جستجوی مقالات مرتبط با کلیدواژه « Southeast of Iran » در نشریات گروه « جغرافیا »

The aim of the present study is to dynamically model the spatial-temporal characteristics of dust in the south and southeast of Iran with REG-CM4 model using monthly dust data and RegCM4 data. For this purpose, the dust distribution of the IDW method along with the dust diagrams were plotted. The RegCM4 model was implemented with the paired Lambert image imaging system for 40 km horizontal separation with the paired chemistry model. The location of monthly and annual dust distribution shows the highest amounts of dust for the cities of Zabol, Bandar Abbas, Zahedan and Jask compared to Sirjan, Kahnooj and Lar stations. The highest frequency of dust in Sistan and Baluchestan (48%), Hormozgan (27%) and Fars provinces with 16% and the lowest frequency for Kerman province (9%). In general, the summer seasons (at Sistan station) and the winter (Kerman station) have the highest and minimum dust events, respectively. The time survey also has the highest amount of dust for the warm months of the year and the lowest for the cold months of the year. July at Zabol station and November and December at Sirjan station have the highest and lowest dust levels, respectively. The RegCM4 climate model also shows maximum dust on the southeast, south and south coasts for different variables.

Precipitation as the most important climatic element is always studied from two perspectives of time and place. Emphasis on the time perspective determines temporal changes and emphasis on the location perspective determines the spatial variation of precipitation. Since Iran is located in an arid and semi-arid region, it lacks large internal and adjacent water resources to supply moisture to its precipitation, and as a result, most of its precipitation moisture sources must be supplied from the surrounding water levels. One of the methods that can be used to study the course of rainfall in the past and present is to analyze the trend of time series at different scales. So far, statistical methods have been presented for the analysis of time series routines, which can be divided into two general categories: parametric and non-parametric methods. Southeastern Iran, which includes Sistan-Baluchestan province, Kerman, southern Khorasan and the eastern parts of Hormozgan province, They are one of the arid regions of Iran. Restriction on water resources and annual precipitation in this part of the country have severely limited agricultural and industrial activities. The lives and deaths of the majority of people are also related to the low precipitation that falls throughout the year. Therefore, considering that a comprehensive study on precipitation trends in the region has not been done, the purpose of this study is to investigate the annual and seasonal precipitation trends by stations in southeastern Iran. The results of this study can play an important role in understanding the precipitation trend in the southeast region for planning related to water resources management, management of unexpected events such as floods and also the optimal utilization of those precipitations.

In order to conduct this study, in order to recruit rainy periods, daily precipitation data were obtained from synoptic stations in the southeast of the country, including selected stations in the three provinces of Hormozgan, Sistan and Baluchestan and Kerman during a 30-year period (1987-2016). Two Mann-Kendall tests and the Sen’s Slope Estimate are among the most common non-parametric methods of trend analysis when considering hydrometeorology. Various studies conducted using these two methods indicate the importance of their widespread use in the rapid evolution of time. Identify the data change using the Man-Kendall method, specify its type and time. The non-parametric Kendall test was proposed by Mann and then developed by Kendall (1975) based on ranking data in a time series. This method is widely and widely used in the analysis of the process of hydrological and meteorological series.

