فصلنامه فیزیک زمین و فضا
سال چهل و یکم شماره 1 (بهار 1394)

By growing the population and need for settlement، many cities have been built on soft sediments and seismic areas. It emphasizes the need for a careful and reliable assessment of site effect phenomena. Beyond the methods of studying site effects، microtremor recordings has become popular over the last decades as it offers a convenient، practical and low cost tool to be used in urbanized areas. Besides، in areas of low to moderate seismicity which gathering a significant number of recordings with satisfactory signal to noise ratio is a time-consuming task، microtermor studies are more useful. Lack of accurate knowledge about the nature of microtremor wave field، would lead to misinterpretation of site effects، hence، investigating microtremor wave field is an important goal to achieve. Two techniques are predominantly used to determine microtremor wave field: the array techniques (such as SPAC and F-K methods) and the single station horizontal to vertical spectral ratio (H/V). Array studies have shown that surface waves dominate microtremor wave field، but the relative proportion of Rayleigh and love waves has still been unclear. In this study، single station horizontal to vertical spectral ratio method was applied to investigate the nature of microtremors in south of Tehran. Theoretical aspects of this method، has always been a considerable issue for researchers in this field. Regarding the dominance of fundamental Rayleigh wave mode on vertical component of microtremors، some researchers believe that، if impedance contrast between surface layers and the bedrock tend to be high، ellipticity curves (ellipticity at each frequency is defined as the ratio between the horizontal and vertical displacement eigenfunctions in the P-SV case، at the free surface) of fundamental Rayleigh wave mode shows a conspicuous peak around the site resonance frequency. It is due to the vanishing of vertical component corresponding to reversal rotation of fundamental Rayleigh wave from retrograde to prograde، In contrast، some other researchers do believe that the SH resonance in surficial layers (removing the effects of surface waves) accounts for H/V ratio peaks. Data used in this study was recorded by Haghshenas et al. (2003) using continuous recording for a period of five months in 13 seismological stations. The results of two stations are shown here. Geopsy software (www. geopsy. org) is used to analyze microtremors. First، particle motion behavior in microtremor wave filed was studied. The results showed an elliptical behavior that can be related to predominance of Rayleigh waves in microtremor wave field. It should be mentioned that if body waves dominate the wave filed، the particle motion will show a linear behavior which is not observed in our study. Then، spectrum amplitude curves were obtained. To compute H/V for each time window، root mean square of two horizontal amplitude spectra is divided by vertical amplitude spectra at each point. H/V curves showed that site resonance frequency varies from 0. 3 to 5 Hz in south of Tehran. Our study revealed that the peaks at site resonance frequency were localized by minima in vertical amplitude spectra as well as by maxima in horizontal amplitude spectra. To study dispersion property of layers beneath each station، shear wave velocity variation with respect to depth was investigated. Dispersion curves were obtained based on earth models. It was shown that the under-structure layers are dispersive. Take into consideration that Tehran has a complicated geological state and lack of borehole information، Jica & Cest report (2000) was used to obtain earth models. Jica & Cest report (2000) includes only thickness and type of layers، while، the shear and longitudinal wave velocity is needed. Jica & Cest report (2000) contains Standard Penetration Test values according to the type and thickness of layers and experimental relations between these values and shear wave velocity. These relations were used to compute shear wave velocity under each station. Longitudinal velocities were computed by the relation proposed by Lay and Wallace (1995). Finally، ellipticity curves of Rayleigh waves were modeled and compared with H/V curves. The same earth models of previous step were used to model ellipticity curves. The ellipticity curves showed a conspicuous peak around the site resonance frequency. These could be due to the reversal motion of fundamental Rayleigh wave mode from retrograde to prograde. To sum up، it could be said that in south of Tehran، fundamental mode of Rayleigh wave accounts for H/V ratio peak.

