فصلنامه فیزیک زمین و فضا
سال سی و هفتم شماره 3 (پاییز 1390)

In this research work the classification of the southern coasts of the Caspian Sea is performed using sedimentary and morphodynamic indices. This includes field study of morphodynamic characteristics of the shore structures. Field measurements include in situ samplings of sediments and actual observations of structures on site. These field activities were done along six transects in the dry coastal zones of Miankaleh, Sorkhrood, Nashtaroud, Anzali, Talesh and Astara regions. The sediments samples were taken from sea bed along 6 transects in these regions. About 48 sediment samples were taken directly as well as photographic observations of sea floor structures, using research diving facilities. The sediments were taken to the laboratory in order to find their materials and particle sizes. The sediment characteristics from all transects found by this method and observational data using direct photographic observations of morphodynamic structures were analyzed and presented on GIS maps. The GIS media can interactively acquire data from Excel files and help the analysis of the acquired results as tables and graphs. Results of the analyses show that different parts of these areas response differently to the hydrodynamic forces considering rapid sea level changes of the Caspian Sea in recent years. The results indicate that the beach area in these regions can be divided into 3 types regarding different flow regime conditions. Namely, low flow regime in the eastern part of the Caspian Sea Sothern coast (accretion beach), transition regime in the central part of Mazandaran and Gilan Provinces (intermediate beach) and high flow regime for the western part of Mazandaran coastal area (erosion beach).

Iran is one of the limited numbers of ancient countries which is almost totally located on earthquake belt. Earthquakes have always been the most important natural hazard in Iran. Many villages, cities, civilizations and monuments have been partly or totally destroyed by past earthquakes in Iran. As a developing country, Iran is expanding its cities, industries, dams, power plants etc. The recent earthquake in Japan showed the effect of an earthquake and tsunami on the nuclear power plants. After the failure of Park field earthquake prediction (based on probabilistic approach), we should think carefully about the importance of deterministic approaches for earthquake hazard assessment in Iran. Therefore, Iran requires mapping its earthquake faults and investigating the activity of faults as first step. We should define the zones and find the codes based on the real data and parameters. Slip rate is one of the most important parameters for natural hazard risk assessment. For slip rate determination we should measure the slip of the fault and the time that has taken for this slip to occur. Therefore, we require a suitable dating method. Meanwhile, Iran is arid, semi arid zone. These make luminescence as the most suitable method for dating past earthquakes, civilizations and environment. Luminescence dating can join studies related to the paleoclimatology, Paleoseismology and archeology of Iran. Optically stimulated luminescence (OSL) has been employed so far for dating the time of recent earthquakes and determination of the slip rate of some important earthquake faults in Iran (e.g., Fattahi et al., 2006; 2007; 2009; Fattahi and Walker, 2007). OSL directly dates the last time that quartz and feldspar in a sample has been exposed to light. Therefore, if we can find a sample that has been exposed to light during an event, we can date that event. The event can be an earthquake, Tsunami, volcanic eruption, sudden environment change and etc. Therefore, OSL samples should not be exposed to light during sampling and sample preparation. For this reason the suitability of the light of the sample preparation lab is vital. It is not possible to work in complete darkness, but dim red light with specific wave length can be employed for quartz preparation. Therefore, in the OSL sample preparation room in the Institute of Geophysics, normal red light which is available in the market, was installed and tested. For this purpose the spectrometer of red lamps with and without available filters were tested. The suitability of the dim light in the lab was also tested using Equivalent dose (De) estimate of well behaved quartz samples. Quartz grains were divided into different parts. One part was kept in complete darkness, the second was exposed to the lab light on the work plates and a third part was put in the fume cupboard. The Equivalent dose (which is the lab dose equal to the natural dose) of these three parts was estimated. Unfortunately, the Equivalent dose of grains that had been exposed to the lab light underestimated the natural dose. The result of all above mentioned experiments showed that the installed light was not suitable.

Permeability is a property of porous medium that quantifies rock capacity to transmit fluids. Frequently, core based permeability data are not available either because of the borehole conditions or due to the high cost of coring. For these reasons, over the years attempts have been made to estimate permeability by alternative ways. Permeability is an elusive parameter in hydrocarbon reservoirs as it is very difficult, if not impossible to determine precisely and directly from current subsurface logging technologies. In this research, an attempt is made to test some methods for estimating permeability as a function of depth from Nuclear Magnetic Resonance (NMR) logging in one of the carbonate reservoirs, bearing heavy oil, in the south of Iran. NMR uses hydrogen protons as an indicator of fluid presence. Not all nuclei possess the ability to interact with magnetic fields (magnetic moment); only those with an odd number of protons, such as hydrogen, possess magnetic moment. In calculating permeability from NMR logging in the upper Sarvak formation, three models such as average-T2, free-fluid and Swanson model have been used. Permeabilities obtained by these models are compared with core permeability and correlation coefficients are calculated which give poor results. It can be considered that the trends of permeabilities obtained by NMR models have good compatibility with core permeability, so they can be used for in-situ permeability estimation. A hydraulic unit (HU) is a reservoir layer or zone that has similar average rock properties affecting fluid flow. By using hydraulic units, the samples are grouped into distinct units with clear porosity and permeability properties. We are trying to consider the effect of using hydraulic units in obtained correlation coefficients. Hydraulic units can be determined from core porosity and permeability. This technique calculating the flow zone indicator (FZI) from the pore volume to solid volume ratio (?z) and reservoir quality index (RQI). Based on core porosity and permeability 3 hydraulic flow units for the desired interval were distinguished. The results obtained from hydraulic unit 3 cannot be reliable because the small amount of samples distinguished in this unit. For accurate permeability estimation, an Artificial Neural Network (ANN) model with two different sets of inputs is applied. In the first case, porosity obtained by NMR logging has been used as one of the input data but in the second case there is no NMR data as an input and core porosity has been used as one of the input data. The predicted permeability by ANN with both sets of input data is then compared with the core permeability. The results show that the correlation between predicted and core permeabilities is very good when the porosity obtained by NMR logging is used as one of the inputs of the ANN model. Using hydraulic units results in increasing obtained correlation coefficients for both NMR models and ANN model. Carbonate formations are more complex than sandstone formations. This is due to the broad range of pore sizes, complex pore structures and low surface relaxitivity values found in carbonate formations. Using ANN models will lead to better results compared with traditional NMR models because ANN models can consider complex relations between permeability and NMR parameters.