The trend of average annual, seasonal precipitation and maximum 24-hour precipitation in southeastern Iran Considering that in the annual, seasonal and maximum 24-hour precipitation trend diagrams, the intersection of the U and U' sequences above and below the significant lines did not occur, which means that acceptance is random (acceptance of H0 hypothesis) and there is no significant trend (H1) variable. Precipitation is in the southeast of Iran and in fact the condition is -1.96 (ti)< U or 1.96 (ti) >U and has a static series.In the Sen's Slope Estimate test, the total reduction of winter precipitation slope was equal to -0.350 mm, which in the case of 95% confidence of the upper and lower slopes of this slope is equal to -0.123 and -0.835, respectively, and in the case of 99% of the slopes. High and low are 1.604 and -2.318, respectively, per year. The Sen’s Slope Estimate test for annual rainfall, summer, autumn, winter and maximum 24-hour precipitation has estimated the negative precipitation slope. Mann Kendall test estimate shows a decrease in precipitation in winter of -1.71 per year.Annual, seasonal and maximum 24-hour precipitation trend by stations in southeastern IranIn the study of changes in annual precipitation using Mann-Kendall test, it is observed that the annual precipitation trend in most stations in the southeast (except Bam and Chabahar) has a decreasing trend. The Sen’s Slope Estimate showed is the highest precipitation at any given time at Bandar-Lengeh station at -4.16 mm per year. The time series of Man-Kendall test in the seasons of the year indicates that in spring, summer and autumn, the precipitation trend in most stations is decreasing, but this trend is not significant in any of the stations in southeastern Iran and only in winter precipitation In Bandar-Lengeh, Jask and Kish stations, it has a decreasing trend at 95% significance level. Sen’s Slope Estimate data showed that the amount of precipitation decreases in the mentioned stations.

The results of by using Methods the Mann-Kendall test showed that the mean annual precipitation trend as well as spring, summer and autumn seasons of southeast Iran was not significant and only winter precipitation had a significant and decreasing trend. Estimates of the slope of sen indicate that the slope of precipitation in southeastern Iran in winter is -0.350 mm in year. The annual precipitation trend of BandarAbbas, BandarLengeh, Abumousa and Kish stations at 95% and Jask and Iranshahr stations at 90% were significant. Test statistics showed that the highest annual precipitation reduction was at the Bandar-e-Lange station at -4.16 mm in year. In spring, summer, and fall, precipitation was not significant in any of the stations in the southeast of Iran and winter precipitation in Bandar-e-Lengh, Jask, and Kish stations had a 95% significant decrease. Assessment of 24-hour rainfall variations showed that the above mentioned precipitation had a decreasing trend at 99.9% at BandarAbbas stations and 95% at Bandarlange, Jask, Abumousa and Kish stations. According to the tests and analyzes performed in this study, what is certain is that in all stations in southeastern Iran, a significant positive trend in annual, seasonal and maximum 24-hour rainfall was not observed at the level of 99% and 95%, and most precipitation trends from It is a kind of decrease and has revealed the fact of decrease in rainfall in the southeastern climate of Iran during the years 1987 to 2016, which decrease in annual rainfall is mostly related to the winter of -1.71 per year.

Applying climatic indices introduced by the Expert Team on Climate Change Detection and Indices is one of the most widely used methods to detect climate change. In present research, daily temperature and precipitation data of Zabol, Zahedan and Iranshahr synoptic stations were applied during the period 1966-2015 to detect the occurrence or absence of climate change. To this end, 8 precipitation and 2 temperature related indices were used, Mann-Kendall and slope estimator methods were applied to determine trend and magnitude of trend, respectively. Results suggested non-significant increasing trend in monthly maximum value of daily maximum temperature and daily minimum temperature. The studied indices related to precipitation are also decreasing without trend significant in all over the province. Consecutive dry days index of is decreasing without specific trend at Iranshahr station, but it increasing without specific trend at other two stations. In addition, Consecutive wet days index has a significant decreasing trend at Iranshahr station while it has non-significant decreasing trend at Zabol and Zahedan stations. The 1-day and 5-day maximum precipitation amount indices are decreased that is no trend observed for the 5-day maximum precipitation at Zahedan station. It can be stated that the climatic indices related to temperature and precipitation are increasing and decreasing, respectively in the study area. Overall, it can be concluded that the happened changes and fluctuations in the study area are not related to climate change phenomena due to the lack of significant trends in the majority of used indices. However, understanding these changes can greatly help decision makers and urban and regional planners, especially in matters related to metropolitan development and agriculture, and so on.Extended AbstractIntroductionRegarding the detection of climate change, the long-term series trend of climate parameters such as precipitation and temperature need to be studied. A major part of climate change studies has been conducted through analysis of precipitation, temperature, pressure, humidity time series and their positive