Journal of the Earth and Space Physics
Year:2016 | Volume:42 | Issue:3 |Papers Count:19

Thermoluminescence (TL) dating was established in Oxford to fulfil the demand for dating ceramics and other heated man made products (Aitken, 1985). It determines the time elapsed since the mineral grains have been heated. Following the establishment of TL dating method, it was used to date fired materials such as pottery, flint and etc. Optically stimulated luminescence (OSL) determines the time elapsed since mineral grains have been last exposed to light just before burial (Aitken, 1989). Ancient walls are mainly built for defensive purposes. Some walls were destroyed and erected again and some had been extended. There is no accurate historical information about the time and purpose of the construction of the most of the ancient walls. Dating methods are key important tools in archaeological investigations. Absolute date for ancient building including walls, facilitate accurate time of construction and interpretation about the reasons that the monument was built. The proud history of association of TL and OSL dating with archaeology is well explained in literature (e.g., Roberts, R.G. 1997; Feather j. K. 2003); Monuments and settlements were also dated by TL and OSL including three Minoan palaces in Crete (Liritzis and Thomas, 1980); stoneware from the period of the early Thai kingdom of Sukhothai (Robertson and Prescott, 1987, 1988); the remains of the strategically-located Roman city of Carnuntum in Austria (Erlach and Vana, 1988); the Terracotta Army in Xi'an, China ( Lu et al., 1988); fifteen Mesolithic to medieval habitation sites in Denmark, Sweden and Finland (Mejdahl, 1989); the foundations of the archaic fortifications on Palatino Hill in Rome itself (Bacci et al., 1990); the Spanish exploration of western Canada in the 18th century AD (Williams et al., 1991); stone lines and cairns on the Arnhem Land plateau in northern Australia (Chaloupka, 1993); Mycenean wall in Greece (Liritzis, 1994); temples and citadels in Sri Lanka (Abeyratne, 1994); the temple of Apollo in Delphi (Liritzis et al., 1997); the archaeological sites of Tall Abu Fahd and Tall Qsubi in the Middle Euphrates Valley, in Syria (Sanchez et al., 2008); the city wall system of the oasis in NW Saudi Arabia (Klasen et al., 2011); the domed Stupas in Sri Lanka (Bailief et al., 2013). Following the explanation of basis of OSL dating, this article presents the application of OSL for dating Tammisheh wall in Iran, as a case study. The Tammisheh Wall in northern Iran was around 12 km long from the Elburz Mountains into the south- of the Caspian Sea and is lined by a fort in dry land in the south and another fort that is currently under water, in the north. A canal, conducted water along most of the wall. Tammisheh Wall was in a good state of repair in the mid-7th century, because its inhabitants resisted against the powerful army of Sa‘id b. al-‘Aṣ, son-inlaw of Caliph ‘Uthman and governor of Kūfa, when it approached the Tammisheh land corridor from the east in AD 650/651. (Sauer et al., 2014). The town of Tammisheh continued to be occupied until at least the 13th. (Bivar and Fehérvári 1966). While Ibn Isfandiyar had attributed, the Tammisheh to Peroz, Ibn Rusta (the early 10th-century author) suggested that the Tammisheh Wall was built by Khusro I (AD 531–579). The Proposed dates, founder or period for construction of the wall is shown in Table 1. Until 2005, there had been no absolute date for the Tammisheh Wall. 14C is one of the most accurate methods but requires organic material. However, the wall is made of bricks that perfectly suits OSL dating. There are quartz and feldspar in the bricks. Quartz and feldspar are 2 main luminescence dosimeters. As bricks are cooked in ovens, the luminescence clock of quartz and feldspar inside the bricks will reset, due to temperature more than 300°C. The sediments contain quartz and feldspar. When sediments are exposed to day light, their luminescence clock will reset. The luminescence clock will start again as soon as bricks cool down or the sediment that was exposed to light is buried. Therefore, we employed both OSL and carbon fourteen methods. We collected one OSL sample sediment below foundations of Tammisheh Wall (Fig 4) which unfortunately overestimated the real age. We also sampled one OSL sample and a charcoal from a preserved section of the kiln in Trench F (Fig 8). Another OSL sample and three radio carbon samples were collected from the trench “O” of Bansaran fort (Figs 14-17). All samples were transferred and dated in Oxford. The dating result of samples is presented in Table 1. The result of OSL and 14C ages proved conclusively that Tammisheh wall and Bansaran fort had been built during the Sasanian period.

SummaryIn this study, we have theoretically investigated designing possibility of a seismometer using Fiber Bragg Grating (FBG) and Metal Bellows pairs attached on a mechanical system. This new seismometer can record earthquakes according to sensitivity of fiber optic to changes in physical parameters such as stress and strain. …

Many steps of seismic data processing sequence suppose that data sets are sampled in time and spatial dimensions uniformly. Today, this assumption is true but only in time dimension. Modern seismic exploration equipment permits seismic data sets to be sampled uniformly and densely in time dimension. However, along spatial dimension uniform and dense sampling are not possible because of operating constraints, failure of equipment, topography conditions or commercial problems. It has been proved that the results of most of seismic data processing techniques are dependent on regularity, adequate sampling and density of input data sets. The fact that we need to interpolate seismic data sets causes several new-born approaches in this field. In most of the available seismic processing software, this task is done by ‘binning’ the data. This operation is one of the error sources of seismic sections. Moreover, there are some other different computational techniques to interpolate and reconstruct seismic data on a regular grid. Some of these approaches reconstruct seismic data at the given points using physical concepts of wave propagation and solving Kirchhoff's formula. In spite of practicability of these methods, need of initial accurate information about velocity model, geological property and high computational efforts restrict the domain of operation for these methods. Nowadays various mathematical methods are provided using the design of prediction filters, mathematical transformation and some other methods use rank reduction of data matrix to interpolate seismic data. According to their utilized assumptions, computational cost, noise, sampling type, and density of input data, each of these methods have their own constraints in performance and artifacts in final results which should be recognized. In science and engineering branches, a well-known algorithm that deals with signals is Matching Pursuit (MP). Originally, MP has been introduced to time-frequency transformation and finding the frequency content of signals. This transformation represents a signal as a linear composition of vectors that are available in a complete bank of time-frequency atoms (also called Dictionary). MP is an iterative algorithm that at each iteration finds a base vector in the dictionary that best matches to the signal, then subtracts the image of signal along this vector from the signal and updates the signal. This process will be continued until the remained signal is negligible. Originally, to have a good decomposition, this dictionary should contain a vast amount and kinds of wavelets like Gabor functions that each has its own dilation, modulation and translation.Heretofore MP is used to produce a single frequency seismic attribute in geophysics. For seismic data reconstruction and interpolation purposes, sine functions are applied as base vectors. The process of interpolation by MP that uses sine functions needs to solve a Lomb-Scargle periodogram at each iteration that may need to have many computations. Due the lots of works that have been done on this subject, today multi-dimension and multi-component seismic data set can be interpolated using sine functions at MP. Other functions that can be used as MP’s base vectors are Fourier coefficients. Here, after some brief explanation about MP’s algorithm and formulations we use Fourier coefficients as the base vectors of MP, interpolate and reconstruct some synthetic and real two and three dimensional seismic data. Despite of some random noises that are due to calculation and other estimations, the traces are reproduced acceptably. The results show that amplitude and frequency contents of events are well preserved. The noticeable point is that the traces that reproduced at original sampling points are nearly identical to original traces. This property and ability to interpolate data with completely non-uniform sampling grid separates Fourier MP from many of previous interpolation methods. Cautiously picking of several base function simultaneously is proposed to reduce needed iterations and speed up the algorithm. Windowing the input data and using an antialiasing mask are proposed to achieve the assumption of sparse frequency content and linearity of events and remove aliasing effects.

