has been analyzed. To this end, network data resulted from daily interpolation of 69 synoptic stations and climatology for 1961-2010 statistical periods was used. Then by using generalized distribution method of extreme values, the daily precipitations of 22mm and more were selected as the Extreme precipitations. In order to recognize the distribution pattern and spatial relations of western Iran extreme precipitations (Hamadan, Kordestan, Kermanshah, Lorestan, and Ilam provinces), Global Moran’s I statistic, Local Moran’s I statistic, and Getis- Ord G* statistic were used. The spatial pattern of western Iran precipitations is a cluster pattern, the significance of which was confirmed at 99 percent confidence.Frequency clusters and average clusters of extreme precipitations are compatible with each other in some regions including Hamadan and Kordestan provinces, but there were no relationship between them in some other regions. The most frequency and average of precipitation frequency was happened in Hamadan and Kordestan provinces. Based on the both indices of Local Moran and hot spots of the region's heights of the study area has had a recognized role in the extreme precipitation patterns with the high clusters. The result of the study showed that the frequency and average of extreme precipitation of western Iran is influenced by unevenness, the deployment of unevenness, as well as synoptic systems.

Understanding the changes in extreme precipitation over a region is very important for adaptation strategies to climate change. One of the most important topics in this field is detection and attribution of climate change. Over the past two decades, there has been an increasing interest for scientists, engineers and policy makers to study about the effects of external forcing to the climatic variables and associated natural resources and human systems and whether such effects have surpassed the influence of the climate’s natural internal variability. The definitions used in the 5th assessment report were taken from the IPCC guidance paper on detection and attribution, and were stated as follows: “Detection of change is defined as the process of demonstrating that climate or a system affected by climate has changed in some defined statistical sense without providing a reason for that change. An identified change is detected in observations if its likelihood of occurrence by chance due to internal variability alone is determined to be small. Attribution is defined as the process of evaluating the relative contributions of multiple causal factors to a change or event with an assignment of statistical confidence”. Detection and attribution of human-induced climate change provide a formal tool to decipher the complex causes of climate change. In this study the optimal fingerprinting detection and attribution have been attempted to investigate the changes in the annual maximum of daily precipitation and the annual maximum of 5-day consecutive precipitation amount over the southwest of Iran.
This is achieved through the use of the Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation of Water Resources Project(APHRODITE) dataset as observation, a climate model runs and the standard optimal fingerprint method. To evaluate the response of climate to external forcing and to estimate the internal variability of the climate system from pre-industrial runs, the Norwegian Climate Center’s Earth System Model- NorESM1-M was used. We used up scaling to remap both grid data of observations and simulations to a large pixel. This remapped pixel coverages the area of the southwest of Iran. The optimal finger printing method needs standardized values like probability index(PI) or anomalies as input data, since the magnitude of precipitation varied highly from one region to another. The General Extreme Value distribution (GEV) is used to convert time series of the Rx1day and Rx5day into corresponding time series of PI. Then we calculated non-overlapping 5-year mean PI time series over the area study. In this research, we applied optimal fingerprinting method by using empirical orthogonal functions. The implementation of optimal fingerprinting often involves projecting onto k leading EOFs in order to decrease the dimension of the data and improve the estimate of internal climate variability. A residual consistency test used to check if the estimated residuals in regression algorithm are consistent with the assumed internal climate variability. Indeed, as the covariance matrix of internal variability is assumed to be known in these statistical models, it is important to check whether the inferred residuals are consistent with it; such that they are a typical realization of such variability. If this test is passed, the overall statistical model can be considered suitable.
Results obtained for response to anthropogenic and natural forcing combined forcing (ALL) for Rx1day and Rx5day show that scaling factors are significantly greater than zero and consistent with unit. These results indicate that the simulated ALL response is consistent with Rx1day observed changes. Also, it is found that the changes in observed extreme precipitation during 1951-2005 lie outside the range that is expected from natural internal variability of climate alone and greenhouse gasses alone, based on NorESM1-M climate model. Such changes are consistent with those expected from anthropogenic forcing alone. The detection results are sensitive to EOFs. We estimate the anthropogenic and natural forcing combined attributable change in PI over 1951–2005 to be 1.64% [0.18%, 3.1%, >90% confidence interval] for RX1day and 2.5% [1%,4%] for RX5day.

