Journal of Spatial Analysis

Hot, humid weather causes to the sultry feel. Sultry condition is usually accompanied with loss of physical ability and human respiratory and it has an adverse effect on peoples who have circulatory or other heart problems and this feeling is more than others. Sultry feel is a feeling like any other sensitive reflections of mental state. And this state apparently can’t be measured by special instruments. With this description, there are a lot of efforts has been done to identify this phenomenon by meteorologists and climatologists. And a series of psychological climate tests show that we can examine the creation and incidence of this sense based on empirical studies as a scientific and objective attitude. Therefore, this study aims to classify the sultry days in the southern half of Iran based on sultry continuous hours. And the obtained results are presented as a form of zoning maps.

     The studied zone in this research is selected stations in the southern half of the country located in the province of Sistan & Baluchestan, Kerman, Hormozgan, Fars, Bushehr and Khuzestan. This area is located between two latitude 25 and 35 north and length of 47 to 63 east degrees. To achieve this goal, hourly partial pressure of water vapor of 13 selected stations were obtained for a period of 15 years (1995-2009) from Meteorological agency. After obtaining data and creating the database, to separate sultry conditions from non-sultry conditions, threshold of partial pressure of water vapor of Scharlou which was equivalent to 8.18 Hpa were used.

    Based on these data, the hours and days that the partial pressure of water vapor was equal or greater than 8.18 hpa will have sultry conditions and otherwise, they have non-sultry conditions. Then, based on this threshold, sultry days were divided into eight categories. The basis of this classification is that if in a particular day among eight branches of observation, one station, only in one observation record a pressure equal to or greater than 8.18 hpa was observed, it will be placed in first class and if only two observed records a value equal or greater than defined value, it will be placed in second catagory and finally, if all eight observations amounts equal to or greater than 8.18 had been recorded, it will be placed in eight class. After placing the sultry days in one of eight branches of classes, long-term averages of monthly, quarterly, quarterly and annual were calculated and mapped.

    Based on defined thresholds, sultry days were separated from non-sultry days, then sultry days were extracted and it was placed in first to eighth classes. The results of this classification showed that on monthly scale, January has the fewest sultry days in twelve months of the year. In this month, only two stations of Chabahar and Bandar Abbas had the sultry days of eighth classes. It means that 24 hours, they were in sultry conditions. Other stations that have a sultry day in this month, often their sultry days are from first to fourth classes and it means that they had maximum 3 to 12 hours of sultry conditions during the day. Most sultry days can be seen in two June and July months. So, in these two months, all studied stations have at least one sultry day,Specially  in three stations of Chabahar, Bandar Abbas and Bushehr. And all 61 days, they have sultry conditions. In terms of classification of sultry days, all 61 days of Chabarhar station are part of sultry days of eighth class. In two stations of Bandar Abbas and Bushehr, except few days that are from sixth and seventh classes, other days are from eightth class, other stations experienced one of the eightth classes of sultry days with different ratios. , and at the seasonal scale, winter has the lowest days of sultry and summer has the most days of sultry days. In term of classification of sultry days in seasonal scale, there are conditions as monthly scale. The interesting point in summer season is that sultry days on two stations of Zabul (35 days) and Iranshahr (51 days) are considered due to their Geographical locations. In Zabul station, the reason of these sultry days can be due to the neighborhood of this station with Hamoon Lake. But it should be mentioned about Iranshahr stationthat the reason of its sultry condition is entrance of monsoon low pressure and moisture transfer by the system on the south-east of Iran an especially Iranshahr. On an annual basis, it was also observed that always in south east of Iran (Especially Chabahar station), the number of sultry days is much more than south west of Iran, also occurring sultry days with eighth, seventh and sixth classes in this zone is so different from south-west of Iran. The reason of these differences in number of sultry days and sultry classes  related to the latitude of south east of Iran which is lower that south west and in other words, we can say that climate of south East of Iran is more similar to tropical climate than subtropical climate. 

Ultra violet radiation has some useful effects and some harmful effects on human health an d create many diseases. Nowadays not only declined but the usefulness of the therapeutic effects of the Sun in the treatment of diseases such as rickets, psoriasis and eczema have been proved. But prolonged exposure to radiation of the Sun is not always beneficial and may cause acute and chronic effects on the health of the skin, eyes and immune system. Ultraviolet radiation of the Sun is one of the most destructive waves for life on Earth. So Ultraviolet radiation index and predict its rate (1 to +11) as well as the analysis of this indicator will help people to protect themselves against the Sun

    Ozone station , global ozone measurement stations and only stratosphere in Isfahan, Iran, which is in the South and in the Northern geographical position latitude 32' 31 and 70 ' 51 is located over the East. The altitude of this station from sea is 1550 m. Also atmospheric parameters in this station which are measured daily include temperature, pressure, humidity, wind speed and direction and in the upper levels of the atmosphere at 12 GMT with the help of Joe's high temp radio instrument.