or negative trends. Researches indicated that, atmospheric parameters are strongly influenced by the global warming, greenhouse gases, surface phenomena (ocean and land temperature increase), urbanization and urban heat island (Ben.Gai et al., 2001; You et al. 2011). Analysis of time series is an appropriate method used for mathematical modeling, prediction of future events, trend detection of climatic data and missing data reconstruction. Generally, it is said that the trend in the climate indices time series may result from a normal gradual change, climate change or human activities effects (Brooks and Carruthers, 1953). It should be noted that, confirming the existence of a significant trend in time series related to the precipitation or temperature (for example extreme climate indices) cannot be solely a decisive reason for the existence and occurrence of climate change in a region, but it reinforces the assumption of the event, because there are many parameters associated with the control and operation of atmospheric systems (Serrano et al. 1999: 2894). The Mann-Kendall test is one of the most common and widely used nonparametric methods for time series analysis, and it is used to identify the trend changes. This method is widely used to analyze hydrological and meteorological time series trend. The Mann–Kendall test is used for trend analysis in ETCCDI workshops.MethodologyExpert Team on Climate Change Detection and Indices (ETCCDI) introduced 27 climate indices to study the climatic parameters (Peterson et al. 2001), consisting of 16 indices for temperature and 11 indices for precipitation. In the present study, climate indices including RX1day, RX5day, PRCPTOT, CWD, CDD, R20, R10, and R95p were used for precipitation, and TXx, TNn were used for temperature, according to the objective of this research. All of these indices were calculated by the RClimDex software package. The indices were calculated for three synoptic station in the area, and then the time series was attained associated with each index.  The Mann-Kendall test was used at 90, 95, and 99 ⁒of confidence level for time series indices at 10, 5, and 1 ⁒level of significance, respectively, and according to the Mann-Kendall test Z-statistic, the ascending and descending trend of each index were determined over time. Subsequently, the gradient of trend line was determined by Sen’s slope estimator. Also, the graph of climatic anomalies of indices was drawn compared to the long -term average for these synoptic stations over the time. The Sistan and Baluchestan province is licated in Southeast of Iran, between 25° 04ʹ to 31° 29ʹ north latitude and 58° 55ʹ to 63° 20ʹ east longitude with 178431 KM2 area. In this study, to achieve precise results, daily data on temperature and precipitation collected from three synoptic stations including Zabol, Zahedan and Iranshahr in Sistan and Baluchestan was used during a 50-year period (1966 -2015).Result and DiscusionThe results indicate that the indices refer to the precipitation including PRCPTOT and R95p have a decrease trend during statistical period and the largest positive and negative anomaly the PRCPTOT index were in 1982 and 2001, respectively, compared to the long-term average, also about R95p occurs in 2007 and 2001. The anomalies related to rainfall intensity including RX1day, RX5day, R10 and R20 also have a decreasing trend. Regarding the temperature indices, it should be noted that temperature has been increasing over the years studied. The TNn anomaly is increasing with a relatively steep incline. This means that the cold days are decreasing during the desired years and generally the minimum temperatures have been followed by an increasing trend. In contrast, the anomaly of TXx has been almost constant trend and does not show much variation. The trend of PRCPTOT, RX1day, R10 and R95p are non-significant decreasing trend at all three stations. Regarding the CWD index, the results showed a decrease in all station, with a significant decrease at 95% confidence level at Iranshahr station and non-significant at the other two stations. In addition, the CDD index increased in Zabol and Zahedan and showed a non-significant decrease in Iranshahr. About the trend of temperature indices, it was found that the trend of TNn was non-significant increasing in Zahedan and Iranshar and there was no trend in Zabol. Also, the TXx index increased without trend in Zabol and Zahedan stations and there is a decrease trend at the 90% significant level in Iranshahr.ConclusionThe present study investigated the occurrence of climate change in Sistan and Baluchestan province using daily temperature and precipitation. For this purpose, was used of 8 indices for precipitation and 2 indices for temperature from ETCCDI. The result showed that the indices under study have changes and fluctuations, but in the vast majority of cases the changes were short-term climate fluctuations and trends are not significant during the time. The study indicates that overall the amount of rainfall decreased in the whole region, especially in the northern part of the province, but the intensity of precipitation decreased in the central and southern regions more than in other areas. As for the temperature the whole region shows an increase in temperature. Occurrence of changes in the region causes dramatic changes in increasing energy and water demand as well as changes in the region’s water resources. Therefore, the results of this study and research like this can provide valuable help and guidance for planners, decision makers and policy makers in adopting strategies to cope with these changes, both in term of risk management and access to renewable and low-cost energy.