Introduction Trend detection is an active area of interest for both hydrology and climatology in order to investigate climate changes scenario and improve climate impact research(Saidi et al., 2013). The assumption of stationary seems to be invalid as a result of anthropogenic influence and the natural variability of the climate system (Karpouzos et al., 2010). One of the most significant consequences of global warming due to increase in greenhouse gases would be an increase in magnitude and frequency of extreme precipitation events (Joshi and Rajeevan, 2006). In the global warming scenario, climate models generally predict an increase in large precipitation events (Houghtonet al 2001). Climate simulations indicate that a warmer climate could result in an increase in the proportion of precipitation occurring in extreme events (Karl et al., 1995). It seems to be generally accepted that the expected climatic changes are not necessarily associated with a higher intensity of extreme values, but rather with a higher frequency of the occurrence of extreme values. There are many indices for examining the extreme rainfall events (Peterson et al. 2001). The joint working group on climate change detection of World Meteorological Organization (WMO-CCL) and the research program on Climate Variability and Prediction CLIVAR (Peterson et al., 2001) recommended 15 indices on extreme rainfall. These indices are similar to indices that recommended by Expert Team of Climate Change Detection and Indices (ETCCDI). In this study the percentile thresholds indices including 90, 95 and 99 have been applied. The aim of this study is changes of extreme precipitation frequency in Iran.
Data and Methods In order to doing this research, interpolated daily precipitation from Asfazari data base during 1/1/1340 to 11/10/1383(15992 days) has been used. One data base with dimension 15992×7187 created. For each calendar days of year calculated 90, 95 and 99 percentiles over pixels. Three new matrixes have been created with dimension 366×7187. If daily precipitation amount over each pixels during study period was equal or over the three mentioned percentile considered as extreme precipitation. The frequency of extreme days on the each pixel separately counted for every months of year. The significance of trend evaluated by non parametric Mann Kendal test at 95% confidence level.
Results and Discussion The result of this study showed that trend of extreme precipitation occurrence over Iran is significant. In general the extension of negative trend of extreme precipitation occurrence is more than positive trend in semi warm seasons of year. The contrast observed for the cold months (December, January and March). In July, the trend of extreme precipitation occurrence frequency over the north parts of Iran is positive. The extensive negative trend observed during September while for the positive trend observed in December and January. General we can say that trend over elevation especially on Zagros mountain range is positive while over low lands trend is negative in yearly scale. Frequency of extreme precipitation is increasing over southwestern and western parts of country in November and March. It seems to that in spatial view increase and decrease of extreme precipitation occurrence is well agreement with increase and decrease of precipitation over Iran. This is clear in the Southwest part of Iran especially. The distribution of precipitation over Iran is controlled by the interaction of the tropical air mass (Sudan Low), the Monsoon, the Persian Gulf, the Mediterranean low pressures, the Siberian high pressure and the western passenger high pressures. It seems that changes in intensity of mentioned synoptic systems during recent decades are the reason for the variability in extreme precipitation occurrence over Iran.

Long-term annual extreme climate events، especially temperature and precipitation، have generally been used as indicators for the assessment of climate change. One of the most changeable climatic variables in time and space is precipitation. There are great number of research papers focusing on extreme precipitation on global، regional and national scales have been written. The results of these studies of precipitation and extremes indicate that there are changes in intensity، amount، duration، timing، rate of precipitation and change on trend of extreme precipitation events (IPCC، 2007) and these precipitation irregularities and extremes are impact of climate change. Change on trend of extreme precipitation events have been caused change on severity، permanence، temporal distribution and rate of precipitation in many regions and can be cause drought and floods or other hazards. Generally، Study of extreme precipitations and their frequency is very important in order to understand why they happen and if there are some signs or particular periodicities. Moreover this kind of researches are fundamental in order، first of all، to save human beings، but also to avert or to limit damages done by these extreme events (Boccolari and Malmusi، 2013). Studies of variability in precipitation can be classified into two categories: long-term changes (trends) and short term (oscillation) (Asakereh & Razmi، 2012). Many studies show that there are a change on trend of extreme precipitation events in Iran، but since the change in this events are associated with indexes and factors that influencing the precipitation of Iran، so this study focus to reveal the extreme precipitation variability in the West and North West of Iran and the relationship of theirs with the effective index of precipitation in Iran. Study Area: Iran is located in the west of Asia، and in the arid and semi-arid belts. The study province is West and Northwester of Iran، that’s includes six state of Kermanshah، Kurdistan، Hamadan، Zanjan، East and West Azerbaijan (from 44. 03 to 52. 49 E and 33. 37 to 39. 46 N). These areas are located near the Iranian border with Iraq، Turkey، Armenia and Azerbaijan in western and Northwestern Iran.

The aim of this study is analysis of variability of extreme precipitation events on West and North West of Iran and theirs relationship with teleconnection patterns include ENSO، MEI، NAO and AO and also pressure centers includes Mediterranean center (MLP)، Sudan low (SLP)، Siberian high pressure (SHP) and Black Sea low pressure (BSLP) center and finally with Sunspots. The extreme precipitation indices that we used are Maximum 1-day precipitation (Rx1day)، Maximum consecutive 5-day precipitation (Rx5day)، Simple precipitation intensity index (SDII)، Number of days with precipitation equal to or greater than 10 and 20 (R10mm abd R20mm)، Maximum number of consecutive dry and wet days (CDD and CWD)، Total precipitation when daily amounts are greater than 95th and 99th percentile of wet days (R95 p and R99 p)، and Total precipitation in wet days (PRCPTOT). Our used data were limited to daily precipitation data from only 8 of Iranian synoptic stations، includes Tabriz، Oroomieh، Khoy، Saghez، Sanandaj، Hamedan، Kermanshah and Zanjan، that have reliable data and covering period 1961-2010. For time series studies and trend analysis in climatological variables، various statistical methods have been used. In this study the non-parametric Mann–Kendall test، which is frequently used to evaluate statistically significant trends in climatological variables time series was used. Studies exploring short-term oscillations in precipitation are based on a different group of methods، including autocorrelation functions، harmonics analysis، spectral analysis and wavelet analysis. One of the most common methods used in climate studies is spectral، which was employed in this study. The short term oscillation of macro scale factors influencing variability in precipitation for the middle Zagros includes El-Nino Southern Oscillation (ENSO)، Multivariate ENSO Index (MEI)، North Atlantic Oscillation (NAO) and Arctic oscillation (AO)، pressure variability from the MLP، SLP، SHP and BSLP pressure center، and potentially sunspots، in relationship with extreme precipitation in the north west of Iran have been analyzed.