    The first step to do this research was gathering of climatic data and the statistical and quantitative analysis in order to study on the subject. Ultraviolet radiation data on the same basis of assessment, ozone station during the period January 2001-December 2010 has been collected. The second batch of data information gathered from meteorological station of Isfahan climatic elements from 2001 to 2010. This data is based on monthly averages for analysis of solar UV radiations from meteorological solidarity with the country.

Adjust the time series at the first step in the study and analysis of the data was done in order to equal intervals in these regular categories and methods of statistical analysis was carried out on them and the overall process of UV changes in the form of daily, monthly, quarterly and annually. Also part of the analysis that was carried out on the data, check how the sequence or they had over time; this way specify whether data periodically changes or trends have been or not. Once the data is based on the time of occurrence, sort and arrange the time series on them.

Annually analysis of UV index showed the general variation is a common feature of studied years but in the spring season have high variation in compared with other season. The main reason of this variation may be related to sunlight angle that can be showed atmosphere effect on received radiation. Descriptive statistic result indicated that the highest mean of UV index is 6.52 and minimum were 4.8 that have very high variations and may be it has different harmful effects. Also seasonal analysis showed highest UV index created in hot summer related to highest temperature in this season. The computational modeling of UV index against years in different season indicates there do not exist a linear relation between two factors. The correlation analysis of UV index and some climatic factors showed there are a significant relation between temperature  with 0.8570 coefficient that  can be said in relation to increase of temperature, UV rate increased and vice versa and with cloud cover correlation coefficient is  -0.393 that have significant negative relation.

    Results showed that the peak time period are output in the first half and the second half of the year, landing in the specified time series. As well as through a linear fit to all charts, increase or decrease of the radiation, changes the trend in recent years, showed that based on the ultraviolet radiation changes the average increase in the spring and summer and fall and winter shows a decline. Also according to the ultraviolet radiation in daily statistics review ozone assessment station in the studied period (2001-2011) maximum amounts of ultraviolet radiation index, (11.5) observed in the middle of the summer and the minimum amounts of radiation index (0.5) observed in mid-winter.

Thunderstorm is one of the most severe atmospheric disturbances in the world and also in Iran, which is characterized by rapid upward movements, abundant moisture, and climatic instability. Since this phenomenon is usually accompanied with hail, lightning, heavy rain, flood and severe winds, it can cause irreparable damage to the environment. Investigation of spring thunderstorms has a great significance regarding the irreparable damages can cause by them and also because of the higher frequency of this phenomenon in the spring and the necessity for preparedness and disaster mitigation actions. To identify the locations of the major thunderstorm risk areas, the entire country with an area of 1648195 square kilometers, which is located between the 25°-40° north latitude and 44°-63° east longitude is considered.     Spatial distribution of the occurrence of hazardous spring thunderstorms was analyzed using a series of monthly thunderstorm frequency data obtained from 25 synoptic stations over a 51-year-long period (1960-2010). Ward's hierarchical clustering and Kriging methods were used for statistical analysis. Initially, total number of thunderstorms in April, May and June were considered as the frequency of occurrence of thunderstorm in different stations in the spring. Measure of central tendency and dispersion which consists of the sum, minimum, maximum, range and coefficient of variation, standard deviation, and skewness were used to clarify the changes of thunderstorms and to determine the spatial and temporal climatic distribution of spring thunderstorms. An appropriate probability distribution function was chosen to determine the distributions of the data.  Due to the large volume of data and the uneven distribution of stations, cluster analysis and kriging methods were used to classify different regions into homogeneous groups for zoning and spatial analysis of spring thunderstorms, respectively. The statistical characteristics of spring thunderstorms were reviewed and fitted with a 3-parameter Weibull distribution. Regions considered for this study were classified in four separate clusters according to the simultaneity of thunderstorms in the spring. After zoning, it was found that the highest rates of thunderstorm took place in the northwest and west of country. The northeast of Iran has the second highest number of thunderstorm occurrence. The least number of thunderstorm event had happened in the central and southern half of the country.     According to the descriptive statistics parameters, maximum number of thunderstorms occurred in May.. Based on the results of the cluster analysis, there is a similar trend in the central and eastern regions, the rest of the country was clustered into five distinct homogeneous regions, including the northwestern, western, southern, northern, central northern and northeastern regions. Zoning results indicate that the highest number of the occurrence of this phenomenon in the country is concentrated in the northwestern and western regions. Higher frequency of occurrence of thunderstorms in the northwestern and western regions may be attributed to local topographic conditions like high mountains, orientation of the terrain, solar radiation on slopes and existence instability conditions, hillside convection, the presence of water resources and specific climatic conditions in these areas. In addition, as a result of a continuous surface obtained by the method of interpolation with the least amount of systematic error and also the use of correlation functions for recognizing the spatial structure of the data and estimating the model error when using the Kriging method, the weights are chosen in order to have a more optimized interpolation function. Also the cluster analysis may significantly reduce the volume of operation without affecting the results and will help in finding a real band due to more appropriate classification of different geographic areas with greater spatial homogeneity and minimal variance within the group. Based on the results of the spatial analysis, it is clear that Kriging and Ward cluster analysis methods are appropriate for thunderstorm zoning and classification of different regions according to occurrence of thunderstorm, respectively.