Analysis of the urban system of the south-east of the country is necessary because of the strategic importance of this region and with the aim of recognizing and providing a platform for balanced development, appropriate distribution of population and utilization of environmental capabilities. Therefore, recognizing the environmental, social and economical potentialities and capabilities of the cities of over 10,000 people in three provinces in southeastern Iran (Kerman, Sistan and Baluchestan and Hormozgan) with a regional development approach, is in line with the development of a balanced development of the reasons for writing this research. In fact, the purpose of the present research is to initially investigate the urban system of the southeastern parts of the country, and then, according to assessments of the current status of the urban hierarchy system, its impact on the future of regional development indicators. The results showed that urban hierarchy imbalance is one of the main characteristics of the urban system in the southeastern region, which has resulted in the lack of necessary small infrastructures and small towns. Also, the results of the futuristic model showed. Considering the importance of demographic indicators and their impact on the future of regional development indicators and the involvement of multiple elements, it is clear that the variables of urban management practices (36) and development status Human Indicators (35) have the highest calculated column value, respectively. In other words, the most important feature of these variables is low impact and high impact, and they are referred to as strategic factors, whose reinforcement boosts development in this region and has a positive impact on the economic, social and environmental dimensions.

This study purposes to identify and analyze the synoptic-dynamic patterns of the inclusive summer super-heavy rainfalls in the southeast of Iran. To do so, the rainfall data of 14 synoptic stations and 126 raingauge stations were investigated over a 26-years period of time between 1989 and 2014.The criteria, considered in this paper, for the inclusive summer super-heavy rainfalls, is the rainfall for which the Standard Score during 24 hours is “99th” percentile and more than that and also it covers at least 50 percent of the area under study. Using this criteria, heavy rainfall for 22 days was identified. In order to extract the effective synoptic patterns in the super-heavy rainfalls, for every rainy day the 0.75*0.75-degree data including sea level pressure, geopotential heights of 850, 700, 500, and 200 hPa, and zonal and meridian components of the wind flow at the levels of 850, 700, 500, and 200 hPa as well as the specific humidity of 1000, 850, 700, and 500 hPa were received from the European Centre for Medium-Range Weather Forecasts and plotted in the GrADS environment. Analyzing different synoptic maps at different levels demonstrates that three patterns of trough, low-pressure Monsoon , and high-altitude have the main role in occurrence of the summer super-heavy rainfalls in the area. One important point about the identified patterns relates to the amount of their specific humidity which ranges from 10 to 20 g / kg at sea level and 850 hpa; This means in the presence of ascent, thermal or dynamic, the summer super-heavy rainfall can be expected.

Lightning is one of the most fascinating climatic phenomena, which has not yet been fully understood. This phenomenon usually occurs during thunderstorms and at the times of electrical field failure in a variety of cloud-to-ground, cloud-to-cloud, and in-cloud or intra-cloud. The cloud-to-ground lightning which strikes the ground is one of the most important causes of mortality due to weather conditions. Lightning can also cause many financial losses such as damaging power lines and causing fire. Therefore, spatial distribution of lightning is essential in terms of energy and safety management. Furthermore, our community, which increasingly relies on information networks, helps to identify the areas prone to lightning in order to protect the information systems. Lightning activities vary widely on the spatial and temporal scales, and depend on local convectional activities to some extent. The knowledge of lightening activities was usually based on surface measurements over time, prior to the arrival of the satellites. But, the activity of these storms is not measured in places where there are no synoptic stations. Therefore, it is necessary to predict the exact location and the severity of convective storms based on the development and monitoring of the route for timely notification. This is because all measurements related to thunderstorms in Iran are recorded with a three hour interval in various codes and only at synoptic stations.