Over the past three decades helicopter-borne electromagnetic (HEM) measurements have been used to reveal the resistivity distribution of the earth's subsurface for a variety of applications. HEM systems include a “bird” or sensor containing one or more pairs of transmitting and receiving coils. The separation between the rigidly mounted transmitting and receiving coils of a coil-pair typically lies between 4 and 8 m. Because the distance between transmitter and receiver coils in the bird is much smaller than the altitude of the bird (typically more than 30 m), we can use magnetic dipole approximation for the transmitter coil. This approximation allows the ease of primary and secondary magnetic field calculations. The EM bird is towed under the helicopter to minimize the helicopter effects. The modern HEM systems use multi-frequency devices operating at 4–6 frequencies ranging from 200 Hz to 200 kHz. The receiving coil measures the voltage induced by the primary field from the transmitting coil and by the secondary? eld from the earth. As the secondary field is very small compared to the primary field, the primary field is generally bucked out and the ratio between the secondary and primary fields is presented in ppm. If there are good electrical conductors below the measuring line there will be electrical currents induced and give rise to a phase shift between the primary and secondary field. This means that the measured data is a complex quantity having in-phase and quadrature components. There are two classes of interpretation tools to apply to HEM data that provide information for use to better understand geological structures and processes. These are either direct transformation of data into a generalized half-space model at certain data frequencies, or inversion of multi-frequency data sets to prepare a layered (1-D) resistivity model of the earth. Transform methods have the advantage of yielding a single solution for the given output parameter, and the disadvantage that the output parameters may provide a poorly resolved image of the geology. On the other hand, inversion methods have the advantage of yielding a much better resolution for the given output parameter and the disadvantage that these methods are slower compared to transform methods. Inversion methods for the interpretation of HEM data for a layered earth are being employed more commonly for helicopter-borne surveys as the data quality is improved and as both the number of frequencies and computer speed are increased. A considerable number of papers exist on the inversion methods used to model the resistivity of a layered earth. These algorithms are useful in conditions where resistivity is locally uniform in the horizontal direction over distances comparable to the footprint of the transmitter. However, if the scale length of the structural variation is small, then differences between the 1-D and 3-D responses will be a problem for the 1-D inversion. The violation of the 1-D assumption may make the recovered models unreliable for interpretation in particular areas of the survey. However, due to the limited extent of the HEM footprint which is less than 200 m in general, one-dimensional inversion of HEM data is often sufficient to explain the data in areas where the subsurface resistivity distribution varies relatively slowly in a lateral direction. Here, we use simultaneously a number of frequencies in the transmitter. So it is convenient to use “EM sounding” in this work because each of these magnetic fields can penetrate to the associated depths of the ground. The inversion of EM sounding data does not yield a unique solution but a single model to interpret the observation is sought. Here we use Occam’s inversion which yields a model as simple as possible. To obtain such models, the nonlinear forward problem is linearized about a starting model in the usual way, but it is solved explicitly for the desired model rather than for a model correction. To obtain the best solution, we make an objective function which is composed of the norm of model as well as the norm of data differences, and then we minimize this objective function. Applying the Occam’s inversion on synthetic data, created over some 1D models with multiple sequences of resistive and conductive layers, shows that this method works well and the predicted models can be good approximations of synthetic models. The quality of results depends on the number of frequencies used. The more frequencies used, the better the results. Besides, as the value of frequencies increase, the penetrations of EM waves decrease and vice versa. So, removing a frequency of low value can affect the results in the higher depths, as is shown in the last two figures. Besides, the method does not need a priori information about subsurface structure. All the results are obtained without a primary model. This shows that the method is stable to recover conductivities. On the other hand, results reveal that the method can detect a resistive layer beneath the conductive one whilst the EM methods are more sensitive to conductors than resistors.