Velocity analysis is one of the most important step in seismic data processing. It affects not only many processing steps directly and indirectly, but also is known as a primary interpretation of the data. However, it can also be assumed as one of the most time consuming processing step. The conventional velocity analysis method measures the energy amplitude along hyperbolic trajectories within a velocity interval and creates a velocity model. In this procedure, the data from time-offset domain is mapped to time-velocity or time-slowness domain. For a number of Nr, Nh and Nv time, offset and velocity samples respectively Nr× Nh× Nv computations is necessary to obtain a velocity model. However, in the presence of large size data and model parameters, computing the velocity spectrum using conventional method would be a time consuming task. On the other hand, in order to improve the initial velocity model obtained in the processing steps, usually velocity analysis is conducted several times during the processing of the seismic data. Hence, there should be a better way to compute the velocity model in a much less time computation. In this paper, we introduce the Butterfly algorithm for fast computation of hyperbolic Radon transform (HRT), as a kind of time variant operator, with an application in seismic velocity analysis. In seismic data processing, Radon transforms map the overlapping data in seismic gathers to another domain which they can be separated.Among different types of Radon transforms, the HRT has the most similarity to the seismic events and hence, produce the most accurate approximation in the velocity spectrum. However, its time-variant kernel prohibits its fast computation especially for large size data. Unlike time-invariant operators which use the convolution theorem in the Fourier domain to compute the velocity domain for each frequency separately and therefore efficiently, Fourier transform of time-variant operators is a function of both frequency and time and using the convolution theorem is not applicable. The Butterfly algorithm can be used as a fast solver for the Fourier Integral Operators (FIO), so reformulating the HRT integral in the Fourier domain as FIO makes it possible to use this algorithm to overcome the problem of the time-variant kernel. The basis of this solution is the existence of low-rank approximations of the kernel when it is restricted to subdomains in data and model spaces. Subdividing the model and data domain properly to smaller subdomains admits low-rank approximations of the kernel. These low-rank approximations enable us to obtain functions of only one variable, time or frequency, which approximate the kernel. This decoupling of time and frequency variables allows fast computation of the HRT integral. In order to do the subdivision properly, a pair of quad trees, one for each data and model domains, is used to restrict the domains in a level-base structure in which the size of data domain subsets are increasing while the size of model domain subsets are decreasing in each level. The Butterfly algorithm is used to compute the kernel equivalent functions in each level of these quad trees for each subdomain. Finally, at the last level, the Radon panel or velocity model is obtained.The complexity of this method for two dimensional data is O (N2 log N) in which N depends on data and model variables range. As it was demonstrated in the synthetic and the real numerical examples, O (N2 log N) complexity results in reduction of computation time in several orders relative to the conventional method.

In this paper the 3D inversion of gravity data using two different regularization methods, namely Tikhonov regularization and truncated singular value decomposition (TSVD), is considered. The earth under the survey area is modeled using a large number of rectangular prisms, in which the size of the prisms are kept fixed during the inversion and the values of densities of the prisms are the model parameters to be determined. A depth weighting matrix is used to counteract the natural decay of the kernel, so the inversion obtains reliable information about the source distribution with respect to depth. To generate a sharp and focused model, the minimum support (MS) constraint is used, which minimizes the total area with non zero departure of the model parameters from a given a priori model. Then, the application of iteratively reweighted least square algorithm is required to deal with non-linearity introduced by MS constraint. At each iteration of the inversion, a priori variable weighting matrix is updated using model parameters obtained at the previous iteration. We use the singular value decomposition (SVD) for computing Tikhonov solution, which also helps us to compare the results with the solution obtained by TSVD. Thus, the algorithms presented here are suitable for small to moderate size problems, where it is feasible to compute the SVD. In Tikhonov regularization method, the optimal regularization parameter at each iteration is obtained by application of the x2 - principle parameter-choice method. The method is based on the statistical distribution of the minimum of the Tikhonov function. For weighting of the data fidelity by a known Gaussian noise distribution on the measured data and, when the regularization term is considered to be weighted by unknown inverse covariance information on the model parameters, the minimum of the Tikhonov functional becomes a random variable that follows a x2 distribution. Then, a Newton rootfinding algorithm can be used to find the regularization parameter. For truncated SVD regularization, the Picard plot is used to find a suitable value of truncation index. In math literature, a plot of singular values together with SVD and solution coefficients is often referred to as Picard plot. To test the algorithms, a density model which consists of a dipping dike embedded in a uniform half-space is used. The surface gravity anomaly produced by this model is contaminated with three different noise levels, and are used as input for introduced inversion algorithms. The results indicate that the algorithms are able to recover the geometry and density distribution of the original model. In general, the reconstructed model is more sparse using TSVD method as compare with Tikhonov solution. This especially happens for high noise level, where there is an important difference between two solutions. In this case, while TSVD produces a sparse model, the solution of Tikhonov regularization is not sparse. Furthermore, the number of iterations, which is required to terminate the algorithms, is more for TSVD as compare with Tikhonov method. This feature, along with automatic determination of regularization parameter, makes the implementation of the Tikhonov regularization method faster than TSVD. The inversion methods are used on real gravity data acquired over the Gotvand dam site in the south-west of Iran. Tertiary deposits of the Gachsaran formation are the dominant geological structure in this area, and it is mainly comprised of marl, gypsum, anhydrite and halite.There are several solution cavities in the area so that relative negative anomalies are distinguishable in the residual map. A window of residual map consists of 640 gridded data, which includes three negative anomalies, that is selected for modeling. The reconstructed models are shown and compare with results obtained by bore holes.