Amplitudes of seismic waves decrease with distance according to anelastic properties of the earth and geometrical spreading. The attenuation of ground-motion amplitudes in the frequency domain is an important problem in engineering seismology. It is of particular practical interest in the regions such as Zagros (Iran). The Zagros fold- thrust belt, as a part of Alpine- Himalayan orogenic belt is one of the most active continental collision zones on the earth, which extends from the Tarus mountains in southeastern Turkey to the Minab fault in the east of the Strait of Hormoz in southern Iran. Structurally, its formation is related to the continuing convergent movement between the Arabian plate to the southwest and the Central Iranian Micro continent to the northeast, resulting from the north- northeastward drift of Afro-Arabia against Eurasia and so this region is seismically active. Hence, attenuation studies as well as other seismic studies seem to be necessary. The ground-motion relations are key inputs to seismic hazard analysis for engineered structures. In such cases, an empirical attenuation model determined from events provides critical input to the models of ground-motion generation. The attenuation model is used to play back attenuation effects to determine the apparent source spectrum for each earthquake in the database. The lack of an appropriate ground-motion prediction model may result in undesirable outcomes, such as unrealistically high or low loading standards in the design and construction of critical infrastructure such as large dams, power stations, and hospitals. For seismological purposes, appropriate attenuation models make it possible to calculate more accurately the source parameters such as magnitude and seismic moment. In this study about 10000 records due to 998 events recorded at the International Institute of Earthquake engineering and Seismology (IIEES) stations during 2006-2013 across the Zagros region, were selected in order to estimate the average attenuation relation parameters. All data were divided into two parts: a) acceleration data (that is derived from velocity data) with moment magnitude between 4-7and b) velocity data with moment magnitude between 2-4. We combined the two north–south and east–west seismograms into a single seismogram for a given azimuth. For each rotated combined horizontal record, a shear-wave window was selected and a 5% taper was applied at each end of the window. After correcting for instrument response, the Fourier spectrum of the shear-wave window and a noise window with the same length as the shear-wave window were calculated and binned in increments of 0.2 log frequency units for a central frequency range of 1-10 Hz. We fit the observed Fourier velocity amplitudes at each frequency to a Hinged-Trilinear function. The distances at which the nature of geometrical spreading attenuation changes significantly was graphically found for both data in 110 km and 200 km using a locally weighted scatterplot smoothing (LOWESS, local regression smoothing method) called robust LOWESS. A trilinear function with hinges at distances of about 110 and 200 km can describe the geometric spreading attenuation with distance. Using unconstrained Nonlinear Optimization algorithm, we found that for acceleration data with and for velocity data with minimize the average absolute value of the Fourier spectrum amplitude residuals. Using an anelastic attenuation coefficient at different frequencies, the direct average of calculated quality factor for both dataset, Q in the Zagros region is obtained as.

Seismic waves when crossing the Earth in heterogeneous and anisotropic environments, having interaction. Recognizing the impact of these factors on the seismograms help us to find out more information about interior of the Earth. Coda waves are the main reason for the random heterogeneities in earth. Local earthquakes in the northeast region of Iran with epicentral distance less than 200 km is used with magnitude range of 2 - 6 recorded in period 2006 to 2013. Finally, data for five stations which have (15441 earthquakes) were chosen. In this study, the attenuation parameters, Q, were estimated using the single scattering models. Aki and Chouet (1975) proposed a single backscattering model to explain the coda waves as a superposition of secondary waves from randomly distributed heterogeneities. The decrease of coda wave amplitude with lapse time at a particular frequency is due to energy attenuation and geometrical spreading, and is independent of earthquake source, path effect and site amplification (Aki, 1969). Generally, the Q factor increases with frequency (Mitchell, 1981) following the relation where Q0 is the quality factor at the reference frequency f0 (generally 1 Hz) and n is the frequency parameter, which is close to 1 and varies from region to region depending on the heterogeneity of the medium (Aki, 1980). This relation indicates that the attenuation of seismic waves with the passage of time (distance from source) is different for different frequencies. Hence, the seismic data are first bandpass-filtered to calculate the attenuation. In the present study, the attenuation of the S-coda wave (Figure 5) is calculated at seven central frequencies after getting bandpass-filtered using a Butterworth four pole filter as given in Table 1.The amplitude of the coda wave at lapse time t seconds from the origin time for a bandpass-filtered seismogram at central frequency f is related to the attenuation parameter Q by the following equation: Where C(f) is the coda source factor at frequency f, which is independent of time and radiation pattern, α is the geometrical spreading parameter and is equal to 1.0, 0.5 or 0.75 for body waves, surface waves or diffusive waves, respectively (Sato and Fehler, 1998), Qc(f) is the quality factor of coda waves. As coda waves are backscattered body waves, α= 1. Equation (1) can then be rewritten as: is determined from the slope (b) of a least-squares straight-line fit between versus t, using the relation Shows different steps involved in the computation of Qc (f) from the RMS values of amplitude with time. According to Rautian and Khalturin (1978), the above relation is valid for lapse times greater than twice the S-wave travel time for avoiding the data of the direct S-wave. Sato (1977) introduced the source receiver offset in a single scattering model so that the coda analysis begins after the arrival of the shear wave. In the present study, the time envelope for the coda decay observation is taken at twice the time of S-wave (2ts) from the origin time of the event. Q0 and n values indicate the average values for each station in the surroundings of the station. As an outcome, average of quality factors and frequency-dependents, is given by: In addition, to evaluate the variation in depth direction, we used the quality factor of 18 Coda windows from five to 90 seconds by 5 seconds step. Low values of Q0 in the initial Q-coda windows, indicating strong heterogeneity in the shallow layers of the Earth. The results in studying region have been compared with another zone in Iran (SSZ) (Figure 8).

