Journal of the Earth and Space Physics
Year:2017 | Volume:43 | Issue:1 |Papers Count:18

Shear wave structure has been determined using data from a temporary network of 23 broadband stations in the north west of Iran. Waveforms have been used from 230 tele-seismic and regional earthquakes to obtain inter station dispersion curves of group velocity of the Rayleigh waves. Events in the epicentral distance range of 250 to 3000 km with magnitudes 3.0≤ Mw ≤ 7 were also used. The individual dispersion curves of group velocity of the Rayleigh waves for each source-station path were calculated; Then via double-station method we calculated 20 dispersion curves for inter station paths. The group velocities are available in the range of 6-48 sec; in general it is only possible to resolve the parameters of upper mantle and crust. We divided the study area to 5 regions, and then we calculated the average dispersion curve in each region. These curves were used to determine shear wave structure in each region via non-linear Hedgehog inversion method. We need the initial velocity model to start the non-linear inversion process, therefore initial model was calculated via linear inversion method. In addition, the obtained velocity models show that crustal thickness in these 5 regions varies between 40 and 56 km. Also the boundary between upper and lower crust changes between 12 and 28 km. The results from the non-linear Hedgehog inversion as applied to derived dispersion curves show a crustal thickness of approximately 40 km in the west part of study area, 56 km in the middle of the area and 43 km in the western coast of Caspian Sea. Based on the obtained results the Moho depth varies from 56 km to 40 km when you move from the middle of the study area to western coast of the Caspian Sea. We propose that under thrusting of Caspian Sea basement beneath the Talesh Mountains impresses Moho depth in Talesh zone. But no geological observation proves the under thrusting of Caspian Sea basement beneath the Talesh Mountains, therefore we cannot be certain about this proposal. On other hand, Talesh zone is located in passive continental margin of the Caspian Sea; these kinds of margins have complicated structure. We can assume that the observed results in Talesh zone have been created by passive continental margin of the Caspian Sea. Also we observed a low velocity anomaly in the range of 12-22 km depths beneath the Sahand volcano. We derived attenuation effects of south Caspian basin when periods are longer than 32 seconds of fundamental mode Rayleigh waves propagating across the south Caspian Basin. We also used 20 events along the Apsheron Sill and calculated the dispersion curves of these events at our stations. We collected 172 waveforms from the used events and found only 31 fundamental mode waveforms of Rayleigh waves. In other waveforms energy of fundamental mode was diffused and we cannot specify any trend for dispersion. The South Caspian Basin contains one of the thickest sedimentary deposits in the world. In the South Caspian Basin, based on Priestley et.al. (2001), attenuation of surface waves is largely controlled by sediments in the basin. Therefore we guess that our observations about attenuation of the Rayleigh waves are related to sediments in this basin.

Amplitude and duration of seismic signals depend on recording distance, propagation path of the wave through different media and geology at the recording site. In addition, amplitude of recorded signals varies according to the P- and S-wave radiation patterns. Influence of these factors on seismic signals has been considered for magnitude computation in many seismic regions (e.g., Michaelson, 1990 and Eaton, 1992). Estimation of earthquake magnitude is a routine task in all seismological observatories. …