In common classical methods of cavity depth estimation through microgravity data, usually when a pre-geometrical model is considered for the cavity shape, the simple geometrical models of sphere, vertical cylinder and horizontal cylinder are commonly used. It is obviously an important fact that in real conditions the shapes of the cavities are not exactly sphere, horizontal cylinder or vertical cylinder but are near or to some extent near to these simple models. The linguistic variables “near to” or “to some extent near to” are consisting of fuzzy concepts and can be described as “fuzzy” variables. The membership degree of each fuzzy variable shows how much the variable is near to the mentioned simple shapes. Using the fuzzy variables leads to better results with more accuracy because in real conditions the nature of the cavities shape is “fuzzy” so that their shape is not exactly but near to the mentioned simple shapes. Consequently, in this paper in order to help the gravity data interpreter to enhance the accuracy of his/her interpretation a neuro-fuzzy model namely Multi Adaptive Neuro-Fuzzy Interference System (MANFIS) is used. When the neural network alone is used the challenge is its black-box operation so that there is no possibility for sensitive analysis but neuro-fuzzy networks consist of the sensitive analysis via the if-then fuzzy rules achieved during the training process. In Multi Adaptive Neuro-Fuzzy Interference System, the network output before the de-fuzzification stage, shows the interpreter how much the cavity shape is near to sphere, horizontal cylinder or vertical cylinder. In this research, two Adaptive Neuro-Fuzzy Interference System (ANFIS) models were paralleled to configure a Multi Adaptive Neuro-Fuzzy Interference System (MANFIS) so that one output of the designed MANFIS is the shape factor and the other is the depth of the cavity. The inputs of the MANFIS are some of the important features selected from the gravity signal along the selected principle profiles of the residual gravity map. In order to evaluate the designed MANFIS in the presence of noise in gravity data, the method was tested for synthetic data with 5% and 10% level of noise. The results showed that the joint neural networks and fuzzy logic makes it a suitable tool to help the interpreter to improve the accuracy of shape and depth estimation of cavities. Furthermore, the method is more robust to noise which were tested for two different noise levels one with low level of noise and other with medium level of noise added to the synthetic gravity data. Despite the available classical methods or net neural methods, here without any pre-assumption about the shape of the cavity, both the shape factor and depth are estimated. In is necessary to mention that the value of the estimated shape factor implies that which of the geometrical models among sphere, vertical cylinder or horizontal cylinder are better fitted to the real shape of the subsurface cavity. After checking and confirming the accuracy of the designed MANFIS for synthetic data, the method was tested for real data through micro-gravity data over a gravity site located in Great Bahama Free Port, west of North America. The results are very near to the available borehole and extracted data.

Using global free air gravity and topography data, first we have calculated a Bouguer Anomaly (BA) map for Iranian plateau and then computed the residual isostasy anomaly map under the Airy-Heiskannen assumption. The term residual is used as to reflect the assumption of local isostatic compensation in contrast to a regional isostatic compensation. The value with which the gravity effect of the compensation mass (the root/anti-root in the Airy model) is calculated are chosen under careful considerations as to produce reliable results. The resulting residual isostasy map is then used to qualitatively interpret the isostatic highs and lows corresponding to crustal/lithospheric features of the Iranian plateau. The study area is a complex region as a result of its still active tectonics which is mostly driven by the continent-continent collision of the Arabian and Eurasian plates. The five most important tectonic settings in Iran are Zagros Mountains, an active belt formed as the result of the collision extending from south-west Iran along the Persian Gulf; Alborz Mountains, a young belt with an average topography of 3-5 km extending nearly in east-west direction, Makran, in south-east Iran, north of the Iran-Arabian plate boundary where an active subduction is taking place; Caspian Sea, with an oceanic crust covered with an average 15-20 km sediment layer at the Iran-Eurasia plate boundaries and Kopeh-Dagh mountains, an uplifted region as a consequence of converging continental plates. Our results indicate that the Zagros Mountains have reached an isostatic equilibrium but the scenario is slightly different for the Alborz chain. It seems that the isostatic equilibrium is not fully reached in the Alborz due to the observation of a continuous isostatic high (positive) anomaly which extends to north-west Iran, however, it may also be partly caused by a simple folding. In the southern Caspian region, there is an enormous isostatic low (negative), for the cause of which we have considered two possible reasons. First, the effect of the sediment layer on the gravity signal due to its negative density contrast. Second, we considered the deficiency in the rock mass at the base of the lithosphere due to an anti-plume or the downward flow of the lithospheric materials towards the mantle which may also explain the high depth of the southern Caspian Basin. Subduction zones are usually characterized with negative isostatic anomalies, but in the case of the subduction of the oceanic lithosphere of the Caspian under the continental crust of the Eurasia, there is no apparent negative isostatic anomaly in our map. We believe that this is probably due to the fact that the subduction is still young while in order to observe a negative effect on the residual isostasy anomaly map, the subducting slab must be in a deep position, in other words, be of older age. The subduction of the Makran, on the other hand, has caused a negative isostatic residual anomaly. This low anomaly is also partly due to the uplift of the Makran area. A high-low (positive-negative) residual isostasy anomaly pairs corresponds to suture zones. An example of which is seen for the Zagros-Bitlis suture zone which marks the continental collision of the Arabian-Eurasian plates. Our map also shows a negative residual isostatic anomaly in the Kopeh-Dagh Mountains, which we interpret as the uplift caused by the convergence of the Iranian and Eurasian plates. It must be noted that every high/low residual isostatic anomaly may not be interpreted as isostatically over/under compensated areas. on the contrary, it could be and usually is related to a geological feature of lithosphere/mantle scale.