Studying active faults behavior for earthquake prediction and recognition is a concentrated subject in earth science. Precise measurements of earthsurface deformation by geodetic observation provide a good reference for studying different geodynamic phenomena. Applying geodetic measurements in postseismic and interseismic intervals is an important tool for estimating strain accumulation and rheological properties of the faults. However, the geodetic measurements only describe the movement of selected points and therefore are not a direct estimation of the rheological properties of the region. To derive the values of those parameters, assumptions on the behavior and on the properties of the lithosphere surrounding the fault should be introduced and then by applying geodetic displacement field as boundary value of elastic and viscoelastic formulation, the inverse problem could be solved. The important problem in these inversions is the complex non-linearity of this formulation which classic inversion methods cannot solve them well. Global optimization methods are usually applied to solve these inversions. In this study, we estimate the interseimic behavior of North Tehran fault. North Tehran fault is a north-dipping thrust fault marking the boundary between Eocene rock formation and alluvium. It is the general term for the abrupt change of elevation between Tehran’s piedmont and rock formation raising over 2.5 km above it. The North Tehran Fault is located at the southernmost piedmont of Central Alborz. It stands out as a major active fault menacing directly the city of Tehran, a 12 million inhabitants mega pole, and would have been the source of several major historical earthquakes in the past. The fault zone extends within the 110 km and corresponds mainly to a reverse fault crossing the northern suburbs of the Tehran metropolis. In order to investigate the recent crustal movements in Tehran north fault, the design of a leveling network containing three leveling circuits across the fault was taken in 1997. The main corrections to the data is applied including gravity irregularities, rod miscalibrations, residual refraction and rod scale expansion because of temperature differences. Another leveling observation was performed in 2005 in three distinct lines. We used these observations for assessing North Tehran interseimic behavior. The methodology of geometrical modeling of surface vertical deformation is applied to fix the datum of leveling observation in non-deformed region. For this, Mean and Gaussian curvature differences were introduced as scalar invariants associated with the tensor of change of curvature. Using precise leveling observations, Okada relations are inverted applying simulated annealing algorithm in Bayesian framework. Simulated annealing is a procedure analogous to thermodynamic annealing where the chaotic motions of atoms of a molten solid settle down to form a crystal with minimal energy under certain suitable conditions. With a similar analogy, the unknown model parameters constitute the molecules of a molten solid in which the chaotic motion of them during temperature reduction gradually ceases and the state corresponding to the global minimum of the cost function becomes highly probable at a very low temperature. The inversion results show the uplift of the hanging wall and subsidence of the footwall of the fault. The estimated slip rate is 1.9±0.2 for the eastern part and 5.7±0.04 for the western part of the faults in 1997-2005 period.

Volcanoes and their eruption indicate dynamic process of the inside of ground, which are often located along the boundaries of tectonic plates. Study of movements and surface deformation of the volcano is essential because surface deformation reflects changes in the subsurface. In the studies of crustal deformation, volcanic models provide valuable insights of the features of volcanoes and their behavior throughout time. These models have been adjusted based on geodetic and seismic geological data. According to the geometry of deformation source, various models have been proposed for volcanoes. One of the analytical geodetic displacement models is Mogi model, which assumes the volcano's magma reservoir with spherical geometry as a source of surface deformation. in the Mogi model, the Earth's crust has been described as a half-bound elastic body which is called an elastic half-space. Half-space is a planar surface, which is taken as surrounding an environment and extended indefinitely in all direction. Displacement field of the Mogi model is caused by hydrostatic pressure change in a finite spherical source with a radius smaller than its depth in an elastic half-space. Modeling of displacement field using the analytical models requires determination of rheological and geological parameters of the volcanic magma reservoir. Hence, by taking into account the assumptions about the properties of the crust in the desired area, one can obtaine displacement field from geodetic observations as the boundary value problem of the elastic models. Then geophysical and geological parameters can be obtained by solving the inverse problem. On the other hand, solving the inverse problem has many answers. Hence, optimization algorithms are used to solve this problem. Optimization algorithms gain the most likely answers. In this study, parameter extraction was performed by genetic optimization algorithm. In this algorithm mating probability 50% and mutation probability 5% was assumed for a population of 1,000 subjects. RMSE (Root Mean Square Error) of inversion was 0.006 mm. After determining the required parameters, the displacement field modeling was done by the Mogi model. Finally, The sensitivity analysis of the displacement field to changes of the model input parameters was evaluated. The purpose of sensitivity analysis is to discover changes in which the input parameters, most affected the model output. An important result that can be extracted from the sensitivity analysis is that a more sensitive parameter is a more one reliable in the parameter extraction process. By performing this analysis, the displacement field showed most sensitivity to the coordinate quantities of the source center and least sensitivity to the volume change of the quantity of magma reservoir. This analysis indicates that the Mogi model is more robust in determining the location parameters of the source, but is poor in determining the source volume change parameters. In order to extract the parameter, it can be possible to obtain the optimal value by changing the sensitive parameters and comparing the output with the observations. It is notable that the Mogi model is very sensitive to the shallow sources.