The economic and social vulnerability of urban areas to seismic risk, because of the heavy tolls caused by earthquake, is very noticeable. Since it is not possible to accurately predict the earthquake occurrence with our current knowledge, then an Earthquake Early Warning System can significantly reduce and minimize the possible death toll. Using CDF (Probability Cumulative Distribution Function) this study aims at investigating the extent to which this Earthquake Early Warning System is implemented for the North Tabriz Fault so as to predict the time of On-Site warning time and Regional warning time in a probabilistic manner. To find out the areas and cities subject to risks of earthquakes, by earthquake simulation using a stochastic method, the peak ground motions of the earth (PGA) were calculated for the cities of northwest Iran. By the results of these calculations, high- priority areas were examined in this study.15 of the top priorities in terms of seismicity on the basis of strong ground motion (PGA) nature, cities such as Khoy, Varzaqan, Sarab, Tabriz, Qarah Zia od Din, Amand, Tekmeh Dash, Osku, Damirchi, Bostan abad, Sufian, Heris, Avin and Khvajeh were considered based on our study. The result of this study shows that the maximum Regional warning time in the cities of Khoy, Qarah Zia od Din, Avin, Bostan abad, Heris, Khvajeh, Sarab, Tekmeh Dash, Varzaqan, Damirchi, Tabriz were 19, 20, 21, 13, 17, 12, 19, 14, 15, 18, 10 seconds respectively. Due to the fact that for the stations with enough distance to the epicenter of the earthquake, the creation of Regional warning time only for distant cities is possible and implementable. The On-Site warning time for earthquakes close to the targets was also measured, as already was clear, it is not possible to establish considerable On-Site warning time for high-risk areas for North Tabriz Fault. It seems that this amount of time (Regional warning time) to set up Earthquake Early Warning Systems in the city of Tabriz where it is the fourth largest city of Iran and has about 1.4 million inhabitants and one of the largest Iranian industrial cities, the Regional warning time is under 10 seconds which in terms of economy, cost, time and energy, according to the existing station arrangement, will not be economical and vital. It has to be mentioned that the warning times were calculated using the existing seismic network geometry in the region. Here we have only calculated the warning times to at least some of the affected population and cities (15 of the top priorities in terms of seismicity on the basis of strong ground motion) in damaging and destructive earthquakes.

In this study, the effects of Earthquake on the excitation of polar motion and the changes in the length of day are investigated. To do so, at first the deformation resulting from Earthquake is computed and then, its effects on the polar motion and length of day are derived. The geodynamic model which determines the crustal deformation is Dahlen's model in which the effects of Earthquake deformation is coupled with the rotational motion of the Earth. For this purpose, it is assumed that the Earth is a spherical symmetric, isotropic, elastic and homogeneous media and the Earthquake is caused by the dislocation discontinuities on fault surface. In this case, the solution of the corresponding boundary value problem determines the deformations of the Earth due to the Earthquake. On the other hand, the rotational motion of the Earth as a deformable body is governed by the Liouville equation, which determines the motion of polar axis under the applied external torque. Since the polar motion is investigated, only the homogeneous solution of the latter equation must be determined. In this case the solution of Liouville equation is only dependent on the moment of inertia of the Earth. Since, the components of the inertia tensor of the Earth are dependent on the shape of the earth and its density distribution, and in this case, the Earth undergoes a shape change, therefore, its moments of inertial are no longer constant and depend on the deformation of the Earth. By computing the deformation results from the Earthquake as discussed at the first step, one may derive shape change and changes in the density distribution of the Earth from which, the changes in the component of inertia tensor may be obtained. Finally, the changes in the inertial tensor through Liouville equation can lead to the excitation of polar motion or the variations in the length of day, which is determined by the solution of the corresponding equation. The results of simulated problems in two cases of strike-slip and dip-slip faults reveal that the amplitude of excitation due to strike-slip fault is maximum at equator and decrease toward poles and it is zero at the pole. However, in the dip-slip fault, the amplitude at mid-latitude regions is maximum and is zero at both equator and poles. The variation in the length of day is zero at poles and is maximum at equator for strike-slip fault. For dip-slip fault, it is zero at both equator and poles and is maximum over the mid-latitude regions. Moreover, using the geometric parameters of the large Earthquakes from Harvard Earthquake Catalogue, occurred during the period of 1976 to 2014, their effects on the polar motion and length of day are studied within the adapted geodynamical model. The results show that among the selected Earthquakes, the 2011 Japan Earthquake had had the most significant effects on the motion of polar axis and the length of day. This excitation is in westward direction. The combined impact of all Earthquakes is also computed which clarifies that the polar excitation is increased in the X direction (prime vertical component) and decreased in the direction of Y (meridian component). For the validation of our results, we use the data of IERS (International Earth Rotation Service) which shows a relatively good agreement.