Geomagnetic observatories are constructed to continuously record the earth’s geomagnetic field. The importance of such buildings has resulted in an increasing construction of geomagnetic observatories all over the world. Although geomagnetic observatories are sometimes unknown to most people and even some scientists, these very important data centers have been measuring the geomagnetic field for about 500 years. The number of standard observatories is now approaching 150, but there are still very few standard geomagnetic observatories in the Middle East. Despite the large area of Iran, Tehran geomagnetic observatory is the only observatory in the country. It was constructed by the Institute of Geophysics in 1961. Unfortunately, in the recent decade, due to the old instruments used in this observatory and considering the expansion of Tehran city, the data obtained at this geomagnetic observatory are subjected to many noise sources. Therefore, its data are not reliable anymore and Tehran observatory is removed from the list of world’s standard geomagnetic observatories. In this paper, which is aimed as an informative research note, the necessity of constructing new geomagnetic observatories in Iran is discussed from various aspects. The most important advantages of constructing a geomagnetic observatory include: providing a data center for the correction of magnetic exploration data, prediction of magnetic storms and providing a constant monitoring of the geomagnetic field variations as one of the probable earthquake precursors. Considering the various advantages of continuous recording of the earth’s geomagnetic field, it is completely necessary to construct new geomagnetic observatories in Iran. The first step to construct a standard geomagnetic observatory that can record highly reliable data, is to select an optimum area for the construction of the observatory. From the very early observations of the geomagnetic field, it was understood that the observatories must be far enough from natural fluctuations resulted from volcanic rocks or mineral deposits. It was also discovered that artificial noises can disturb the data recorded in a geomagnetic observatory. However, there is still no comprehensive report discussing the various criteria to be studied while selecting a site for the construction of these observatories. This paper presents different parameters that should be carefully investigated to select optimum sites for the construction of geomagnetic observatories. Considering the type of data that should be recorded in geomagnetic observatories, knowledge of the criteria affecting the geomagnetic data is critical. Various criteria such as the magnetic intensity, variations of the electrical conductivity of subsurface soils, artificial sources of geomagnetic changes, development of cities, geology, topography, access roads, and underground possible economical deposits can affect selection of the optimum sites for the construction of geomagnetic observatories. Keeping a proper distance away from magnetic anomalies and controlling the homogeneity of the electrical conductivity of subsurface soils fall among the most important factors to be considered at the first stage. Then, artificial sources of the geomagnetic disturbance and urban development patterns must be carefully considered. It should be noted that finding the areas that can fully satisfy all the criteria might be impossible, but the minimum requirements should be satisfied to construct an observatory. Closure or relocation of several geomagnetic observatories all over the world is an experience showing how carefully the site selection of these structures should be carried out. Having understood the necessity of constructing new geomagnetic observatories in Iran, Kerman Province is considered as one of the favorable areas for the construction of an observatory. A comprehensive research is being carried out by authors to carefully acquire and interpret all the required data to find the best sites for this purpose.

Among all the geophysical techniques, the magnetotelluric method has improved considerably in recent years and is widely being used in hydrocarbon exploration especially in regions where reflection seismic has difficulties. Areas which are covered with high velocity rocks in the near surface are most popular cases. A huge high resolution magnetotelluric investigation was conducted in the Sehqanat oil field, SW of Iran, in 2013 to map geoelectrical structure of the region from surface down to several kilometers. The Sehqanat oil field is located in sedimentary Zagros zone which is encompasses more than 95 percent of Iran’s oil fields. The main geological interface which is targeted to be imaged with magnetotelluric method, due to the large resistivity contrast (based on the well logs information), is the contact between the highly conductive evaporites of Gachsaran formation and the more resistive underlying carbonates of Asmari formation. Regarding the large thickness of the high-velocity (ca.4500 m/s) and heterogeneous Gachsaran Formation outcropping in the Sehqanat oil field and several adjoining oil fields in the study area, imaging of the underlying layers is difficult with the reflection seismic technique. On the other hand, the big contrast of the electrical resistivity between the Gachsaran Formation and the underlying layers is favourable for MT exploration. The geoelectrical contrast is well documented from the full-set log measured along the explorative Sehqanat well. The high velocity and very heterogeneous Gachsaran formation is exposed on the surface and has a varying thickness from 500 meter to more than two kilometers in the region and also covers the Asmari formation which is the main reservoir in SW oil fields of Iran, as a cap rock. Geologically, the Sehqanat oil field has been formed by a gentle and moderate-size anticline called “Sehqanat” which its structural shape, due to the low quality of reflection seismic data, is not clearly known for geologists. The Sehqanat anticline acts as a structural oil trap from aspect of the petroleum geology. In order to collect more geophysical information about the subsurface morphology of the Gachsaran-Asmari formations boundary as well as Sehqanat anticline, broadband magnetotelluric data were acquired at more than 600 stations along five parallel southwest-northeast profiles crossing the main geological trend of the study area. Transient electromagnetic data were also acquired over 400 stations along the mentioned profiles to be used for static correction of magnetotelluric data. Dimensionality and strike analysis of the MT data show 3-D effects in a considerable amount of sites and periods. Therefore in order to get a comprehensive view through the subsurface resistivity distribution of the Sehqanat oil field, two- and three-dimensional inversions were performed on the magnetotelluric data. The 2-D and more precisely 3-D resistivity models, resolved the Gachsaran-Asmari formations boundary as a transition zone from high conductivity to more resistivity range. The Sehqanat anticline has also been delineated throughout the 2-D and 3-D resistivity models as a resistive dome-shaped body corresponded to the middle parts of MT acquisition profiles. Correlation of the magnetotelluric resistivity models with the adjacent 2-D reflection seismic sections is remarkable, letting us to accomplish more reliable interpretation of subsurface geology of the survey area.