Ground Penetration Radar (GPR) as a nondestructive method for identifying underground objects has been successfully applied to different fields of science such as geotechnical investigations, oil and gas exploration, geology, pipe detection and archeology investigations. Metallic and nonmetallic objects can be identified by this method. The depth of penetration is dictated by the GPR antennas. Low frequency antennas (from 25-200 MHz) explore materials from deeper depths in the low cost resolutions. High-frequency antenna (>200 MHz) obtains reflections from shallow depths with higher resolutions. Ground penetrating radar is considered as the most suitable approach to detect shallow buried objects. Transmitter and receiver antenna are closely spaced together and can detect changes in the electromagnetic properties of an object. Electromagnetic waves are transmitted through an antenna and the reflected waves form various buried objects or contacts between different materials are received and stored in digital control unit. Antenna shielding is performed to eliminate interferences from other intruder sources. Electromagnetic waves are emitted by the transmitting antenna and distorted by the soil conductivity variation, dielectric permittivity, and magnetic permeability. The reflected waves are recorded by the receiving antenna in nanoseconds. The shape of GPR radargrams, vertical map of the radar reflection returned from subsurface objects, of cylindrical objects is similar to a hyperbola. Interpretation of acquired GPR data needs an expert geoscientist with a lot of knowledge and time. The classical Hough transform is a common method for identification of buried objects (Capineri et al. 1998, Simi et al. 2008). However, this method is time-consuming and computationally expensive. Alternatively, artificial neural network used by some authors (Al-Nuaimy et al. (2000), Gamba and Lossani (2000)), but these methods also need many training data to gain high accuracy and producing such data is difficult. Genetic optimization algorithm has been applied by Pasoli (2009) to detect the hyperbolic objects in GPR images. Local search of original genetic algorithm is poor. Chen and Cohn (2010) have presented a method for detecting hyperbola shapes based on probabilistic mixture model. However, the method is computationally expensive and is not robust with respect to noise. In the current study, a modified genetic optimization algorithm has been applied to GPR sectional images for identifying hyperbola signatures of small-buried objects (mainly pipes and channels). The performance of genetic algorithm highly depends on genetic operators. Arithmetic crossover is used to improve the local search ability and point-wise crossover is applied to explore new regions. The hyperbolas are searched through the edge image resulting from an image pre-processing step. Hyperbola detection is achieved with sub-pixel accuracy. After identifying each hyperbolic object, the object is removed from the image and algorithm searches for new possible hyperbolas in the GPR image. The performance of proposed method is evaluated using synthetic and real data. The synthetic data were generated with GprMax 2D, a computer program that generates GPR images using an electromagnetic simulator, based on the finite-difference time-domain (FDTD) method in 2D, and real data surveyed in campus of Isfahan University of Technology (IUT). Some preprocessing steps including dewow filtering and removing DC bias, background removal, manual gain function, and image thresholding were applied to the data, before employing the proposed method. Then, hyperbola parameters extracted using a modified genetic algorithm. Depth and radius of the buried object were estimated by hyperbola parameters. The results show that the proposed method gains high accuracy in estimating depth and radius of buried objects.

According to General Circulation Model (GCM), zonal thermal belts are 1- Inter-Tropical Convergence Zones (ITCZ) around eqator; 2- Sub Tropical High (STH) belt around 30 degree latitude; 3- Sub Polar Low (SPL) belt around high latitudes. The belt of Inter-Tropical Convergence Zone (ITCZ) displaces in meridional path, about 5° over the oceans and up to 40° over continents, during the seasons of a year. The position of Sub-Tropical High (STH) belt is also affected by ITCZ movement. STH displacement may change the area covered by the westerly Baroclinic Waves (BW) in temperate regions. The position of the STH is an important issue for changing precipitation regime and onset of precipitation events in Iran. The goal of this research is to determine the position of STH belt over Iran in monthly scale during 1948-2010 period undertaking its meridional displacement. Geopotential height data was extracted from NCEP/NCAR reanalysis with 2.5 degrees resolutions (42.5 °E, 45 °E, 47.5 °E, 50 °E, 52.5 °E, 55 °E, 57.5 °E, 60 °E and 62.5 °E) for nine meridians over Iran ranging from 42.5°E to 62.5°E. Goal of this research consist of: 1- Position determination of Sub Tropical High (STH) belt in monthly scale passing over Iran in 1948 - 2010 period; 2- Evalution of meridional displacement of STH position over Iran in 1948 - 2010 period in order to assess climate changes. By consecutive observations of 756 of 500 hPa monthly maps in GrADS (Grid Analysis and Display System) scope, 5840 gpm contour was indicated as the STH indicator. It is because the southern area of 5840 gpm contour, almost covered by northern latitude of the system while the northern area is occupied by the westerly waves during monthly round maps. This result agrees with previous studies. The strip of northern latitude is determined by 20 m width ranging from 5830 gpm to 5850 gpm. Monthly time series of STH position (unit: degree of northern latitude) was then detected using GrADS programming. Results show that the position of STH is between 10°N and 47.5°N as the most extremes in winter and summer respectively. For the long term means, the minimum northern latitude was averagely observed in January placed on 18°N zone, while maximum happened in August crossing 39 °N zone during the investigated period. Its meridional displacement then reaches 21° over Iran averagely. Moreover climatic means of STH positions during 1981 - 2010 period with respect to 1951-1980 period were migrated approximately 2.8° northward. It is concluded that STH position was moved toward higher latitudes, about 2.8 degrees, in recent decade. The non-parametric Mann - Kendall trend test was applied on time series of STH position in monthly and annual scale. Results showed generally rising trends under 0.01 significance level, with 0.07 slope approximations during 1948 - 2010 period. It demonstrated the signal of climatic variability of atmospheric circulation over Iran. It is suggested that the time series of Sub Tropical High position be as the input of climate prediction models yielding temperature and precipitation as well as drought study.