This study was carried out using lightning data recorded in space by LIS sensor in a period from January 1998 to December 2013 (16 years). Lightning imaging sensor (LIS) is installed on the TRMM satellite. The LIS sensor is an optical detector that measures light-induced and light-intensity variations in clouds in the range of 777 nm/s and is capable of observing thunderstorms with a scale of 3 to 6 km on a 600x600-km while the effective LIS efficiency is 90% at night and 70% at local noon time.
At the first stage of data analysis, it should be determined that the data are randomly distributed or have a certain spatial trend. Some of geographic processing functions were applied to data in the GIS software to compute the statistical values and to determine the locations having significant lightning levels. These calculations are done based on the Euclidean distance between the points (thunder and lightning) and the spatial concept of that weighting method based on the inverse distance. Other indices also compute the spatial distribution of the data. The nearest neighbor index (NNI) and the Kernel density function are among these indices. The NNI is expressed as a proportion of the observed distance to the expected distance, assuming the random distribution of the images. To generalize the geographic location of a phenomenon (lightning occurrence) to the whole area, the Kernel density interpolation estimator has been used throughout the region. In fact, the Kernel density function in the GIS software calculates the density of the features in their neighborhood and can be used for linear and point features (lightning).
The results of this research showed that the maximum frequency of lightning occurs in the southeast of Iran in the months of March to August (warm period of the year). Its highest frequency is in August and its lowest frequency is in December. In the study of daily changes it was also found that from the early afternoon until late afternoon (from 1300 to 1600 hours local time), the lightning activities significantly increase, which seems to be related to local convectional activities which are along with the surface heat created by daily radiation of the sun. The nearest neighbor index results showed that the data distribution follows the cluster pattern. In other words, some regions have more favorable conditions for lightning. The results of the Kernel density index indicated that these areas are in the southern slopes of the region and its maximum is located before the main peak. The maximum frequency of lightning lies between 26° and 27° N, and is on the same orbital direction. Given the maximum lightning occurrence time which is during the warm period of the year, it seems that the southern currents created by the monsoons of the Southeast Asia along with local topography, is the exacerbating factor for the lightning activities in the southeast of Iran, and in particular, the region with a maximum lightning activities.
The use of satellite data to illustrate the distribution of some climatic phenomena can be very useful, since the frequency of some phenomena (especially lightning) is not recorded on ground stations. On the other hand, the distribution and density of ground stations are not appropriate, because the density of synoptic stations is particularly in low mountainous regions and the shape of the land in these areas is complex, and the distribution of thunderstorms is affected by this form of land. As it was observed in the results, one of the most important factors of the frequency distribution of lightning is the roughness, and these results indicate that remote sensing technology can be used to calculate the distribution of the phenomena of interest with high precision.

Introduction Long-term synoptic maps related to sea levels show the presence of a semi-permanent, low-pressure system in the warm season in the Indian subcontinent, southern Afghanistan, Pakistan and Central Plateau of Iran, known as Low-Pressure Pakistan or Gang. The above mentioned low pressure refers to thermal low pressure created on Sindh basin in Pakistan due to the entry of solar radiation in May and June. Since the daily radiation is more than the nightly radiation, this thermal low pressure has become a permanent summer system (Boucher, 1975, 132; Kaviani and Alijani, 1999, 192). Pakistan thermal low pressure is an important and effective system in the climate of Pakistan, the northwest of India, the southwest of Afghanistan, and the southeast and east of Iran. Therefore, extensive studies have been conducted to examine the effect of this system on other parameters and climatic phenomena such as the studies by Iqbal and Jawaid (2008), Faisal and et al., (2013); Alijani et al., (2011); Khosravi et al., (2011). The study by Bollasina and Nigam (2011) which is a complete study on Pakistan low pressure, on the origins and changes of summer low pressure in Pakistan and northwest India, concluded that Pakistan-India low-pressure current influence two regional and remote forces. In regional scale, the effects of Hindu Kush Mountains were stronger than those of Earth surface and talent temperatures. The effects caused by remote factors, rooted in convection currents in Gulf of Bengal and East India in June and July, are also of importance. According to the importance of this system and its effect on the Iranian climate especially in the southeast, it is essential to study the tempo spatial variation. Therefore, the main questions outlined here are as follows: What are the changes of Pakistan low pressure during the statistical period? How are the spatial changes over time? How are the changes in terms of intensity over time?