Geophysical techniques remain the only ways to remotely and non-destructively sense the earth’s near subsurface and as such have the most promising prospect for rapid and accurate detection of underground tunnels. Today, electrical resistivity and seismic refraction geophysical methods have been greatly developed to identify structures and underground cavities. In this study, the ability of these methods to detect tunnels has been investigated using a case study. Seismic methods are sensitive to velocity and density changes of the rock, while the electrical response is dependent upon the electrical resistivity of the rock. In this paper, we present a case study using electrical resistivity tomography (ERT) data and refraction seismic tomography (SRT) data of a tunnel site. Also, to evaluate the capabilities of resistivity method as the main method to detect buried structures in this paper, geo-electrical abnormalities of a rectangular block through various simulations are examined. Electrical resistivity methods utilize direct currents or low frequency alternating currents to investigate the electrical properties of the subsurface. In the resistivity method, the source is artificially-generated electric current introduced into the ground using electrodes. The potential differences are measured at the surface and the pattern of potential differences provides information on the distribution of subsurface electrical resistivity. In near-surface refraction tomography, the travel times of seismic energy recorded at the surface by multiple source-receiver combinations are used to generate an optimized model of the distribution of seismic velocities in the subsurface. In ERT, the forward problem uses the finite-element method to compute the electric potential response of the earth due to a given input electric current. The inverse algorithm iteratively finds the best distribution of subsurface resistivity that best fits the observed data. The purpose of this research is to determine the location of underground tunnel using inverse modeling of ERT and SRT data, and evaluate the capabilities of resistivity method to determine the location of underground tunnels using geo-electrical abnormalities of a rectangular block through various simulations. Geophysical field surveys were performed at a site with a known tunnel. The tunnel is a 1 mx1.6 m concrete lined tunnel about 80m long. The data presented here was collected where the tunnel is at a depth of about 6m. Based on prior knowledge of the tunnel location the surveys are approximately perpendicular to the tunnel and were purposely centered on the approximate location of the tunnel in order maximize the geophysical sampling in the vicinity of the tunnel. The seismic refraction survey was performed using 96 geophones. A geophone spacing of 0.5m was used for a total spread length of 47.5m. The electrode layout consisted of 50 electrodes in a 1m dipole-dipole configuration for a total 49m spread length. In this study, we chose to use the dipole-dipole configuration due to its good lateral resolution. In this research, to determine the exact location of the tunnel, data obtained from ERT and SRT survey were inverted using Res2Dinv software and Rayfract software, respectively. The results of both methods show abnormalities in the tunnel under test site. The tunnel shows up in the electrical imaging as regions of high resistivity since both the concrete and air of the tunnel are higher resistivity than the conductive weathered rock. In practice, the resistive abnormally of the tunnel gets smoothed out and is larger than the actual tunnel. Therefore, in the ERT, the tunnel coincides with one of the high resistivity anomalies, but a second, shallower resistive abnormally of unknown provenance appears just to the east. Based on the results of the seismic survey, the velocity tomographic image is inadequate for tunnel detection as the smoothing inherent to the tomographic calculations results in only slight changes in velocity near the tunnel location. Instead, the ray coverage density mapping associated with ray tracing displays small regions of low coverage associated with the tunnel. In this instance the use of both methods would suggest that this second ERT abnormality is not a tunnel and illustrates how the use of both seismic refraction and ERT can be used to increase the reliability of detecting tunnels. Finally, with the simulation of resistivity data obtained from a rectangular block, the effects of various parameters such as depth of the tunnel, overburden conductivity, thickness of overburden on identifying underground tunnel, wasere investigated; this is done to clarify the status and ability of this method in detecting underground cavities. To approximate simulated data to the fact, five percent extra noise was added to the data. To this end geological models, which can be a target in the ground like an underground tunnel, were produced in Res2Dmod software. These synthetic models were provided with reverse modeling using Res2Dinv software. The results of simulation and modeling show that the electrical resistivity method is most widely geophysical method used for detecting underground tunnels.

The main limitation of radar interferometry in measuring ground displacements is due to phase propagation delays caused by the troposphere. Tropospheric water vapor is a major limitation for high precision Interferometric Synthetic Aperture Radar (InSAR) applications. Using global meteorological reanalysis models and MERIS data are two methods that can be used for correcting the effects of the troposphere. The purpose of this study is comparison of these two methods. The MERIS instrument is located on the platform of ENVISAT satellite and measures reflected solar radiation. We adopt the use of data of this sensor for our study as MERIS provides a direct estimate of atmospheric water simultaneously with Synthetic Aperture Radar (SAR) acquisition. ERA-Interim is a global atmospheric model computed by the ECMWF based on a 4D-Var assimilation of global surface and satellite meteorological data.This reanalysis provides values of several meteorological parameters on a global 70 km grid from 1989 to the present day, at 0 am, 6 am, 12 pm and 6 pmUniversal Time Coordinated) UTC (daily. The vertical stratification is described on 37 pressure levels, densely spaced at low elevation (interval of 25 hPa), with the highest level around 50 km (1 hPa). For each acquisition date, we select the ERA-Interim and MERIS outputs that are of the closest time spans to the SAR acquisition time. A Kriging interpolation in the horizontal dimensions and a spline interpolation along altitude is then applied to produce a map of the predicted delay. Total delay maps at epoch of acquisitions are then combined by pairs to produce differential delay maps corresponding to each interferogram. The use of the precise formulation of the single path delay and of the profiles of temperature, water vapor and dry air partial pressure is of importance to compute an accurate delay function. We used the two ENVISAT radar acquisitions of a region in the north west of Iran. We calculated the displacement velocity field and we corrected it (by ERA-Interim and MERIS data) and then compared the results with reported displacement velocities of GPS stations. The RMSE of two methods were 1.84 mm and 2.37 mm. The maximum difference between two methods is about 7.7 mm. This difference could be due to the presence of cloudy pixels in the MERIS data. The minimum difference between two methods is about 0.3 mm. The reason for this difference is negligible horizontal changes in the tropospheric indicators. The results show that cloudy weather and changes in the troposphere indicators, are the most important factors in the accuracy of the results of the two methods.

Mineral dust is produced from both natural and anthropogenic sources. Dust aerosols can be transported over long distances in the atmosphere. They reduce the incident shortwave radiation to the surface by absorbing and scattering the solar radiation; thereby leading to a cooling effect at the surface and lower tropospheric temperature. On the other hand, by absorption and re-emission of longwave radiation, they increase the net surface longwave radiation at the surface. This direct interaction of dust aerosols with shortwave and longwave radiation, known as the direct radiative impact, plays a key role in the radiation budget of the atmosphere. Although mineral dust is one of the most significant aerosols in the atmosphere, according to the Intergovernmental Panel on Climate Change (IPCC, 2007), uncertainty in its spatial distribution and radiative forcing, remains as a great challenge in climate studies. In the present study, the Weather Research and Forecasting with Chemistry (WRF-Chem) regional model is used to simulate distribution of mineral dust and its impacts on radiation fluxes on the global scale. The model was executed using 335 × 168 horizontal grid points with a horizontal spacing of 120 km, and 28 vertical levels for January and July 2011. The National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) re-analysis data were used as meteorological initial conditions. The GOCART (Goddard Global Ozone Chemistry Aerosol Radiation and Transport) simple aerosol scheme was used for the simulation of dust emission and airborne dust distribution. Two experiments were conducted: the control simulation with no dust; and the interactive simulation for which dust aerosols feedback to the atmosphere. Differences between these two simulations indicate the perturbation of radiation by dust. Results indicate that the concentration of dust particles is generally much higher in the Northern Hemisphere than the Southern Hemisphere. The main sources of dust are located over the Sahara and Sahel, the Middle East, and East Asia, especially the Gobi Desert of China and Mongolia. The Eyre Basin in central Australia was identified as the most important source of dust in the Southern Hemisphere. Over the Sahara, dust emission was most intense in January, but substantially decreased in July. In contrast, in response to drier soils and higher wind speeds, sources of dust in the Middle East were more active in July than January. The Gobi Desert was also found to have much more dust activity in January than July, primarily due to stronger wind speeds during this month. On the global scale, monthly-averaged dust optical depth (DOD) was estimated to be 0.046 and 0.069 in January and July, respectively. Globally, perturbation of shortwave and longwave radiation by dust at the top of the atmosphere (TOA) was estimated to be -1.84 and 1.34 W m-2 in January, and -2.38 and 0.68 W m-2 in July, respectively. At the surface, it was estimated that perturbation of shortwave and longwave radiation to be -2.07 and 0.82 W m-2 in January, and -4.14 and 1.02 W m-2 in July, respectively. It was also found that perturbation of radiation is larger closer to the sources of dust. For instance, the perturbation of shortwave radiation exceeds -20 W m-2 over the Sahara. Globally, we identified that dust has a negative effect on the shortwave, but a positive effect on the longwave radiation at the surface. However, in snow covered regions (such as over the Tibetan Plateau, northern parts of the Scandinavia and the United States in January) deposition of dust on the surface increases the net shortwave radiation reaching the surface (due to reduction of surface albedo) and decreases net longwave radiation by increasing outgoing longwave radiation from the surface.