Tehran, Iran’s capital with a population of more than 10 million is located in the southern foothills of the Alborz collision zone. The Alborz mountain belt of northern Iran results from the collision of a piece of the Gondwana with Eurasia in the late Triassic (Sengor et al., 1988). The Alborz active mountain range which consists of several sedimentary and volcanic layers, with east-west trending mountain belt 100-km wide and 600-km long, is bounded by the Talesh Mountains to the west and by the Kopet Dagh Mountains to the east (Stocklin, 1974). 5±2 mm/yr shortening and 4±2 mm/yr left-lateral strike-slip motion in the central Alborz imply slip partitioning between strike-slip and reverse faults across the Alborz (Vernant et al., 2004b). The crustal structure of the Alborz is rather poorly known. Determination of the accurate velocity model for the shallow and deep structure of the study area is useful for routine event locations, and for a precise study of seismic activities and tectonics around the Tehran area surrounded by many active faults. The first crustal thickness variations computed from surface wave analysis of a few events by Asudeh (1982) suggested a crustal thickness of 45 km beneath the Alborz mountain range. Other crustal thickness estimations have been computed from Bouguer anomaly modeling by Dehghani and Makris (1984) for the whole of Iran. They showed that the Bouguer gravity along the Alborz mountain range varies between -100 and -120 mgal implying a crustal thickness of less than 35 km. Mangino and Priestley (1998), based on receiver function analysis showed that the crust in the southwestern and southeastern parts of the Caspian basin is 30-33 km thick and consists of a 10 km sedimentary section overlying a 15–20 km crystalline crust of Vp= 5.8 km s which in turn overlies a thin lower crust. Javan and Roberts (2003) applying the same technique on 20 teleseismic earthquakes recorded at seven stations of Iranian Long Period Array (ILPA) located to the southwest of the central Alborz estimated a crustal thickness of 46 ± 2 km for this area. They showed that the upper crust has a P-wave velocity between 4 and 5.8 km/s and a 14-km thickness, the middle crust has a positive P-wave velocity gradient from 6 to 6.4 km s down to ~30 km depth and a P-wave velocity gradient from 6.4 to 7.5 km s characterizes the lower crust in this area. Ashtari et al., (2005) using microearthquakes recorded by a temporary local seismological network operating for several weeks around Tehran in addition to data from permanent Tehran Digital Seismic Network (TDSN), investigated the velocity model for the region around Tehran. They used arrival times of 36 well located earthquakes that were recorded during their two temporary experiments and estimated that the crust consists of a very thin layer, 2-km thick (Vp~5.4 km s) over a 6 km thick (Vp~5.8 km s) both associated with the sedimentary layer. Based on their results the crystalline crust consists of two layers 4 and 22 km thick with P-wave velocities of 6.0 and 6.3 km s respectively. They estimated a depth of 35 km for the Moho discontinuity beneath the study area. Recent studies of Rajaee et al. (2007) based on receiver function analysis on the one data set belonging to the seismic temporary profile show that the crust in the southern parts of the central Alborz has a thickness of about 54 and 52 km respectively. This study indicates a small increase of crustal thickness (about 5 km) toward the southern flank on the central Alborz, consistent with Bouguer anomalies of Dehgani and Makris (1984). P and S receiver functions analysis by Sodoudi et al. (2009) using data from 11 permanent stations of the Tehran Telemetry Seismic Network reveals ~51-54 km crustal and ~90 km lithosphere thickness beneath the central Alborz. In this study the velocity structure beneath Tehran region was studied by 309 Teleseismic and 253 mining explosions data recorded in the Tehran City Seismic Network (TCSN), operated by Tehran Disaster Management and Mitigation Organization (TDMMO), from June 2004 to January 2007. Tehran City Seismic Network consists of 13 three component short period seismographs established in June 2004 in order to monitor the stress field and seismicity of Tehran city and its vicinity. Receiver function analysis of Teleseismic events which was recorded in the TCSN network shows Moho depth at 50 (km) southeast of Tehran. This Moho depth in this region reveals increasing Moho depth at the the southern border of the Alborz collision zone into the Central Iran block. Using 1D inversion of first P wave arrivals of mining activity (explosions) which were recorded in TCSN, we obtained two layers at very shallow depths with borders in 1 and 2 (km). Such shallow layers based on crustal velocity studies have not been seen in other Iranian regions like the Zagros. A better result could be achieved when the exact origin times and locations of explosions are reachable and if the explosions were fired bigger and recorded by a dense seismic profile.

Recordings of ambient noise or microtremors are increasingly used to find valuable information on soil in one dimension at a given site. Ambient vibrations, which are assumed to be mainly composed of surface waves, can be used to determine the surface wave dispersion curve in order to retrieve shear wave velocity profile. In this regard, microtremors are usually recorded simultaneously in an array of stations and they are processed in two steps; finding the dispersion (autocorrelation) curve and then inversing it to estimate the shear wave velocity profile. Microtremors are usually recorded in various apertures in order to get the spectral curves over a wide frequency band, and different methods also exist for processing the raw signals. The two most popular microtremor processing techniques are frequency-wave number (F-K) and spatial autocorrelation (SPAC). The SPAC method, which generally employs a circular array of stations and one central station, permits an in-depth understanding of the temporal and spatial spectra of seismic waves. Nowadays, it is widely used to estimate the structure of sub-surface layers and the shear wave velocities of sediments. In the SPAC method, the dispersion curves (phase velocity versus frequency) of surface waves are deduced by analyzing the normalized correlations between microtremors recorded at different stations. The dispersion curves are then used to characterize the structure of the medium. The method is based on a statistical analysis of the observed signal, which is assumed to be stationary and ergodic in time and space. In this paper to find reliable results in the processing of microtremors in shallow structures, the spatial autocorrelation coefficients are calculated for the vertical components of recorded signals using the MSPAC method and a new one (the revised SPAC method). Both methods are based on considering all possible autocorrelation pairs among the circumference stations. Their difference is that the new model considers all possible autocorrelation pairs among the circumference stations and makes an average on the calculated autocorrelations, on the other hand in the MSPAC model the pairs are put in different rings according to the distance between each pair. The deduced autocorrelation coefficients are then inverted. The results of applying the two models on real data are presented and compared. This comparison reveals that the results of both models are in good agreements with the site geology, although the new method expresses the Vs profile at depths smaller than 10 meters more successfully than the MSPAC method.