Nowadays there are many attempts for exploring stratigraphic traps all over the world. Because of existing Sarvak reservoir rock Formation in central Persian Gulf which consists of carbonate with various lateral changes in the terms of lithology, there is high probability for information of these stratigraphic traps in this region. The main aim of this research is to recognize the oil and gas stratigraphy traps using seismic attributes and petrophysical and geological logs in the Bahregansar oil field, NW of the Persian Gulf basin. In order to reconnaissance these regions, petrophysical logs (density, acoustic, neutron and gamma) and seismic reflection data from three wells have been studied. On the other hand, the obtained data have been interpreted with some seismic volume attributes such as momentary frequency, domain and acoustic impedance, reflection coefficient, normalized amplitude and envelope amplitude attributes to show the situation of hydrocarbon basin in the study area. By using seismic attributes with geological information we can infer reliable interpretation for some following reasons. The first reason is seismic velocity that allows us to understand the situation of lithology, fluid content and abnormal pressure or temperature. The second reason is lateral amplitude changes that permits the inference of geological situation such as changes in porosity, existence of hydrocarbon and thickness of lithology. The third reason is seismic trace morphologies or interpretation sections that allows us to recognize depositional environments or faults and fractures. Finally, changes in seismic waves directions that permits to deduce velocity anisotropy, or fracture orientation. The software which was used in this study was Petrel. The density log is created using neural network method by application of well No.3 in this oil field. The petrophysical study of gamma log shows well identity of formation boundaries in sections. Also the use of cross plot graph of density-neutron logs applied to well recognized the efficient zones in Gurpi-Ilam, Sarvak and Kazhdumi-sand Formation. The Turonian epirogenic event is caused erosion at the top of the Sarvak Formation and on the other hand Santonian epirogenic is caused hiatus stratigraphic trace in the lower part of Gurpi and Ilam Formation. By the seismic volume attributes interpretation a number of the stratigraphy traps were detected over some seismic sections. Furthermore, recognizing the main fault which exists in the western part of Hendijan oil field has the main role in changing of lithological effect in continuity quality of seismic reflection. In order to increase the interpretation accuracy, some seismic inversion has been made on considered sections and the obtained data were compared with the petrophysical logs and seismic attributes. By doing the interpretation of sections, two type of stratigraphic traps were recognized. The first type is oil trap related to the top of Turonian unconformity (truncation) which exists in the eastern part of the fault. The second is relation to narrowing part which belongs to the above of the reservoir layer (pinch out) under Turonian unconformity in the western part of seismic section. Meanwhile the study shows that there is an oil trap as hydrocarbon accumulation in the upper part of Kazhdumi sand formation seismic subunit that acts like stratigraphy trap in the above unconformity. In general, all of oil traps recognized in this study were composed of anticline structural dip and on the other hand existence of faults has the main role in geological structure in this region. The obtained results clearly demonstrated the shape and the geological situation of the existing structural traps in the studied area.

Interpretation of potential field data generally is quantitative or qualitative. An important factor in the issue of interpretation is how much interpreter is confident on data that provides the information needed to achieve the objectives of the study. Reliance on interpretation can be increased by the use of effective methods for parameters determination of causative sources. Although do most methods do not require knowing the density or susceptibility contrast, but these methods are based on the assumption that the source is a certain type (horizontal slab, vertical dykes, etc.) and two-dimensional. By selecting the wrong type of source, large errors may occur. Despite all these problems, numerous automatic techniques are designed that can be applied over the magnetic or gravity anomalies to quickly estimate the depth of the sources. Curvature method is used to analyze and interpret the potential field anomalies. Potential field anomalies can be transformed into special functions that formed peaks and ridges over isolated sources. All of these special functions have a mathematical form over sources that lead to a common equation, to estimate the depth of the source from the peak value and curvature at the peak. Curvature attributes that are used in this case are mostly negative curvatures. Special functions are divided into two categories: Model-specific special functions and Model-independent special functions. Model-specific special functions are usually calculated from a transformed potential field for locating the specific sources such as a vertical magnetic contact, vertical density contact, etc. The horizontal gradient magnitude (HGM) and observed potential field (absolute value) are two types of model-specific special functions that forms ridges over specific sources. Model-independent special functions are used to calculate locations of various types of sources from the observational or modified potential field. Total gradient (TG), also called the analytic signal, and local wavenumber (LW) fall into this group. Usually, special functions need that the potential field undergoes a transformation, such as reduction-to-pole and vertical derivative. For gridded data, eigenvalues of the curvature matrix associated with quadratic surface is fitted to a special function within 3×3 window, to locate and estimate the depth of sources. Another curvature attributes is shape index that quantitatively stated the local shape in terms of bowl, valley, flat, ridge and dome. Shape index attribute (SHI) and geometry factor provide a way to easily reject some of invalid estimations. In this study, method of curvature attributes has been applied on noisy and noise free synthetic data using Model-specific (HGM and absolute value) and Model-independent special functions (Total gradient and local wavenumber). Finally, this method was tested on real data from Mobrun massive sulfide ore of Canada using special functions of two models and a structural index (SI) from local wavenumber special function for a mine was estimated. The results of estimating the depth by this method had a good match with the results of the boreholes. Finally, the depth results of this method were compared with Euler deconvolution method, which shows that the method of using curvature attributes is more accurate in depth estimation.