Drought indices are commonly used to quantify and assess drought characteristics. The Standardized Precipitation Index (SPI), and recently introduced Standardized Precipitation-Evapotranspiration Index (SPEI) are considered as universal meteorological drought indices which allow comparisons of drought conditions across different climate regions. The SPI captures anomalies in precipitation, whereas the SPEI estimates anomalies in climatic water balance that incorporates temperature. The main aim of this study is to compare historical drought occurrence based on SPI and SPEI indices using R programming. The SPEI index is used because of multi-scalar nature of index and the advantage of identifying the multi-temporal nature of droughts. According to data availability, seven synoptic stations were selected for a drought analysis across Kurdistan Province. The two-parameter gamma distribution was used for calculating SPI across the study period (1995-2013) and stations within the study area. The potential evapotranspiration (PET) was computed using the Thornthwaite's equation, and then the SPEI is calculated at a monthly temporal resolution using SPEI package in R software. The SPI and SPEI values are calculated and then the statistical analysis along with significant level scatter plot was performed. The graphical plot of 3-month SPI and SPEI values were prepared to visualize the capabilities of used indices in determination of wet and dry spells over studied stations. The relationships between computed SPI and SPEI values were analyzed using correlation coefficient and p-value at each station. The results indicated that some differences in the pattern and sequence of wet and dry spells exist based on calculated indices. Also, the SPEI index identified the longer wet and dry spell conditions than SPI in almost all cases. The results of the comparative analysis indicated that the SPI and SPEI were varied between 0.19 (p<0.01), and 0.52 (P<0.01), which were statistically significant in all stations. A very low correlation between the SPI and SPEI was identified in Saghez station (correlation coefficient=0.19), which seems to be due to evapotranspiration and moisture loss during spring/summer with the increasing temperatures that is accounted for by SPEI. The highest correlation coefficient was calculated between SPI and SPEI in the Sanadaj station (0.52%). Since, the SPEI accounts temperature in defining drought spells, therefore, it is advisable to use SPEI instead of SPI for drought assessment. According to the graphical interpretation of the results, there was large difference between the droughts depicted by the precipitation-based SPI and the temperature influenced SPEI. Also the SPEI captured the influence of temperature and depicted severe and longer duration droughts which provide support for better performance and reliability of the SPEI index. It should be noted that in terms of lack of data, evapotranspiration can be calculated by simple methods such as Thornthwaite, but considering detailed available data, the Hargreaves and Penman methods can be used to determine drought occurrences in the SPEI calculation. The calculation of drought indices should be simple and statistically reliable, in this regard, SPEI indicators in different climatic conditions and climate change issues has a significant advantage. Also, more climate variables are needed to calculate the SPEI index than the SPI index. Also, the calculated evapotranspiration value is sensitive to the used method and requires a longer data period with natural variabilities. Further research is recommended in other climatic regions which is needed for comparison of SPEI with other common drought indices to draw comprehensive conclusions.

A major part of tidal energy is usually dissipated by the interaction of tidal currents with bottom topography. Gulf of Oman is a marginal sea which has variable topography and its dominant tidal constituent is M2 semi-diurnal tide. In this paper, the interaction of barotropic tidal current with bottom topography is evaluated. This phenomenon causes the formation of internal tide. Internal tide is a large scale and baroclinic phenomena which causes long wave oscillations of water column. Whereas the M2 semi-diurnal constituent is dominant, therefore this constituent is the main force for formation of internal tide in the Gulf of Oman. In this paper, numerical modeling of internal tide due to M2 semi-diurnal constituent is presented. This modeling is done using iTides model. This model is a software package which produces the internal wave field from the barotropic tide. The iTides package provides a graphical user interface (GUI) that combines all the theoretical elements necessary for producing a desired internal tide field given a set of system parameters. The model setup begins by specifying the pathway of the file to the topography, where the topography shape is specified by the horizontal coordinate assigned x, topography height h and the topographic change dh (both h and dh are functions of x). We use this dataset to define the maximum depth of the problem Ho as the maximum depth reached by the topography. Then, the density stratification must be given. The final step requires the user to specify the tide (forcing) frequency and the Coriolis frequency of the problem. After all parameters have been declared, the topography shape and stratification profile can be reviewed. This work has been done by implementation of iTides numerical model, which is a borotropic model, and forcing of an oscillating tidal current with semi-diurnal period. The model results show the formation of internal tide with a wavelength of order of O (10km) which reduces to O (1km) when reaches the shallow water. According to studied profiles of stability frequency, density stratification is quite stable in the Gulf of Oman and this Gulf is capable for formation of internal tide. Internal tide wavelength is of order of tens kilometers which reduces to a few kilometers when reaching the shallow zones. In the results, also the energy dissipation over the topography is visible. Most of internal tide energy is related to first modes. This phenomenon is mostly extended to deep zones, but for shallow zones internal tide energy is considerable between 1 to 3th internal tide modes. This fact may be due to iterated reflection of internal tidal beams from continental shelf and coastal shallow waters. The maximum energy Flux of primary modes in deep water (with depth of about 3000 meters) reaches to 20 kiloWatt per meter, whereas by decreasing the water depth, this amount of energy Flux reduces. The amount of internal tidal energy Flux in the Strait of Hormuz shallow water reaches bellow five kiloWatt per meter.