AN_EUL is a new automatic method for simultaneous approximation of location, depth, and structural index (geometry) of magnetic sources. In the 2D case analytic signal is defined as a conjugate function whose imaginary part is the Hilbert transform of its real part. Since the first vertical derivative of the magnetic field is the Hilbert transform of its horizontal derivative, vertical and horizontal derivatives of the magnetic field can produce an analytic signal function whose amplitude is equal to the root of the summation of square of the horizontal and vertical derivatives. Analytic signal has some useful properties. For 2D sources the amplitude shape of the analytic signal is an even and symmetric function whose maximum determines the location of the source. Moreover, the shape of the amplitude does not depend on the orientation of magnetization, strike, inclination and declination of the magnetic field. The Euler Deconvolution method is an automatic procedure to approximate the geometry, depth and location of the magnetic sources. In this method there is no need for reduction to the pole and remnant magnetization is not an interfering factor. The principle of the Euler Deconvolution method is based on the Euler Homogeneous differential equation. The AN_EUL method is a combination of analytic signal and Euler Deconvolution methods, and its main equations are derived by substituting appropriate derivatives of the Euler homogeneous equation into the expression of analytic signal of the potential field. AN_EUL equations are calculated at the source location that is approximated by the location of the maximum of analytic signal amplitude. In this paper, the AN- EUL method has been used for the determination of location, depth and structural index of 2D magnetic structures. At the first step, by using the forward modeling for some ideal 2D magnetic models, such as thin dike, thick dike and horizontal cylinder with given parameters, the synthetic data has been produced. At the next step, all of the required quantities in the AN-EUL method have been calculated for these series of data. In the final step, the depth and structural index of these models are calculated using the general formulas of AN-EUL and are compared with their real values. The levels of error and difference between the calculated values and real values of depth and structural index show that this method has an acceptable accuracy in approximating the structural index and depth of sources. Because AN_EUL equations use high order magnetic derivatives, the noises are amplified intensely; consequently for better resolution an upward continuation filter should be used. For some models like thick dikes, the analytic signal amplitude may have two maximums. For solving this problem the data should be continued to a higher level by upward continuation filter. In addition, since the derivatives are calculated by Fourier transform, it is necessary to taper the data before using this transform to avoid Gibbs effect. All of the computational steps in this paper, such as creation of synthetic data, necessary filters and the main equations of AN-EUL have been done by codes written in MATLAB.

In gravity interpretation, inversion algorithms have been used widely over the years, but as the potential follows the Gauss theorem, there are many equivalent source distributions that can produce the same known field. So to obtain a unique solution, suitable constraints should be introduced to the algorithm. During the last decades many authors have used several approaches to introduce a priori information into the inversion. Green (1975) found the model closest to the initially fixed model, Last and Kubik (1983) minimized the volume of the causative body, Guillen and Menichetti (1984) concentrated the solution about a geometric element, such as an axis. Li and Oldenburg (1996, 1998) used a constraint called ‘smoothness’ to find a model with minimum spatial variation of the physical property. Also they counteracted the decreasing sensitivity of the cells with depth by weighting it with an inverse function of depth. In this paper we have presented a method to interpret gravity data using a selection of constraints including minimum distance, smoothness and compactness that can be combined using a Lagrangian formulation. In this approach the earth is divided into a large number of rectangular prismatic blocks of fixed size where each block side is equal to the distance between two observation points and the problem has been solved by calculating the model parameters linearly (i.e. the densities of each block). Since the number of parameters can be many thousands, the linear system of equations is inverted using a conjugate gradient approach. The given weights to each block depend on depth, a priori information on density and the density ranges allowed for the region under investigation. A MATLAB-based inversion code for the presented method was prepared. The program uses a primary density model in the input file and calculates densities of blocks at each iteration. The program was tested on two different synthetic models. The first model includes two vertical dikes with different densities and the second model has encircled multiple bodies with different geometries and densities. The results on the synthetic models seem to be acceptable with a suitable convergence. The calculated density contrasts are according to the model contrasts and the horizontal boundaries are fairly reconstructed by the algorithm. Finally the inversion procedure has been applied on the real gravity data from the Golmandareh dam site (the north-eastd Khorasan, Iran). The computations show severe karsting of the area that makes the regional stabilization uneconomical and impossible.

The Stolt (f-k) migration algorithm is a direct (i.e. non-recursive) Fourier-domain technique based on a change of variables (or equivalently, a mapping) that converts the input spectrum to the output spectrum. The algorithm is simple and efficient but limited to constant velocity. A v(z)(f-k) migration method, capable of very high accuracy for vertical variations of velocity, can be formulated as a non-stationary combination filter that avoids the change of variables. In this article, we compare the efficiency of Stolt (f-k) migration (eq. 1) with two non-stationary filters based on v(z)(f-k) migration methods. (1) The result of applying v(z)(f-k) migration is a direct Fourier-domain process that for each wavenumber applies a non-stationary migration filter to a vector of input frequency samples to create a vector of output frequency samples (eq. 2). (2) The filter matrix is analytically specified in the mixed domain of input frequency and migrated time. It can be moved to the full Fourier domain of input frequency and output frequency by a fast Fourier transform. When applied for seismic traces the v(z)(f-k) algorithm is slower than the Stolt method but without the usual artifacts related to complex-valued frequency domain interpolation. We used two different schemes to consider the variations of velocity with depth. Vertical variations through an rms velocity (straight-ray) assumption are handled by v(z)(f-k) method with no additional cost. Greater accuracy at slight additional expense is obtained by extending the method to a WKBJ phase shift integral. We tested the efficiency of these methods on synthetic seismic records. Finally v(z)(f-k) method is applied to a real seismic section and the result are presented.