Data and Methodology ECMWF (ERA-Interim Version) with a spatial resolution of 1*1° was used in the geographical area (Latitude of 20-50° N and Longitude of 20-90° E) for the warm seasons (June to September). The statistical period 1980-2015 was taken into account. In order to extract the central pressure, the longitude of 62.5° to 72.5°E and latitude of 22.5°to 32.5°N were defined. First, the annual minimum pressure was extracted in the form of time series. Man-Kendal non-parametric trend tests were employed to study the variations.
Results and Discussion 36-year medium maps (1980-2015) for sea level pressure over the warm seasons show the deployment of the low-pressure system with two closed cells. As it is clear in the literature review, the system is a feature of warm seasons usually created as a result of extreme heats of underlying atmosphere along with the dynamical subduction originating from the West Indies in the south of Pakistan (Ramage, 1966). According to the time-series results, the lowest pressure was reported in 1984 with the central pressure of 996, and the maximum was reported in 2015 (999). A review of monthly Pakistan low pressure shows that the central pressure of this system has different fluctuations. It experiences a rising trend over all months. The increase was evaluated at three confidence levels (90%, 95%, and 99%). They are not significant, however. The greatest rising trend was observed in June and lowest in July. As a result, the system experiences a slightly increasing trend. Decade anomaly of central pressure was also studied in monthly and yearly scale. Table 1 shows the results. According to the results, the central pressure of the system is weakening and the last decade has the highest central pressure.
Table 1: Anomaly of Central Pressure of Pakistan Low Pressure (1981-2015), Based on Spatial Period (Latitude of 22.5*32.5°N and of Longitude 72.5*62.5° E)
Period
Pressure
Difference
Total Average (1981-2015)
997.31
-
First decade
997.26
-0.05
Second decade
997.19
-0.12
Third decade
997.29
-0.02
Five years of latest
997.63
0/32
Finally, Hoff Muller Maps were used to describe the static continuity variations, that is, spatial changes of this low-pressure region during two periods (1980-1989 and 2005-2016). The results showed that Pakistan low pressure has no specific spatial extent or displacement of the East or the West direction. In other words, the system has equal extent over the initial and closing decades.
Conclusion Pakistan low pressure is an important, effective system in South Asian regions. It is of great importance in the region. This article aimed to study the tempo variations of this system using Man-Kendal nonparametric test and the Sen's estimator of slope. The monthly and annual review show that this system has a rising central pressure trend. In other words, it is weakening. Note that the increase is slight and is not significant at 95%, 90%, and 99%. Anomaly map review shows verified it, too so that the greatest central pressure was observed in the recent decade. The system did not show any specific spatial variation.

Unusual periods of heavy rainfall in Iran with climatic variation in each part of the country are very important.The heavy rainfall always have been one of the hazards of climate That the destruction and irreparable damages life and property is involved. Therefore, understanding the factors and parameters that create the climate system precipitation in any place and at any time of the year, especially transitional period is necessary. Rainfall phenomenon is very complex and nonlinear that the great variability over time and space and a variety of conditions that have important role in the occurrence can be divided into two categories: Synoptic Patterns and local conditions.
Weather is largely controlled by the passage of Synoptic Patterns. On the other hand the occurrence of any weather's particular pattern is to a large extend determined by the distributions of land masses, sea surface temperature gradients,Characteristics and type of land cover (biosphere), topography and the orientation of baroclinic zones.
The objective in this paper is analysis of synoptic patterns and vertical profiles of air in local heavy rainfall in South East of Iran including Sistan and Baluchestan, Kerman, Hormozgan and South Khorasan provinces.