Global changes in extremes of the climatic variables that have been observed in recent decades can only be accounted anthropogenic, as well as natural changes. Factors are considered, and under enhanced greenhouse gas forcing the frequency of some of these extreme events is likely to change (IPCC, 2007 Alexander et al., 2007). Folland et al. (2001) showed that in some regions both temperature and precipitation extremes have already shown amplified responses to changes in mean values. Extreme climatic events, such as heat waves, floods and droughts, can have strong impact on society and ecosystems and are thus important to study (Moberg and Jones, 2005). Climate change is characterized by variations of climatic variables both in mean and extremes values, as well as in the shape of their statistical distribution (Toreti and Desiato, 2008) and knowledge of climate extremes is important for everyday life and plays a critical role in the development and in the management of emergency situations. Studying climate change using climate extremes is rather complex, and can be tackled using a set of suitable indices describing the extremes of the climatic variables.    The Expert Team on climate change detection, monitoring and indices, sponsored by WMO (World Meteorological Organization) Commission for Climatology (CCL) and the Climate Variability and Predictability project (CLIVAR), an international research program started in 1995 in the framework of the World Climate Research Programme, has developed a set of indices (Peterson et al., 2001) that represents a common guideline for regional analysis of climate.    It is widely conceived that with the increase of temperature, the water cycling process will be accelerated, which will possibly result in the increase of precipitation amount and intensity. Wang et al. (2008), show that many outputs from Global Climate Models (GCMs) indicate the possibility of substantial increases in the frequency and magnitude of extreme daily precipitation.     eneral circulation models (GCMs) are three-dimensional mathematical models based on principles of fluid dynamics, thermodynamics and radiative heat transfer. These are easily capable of simulating or forecasting present-future values of various climatic parameters. Output of GCMs can be used to analyze Extreme climate. For this study high quality time series data of key climate variables (daily rainfall totals and Maximum and minimum temperature) of 27 Synoptic stations were used across Iran from a network of meteorological stations in the country. In order to get a downscaled time series using a weather generator (LARS-WG), the daily precipitation output of HadCM3 GCM, SRES A2 and A1B scenario for 2011-2040 are estimated.     The Nine selected precipitation indices of ETCCDMI[1] core climate indices are used to assess changes in precipitation extremes and monitor their trends in Iran in the standard-normal period 1961–1990 and future (2011-2030).    Due to the purpose of this study, at first changes in extreme precipitation indices in the standard-normal period is evaluated and its results show annual maximum 1-day precipitation increased in many regions in the East of Iran. Simple measure of daily rainfall intensity (SDII), annual maximum consecutive 5-day precipitation, annual count of days with daily precipitation greater than 10mm (R10mm), annual count of days when rainfall is equal to or greater than 20 mm (R20mm) have increased in the central areas, regions in the north , north east and southern parts of Iran. Similar results are obtained for the R25mm index.    The consecutive dry days (CDD) index has generally increased across the west areas, southwest, north, northwest and southeast of Iran and indices of consecutive wet days (CWD) decreased in these areas.    Trends of extreme precipitation indices simulated by HadCM3 SRES A2 showing increases RX1Day in North West expect west Azerbaijan Province, central, southwest, north east and coasts of Caspian Sea. Similar results are obtained for the R5mm index expects northeast. There are mixed changes in R10mm across Iran, increasing in west, southwest, coasts of Caspian Sea, Hormozgan and Ardebil provinces, East Azerbaijan, Zanjan and Qazvin  provinces. Similar results are obtained for the R20, 25 mm index in northeast, south of Caspian Sea, and some parts in western and central areas. Same as HadCM3 SRES A2 pattern there are mixed changes in R10mm across the region. Positive trends are seen in part of the Isfahan, Markazi, Kuhkilue , Lorestan, Ilam, Chaharmahaland Khozestan provinces and some part of Hormozgan and Kerman and some areas in north west. Similar results are obtained for the R20mm and R25mm index and in west of Yazd to north of Khozestan provinces have increased.    Consecutive wet days (CWD) have increased over most of the west of Iran, Khorasn Razavi and Southern Khorasn provinces, In contrast consecutive dry days (CDD) index has generally increased in many parts of the region.  
[1]. Expert Team on Climate Change Detection and Monitoring Indices