Using tidal potential, the effect of tide on the gravity field, crustal deformation due to tidal force, and gravity variations resulted from the crustal deformation are presented. Tidal potential is divided into constant and periodic (diurnal and semi-diurnal) constituents, and for each constituents crustal displacements in radial, South-North, and East-West directions are computed. The aforementioned computations, which algorithmically can be summarized as follows, are implemented in a software with the capability of computing the tidal potential and the resulting crustal deformation at any time and location: (i) Using right ascension coordinates (?,? ) of the Moon and Sun, and time, zenith angle of the celestial bodies is computed as a function of time and location on the surface of the Earth. (ii) Constant and periodic constituents of the tidal potential are computed for the given points on Earth surface at the given times. (iii) Crustal displacements caused by the tidal force in the radial, South-North, and East-West directions are computed. (iv) The computed tidal potential constituents and the related tidal displacements are presented in both graphical and tabular formats. As the case study, using the aforementioned software, tidal potential and tidal deformation of the crust at geographical region of Iran is computed. Among the practical applications of this study and the developed software followings are outstanding: (i) Removal of the crustal deformation due to tide from the Global Navigation Satellite System (GNSS) observations. (ii) Removal of direct tidal effect from gravity observations. (iii) Removal of the indirect tidal gravity effect due to crustal deformation from the gravity observations. (iv) Removal of the direct tidal effect from the geoid. (v) Removal of indirect effect due to crustal deformation from the geoid. (vi) Removal of the tidal effects from the height systems.

The main driving force of the earth atmospheric system is solar radiation. Radiation flux determines the surface temperature and impacts life on the Earth through photosynthesis. A quantitative knowledge of the earth radiation field is important to evaluate the atmosphere–surface interactions and the global hydrological cycle. Various atmospheric radiative transfer models have been proposed in order to compute radiation levels accurately. The Santa Barbara DISORT Atmospheric Radiative Transfer model (SBDART) is one of the plane-parallel multiple scattering radiative models which is used in this study. SBDART includes all important effective processes on the ultraviolet, visible, and infrared wavelengths of radiation. The model was developed as a software tool to compute radiative transfer in clear and cloudy conditions within the Earth’s atmosphere and at the surface. This model incorporates the DISORT discrete ordinate method, low resolution atmospheric transmission models and Mie scattering results for light scattering by water droplets and ice crystals. In order to use the model in the Middle East with its dry climate, we evaluated the model for estimation of the net surface radiative flux in the central desert of Iran. The observation data included latent heat, ground heat and net radiative flux during August to September 2006 in the region having the latitude of 32°N and longitude of 54°E. The data wed were from the heights of 1.5 m and 3 m. The evaluation of the SBDART on the 22 clear days during that period shows good agreement between the simulation of diurnal cycle of the net radiation flux and the observations. Since the model considers the ground temperature as a constant value, it is not able to capture the discrepancy of longwave radiation flux due to the significant difference between maximum and minimum temperature in the desert area. We have modified SBDART by implementing the diurnal cycle of ground temperature in the model to improve the simulation of the surface net radiation flux. The modified SBDART is used to study the effects of changes in water vapor, ozone and carbon dioxide on the radiative flux at the surface and in the atmosphere. Calculations are carried out for both upward and downward fluxes of shortwave, longwave and net radiation. To solve the radiative transfer equations, the required parameters are the optical thickness and asymmetry factor due to gaseous absorption, and Rayleigh scattering. They depend on the atmospheric profiles; total amount and distribution of water vapour, ozone, carbon dioxide and other gases and type and concentration of aerosols. In order to quantify the water vapour effects on shortwave and longwave radiation fluxes, we ran the model for the atmosphere with water vapour content of 1 g/cm2 and a dry atmosphere at 00:30 and 12:30 UTC. The differences between shortwave radiation fluxes in wet and dry atmospheres (for August 26th) vary from 5% at noon to 25% at sunrise and sunset. Moreover, longwave radiation flux in the wet atmosphere exceeds the flux in the dry atmosphere at all levels and reaches the maximum value of 67% near the ground level. A similar test was done to determine the effects of doubling the typical carbon dioxide value (360 ppm) on the radiation flux. The results show that downward radiation flux was raised by 2% and the upward flux decreased by 10% due to the increased CO2 level. Results also show that the net radiation flux in the atmosphere is greater for the double CO2 case, with maximum difference of 2% occurring at an altitude of 10km. Depletion of the stratospheric ozone as well as its increase in the troposphere cause significant impacts on UV irradiance and tropospheric chemistry. In this study, we have also addressed the effects of changes of ozone on the radiation fluxes, by doubling and halving the typical total columnar ozone concentration of 296 DU. Results show that the increased ozone decreases the upward shortwave radiation flux by 2.2% and the downward flux by 1%. The reduction of the ozone columnar concentration decreases the net radiation flux in the atmosphere above an altitude of 5 km, with the maximum decrease of 1.7% occurring at an altitude of around 30 km. In general, the results of this study show that the net surface radiative flux is most sensitive to variations in the value of atmospheric water vapor, carbon dioxide and ozone, respectively. Changes in the atmospheric water vapor highly impact the net surface radiative flux, while those of carbon dioxide and ozone lead to changes in the net atmospheric radiative flux, particularly between 10 km and 30 km above the surface.