In the summer, synoptic patterns of seasonal rains in South East of Iran often Due of the spread of monsoon air mass. In winter, westerly winds extend towards lower latitudes including the study area; the seasonal rainfall pattern in the region brings.
In this study, the main question is that the synoptic patterns of rainfall during the transitional period (spring and summer) how do they arise? And what are the characteristics?
Data and The purpose of this research is analysis of synoptic patterns and vertical profiles of air in local heavy rainfall in South East of Iran. Meteorological stations studied in this article are located in four provinces including Sistan and Baluchestan province, Kerman province, Hormozgan province and South Khorasan province. Review of daily precipitation data of 31 meteorological stations during (1981-2013) showed that heavy rainfall occurred in October 1390 in South East of Iran, one of the heaviest rain falls during transitional period is local function and the amount of rainfall is greater in most of the stations to compared whit the normal monthly rainfall. To investigate the Characteristics of meteorological parameters in rainyday and the days before rainyday, initially thermodynamic diagrams were analyzed. To determine the synoptic pattern, Weather maps up to 250 hPa Geopotential were examined.
Thermodynamic diagrams in rainy days as compared to the days before rainy days showed that the temperature and air pressure has dropped; Relative humidity and dew point temperature has increased. Thermodynamic diagrams in rainy days as compared to the days before rainy days showed that the temperature and air pressure has dropped; Relative humidity and dew point temperature has increased.
The results of the plot Ski-T, height of FCL and LCL, altitude difference Cloud top relative to the FCL and the amount of Dynamic indices: KINX, SHOW, CAPE, was Show prepared for the unstable Weather conditions. Calculation of instability indices showed that the convection factor was a supporting role in the occurrence of such precipitation, because when convective precipitation is the main factor the Convection is enough intensity and provide the instability needed to create precipitation. Synoptic pattern analysis suggests the establishment of Cut off low. The cut-off low is a cold low (depression) in mid-latitudes (occasionally almost in subtropical latitudes) where air of polar origin is cut off from the main subpolar belt of low pressure and cold air, the normal track of depressions. Cyclonicity around the the core of Cut off low and South wind flow on the eastern edge of Cut off low, arrangements for air convection is unstable in South East of Iran. Cut off low activity from this point is very important, which complements the summer rainfall caused by the monsoon system and winter precipitation caused by western cyclones can play a significant role for autumn rains transitional period In South East of Iran. Calculation of instability indices showed that the convection factor was a supporting role in the occurrence of such precipitation, because when convective precipitation is the main factor the Convection is enough intensity and provide the instability needed to create precipitation. Synoptic pattern analysis suggests the establishment of Cut off low. The cut-off low is a cold low (depression) in mid-latitudes (occasionally almost in subtropical latitudes) where air of polar origin is cut off from the main subpolar belt of low pressure and cold air, the normal track of depressions. Cyclonicity around the the core of Cut off low and South wind flow on the eastern edge of Cut off low, arrangements for air convection is unstable in South East of Iran. Cut off low activity from this point is very important, which complements the summer rainfall caused by the monsoon system and winter precipitation caused by western cyclones can play a significant role for autumn rains transitional period In South East of Iran.