The Iranian plateau formed by the active tectonics of the Alpine-Himalayan belt, is situated between the Eurasian and Arabian plates. The plateau is considered as one of the most seismically active regions in the world and is faced with different earthquakes each year. Active tectonic conditions, different faults and seismic sources and a large population in earthquake-prone areas makes it necessary to perform more considerations and scientific studies in order to analyze the seismic hazards and risks.

In this paper, different aspects and effects of the Iranian seismicity has been determined. In order to review the status of seismicity and distribution of earthquakes in Iran, we need first to consider the tectonic setting, structural environment and the active faults of the country. To date, there have been some different studies to divide the the seismotectonic setting of Iran into different seismic zones which are explained in this paper briefly. Moreover, the seismicity and most destructive past earthquakes in the Iranian plateau and distribution of earthquakes are shown.

    One of the most important tools in studying earthquakes is to perform continuous recording and monitoring of the seismic event and ground motions which is implemented using seismic and strong motion networks. The systematic networks have been set up within the country and are working and responsible for data collection and monitoring of seismic events permanently. These networks including the Iranian Seismological Center (IRSC), broadband seismic network of the International Institute of Earthquake Engineering and Seismology (IIEES) and strong motion network of the Road and Housing and Urban Development Research Center (BHRC) are also introduced in the current study.

Given the high seismicity rate in Iran and rapid development and growing of the populated cities and buildings on seismic hazard prone areas, attention to seismic hazard and risk assessments has been become as a particular issue that should be addressed carefully. Therefore, seismic hazard analysis and estimation for the constructions of human structures has become an enforcement for which several seismic regulations and codes have been defined. In this regard, deterministic and probabilistic seismic hazard methods have been developed as the two most important techniques. The deterministic method is a conservative approach that is mostly used to determine the highest level of strong ground motion (acceleration) for a special site (such as dams and power plants). On the other hand, the probabilistic method provides probabilities of different strong ground motion levels considering different uncertainties and the useful life of a structure.

    In addition, considering the level of seismic hazard in a region and its population can lead to risk assessment, vulnerability and resiliency of the human societies. Thus, parallel to seismic hazard and risk analysis, it is so important to conduct crisis management, reduce efforts and a continuing assessment of the situation in the country. In the present study, problems and challenges facing the crisis management, as well as urban distressed areas are mentioned.

    Regarding the existence of constant threat of natural disasters, especially high risk of earthquakes, there is a serious need to conduct more scientific researches in various fields, including detailed research on various aspects of seismology in Iran, retrofitting of constructions, crisis management and disaster risk reduction. To achieve this purpose, we need a scientific network in Iran. There sould be several experts and organizations as the members of this network who are able to understand and control the earthquake effects on the society. Necessity of such a scientific network is due to that it is impossible to take efforts in order to reduce the earthquake risks without a holistic perspective and earthquake data completion.

In this regard, we need significant infrastructures in terms of human resources and technical cooperation to motivate a set of organizations, universities and research institutes. The responsible organizations such as geological survey of Iran, National Cartographic Center of Iran, meteorological organization, Institute of Geophysics of the University of Tehran, International Institute of Earthquake Engineering and Seismology, Road and Housing and Urban Development Research Center, National Disaster Management Organization, Red Crescent Society of the Islamic Republic of Iran, as well as universities and NGOs must work together to make it possible to review and integrate the existence potentials and to share the information and data of the earthquakes in Iran and define various response scenarios faceing natural disasters, especially earthquakes.