The regions of northwestern Iran, eastern Turkey and Caucasus are the most intriguing regions of the Arabia-Eurasia collision. It is a pure intercontinental collision zone with the highest elevation in western Asia. This region is known for a spatial separation of sub-parallel thrusts and strike-slip faults. Iranian plateau includes two major mountain belts, Alborz in the north and Zagros in the south and west of Iran. Azerbaijan includes Alborz mountains, Talesh and Lesser Caucasus along with mountains in the Azerbaijan plateau. Azerbaijan is between the two great mountains of Caucasus in the north and Alborz in the east and a distance away from Zagros in the south. A lot number of faults including Tabriz fault and Aras fault meet in the west of the study area. One of the most fundamental and important new area of research in geodesy is earth surface deformation modeling at local and global scales. Also, study of the effective factors in deformation, and various computation methods in order to determine the movement of the earth's crust are considered as recent developments in geodesy. In recent years, space geodetic techniques with high precision and reliability have provided new sources of information to determine the geodetic positions. This information is used for the detection and quantification of surface deformations. In this paper, Novozhilov method has been used for mean rotation calculation with finite difference approach on earth surface in N-W of Iran, especially north Tabriz fault. To achieve this goal, linear strain and rotation tensors on earth surface based on shell theory in continuum mechanics are calculated using finite difference approach and then the mean rotation is extracted using linear strain and rotation tensors. The used finite difference method is a numerical method based on mathematical discretization of the equations of boundary problems. By using this method, the continuous process is studied in a finite number of sufficiently small time intervals. Small intervals, the function are approximated by approximate expressions. In each interval the results of integration in the previous interval are taken as initial conditions for the next time interval. In the fourth decade of the 20th century Novozhilov obtained a measure of the mean rotation by modifying a previous definition produced by Cauchy. In the literature, this measure has been named Novozhilov's mean rotation measure ever since. The measure introduced by Novozhilov for the mean rotation indicates the importance of the infinitesimal rotation tensors. The results obtained from the linear strain and rotation tensors that are computed using geodetic observations (GPS) in 2005, have good agreement with the results of previous work. The resultsof Novozhilov’s mean rotation criteria in the part of the Azerbaijan plateau shows that the highest right turn rotation is related to YKKZ station (2.975±0.631deg/Myr). An important feature of Novozhilov’s mean rotation analysis on earth surface different from the analysis of this parameter in Cartesian system is that the results of this measure on earth surface is very close to the results of previous studies on blocks rotation in different areas in Iran. Accuracy of this measure on earth surface is acceptable in most parts of the case study.