Long-term rainfall prediction is very important to countries thriving on agro-based economy. In general, climate and rainfall are highly non-linear phenomena in nature giving rise to what is known as "butterfly effect". The parameters that are required to predict the rainfall are enormous even for a short period. Soft computing is an innovative approach to constructing computationally intelligent systems that are supposed to possess humanlike expertise within a specific domain, adapt themselves and learn to do better in changing environments, and explain how they make decisions. Unlike conventional artificial intelligence techniques the guiding principle of soft computing is to exploit tolerance for imprecision, uncertainty, robustness, partial truth to achieve tractability, and better rapport with reality. In this paper, we analyzed 38 years of rainfall data in Khorasan-e Razavi province, the northeastern part of Iran. Total precipitation from April to June over a period of 38 yeas (1970-2007) was selected as data of our interest in this research and the RUN TEST homogeneity was performed to find out if the rainfall data were randomly collected. Data of 38 stations including 4 synoptic, 10 climatology and 24 rain gauge stations (all belong to Iranian Meteorological Organization and Ministry of Energy) were selected for each year. Calculation of local average rainfall: The Kriging method is used to estimate the amount of local average rainfall. Data: The data used in this study are: 1) 38 Rainfall station data for the seasonal rainfall (Apr – Jun), a All of these stations are in the northeastern region of Iran. 2) Large-scale ocean and atmospheric circulation variables such as Sea Level Pressure (SLP) and the Sea Level Pressure difference in pre-rainfall months (Oct – March). These data were obtained from NCEP/NCAR Re-analysis data. These data sets span the period of 1948 – current, covering the globe on a 2.5*2.5? grid and available at http://www.cdc.noaa.gov NOAA website. Identification of Predictors: The aim in this section is to identify predictors for seasonal rainfall, which can then be used in forecast models. The two main requirements for any useful predictors are: (i) good relationship with the seasonal rainfall, (ii) reasonable lead-time (i.e. months to season). Our earlier work indicated that seasonal rainfall in the region is strongly correlated with predictors. So, the first step is to look for relationship with standardized predictors during the pre-rainfall seasons (Oct-March) and follow up with correlations between the rainfall and large-scale ocean-atmospheric variables (SLP, and SLP difference). This approach of correlation with large-scale ocean-atmospheric circulation variables is used to identify predictors for seasonal rainfall in the northeast of Iran Correlation with Large-Scale Variables: We would like to check predictors large-scale aspects and also the seasonal rainfall correlation with predictors such as SLP and SLP difference during pre- season rainfall (Oct-March). In this research, the correlations that are significant at 95% confidence level have been selected. Results showed strong relation between Sea Level Pressure (SLP) and sea Level Pressure difference (?SLP) changes with the rainfall of the studied areas. It can be concluded that meteorological signals may help us to predict the wet and dry seasons.

It is well known that, contaminant transportation is a major problem in coastal zones and has to be faced when coastal structures are being planned. Sea pollution not only causes environmental damage, but also impacts quality and population of sea resources. Oil is the most important pollutant, pollutants emanating from industries, ships, drilling and exploration in the seabed, ship sewage, toxic waste dumping, and civic sewer systems. Being alongshore the northern coasts of the Persian Gulf, Bushehr Bay is considered important in sea pollution due to the frequent sources of industrial and oil pollutants, ship transportation, and sewage and toxic waste dumping. Therefore, it is necessary to study and find the way the pollutants are dispersed along the bay. To do so, this study concentrates on physical and atmospheric factors affecting pollution dispersion. Bingchen Liang (2008), surveyed a hydrodynamic sediment coupled model COHERENS-SED, which has been developed by the first two authors through introducing wave-enhanced bottom stress, wave dependent surface drag coefficient, wave-induced surface mixing, SWAN and sediment model to COHERENS, and is modified through introducing a contaminant transportation model. They showed that the fields of current velocity and contaminant concentration obtained by the modeling of case with wave-induced longshore current are quite different. Using COHERENS, Mahmudi (1386) modeled pollution dispersion in the Persian Gulf. He proved that pollution dispersion in the Gulf is a function of flushing time and current movement at water surface and sea bottom. Since Bushehr Bay is an important area from aspects of economy, marine transportation, and environment, there is a high potentiality to disperse the pollution in different ways. Due to the prevalence of the tidal current in the bay, this study uses COHERENS to simulate the horizontal dispersion of pollution affected by tidal currents in the bay. Therefore, COHERENS, a hydrodynamic multipurpose 3D modeling system for coastal and shelf waters, has been used to model and survey dispersion of pollution in Bushehr Bay. The recorded data of the Marine Meteorology Station for a 40-year period, besides 4 major tidal components (M2, S2, O1, and K1) of the bay were used as the inputs of the model. When the model was adjusted and the data inserted, the model was run for the bay. After the model reached a stability point, tidal currents were validated with field observation which resulted in prediction of horizontal dispersion of pollution in different layers. The results show that dispersion is highly affected by tidal currents, and the results gained from the current field are in a good accordance with field observation of the bay. These results can be applied to predict the direction and dispersion of pollution and the ways to deal with them in the future.