Human and social crisis and natural hazards are of great importance and urgency in urban development planning. As a result, in order to reduce the loss of life and financial damages, one of the necessities of urban planning and spatial analysis is identification of vulnerable areas. In Piranshahr city due to its sensitive geographical location and zoning the implementation of passive defense in urban planning is of utmost importance. The importance of this study is to examine vulnerabilities in order to operate an optimal crisis management. The main objectives of the study are:

- Identifying the most vulnerable neighborhoods of the city.

- Identification of vulnerable facilities and equipments.

The research method is descriptive - analytical and research space is Piranshahr city limits. In order to identify the characteristics and distribution of facilities and equipment in the border town Piranshahr library and field methods have been used. The results of the last census (1390) of Statistical Center of Iran, observation and interviews with local people and experts was used. The master plan and detailed studies of 1391 and relevant maps of the municipalities, the aggregation and dispersion of urban facilities and equipments were used. To value the passive defense importance in the city sixteen vulnerability variables were defined and measured according to opinions of people and experts. Then the data were analyised with the  Delphi software. The main variables include: Lifeline, crisis management centers, military bases, equipment and support centers. After determining the rating of each factor and sub-sectors, by using AHP and Expert Choice software vulnerability of each of the following criteria were calculated. For mapping the city Piranshahr fuzzy model is used.

The results showed that the variables of vital artery with coefficient of (0.469), crisis management centers and joint support centers with coefficient (0.201), municipal equipment by a factor of (0.086) and military centers coefficient (0.043) are among the most vulnerable facilities and equipments in Piranshahr city. The neighborhood of western, central and south-west of the city, including the Kohneh-Khaneh and Grow of a cultural1 neighborhoods, Ghods, Isargaran, Zrgtn and Mom-Khalil, were the most vulnerable neighborhoods in the city regarding the military attacks. Spatial analysis of vulnerability of the city resulted in three vulnerability regions. The neighborhoods of the West, Central and South West (Kohneh-Khaneh and Grove neighborhoods and part of a cultural1 neighborhoods, Ghods, Isargaran, Zrgtn and Mom-Khalil) are the most vulnerable neighborhoods of the city. The reason for this situation are the physical characteristics of the city such as texture, organic, fine texture and high density residential units, existence of urban infrastructure, core founding of the city (the Kohneh-Khaneh neighborhood) and the secondary core (Zrgtn neighborhood). whereas the neighborhood (Park City and part of Koy-e-Khayyam and new neighborhoods of Mohammadkhan in the north and the south and southeast of the city) due to the preparations made for the perfect skeletal indices as well as the extent of large open spaces are somewhat immune and safe regarding the passive defense.

Keywords: Spatial analysis, vulnerability, Passive defense, city of Piranshahr.

We can identify the flood not only considering circulation pattern in occurring day but also by studying circulation pattern a few days before fresh event. This subject has mutual approach. In one hand, it indicates  that circulation patterns which were before flood event have important role in determining the conditions and moisture content of studied area and playing the fundamental role in few coefficient of region because it determines the previous moisture. On the other hand, it indicates that we should tracking the rain-genesis synoptic systems from source to end place of their activity for studying floods and their meteorology factors which have created them. By this way, we can acquire more comprehensive recognition about the relationship between circulation pattern and floods. In the other words, the identification of synoptic patterns that have created the flood reveals not only the mechanism of their emergence but also is useful for prognosis and encountering with them. The extensive researches have been accomplished about Inundation in the world and Iran, but Iran haven’t much antiquity about synoptic researches. For foreign researches, we can name researchers such as Hireschboeck (1987), Kutiel et al(1996), Komusce and et al (1998), Krichak  and et al (2000), Rohli and et al (2001), Kahana (2002), Teruyuki Kato(2004), Ziv and et al (2005), Carlalima and et al (2009). The numerous researchers have studied the Inundation climatology in internal of country such as Bagheri (1373), Ghayour (1373), Kaviani and Hojatizadeh (1380), Moradi (1380), moradi (1383), Mofidy (1383), Masoodian (1384), Masoodian (1384), Hejazizadeh et al(1386), Parandeh Khozani and Lashkari (1389). In this research, we considered the heavy precipitation of Azar 1391 in southwestern of Iran that resulted in flood phenomenon in the cause and effect manner so that can do necessary prevention actions before occurring the flood for preventing the probable damages and optimal use of precipitations by forecasting the patterns that have created the flood.