A drought is a prolonged period of water deficit and usually occurs when an area does not receive significant precipitation for a sustained period of time, say several months (Chen, Kuo, & Yu, 2009; Linsely, Kohlerm, & Paulhus, 1959). The effects of drought often accumulate slowly over a considerable period of time that may linger for several years even after the termination of drought. Therefore, some authors have called it a creeping phenomenon (Wilhite, 2000). It is difficult to precisely determine the onset and end of a drought event. A drought can be short, lasting for a just a few months, or it may persist for years before climatic conditions return to normal. Drought considered as the most complex, but the least understandable phenomenon of all the natural hazards affecting more people than any other hazards (Mishra & Desai, 2005). Droughts can be classified into four categories as meteorological, hydrological, agricultural and socioeconomic (American Meteorological Society, 1997; Palmer, 1965; White & Walcott, 2009). The preparedness and planning for a drought depend on the information about its areal extent, severity and duration (Mishra & Singh, 2011). This information can be obtained through drought monitoring that is usually done with the use of drought indices (DIs) which provide information to decision makers about drought characteristics. Thus, these indices can be used to initiate drought action plans. Prediction of droughts is useful for early warning that may reduce the response time and consequently the impact of a drought. For many regions, especially semi-arid regions, limited knowledge is available about the diurnal and seasonal cycles of land surface interactions. Semi-arid areas pose a challenge due to large contrasts between dry and wet conditions within a temporal cycle (Schuttemeyer, 2005). Meteorological drought is generally an indicator of other drought types with below normal precipitation, and usually occurs first before other drought types do. The seasonality and climatological conditions vary by location. Drought severity may differ from site to site under different climatic conditions, hence, as many as applications of DIs and their comparisons are beneficial for specific regions in the world. The objective of this study is to develop an aggregate drought index (ADI) based on principal component analysis (PCA) to assess the severity of Hydro-Meteorological drought in the southeast of Iran. Therefore, Stream flow drought index (SDI) and effective drought index (EDI) is determined for several different monthly time steps. The ADI is calculated after a principal component analysis to determine aggregated index value.
Study Area : Southeast area of Iran is confined to Sistan and Baluchestan province and located southeast of the intersection of between 29ºN and 57ºE. In this area, precipitation mostly falls in winter and summer seasons. Summer rainfall related to the monsoon mass effect, which comes from Indian Ocean. Climate is arid and semi-arid. Bahouklat is the most important river in area. The origin of this river is the Pir Abad Mountains in the southeastern of Iranshahr city and the passing of Sarbaz, Bahoukalat, Pishin and Dashtyari regions eventually lead to Govare Bay. This river has various names in different regions and called Sarbaz River from Sarbaz to Rask and passes of Pishin dam. Discharge of this river (Sarbaz) is very important in this area.
Material and Hydrological and meteorological drought values are necessary for ADI computation over a long period. Therefore, streamflow drought (SDI) and effective drought (EDI) Indicators were used to estimate the hydrological and meteorological droughts. The input variables include the daily values of stream flow of Sarbaz River in the Pirdan hydrometric station and rainfall during the 21 March 1985 to 20 March 2011 common period. Variables were arranged according to water year (also water year, flow year or discharge year), which begins in October in Iran. Daily timestep of SDI and EDI were estimated respectively according to Nalbantis (2008) and Byun and Wilhite (1999) and then ADI were calculated based on principal component analysis according to Keyantash and Dracup (2004).
Drought is a very common phenomenon in Iran and particularly in the south east and it has become a recurrent phenomenon in this area in the last few decades .The hydrometeorological drought index was applied for the identification of drought severity in south east of Iran and drought occurrences were monitored during the experimental years of 1985/86 to 2010/11. Results based on the aggregate drought index (ADI) revealed that a long period of hydro-meteorological drought occurred from 1994/95 to 1998/99. Also, a prolonged wet period has started immediately after the end of drought and has continued to June 2005. In addition, according to drought severity, 1997/98 and 2003/04 water years respectively are extreme drought and extreme wet years. Finally, we have compared the performance of EDI (Meteorological drought index) and SDI (Hydrological drought index) with aggregate drought index. Based on this comparison, aggregate drought index (ADI) could be better highlighting the drought conditions and its characteristics.
Aggregate drought index (ADI) is methodology presented for replacing the unidimensional analysis of drought phenomena which can assist authorities and stakeholders to take rational decisions for combating droughts. Using this approach, a more effective way for assessing the severity of drought is obtained. On the other hand, ADI shows capability to detect dry and wet years. Moreover, it has capability to detect historical drought. Overall, by considering the results, the ADI is more reliable than EDI and SDI for drought monitoring in the study area. In this study, ADI time series were compared against the EDI and SDI to describe an important and long drought event in south east of Iran, the 2003-2004 event from a hydro-meteorological perspective. The ADI methodology provides a clear, objective approach for describing the intensity of drought and can be readily adapted to characterize drought on each area.