The pattern of annual precipitation in developing areas and the related industries is known as one the most important infrastructure in such studies. This investigation is based on statistical analysis of the frequency of the total annual amount of precipitation using Empirical Orthogonal Function (EOF). The long time statistical studies support the effectiveness of the implemented statistical EOF in the area. Fuzzy logic is a new fold of logical reasoning that is estimated rather than a fixed and exact form. It has been developed to implement the concept of partial truth, where the truth value may vary between completely true and false. In this study, two concepts for fuzzification are implemented, the first one is based on Standardized Precipitation Index (SPI) and the other is founded on long term annual precipitation. These two concepts have been compared for analyzing the stability of extracted patterns of EOF on the area of interest. Investigation of the spatiotemporal pattern of annual rainfall in the Ghazvin province, as one of the most important developing area, is an important issue. This pattern may highly affect the future program for this region in the North West of Iran. This investigation is based on about thirty years of annual precipitation fifty rain gauge stations over the area of interest. The precipitation data from the Islamic Republic of Iran Ministry of Energy have been used. The first regionalization was implemented by means of the EOF method. The first extracted component described more than 80% of the total information on the annual precipitation over the area, and its spatio-temporal pattern was classified as one the most stable structures as well. In this paper based on Empirical Orthogonal Function (EOF) and its fuzzy form (FEOF), spatial and temporal behavior and stability of regional precipitation are investigated. Normal EOF is categorized as the linear decomposition method, but these new fuzzy weighted methods are classified as a class of nonlinear structures as well. EOF, FEOF and SPI was performed using "MATLAB" software. Finally, based on the linear and nonlinear spatio-temporal pattern recognition, the original space-time precipitation structure of the studied area has been evaluated. After extracting the most important space-time pattern of precipitation based on EOF and FEOF, the stability of the linear form was evaluated. These three approaches, EOF, FEOF based on SPI weight and mean annual precipitation, represent the whole information via their first component and their projected first spatial patterns depict is high compatibility as is possible because of the structure of long term rainfall over the studied area. These spatial compatibilities are presented in Fig. 5, Fig. 6, Fig. 9 and Fig. 11. The temporal variabilities of the first component are also showed in Fig. 12 to Fig. 14. These resulted patterns are investigated for considering the anomalous structure of rainfall. These resulted anomaly models are very similar and take a unique variation form and, this similarity may be explained as stable precipitation structure over the area of interest. The most important point in the space-time projections is the well-matched structure of the area DEM and first spatial component. This shows the impact of elevation on the configuration of space-time precipitation in this mountainous area. On the other hand, two spatial fronts of highlighted and intensive precipitation recognized in the projected first components may be taken as signs of two important rain cloud paths over internal of Iran as well. On the projected second spatial terms, both of linear and nonlinear methods, some local areas with high or low intensive precipitation can be concluded. But their spatial compatibilities are less than the first spatial components. Based on this comparison, the linearity of the space-time structure of precipitation over the Ghazvin province could be inferred.

A synoptic method based on stream analysis is applied to understand the governing mechanism of summer rainfall occurrence in the south of Iran. Based on this, the rainfall data of 152 stations of Iran were analyzed for a 33-year period (1970-2002). Investigating the spatial and temporal distribution of summer rainfall, a typical rainy region is recognized in the south east of Iran. It is found that July 1994 had the greatest and most widespread rainfall during the study period. In order to understand the circulation patterns causing the summer rainfalls in the south east of Iran, 6-hour, daily and monthly mean values of geopotential height, specific humidity and zonal and meridional wind components of the different atmospheric levels were obtained from NCEP/NCAR reanalysis dataset. Using the abovementioned dataset, the geopotential height, streamline, vector wind and relative vorticity composite maps, the hovmoller diagrams and vorticity cross-sections are produced and analyzed. Also, the monsoon depressions track is drawn for July 1994 and summer monsoon intensity is determined for the study period by using the WY, OLR and AISMR indices. Finally, their relationship with the summer rainfall of the south east of Iran is analyzed. The result showed that there is a triangular area in the south east of the country located to the east of 58:30 E and south of 28:30 N which has rain almost every summer. It is also found that the monthly and interannual variation of summer rainfall over the south east of Iran is in close relationship with the variation of summer monsoon intensity over India. The most humid period in southeast Iran, July 1994, is associated with the increased summer monsoon intensity, increased monsoon depression numbers over west India and the positive rainfall anomalies over India. Additionally, the upper and middle troposphere subtropical anticyclones over southwest Asia were stronger and experience the considerable north and eastward propagation. Conversely, the cyclonic circulation of the lower troposphere was significantly stronger. The results revealed that the eastward extension of the Iranian subtropical anticyclone at mid-troposphere and the associated increase of anticyclonic circulation over northern India and Pakistan are followed by the westward movement of monsoon depressions and their entering the Arabian Sea. In this case, the monsoon depressions by creating or strengthening the convergence centers over the south and south east of Iran have an important role in increasing the cyclonic circulation and precipitation occurrence. It is also found that Iran low is the main factor of moisture transport and the rainfall occurrence of 1-10 July 1994 in southeastern Iran. The formation of this low pressure in the north of the Persian Gulf, in addition to the increase of positive vorticity over the area, is the key factor in 5-10 July rainfalls of south eastern Iran, by making suitable southern winds over southeastern Iran and transporting the Oman sea moisture in a thin layer to the study region.