Results of numerical simulation of intra-cloud electrification depend on a mechanism that determines the sign and magnitude of charge transferred to hydrometeors (including graupels and ice crystals), through their collision (Mansell et al., 2005). Some of the microphysical processes play an important role in the above mechanism. In order to estimate the amount and sign of the transmitted charge per collision for numerical purpose, the results of laboratory researches are commonly used. Two kinds of inductive and non-inductive (used in the current paper) mechanisms could be applied. The research studies conducted for the non-inductive one can be determined based on the liquid water content (LWC), temperature (T), ice accretion rate and the particle size spectrum (Takahashi, 1978; Jayaratne et al., 1983; Gardiner et al., 1985; Saunders et al., 1991; Ziegler et al., 1991; Saunders and Peck, 1998; Pereyra and Avila, 2002). According to the importance of this issue, in this research three sets of relations resulted from laboratory studies have been used. These sets were proposed by Takahashi (TAK, 1978 and 1984), Jayaratne / Gardiner / Ziegler (JGZ, Jayaratne and colleagues 1983; Gardiner et al. 1985; Ziegler et al. 1991) and Sanders et al. (SAN, Sanders et al. 1991). These parameterizations relate the mean charge transferred per collision to liquid water content and temperature. Following these studies, the prepared schemes of three sets have been implemented in an explicit time-dependent one-dimensional cloud model (ETM), based on Chen and Sun (2002). In the 1-D cloud model entrainment-detrainment and eddy diffusion processes have been considered. Also microphysical processes have been parameterized using Lin et al. (1983) and Rutledge and Hobbs (1984) schemes. The convection is initiated using potential temperature perturbation, defined by Chen and Sun (2004). The input data for the simulation of vertical cloud is from an idealized sounding including pressure, temperature and water vapor mixing ratio. This cloud model simulates vertical velocity (w), equivalent ice potential temperature (θei), water vapor mixing ratio (qv), cloud water mixing ratio (qc), ice mixing ratio (qi), rain water mixing ratio (qr), snow mixing ratio (qs) and graupel mixing ratio (qg). The cloud model was set up with 1 second time step, 70-minutes simulation duration and 250 m spatial resolution in the vertical direction up to a height of 15 km. The initial radius for the cloud column was considered as 3000 m. The results of simulated mean charge transferred per collision using three sets of parameterizations (TAK, JGZ and SAN) show that their dipole pattern outputs are not the same. Simulations based on TAK and JGZ relations produced positive dipole (positive charge distribution lies over negative charge one), while simulation using SAN parameterization produced negative dipole pattern (the negative charge distribution on the top of the positive charge one). The simulation results show that the electric field was produced between 25-56, 19-34 and 27-57 minutes using TAK, JGZ and SAN parametric relations, respectively. It is noteworthy that the maximum values of positive and negative intra-cloud electric fields were obtained when applying TAK relations in the charge-transfer simulations. While, simulations using JGZ and SAN parameterizations led to the minimum values for positive and negative intra-cloud electric fields. The time and height of positive and negative electric field occurrences based on three sets of applied parameterizations were also compared. The results of comparisons demonstrated that the values acquired from TAK and SAN parameterizations were close. However, the values for simulation using JGZ indicated three minutes time discrepancy and 12.5 km height difference. Finally, the simulated intra-cloud electric fields using three TAK, JGZ and SAN parameterization sets were compared with the threshold electric field, defined by Marshall et al. (1995), to extract the number of lightning occurrences. Our findings show that the maximum and minimum values of lightning events were seen in simulations using TAK and JGZ parametric relations, respectively. The number of lightning occurrences was 40, 12 and 30 for simulations using TAK, JGZ and SAN parameterizations respectively.