In this synoptic study, we need to two database: one group is variables and atmospheric data consisting of geopotential height of 500 hpa level (in meter geopotential), zonal wind and meridional wind (in m/s) and special humidity (in gr/kg) during this times 00:00, 06:00, 12:00 and 18:00 Greenwich in 0-80° northern and 0-120° eastern with local resolution of 2.5*2.5 Arc that have been borrowed from database of (NCEP/NCAR) dependent to National Atmosphere and Oceanography Institute of USA, and other group is daily precipitation data of region rain gauge stations during 4-8^th Azar of 1391 (24^th November – 28^th November 2012). In continuation. By applying the environment- circulation approach, we took action to drawing circulation pattern maps of 500 hpa level, thickness of atmosphere patterns of 500-1000 hpa and moisture flux convergence function from 4-8^th Azar of 1391 (that for calendar, conform with 48 hours before beginning the showery precipitation until ending the storm activity) by using data which obtained from database of NCEP/NCAR and the synoptic conditions of above flood have been studied and interpreted in the region.

Flood is one of the most destructive natural hazards that have imposed and impose many damages to people during the history. Hence, the final aim of this research is to explain the key interactions between atmosphere and surface environment and in other words exploration of the relationship between circulation patterns leading to the flood generating precipitation in the southwestern of Iran for forecasting the time and intensity of showers occurrence that lead to flood. For this purpose, by applying environmental-circulation approach, the circulation patterns identified and studied which resulted in flood generating precipitation. The result of this research indicated that torrential precipitations in the region have formed the deep trough in days 4-8 of Azar on the east of Mediterranean and the studied region placed in the east half of this trough that is the location of atmosphere instability. At same time, thickness patterns, indicate the flux of cold air from northern Europe to lower latitudes and spreading the warm air of north of Africa to latitude 50° northern. As a result we expected the frontal discontinuity in the encountering place of these two air mass. Analysis of the moisture flux convergence patterns also indicated that torrential precipitations were the result of moisture flux from Mediterranean and Persian Gulf; and Red Sea and Arab Sea taken into account as reinforced sources.

Due to the growth of industries and factories, deforestation and other environmental degradation as well as greenhouse gases have been increasing on the Earth's surface in recent decades. This increase disturbs the climate of the Earth and is called climate change. An Increase in greenhouse gases in the future could exacerbate the climate change phenomenon and have several negative consequences on different systems, including water resources, agriculture, environment, health and industry. On the other hand to evaluate the destructive effects of climate change on different systems, it is necessary to initially study the area affected by climate change phenomena. One of the most important effects of climate change on water resource is Drought.  On the other hand, one of the most serious consequences of climate change is how it will affect droughts and water resources.

Drought along with warmer temperature and less precipitation will threaten the water supplies for the crop irrigation, which will directly reduce the production of crops.The climate of the 21st century will very likely be quite different from the climate we observed in the past. The changes will continue to be large in the future period with increasing carbon dioxide emissions. Analyzing and quantifying the signal of climate change will be much in demand considering the above sectors, which are highly relating to the sustainability and human living.

In the past several decades, global climate models have been used to estimate future projections of precipitation [Intergovernmental Panel on Climate Change (IPCC), 2007], and have led to future estimation of drought, to quantify the impact of climate change and comparing the duration  and intensity of droughts under future climate conditions with current climate by using Atmospheric-Ocean General Circulation Models AOGCMs to predict future Precipitation. Global circulation models namely, coupled Atmosphere-Ocean Global Climate Models (AOGCMs) are current state of the art in climate change research. in This study aims at investigating the impact of climate change on droughts conditions in Iran using the Standard Precipitation Index (SPI).

The precipitation time series have been used for the estimation of Standardized Precipitation Index

(SPI) for three timescales, 3, 12 and 24 months, for the region. The outputs of HadCM3-A2 and A1B were applied for the assessment of climate change impact on droughts. One of the major problems in using the output of AOGCMs , is their low degree of resolution compared to the study area so to make them appropriate for use, downscaling methods are required. In this study we have used lars WG for downscaling monthly average of rainfall of AOGCM-HadCM3, and The HadCM3 outputs were downscaled statistically to the study area for a future period 2011-2040.then, was evaluated by the coefficient of determination (R2) between observed and downscaled data.  A method has been used for the estimation of annual cumulative drought severity-time scale-frequency curves. According to the rainfall results, in the 2011- 2040 period rainfall would decrease  to compared to baseline period in the study area.

The SPI time series were estimated (2011-2040) and compared with the respective time series of the historical period 1961-1990. Results revealed that there are decreases in the frequency of severe and mild droughts for the three examined SPI time series while there are increases in the duration of moderate droughts. This implies that droughts will be a concern in the future during the growing season (for the dominant crop) which should be considered in water resources management. specially in the west station of Iran.