The lack of reliable and updated precipitation datasets is the most important limitation in the study of many climatological and hydrological subjects, including climate change and temporal variability of precipitation in many data sparse areas around the globe. This is particularly valid for Iran where vast areas of central-eastern country that host the Iranian deserts, suffer from an inadequate network of rain-gage stations, required for climatological studies. The highlands of the mountainous regions of western and northern Iran have the same problem and limited representative stations are available for high elevation areas of these regions. One of solution to overcome this obstacle is to use available gridded precipitation datasets that have proved their representativeness for many different parts of the world. Among many available precipitation datasets are the Global Precipitation Climatology Center (GPCC) and the Tropical Rainfall Measuring Mission (TRMM) that have been widely used in many researches, indicating their accurate estimation of precipitation values and intera-annual variation for the regions studied. The GPCC is a gage based dataset that is routinely creating through interpolation of worldwide precipitation stations combined with satellite records, whereas the TRMM is a purely remote sensed data developed by joint collaboration between NASA and the Japan Aerospace Exploration Agency (JAXA). The representativeness and performance of the GPCC and TRMM-3B43V7 precipitation datasets in estimating precipitation amounts at the locations of 46 Iranian synoptic stations distributed across the country is herein examined. Spatial resolutions of TRMM-3B43V7 and GPCC datasets used in this study are respectively 0.25 × 0.25 and 0.5 × 0.5 latitude and longitude. For each station, the closest grid point of each of the datasets to the station coordinates were chosen for statistically comparison analysis. To evaluate the performance of these datasets in comparison with the observed precipitation records at the considered locations we have used R squared, the Nash–Sutcliffe model efficiency coefficient, RMSE, Bias, B slope of the regression and the standardized RMSE indicators. The performances of the datasets were also graphically represented through scatter plots of the established regression between the observation and each of the two used datasets. The results of the statistical indicators were represented through plotting the indicators over the map of Iran to ease revealing spatial tendency of the indicators and explaining the possible geographical role in controlling the spatial variation of the indicators. The results revealed that both GPCC and TRMM-3B43V7 perform well in majority of the studied stations with strong correlation coefficients. However, it was found that the TRMM-3B43V7 underestimates precipitation in some stations located in the coastal areas of the Caspian Sea as well as in some stations along the Persian Gulf and the Oman seas, indicating that TRMM-3B43V7 is somewhat inefficient in adequately estimating precipitation in the coastal areas; which is very likely due to being unable to remove the effect of sea atmosphere interaction in stations nearby the seas. Contrarily, in some locations mostly situated in northwestern and northeastern mountainous areas of the country the TRMM-3B43V7 moderately over estimates the observed precipitation. Similarly, the GPCC well estimates precipitation in almost all stations with very high correlation coefficient and Nash–Sutcliffe model efficiency coefficient. Similar to TRMM-3B43V7, again it was found that the GPCC underestimates precipitation in most stations located along the coastal areas of the Caspian Sea. As for TRMM-3B43V7, the over-estimations of GPCC are mostly observed in northwestern Iran which is very likely due to not incorporating enough stations from high elevation areas of western Iran by the GPCC. On the whole, the results indicate that both datasets perform well in most locations of Iran and can be confidentially used in climatological and hydrological studies with or without the observation data. The results also indicate that the GPCC perform better in areas that share a denser network of stations with GPCC and vice versa. However, the very good results achieved with TRMM-3B43V7 that are completely independent from the observation indicates a promising future in having much improved remotely sensed precipitation records that well match the observed precipitation in very remote areas having no rain gages.

In this study, the daily Total Ozone Column (TOC) measured by the instruments of TOMS (2001) and OMI (2005-2011) satellites and Brewer ground station (2002-2004) is used to investigate the extreme ozone mini-holes over Esfahan. Based on previous reports on validation of the TOC data products, it is found that there is no problem with homogenization of data records, which was provided by the above measuring instruments. Firstly, it is shown that the TOC monthly mean and standard deviation over central Iran depend on the seasonal cycle with maximum values of 298 and 27 DU in winter and minimum values of 270 and 8 DU in summer, respectively. The difference between the maximum and minimum climatological monthly means is 53 DU. Regarding the absolute values of TOC, the maximum (minimum) amplitude is related to the winter season with 169 DU in Feb (summer with 39 DU in Aug). Due to the minus twice standard deviation of the monthly average which is known as the threshold chosen to identify the possible ozone mini-holes, 25 events are detected during the study period with maximum concentrations, of which 16 and 7 cases occurred in autumn and winter seasons, respectively. The most occurrences of ozone mini-hole are seen in 2005 and 2011 with 7 and 6 events, respectively. It is worthwhile to mention that the lowest levels of ozone in Arctic were also seen during the two mentioned years from 2001 to 2011. Nevertheless, no mini-holes were detected for three years 2003, 2004 and 2009. The range of ozone negative anomalies is confined from around 24% in winter (Jan) to 6% in summer (Aug). However, it was reported that ozone mini-holes in some regions have reduced the TOC up to 40% of climatology mean of mid and high latitudes over the northern hemisphere. It is found that during ozone mini-hole events, the Tropopause Height (TH) tends to move upwards (with a maximum of 5.5 km higher than monthly average on 10 March 2008) which in turn leads to decrease in the temperature and pressure of TH. Similar to its seasonal cycle, the low observed values of the tropopause temperature and pressure in summer is stronger than winter season. In general, the ranges of temperature (pressure) in the thermal tropopause during low ozone events becomes from -2.3°C (-27 hPa) in February 2006 to -15.5°C (-115 hPa) in March 2008. However, the mentioned above pattern almost explains the maximum events, the observed ozone mini-holes in January 2002 don not show similar anomalies in TH. It is more probably that low ozone events during the January of 2002 are more related to the meridional transport of air masses with climatology low ozone from the subtropical latitude which is poleward near the tropopause. Backward trajectory analysis also showed that the origins of poor ozone air masses in the spring/summer (autumn/winter) seasons are related to the eastern areas (western areas) of Iran. On 7 Jan 2002 at 16 km altitude (on 16 Oct 2011 at 22km altitude), the lower part of trajectory analysis, is more characterized by horizontal movement of poor ozone air mass from lower latitude (higher latitude). During the two extreme low ozone events over Esfahan which approximately correspond to the deepest events and eventful periods, two broad ridges are seen over coastal line of North-West Europe along with two deep troughs in the eastern-central Mediterranean Sea. The blocking ozone mini-holes over North-West Europe are related to the upward movement of geopotential height in the upper troposphere and lower stratosphere (UTLS) region which is in agreement with both the advection of poor ozone air from the sub-tropical (7 Jan 2002) and the higher latitudes (16 Oct 2011) toward the mid latitudes over central Iran.