About the main factors that affecting the precipitation of West and North West of Iran، Negative phases of the ENSO index has increased and this factor can reduce of winter precipitation in study area. In AO and NAO، trend in positive phases is increased and by this condition can be caused reduce in annual precipitation. Z-statistic in pressure centers indicates in a way the pressure of those centers over the past 50 years has increased. Change in pressure of these centers probably can affect the pattern of precipitation in the study area and cause change of precipitation rate in study area. The Z statistic of the 10 extreme precipitation indices shows the trends in all the extreme precipitation indices in more stations have been decreased. Rx1day in Tabriz، Khoy، Kermanshah and Znjan were negative trend and in others are positive. By using spectral analyses technique on Rx1day، significant oscillations 2-3 and 3-5 years have been discovered. This oscillation is related to ENSO، MEI، AO and NAO and also is related to MLP، SLP، SHP and BSLP oscillation. Rx5day only in Hamedan and Sanandaj are positive and the significant oscillations 2-3 is related to ENSO، MEI، AO and NAO، MLP، SLP and BSLP oscillation. SDII trend in Oroomieh، Kermanshah and Zanjan were negative. The 2-3 years oscillation in Hamedan is related to Sudan low oscillation and 3-5 years in oroomieh is related to ENSO. R10mm in all stations، except in Sanandaj، were negative trend and the 2-3 years oscillation in this index in Hamedan is related to NAO and the 3-5 years oscillation in Kermanshah and Zanjan is related to MLP and also in oroomieh is related to ENSO. As R10mm index، except in Sanandaj، the R20mm and CWD indices the trends in all stations were decreased. R20mm in Kermanshah and oroomieh stations 2-3 years oscillation consequently is related to MLP and ENSO. The CDD trend in Hamedan، Zanjan and Sanandaj were negative and in others station were positive. The 2-3 years oscillation in Zanjan and Hamedan is related to NAO، ENSO or MEI oscillation. The 12 years oscillation of this index in Khoy and Oroomieh is related to 12 years oscillation in Sunspots. The R95p trend in Sanandaj and Saghez were positive and in the others were negative. This trend indicates indicate that number of heavy rainfall in more stations have been decreased. Finally the PRCPTOT in all station، except in Sanandaj، were negative that’s show the trend of precipitation in study area have been decreased. The 2-3 years oscillation in this index in Oroomieh، Hamedan، Kermanshah and Khoy consequently are related to ENSO، NAO and MLP and also in Zanjan is related to ENSO and MLP and in Tabriz is related to NAO، AO، ENSO، MLP and BSLP.

Typically the trend of precipitation in the study area was negative that’s show trend of precipitation has been decreased. Only the precipitation trend in Sanandaj station was positive. The trend of teleconnection patterns in a way that justifies the decrease in precipitation and also this condition applies to pressure centers. Spectral analyses showed significant oscillations in 2-3، 3-5، 5-8 and 12 years. Major area experienced 2-2 and 3-5 years oscillations. These oscillations periods are due to macro-scales circulations; mainly include the oscillation in ENSO، NAO and AO and also Mediterranean Low Pressure.

To doing this study، daily precipitation، minimum and maximum daily data from synoptic Kermanshah station during 1/1/1961 to 31/12/2011 have been used. In order to detection extreme temperature and precipitation، 27 indices recommended by Expert Team Climate Change and Indices (ETCCDI) and 6 other extreme indices have been used. Before any analysis، data have been quality controlled and pert values eliminated from data time series. To investigation climate change occurrence، recommended statistics tests by World Meteorology Organization (WMO) have been used. Two test Cumulative Density Test (CDT) and Worseley Likelihood Ratio Test (WLRT) applied in order to clarify the homogeneity and non homogeneity and jump in the indices time series. The significant of the jump in time series examined by Mann Whitney test and significant trend tested by Mann Kendal. So changing rate of trend for each 33 indices estimated by Sen Estimator. The results showed that cold extreme indices including FD0، TNx، TN10P، TX10P in Kermanshah are decreasing while extreme warm indices SU25، TR20، TX90P، TN90P، WSDI، TMIN Mean and TMAX Mean are increasing. The indices of R5، R10، CWD and PRCPTOTO are decreasing. In 1976 displacement of Kermanshah station occurred that result in jumping of DTR، TN10P and TMIN Mean indices. The behavior of these indices after jumping year is significant.