Also, these frequency ratios were mapped by GIS on study area. Results showed that generally in the future periods, frequency of droughts ratio of three months drought time- scale will be increase in the North, North West and some parts of the south Alborz mountains and, The Ratio of long ( 24 months) drought for scenario A2 compare to the current climate shows increasing drought in the parts of the North khorasn, sistan and baluchestan and kerman provinces and parts of South West of Iran. scenario A1B shows increasing drought in the parts of the East of Mazandaran , Tehran , Horozgan and parts of Fars and Yazd  provinces.

Finally ,further  more analysis of drought, AWCDS-Timescale-Return Periods computed. These curves integrate the drought severity and frequency for various types of drought. The AWCDS time series were estimated

for basic period and 2011-2040 under scenarios A2 and A1B. The comparison indicated the three types of drought intensity increases for the three examined SPI time series in the South East of Iran.

Drought is the most important natural disaster, due to its widespread and comprehensive short and long term consequences. Several meteorological drought indices have been offered to determine the features. These indices are generally calculated based on one or more climatic elements. Due to ease of calculation and use of available precipitation data, SPI index usually was calculated for any desired time scale and it’s known as one of the most appropriate indices for drought analysis, especially analysis of location. In connection time changes, most studies were largely based on an analysis of trends and changes in environment but today special attention is to the variability and spatial autocorrelation. In this study we tried to analyze drought zones in the North West of Iran, using the approach spatial analysis functions of spatial statistics and detecting spatial autocorrelation relationship, due to repeated droughts in North West of Iran and the involvement of this area in the natural disaster.

In this study, the study area is North West of Iran which includes the provinces of Ardebil, West Azerbaijan and East Azerbaijan. In this study, the 20-year average total monthly precipitation data (1995-2014) was used for 23 stations in the North West of Iran. In this study, to study SPI drought index, the annual precipitation data of considered stations were used. According to the statistical gaps in some studied meteorological stations, first considered statistics were completed. The correlation between the stations and linear regression model were used to reconstruct the statistical errors. Stations annual precipitation data for each month, were entered into Excel file for the under consideration separately and then these files were entered into Minitab software environment and the correlation between them was obtained to rebuild the statistical gaps. Using SPI values drought and wet period’s region were identified and zoning drought was done using ordinary kriging interpolation method with a variogram Gaussian model with the lowest RMS error. Using appropriate variogram, cells with dimensions of 5_×5km were extended to perform spatial analysis on the study area. With the establishment of spatial data in ARC GIS10.3 environment, Geostatistic Analyze redundant was used to Interpolation analysis Space and Global Moran's autocorrelation in GIS software and GeoDa was used to reveal the spatial relationships of variables.

The results showed that most studied stations are relatively well wet and this shows the accuracy of the results of the SPI index. Validation results of the various models revealed that Ordinary Kriging interpolation method with a variogram Gaussian model best explains the spatial distribution of drought in North West of Iran. So, using the above method the stations data interpolation related to SPI index in North West of Iran was done. The results showed that Moran index values for the analysis of results of standardized precipitation index (SPI) in all studied years, is more than 0.95. Since Moran’s obtained values are positive close to 1, it can be concluded that drought, in the North West of Iran during the statistical period has high spatial autocorrelation cluster pattern of 90, 95 and 99 percent. Results also showed that in all the years of study, Moran's global index is more than 0.95 percent. This type of distributed data suggests that spatial distribution patterns of drought in North West of Iran changes in multiple scales and distances from one distance to another and from scale to another and this result shows special space differences in different distances and scales in this region of the country. Results also showed that drought in North West of Iran in 2008 is composed of two parts: Moderate drought in parts of West and North West region (stations of Maku, Khoy, Salmas, Urmia, naghadeh, Mahabad and Piranshahr) and severe drought in the southeastern part of the study area (stations: Sarab, Khalkhal, Takab, Tabriz and Mianeh). So the pattern of cluster drought in the North West of Iran in 2008 is on the first and fourth quarter. The results of this index showed that drought and rain periods are similar in the studied stations. The results of the application of Moran's index about identifying spatial distribution of drought patterns showed that The values of the different years during the period,  have a positive a positive coefficient close to 1 (Moran's I> 0.959344) and this shows that the spatial distribution of drought is clustered. The results of the standard score Z values and the P-Value proved the clustering of spatial distribution of drought.