As a direct consequence of warmer temperatures, the hydrologic cycle will undergo significant impact with accompanying changes in the rates of precipitation and evaporation. Climate change will cause changes in climate variable such as precipitation, temperature, sunshine hours, wind speed and etc. So as a result of climate variable change, the related variable such as potential evapotranspiration will change too. As the soft computing skills increased in recent decades, more number of climate models has been developed for weather and climate predictions which have significantly improved the quality and quantity of projections. This notable increase in number of climate models has enabled the scientists to estimate a wide range of main climate variables such as precipitation and temperature in fine temporal and spatial resolutions. Although the uncertainty in model outputs still remains a main challenge. Upon the release of new scenarios based on radiative forcing which are known as Representative Concentration Pathway scenarios (RCP scenarios), by Intergovernmental panel on climate change (IPCC) in fifth assessment report (AR5), a new set of 42 global climate models (GCMs) have been proposed for future climate projections. Apart from increased number of available models, three main sources of uncertainty including: measurement error, variability, and model structure, that have been explained and studied in AR5.The aim of the current study is to investigate of changes of potential evapotranspiration (ET) over Mashhad plain, Northeast of Iran in future period 2021-2070 under two RCP scenarios i.e. RCP4.5 and RCP8.5. The main synoptic station inthe region is Mashhad Station located at 59◦ 38َE, 36◦ 18َN, with elevation of 990 m. above M.S.L. The required meteorological data including maximum and minimum temperature, sunshine hours, wind speed for period of 1991 to 2005 were obtained from Iran Meteorological Organization for ET calculation using FAO Penman-Monteith (hereafter, FAO-PM) equation. Besides, the downscaled historical data of potential evapotranspiration provided by Swedish Meteorological and Hydrological Institute (SMHI) have been retrieved for the baseline period of 1991-2005.Then these historical estimated data were compared with those estimated using FAO-PM equation. The historical ET values were post-processed using a statistical proposed method for more accuracy. By completion of this part, the accuracy of historical dataset provided by SMHI was confirmed and used for further comparisons. In the second section the ET variations for future period of 2021 to 2070 under two RCP scenarios of 4.5 and 8.5 was studied. The results showed better estimation of ET during warm months. Statistical comparisons using T-test revealed significant differences between historical and estimated values of ET in months of February, March and December. The correlation coefficient between post processed and observed data showed similar results as in T-test. Since the historical dataset of potential evapotranspiration provided by SMHI was acceptable, it was used for the analysis during future period (2021-2070) under RCP4.5 and RCP8.5 scenarios compared to baseline observed data. The result of this part showed that the highest increase of potential evapotranspiration would be for January by 15.4% and 16.4% under RCP4.5 and RCP8.5 scenarios respectively and October would experience lowest decrease by -12.5% and -10.0% decrease, respectively. In general ET increase will be more under RCP 8.5 scenario comparing to RCP 4.5.

Thunderstorms are regarded not only as a significant weather event but also as a key element in water and electricity cycles of the atmosphere. Generally, researchers consider the intense weather instability as a result of convection in lower levels of the atmosphere with high levels enough of humidity. Usually statistic instability, the humidity of lower levels of the atmosphere and lifting mechanisms near the ground are the main factors leading to convection. Moreover, the combination of three factors, instability, humidity and convergence in lower levels of the atmosphere plays an important role in increasing the possibility of thunderstorms. Accompanying phenomena like lightning, tornado, hail, winds, heavy precipitations (Changnon, 2001 and 1925) and hazardous atmospheric phenomena like turbulence, freezing, and wind sheering make considerable irrecoverable damages to natural and human environments, therefore recognizing the features of these phenomena have always been attracting the attention of researchers. The present study aims at recognizing statistic of thermodynamic, and synoptic features of thunderstorms of southern coasts of Iran. Referring to the archive of National Meteorological Organization, hourly data of atmospheric phenomena of 10 synoptic stations during a common twenty-year period (1995- 2014) were extracted. The data were processed in temporal scales of year, season and month. The data of upper atmosphere (radio-sound data), available in the website of Wayoming University, were applied to investigate the thermodynamic features of the occurred thunderstorms. The thermodynamic features include KI, SI, TT, LI, CAPE indices and skew- T chart in RAOB software. The days with the occurrence of thunderstorms had 5 mm or more at least in two stations that were selected to find synoptic patterns. As the samples were limited, synoptic patterns were done manually. The required maps were prepared using the data of geopotential height in 1000 - 500 hPa levels. Besides wind components u and v and sea level pressure, extracted from NCEP/ NCAR website, were mapped by GrADS software. Checking yearly frequency of thunderstorm occurrence in the southern coasts of Iran showed that the frequency of occurrence of storms in Booshehr station was more than its frequency in Hormozgan station. Moreover, the thunderstorms of Booshehr have a better chronological order as it occurs during all common years. However, except for Bandar Abbas, there is no chronological order for this phenomena. Therefore, it can be said that the occurrence of thunderstorm in the western coasts of the south of Iran has higher frequency than the central and the eastern regions, making it a potential area in this region for storm formation. The largest number of thunderstorm occurrence in seasonal scale is recorded for fall with 45% and winter with 43% respectively. Following seasonal conditions, the largest number of thunderstorm occurrence in monthly scale is recorded for cold months. In Hormozgan station, November, December, and January have more frequencies, while in Booshehr station January, February and March have more frequencies. Analyzing the applied instability indices showed that there was a slight extreme and great CAPE (more than 2500) in Bandarabas station. Besides the values of convection indices TT and KI for most of the thunderstorms suggested the possibility of convection occurrence. Instability indices LI and SI for the occurred thunderstorms reveals conditions of limited instability. Synoptic analysis shows not only the dominance of the westerly winds extending to the south of Saudi Arabia but also the location of divergent region and positive vorticity advection region in the studied region, making instability conditions raising air. The spread of the westerly winds is either due to formation of blocking system in the atmospheric middle level or their meridional blowing and cold air advection from Europe or the north of Asia to the east of Mediterranean. Statistical findings reveal that the occurrence of thunderstorms of western coasts of the Persian Gulf, have higher potential, and more frequency than the central and eastern regions. In seasonal scale, the largest number of occurrences is recorded for fall and winter respectively, while there is no substantial difference in different hours of day and night in hourly scale. As a matter of fact, they are possible to happen all the times. Synoptic analyses show that there is the dominance of two patterns of blocking systems and westerlies trough in the middle of atmosphere leading to instability and rising air in the studied region. The divergent region and positive vorticity advection region in the studied regions make instability condition and hence rising air. Based on the findings of thermodynamic indices, it can be said that convective activities and local instabilities are rarely responsible for thunderstorm occurrence in the region. Also for the occurrence of severe convective activities and relatively high instability, extreme instability and extreme severe instability is coincident with limited thunderstorm occurrences.