Geophysical fluids such as atmosphere and ocean often have stable density stratification; hence internal gravity waves are generated and propagated through them which are important in momentum and energy transfer in these media. These waves are also believed to generate layered structures in such media. Recently there have been numerous theoretical, experimental and numerical studies on the ways that these waves are produced and propagated, including the nature of these internal gravity waves. Density driven flows such as katabatic winds or cold air that flow over the mountain slopes, in stable atmospheric surface layer at night, and the movement of salty dense water over the sloped ocean bottom are examples of mechanisms associated with the generation of internal gravity waves that lead to energy transfer in these stratified regions with various vertical density stratifications. In the present work, a two dimensional fully nonlinear numerical model is developed for the simulation of a down slope flow in a confined stratified region. The governing equations are written in terms of vorticity and density as prognostic variables, and stream function as a diagnostic variable. A three level leapfrog time stepping method is used to advance the equations in time and a second-order centered finite difference scheme is applied for the spatial differencing of the governing equations. Numerical results are presented for the way that non-hydrostatic internal gravity waves are generated and propagated as a result of downslope flow in stratified confined region. In addition, numerical results are compared with some existing experimental observations. The results show that the shear layers in the stratified region is produced by the internal waves propagation. Typical vertical structures in the flow field and the number of layers in the stratified region are similar to that of experimental work. For example the number of layers due to the modal structure of propagating internal gravity waves is 6-7. The normal modes of such internal gravity waves, propagating vertically in stratified regions produce shear layers that may be responsible for layered structures in geophysical flows in nature.

The Madden Julian Oscillation (MJO) is known as the primary mode of large-scale inter-seasonal variability in tropical regions that affects equatorial and extra-tropical climates. It was characterized as a 45-60 day wave that develops over the tropical Indian Ocean and then travels east across the tropics at 5-10 m/s. The phenomenon has a frequency of 6-12 events per year associated with a period ranging from 30 to 60 days. In its active stage, the MJO is associated with increased convective activity over the equatorial eastern Indian and western Pacific Oceans. This study investigated the effects of the MJO on the occurrence of wet and dry events in Khouzestan Province, the south west part of Iran during November-April. Monthly precipitation data from eight stations spread over various parts of the province was analyzed during 1979-2005. By using two well-known MJO indices (MK and WH), the positive and negative phases of the MJO phases (enhanced and suppressed convective activity over the equatorial Indonesian region, respectively) were identified for monthly and seasonal periods. The MJO-precipitation composites associated with opposite phases of the oscillation were constructed on seasonal timescales. Eight sets of the seasonal MJO-precipitation composites were, therefore, constructed for every station. The non-parametric Mann-Whitney test was then applied to investigate if the precipitation mean during the MJO positive phase of each composite is significantly different from its corresponding value during the negative phase. Moreover, the ratios of, and were computed for each station for monthly and seasonal timescales. Since the ratio of is greater than one, precipitation is reduced (enhanced) in the positive (negative) MJO phase. Another examination was also performed to investigate if the frequency of dry or wet events was significantly associated with the occurrence of the positive or negative MJO phase, respectively. For conducting this examination, the events where precipitation amount was below or above the long-term average were first counted and considered as the frequency of dry or wet incidents, respectively. These frequencies were then put in a 2 by 2 contingency table to delineate the incidents of dry or wet events during each of the MJO phases. The Fisher Exact test was then applied to the constructed contingency tables. If the computed p was less than 0.05, the frequency of wet or dry events was significantly associated with the occurrence of the negative or positive phase of the MJO, respectively. The results were shown that, for all considered stations, seasonal precipitation during the negative MJO phase was significantly greater (from about 1.9 to 3.0 fold) than corresponding values during the positive phase. Furthermore, the applied Mann-Whitney test indicates that the mean values of precipitation during the positive phase are statistically less than the corresponding values during the negative phase. In other words, the precipitation is reduced (enhanced) in the positive (negative) MJO phase. Moreover, the applied statistical tests have proved that the frequency of wet or dry events is related to the prevalence of the negative or positive MJO phase, respectively. As the positive MJO phase was engulfed, the probability of dry events varied from 50% to 90%. On the other hand, the probability of wet events was found to vary from 55% to 80% during the MJO negative phase.

In this paper, fourteen MT stations along a profile perpendicular to the main geological structure were used in order to identify the geology of Sabalan geothermal field including the extension of the surface cap-rock and clay-cap layers. The MT data collected between 1-8192 Hz is of useful quality and provides good control on the surface layers in many areas. It means that reliable modeling should be possible to a depth of 1000 m depending on resistivity distribution. TE and TM-mode data and skew parameter show that the earth dimensionality differs from site to site, so we examined the 1D and 2D modeling along the profile. To have the best possible interpretation we used determinant data for 1D modeling and joint TE and TM-mode data in 2D modeling. The data was processed and modeled using an improved modeling method. One-dimensional modeling was performed using a forward operator based on reflection coefficient of the layers (Zhadanov and Keller 1998) and the two-dimensional inversion has been done by using a code from Siripunvaraporn and Egbert (2000).The resulting 1D and 2D models show a high–very low–low resistivity sequence with depth. The high resistive layer at the surface was assigned to basalt, andesitic and old trachyandesitic flows and other impermeable rocks that have thermal conduction and act as the cap-rock of the system. The role of the cap- rock is very important in sustainability of the system, because it prevents the reservoir from cooling by mixing with surface water. The second layer is a very conductive layer and is interpreted as the reservoir that has thermal convection and hot fluids contained in its fractures and pores. The resistive basement is a hot and solid magmatic intrusion and is interpreted as a heat source that produces a conductive heat flow towards the reservoir. As a result, the shallow resistivity model of the Sabalan area is in a good correlation with the geological features. It shows the common conceptual resistivity model which has been presented for the geothermal reservoirs.