The results of the analysis of G public value, In order to ensure the existence of areas with clusters of high and low values showed that The stations of Maku, Khoy, Salmas, Urmia, naghadeh, Mahabad, Piranshahr and Parsabad follow the moderate drought pattern in the region and are significant at the 0.99 level. Jolfa station also has a mild drought of 0.95 percent confidence level and for Sardasht station is significant in 0.90 percent. High drought pattern in Sarab, Khalkhal, Takab, Tabriz and Mianeh stations was significant in 0.99 percent level and also for Ardabil, Sahand and Maragheh stations very high drought pattern was significant in 0.95 percent level and for Meshkinshahr and Ahar high drought pattern is significant in 0.90 percent. By detection of clusters of drought and rain in the North West of Iran using Moran’s spatial analysis technique and G general statistics a full recognition of the drought affected areas in this region can be obtained and take the necessary measures in its management 

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.

Drought is one of the most important hazards that occur in all the earth especially in arid and semi-arid climates. Every year, about half of the earth’s surface experienced droughts and while drought is not a constant feature of any climate but occur more frequently in arid and semi-arid regions of the world. Although the occurrence of droughts cannot be prevented but by studying the nature and characteristics of droughts and also identify factors that affecting their occurrence useful information can be gained about drought and their destructive effects. The researches in recent years designed and proposed a lot of indices to study and analyze the droughts and today various characteristics such as intensity, duration, area and so on with these indices are studied. Many indices used by researches to analysis and identify properties of climatic droughts and dry periods. In these indices often the variables of precipitations, combination of precipitations and temperature, humidity or evaporation, crops yields and teleconnection climatic indices are used.

In this study using the CPEI index and 30 years (1980-2009) daily rainfall data in 40 synoptic stations overall Iran, to analysis and assess of Iran droughts suitable variables detected. Four seasons and annual period is considered in this study. To determine the appropriate variables in the design of suitable models and modeling of drought to assess and predict droughts Otun in 2005 proposed CPEI index as Conjunctive Precipitation Effectiveness Index. He selected 10 conjunctive precipitation variables as ORS(Onset of Rainy Season), CRS(Cessation of Rainy Season), LRS(Length of Rainy Season), TWD(The Total no of Wet Days), TDS(Total no of Dry Spell), TDW(Total no of Dry Days within a Wet Season), TDY(Total no of Dry Days within a Year), LDS(Length of the Dry Season), MDL(Maximum Dry Spell Length within a Wet Season), MAR(Mean Annual / Seasonal Rainfall Depth) and determined the relationships between variables in each synoptic stations and climatic regions. Since the units of measurement the rainfall variables are diverse, it is essential that the units be converted to a standard unit, in other words variables be standardized. The relationship between variables was determined by Pearson correlation coefficient. Finally, the right combination of precipitation variables for each station through the proposed formula Otun(2005) were determined. In the end, for each of the seasons and the annually period regionalization maps were prepared.

 All 40 synoptic stations were evaluated by Otun’s method (Aton, 2005). The results showed that 95 percent of stations in spring, 75 percent in fall, 57 percent in winter and 75 percent in annual period are compatible with used method. Thus, spring, fall and winter seasons and also annual period are compatible with above mentioned index. Among the used variables MAR, MDL, TDY and TDS which with respectively are as follows: total amount of precipitation in any period, the maximum duration of dry periods in a wet period, the total number of dry days in a wet period and the total number of dry period during wet period among the stations are more abundant. In annually period, in addition to the above mentioned variables, precipitation variable of LPS (length of dry period) also seen among some stations. Also, results showed that CPEI index can be used on most stations and climatic regions of Iran. It was also found that the spring compared the other seasons and annual period is more comparable on the base of CPEI index.   

  Otun in 2010 used the CPEI index in semi-arid region of Nigeria and has achieved good results. The results of our study show good agreement with Otun’s work. The use of this index in the study of meteorology, climatology, agriculture and many environmental projects can be beneficial because in many of these fields of study, precipitation and its characteristics have an important role. In general we can say that in regions where CPEI index does not show a high proportion or set of variables are not enough it is better to use other indices such as SPI and RAI. The results obtained in similar climate zones such as Nigeria has shown that CPEI index has very good ability to identify and explain the precipitation effectiveness variables which can be used in modeling of droughts and dry periods. There are many similarities between combination of precipitation variables that identified by CPEI index for Iran and other regions of the world. Similarities, especially with respect to MAR, MDL, TDY and TDS are abundant.