Spatial Autocorrelation (SA) is the correlations of the observed data of an area in the form of spatial pattern. The criterion of SA phenomenon occurrence is when the distribution of one observed variable value follows a particular pattern systematically. The SA analysis is most useful and an important tool for investigating the spatial database, This analysis not only itself gives useful information about the relationship between the inner side, but the results for the most complex statistical analysis are given. The aim of this study is to investigate the pattern of the spatial distribution of temperature, rainfall and humidity model of spatial autocorrelation using Moran's central local and global statistics. The main aim of this study is to investigate the spatial distribution patterns of temperature, precipitation, and humidity using geostatistical exploratory analysis in the central area of Iran. For this purpose, data from 72 synoptic stations of Iranian Meteorological Organization for the period from 1972 to 2012 were collected, reviewed, and analyzed. Methods used include ordinary, Sample and General Kriging with Circular, Gaussian, Spherical, and Exponential variograms, which is done in Arc GIS 10.2. Then, the errors criteria measures to assess their accuracy and precision have been used. Kriging is a moderately quick interpolator that can be exact or smoothed depending on the measurement error model. Kriging uses statistical models that allow a variety of map outputs including predictions, standard errors, and probabilities. Kriging assigns weights according to a (moderately) data-driven weighting function, rather than an arbitrary function, but it is still an interpolation algorithm and will give very similar results to those of others methods in many cases. All Kriging techniques are based on the simple linear models as: Whereis the estimator of the true value at any location, andare the weights allocated to each observation such that.The technique minimizes estimation variables by solving a set of Kriging equations, which include covariance between the point or volume to be estimated and the sample points and covariance between each pair of sample points. In this investigation, we have used the Simple, Ordinary, and Universal Kriging for interpolation of temperature, precipitation, and humidity. Various results are obtained with the use of different interpolation methods on similar data. With the wide and increasing applications of the spatial interpolation methods, there is also a growing concern about their accuracy and precision. Several error measurements have been proposed. Commonly used error measurements include: mean error (ME) or mean bias error (MBE), mean absolute error (MAE), mean squared error (MSE) and root mean squared error (RMSE). If ME and MSE are closer to zero, and RMSE is smaller, the better is the model. ASE and RSME should be the same or close. If ASE>RSME, then the method overestimates the primary variable. If ASE1, the method underestimates the primary variable, and if RMSSE<1, it overestimates the primary variable. The use of SA method for determining the degree of connectivity of the inter spatial objects was done through two approaches, they were: (1) Global Indicator Spatial Association (GISA) and (2) Local Indicator Spatial Association (LISA).The Moran’s method worked in comparing particular variable value in each area with the value in all observed areas. GISA is the analysis of spatial associated pattern on a broader scale to see the data distribution, whether clustering was formed or not, dispersed, random in one space. GISA is defined in the equation (3). Notation is the total observed case data, is the spatial weight matrix element,is observed value I andis the value of neighbor observation j, and is the average value x.GIS A value is interpreted by the use of Moran’s I (I) ranging from – 1 to +1.Index I that had value of -1 represents data spread or averaged objects (uniform), I that had value of 0 represented random spread and independent. I that had value of +1 represented data/objects that were alike to form clustering. LISA is the analysis for SA quantification in the smaller area, which produces higher statistically significance (hotspots), lower statistically significance (cold spots), and outlier. LISA is defined in the equation (4). Where and are the amounts of I deviations. LISA was interpreted as follows, (1) if the variable in one observed location is the same with its neighborand has high value, it will be called as HH (high-high) or hotspots, (2) if the variable in one observed location is the same with its neighbor and has low value, it will be called as LL (low-low) or cold spots, (3) if the variable in one observed location has high value while its neighbor has low value, it will becalled as HL (high-low) or outlier, (4), if the variable in one observed location has low value while its neighbor has high value, it will be called as LH (low-high) or outlier. Moran's global distribution pattern of the local and spatial analysis of precipitation in Iran suggests the fact that Iran has a very strong cluster pattern because the Moran index value was obtained near 1 (0.94). This indicates that local distribution of precipitation is non-uniform (spatial imbalance). Given the fact that Moran index only determines the cluster or random nature of precipitation distribution, hot and cold spots index was used to identify the locations of the clusters. The results of this study showed that the pattern of trends in temperature, precipitation, and humidity are high clustered based on the global Moran index for moisture, which is higher than other elements of the cluster. Local Moran's results showed that the temperature, humidity, rainfall, and more central area follows a random pattern, however the pattern of temperature distribution is more scattered. Whereas the high value for the pattern of the rainfall and humidity levels are higher for high-elevated areas of Kerman and in part of the Zagros Mountains.

Keywords: Exploratory spatial data analysis (ESDA), Spatial autocorrelation (SA), Global indicator spatial association (GISA), Local indicator spatial association (LISA), Central area of Iran

In seismology, we use ray tracing to study subsurface geology and determine the structure of the earth. Rays are solutions of the Hamilton equations. In many cases, rays also can be obtained by following Fermat’s principle of stationary travel time. According to Fermat's principle, ray travels along a curve that renders the travel time, minimum. So the ray path can be obtained by minimizing the travel time, so that the obtained path satisfies the ray equation. Hamilton equations can be solved by specifying boundary conditions. The most important case of boundary-value ray tracing is the two-point ray tracing. The shooting and bending methods are two commonly used numerical approaches to solve boundary-value ray-tracing problems. The shooting method is based on solving ray equations as initial-value problems by specifying the takeoff angle. The takeoff angle is varied until the ray passes through the receiver position. The shooting method works well to find rays connecting sources and receivers in simple 2D media. It breaks down in areas where ray equations break down, such as shadow zones and in complicated media where a slight variation in the takeoff angle might result in a significantly different ray, thus causing difficulty in connecting sources to receivers. The bending method addresses intrinsically the problem of connecting sources to receivers. One begins by connecting source to receiver with an initial path. This initial path is bent according to a prescribed method based on minimizing travel time (Fermat’s principle) until the desired ray is obtained. In this study, we minimized the travel time using simulated annealing to obtain global minima. Simulated annealing is based on the annealing process of solids in physics and is used in mathematics and physics to obtain an optimal solution to problems subjected led to constraints. Using this method, we found rays between fixed sources and receivers that render travel time globally minimal. By small change in the procedure, our algorithm can be modified to calculate rays of locally minimum travel time, such as reflected rays, by constraining the ray to pass through a set of points that are on the layers of the boundary. We formulate the concept of rays, which emerges from the Hamilton equations. Then, we show that these rays are solutions of the variation problem stated by Fermat’s principle. The proposed method is applied to the three velocity models. In all of these cases, we found that the path renders global minimum travel time. We have also tested the method to determine the path for a reflected ray from a known reflector. The results are compared to that of a ray tracing method called "fast ray tracing algorithm.” For the first two models, the results were similar but for the third model, we had no response from fast ray tracing algorithm while we determined the correct ray path by the proposed method, which surpassed our expectations. Our method overcomes two common shortcomings of other bending methods. First, solutions calculated using our algorithm is independent of the initial path. Second, our algorithm does not require using smoothly varying velocity models. We demonstrated the efficiency of our method by applying in to three different velocity models. The method is also generalized to a three-point problem, which is applicable for calculating rays constrained to pass through multiple interfaces.

In many seismological applications, the Earth is considered as a perfectly elastic, homogeneous, and isotropic body. Although this assumption is approximately valid, it is known that seismic waves pass through the real Earth that is anelastic, inhomogeneous and anisotropic. We consider four processes that can reduce wave amplitude, i.e.: geometrical spreading, scattering, multi-pathing, and anelasticity. The first three are elastic processes, in which the energy in the propagating wave field is conserved. By contrast, anelasticity, sometimes also called intrinsic attenuation, results because the kinetic energy of elastic wave motion is lost to heat by permanent deformation of the medium (Stein and Wysession, 2002). Intrinsic attenuation as one of the factor affecting the attenuation of seismic wave during propagation is discussed in terms of quality factor. Estimation of quality factor is valuable for seismic hazard assessment, ground motion simulation, attenuation relationships, and other seismological studies. The quality factor is an effective Q, which includes other damping mechanisms. The effective Q is the sum of intrinsic and additional attenuation: Generally, it is impossible to control all effects and the result is an effective Q (Tonn, 1989) Regional variations in crustal Q are often studied using Lg waves. The most prominent regional phase is the Lg wave that was identified by Press and Ewing (1952). Lg phase is commonly observed in the continental crusts. It is variously described as a superposition of higher mode surface waves or trapped post-critical S waves. Lg phase does not propagate efficiently in the thin oceanic crust. Lg phase has also been observed to have large amplitude in the group velocity windows of 2.8 - 3.5 km/s (Cara et al., 1981). We applied the stack spectral ratio (SSR) method originally developed by Xie and Nuttli (1988) to obtain Q0 (Q at 1 Hz) and its frequency dependence (η) of each path integral between different station-event pairs in frequency range of 0.2 - 5.0 Hz for the northern part of Iran (lat. 32 - 40 °N and long. 44 - 62 °E). This part consists of Kopeh Dagh, Alborz-Azarbayejan, Some part of Zagros, some part of Central Iran and the Caspian Sea block. The use of the stacking procedure is a major development in obtaining stable Q (f). The dataset used in this research consist of the vertical component seismograms from 409 events with magnitude (MN) greater than 4, occurred during the period of 2006- 2013. According to the results obtained in this study, the maximum Q0 values are in the range of100 - 500 and maximum frequency dependence values are in the range of 0 - 1. In addition, if it is assumed that, the average values of these two parameters are given by for the entire region. According to the tectonic evidences and seismicity pattern, the study region is tectonically active. Therefore, for active regions, attenuation of seismic waves is increased and the values of Q0 are reduced because of crust heterogeneity, fractures and energy scattering in fractures. Table 1 shows Q0-values obtained for different seismotectonic provinces. Analysis of this table shows that the lowest values of Q0 characterize the Azarbayejan region and these values are closed to the Alborz region. In addition, Q0-values of Zagros and Kopeh Dagh regions are similar to each other. Structurally, Kopeh Dagh is similar to Zagros. So, similar values of Q0 and η are expected for these similar tectonic regions. The low Q0-values for the Alborz and the Azarbayejan regions compared to the values for Zagros and Kopeh Dagh regions may be due to volcanic mountains in this region. It confirms that for the regions with recent volcanic activities, low Q0 values are expected. For the central Iran in our study region, the moderate to high Q0 values are obtained. Because this province is an intraplate environment between Zagros and Kopeh Dagh, thus it can be suggested that for this kind of region, moderate to high Q0 values are obtained because of the differences in seismicity patterns. The highest Q0 is for the Caspian Sea that consists of a thin oceanic crust. For this region the number of surface waves modes is reduced and the Lg phase cannot propagate sufficiently long. Variation of frequency dependence versus quality factor shows different behavior for different seismotectonic provinces. For the Alborz and the Azarbayejan regions, frequency dependence decreases with increasing Q0 values. For Zagros and Kopeh Dagh, frequency dependence increases with increasing Q0 values. Overall, we can conclude that similar tectonic regions show similar frequency dependence versus the quality factor. The quality factor values are plotted versus epicentral distance. It shows a direct relationship between these two parameters and with increasing epicentral distance, the quality factor increases. This trend is not observed in the different seismotectonic provinces. Generally it is expected that with increasing distance from the seismic source, the attenuation of seismic waves is increased. However, several factors such as the regional tectonic conditions, rate of seismicity, sediment thickness and thermal conditions, etc. can affect the value of the quality factor. Since regional tectonic condition has the most important role in determining the quality factor, we cannot solely assess variations of quality factor versus epicentral distance.

Identifying and measuring the impact and value of scientific output plays an important role in today’s world of information overload. On one side, governments are trying to distribute research funds in ways that support research in strategically important fields, on the other side, researchers and scientists are seeking to access only relevant and quality information that have mainly worthy of their attention. Nowadays, countries are evaluated not only by their national products, military power, geographical area, etc., but also by such factors as the production and consumption of scientific information. Scientometric approaches are used to provide appropriate tools for evaluating scientific products at local, national, and international levels. These tools have a number of advantages, including identifying core and significant journals, authors, institutions, universities, and papers; navigating thoughts and developing literature and resources; anticipating scientific products trend; visualizing different subject fields and determining the most important subjects; identifying collaboration and co-authorship patterns; comparing courtiers based on scholarly publications etc. Regarding to the above-mentioned tools it seems that citation indexes and databases such as Scopus database are suitable tools, which can measure scientific products in all the fields. Scientific products of geophysics, the same as other fields constitute a part of the Iran's scientific output. The purpose of this study is better to understand the scientific production of geophysics and to present a scientific map. This study is a descriptive approach using scientometric methods. The population of this research comprises of 1996 documents indexed in Scopus database. Network workbench tool (NWB) software was used for mapping and other data were extracted manually. The results showed that the published papers of Iranian researchers in the field of geophysics showed a good trend in period of 1975-2013. The contributaion of Iran in the geophysics outputs constituted 0.65% of total publications and ranked 30 in the world during 39 years. Riahi from Tehran University and Ataei from Shahrood University were the most productive authors in the field of geophysics. Tehran University and Islamic Azad University accounted for most products in geophysics. Most of articles were published in the Journal of the Earth and Space Physics released by the Institute of Geophysics, University of Tehran, Journal of Geophysics and Engineering, Geophysical Journal International, and Journal of Asian Earth Sciences. A writing pattern of three and more authors had the highest frequency. Results indicated that the level of productivity for single author or one-author products is stagnating and the number of publications with two and three or more authors is increasing sharply. Fifty-nine countries had the most academic collaboration with Iranian researchers in geophysics field. Iran has collaborated more often with USA, England, and France. The international cooperation is much lower than the national cooperation. From 1996 articles were extracted 5304 subjects and Iran, Zagros, Artificial Neural Network, Fuzzy logic, Tehran, Inversion, Seismic attributes, Simulation, Resistivity, and Earthquake were the most important topics in the field of geophysics. In addition, it was found that most papers in the field of geophysics were in geophysical observation, instrumentation, and techniques.