Magnetic survey data are generally used to map faults, geologic contacts and magnetic ore bodies. The spatial distribution of magnetic sources is usually determined during the mapping process. Variation in depth, magnetization and geometrical parameters generate magnetic anomaly waveform. Direction of the remanent and induced magnetization vector also affect the shape of these waveform. A magnetic anomaly waveform, includes amplitude, phase and wavelength. Putting these parameters altogether makes the interpretation of the magnetic data a difficult task. There are different useful methods for interpretation of a magnetic map. Generally, these methods are based on reduction of data to a simpler form, so that the edges and center of the causative bodies are determined easily. In the recent years many methods have been used to balance the difference between various anomaly amplitudes. Each method is designed to determine a specific parameter of the magnetic anomalies. Using local phase filters are being common in potential field data interpretation. They are high-pass filters based on horizontal and vertical derivatives, such as total horizontal derivative, tilt angle, theta map, etc. Edge detection of a magnetic structure is one of the most important task in the interpretation of magnetic data. For this purpose, in this research we have used two local phase filters: Tilt angle (TDR) and Total Gradient of Tilt angle (TAHG). As stated, tilt angle filter is used in determining the boundary of source anomaly. It is relatively less sensitive to the depth of the source, so, it can resolve shallow and deep sources as well. As tilt derivative is a function of the ratio of the vertical and horizontal derivatives of field intensity, it does not contain information on the strength of the geomagnetic field nor the susceptibility of the causative bodies. The peaks of tilt angle amplitude should be located over the center and its zeros over the edges of the source body. It strongly depends on the inclination of magnetic field. Another enhanced method we have used in this study for determining the boundaries of the structures is the horizontal gradient of tilt angle (the TAHG). It is defined by taking the arctangent of the vertical derivative of the horizontal gradient, divided by the modulus of the horizontal gradient. TAHG equalizes the signals obtained from the shallow and deep sources. Its notable features are that it produces amplitude maxima over the source's edges, gives suitable resolution and is less dependent on the depth of structures. Like the TDR, this method depends on the inclination of magnetic field. We applied these methods for synthetic noise-free and noisy data. Preparing the total magnetic responses of synthetic models as well as edge detection calculations have all been done in MATLAB. In comparison with common methods like horizontal gradient and analytic signal, it delineates the edges of source bodies more efficiently and accurately. Furthermore the TAHG method has better resolution in determining the boundaries of deeper sources than the TDR method. We applied the stated algorithm, on real data. The aeromagnetic dataset from Zanjan region was selected to be used in the TAHG method. The Zanjan depression is a narrow and continuous igneous basin, located in the north western Zanjan province. There are many young active and basement faults in the study area. Total magnetic anomaly map of the region, shows two major structural trends in NW-SE and NE-SW, respectively. By applying the two different edge detection algorithms we obtained the hidden boundaries of the basement which is not detectable in the geological maps because of the thick sedimentary covers. The results show that TAHG method is suitable for determining the basement faults and boundaries, as well as mapping the contacts of magnetic units.

A reliable analysis of magnetic data is the correct estimation of the causative sources to plan for drilling to achieve the targets. This paper presents enhanced local wave number (ELW) method for interpretation of the magnetic data. ELW method has been proposed during the previous decades and is based on the analytic signal to estimate the location and depth of the anomalies without having any knowledge about the geometry and magnetic susceptibility of the source. Final equation in this technique, is based on the depth and position and is independent of the structural index. The normal solution of this equation is obtained by assigning ELW kx and kz (the local wave number with respect to x and z) for different values of x and heights of continuation; z within a window is centred with the peak of the analytic signal amplitude. A problem of over determined unknown parameters can be solved through a standard technique, as using the least squares approach, therefore, the Golub algorithm is used to solve a set of linear equations. The ELW technique requires computation of horizontal and vertical derivatives of the first and second orders. Due to this characteristic, any high frequency noise present in the data gets substantially enhanced, masking the response from a target. To restrict the high frequency response, a window function is designed on the basis of the maximum frequency computed from the work of Agrawal and Lal (1972). After finding these quantities the method can approximate the structure index. Although, an appropriate Matlab code for the method is introduced and tested on two dimensional synthetic data before and after adding noises. There is a peak in the curves of analytic signal and kx of ELW and also a turning point in the curve of kz of ELW which shows the position of anomaly. Existence of these features shows that final responses of ELW method are correct. Synthetic data produced from a dyke like body with dip, magnetization, declination, inclination, depth and thickness are 45º, 1 (𝐴𝑚⁄), 10º, 64º, 10m and 5m respectively. The ELW method has had reasonable responses for noises with different amplitudes up to 20nT and for noises with amplitude more than 20nT, ELW method loses its efficiency. Then, the method is tested by applying it on the real data of Golbolaghi area in Zanjan, and the results are compared with the results obtained from Model vision software. To do this a 525m profile is used. At the end, the depth and structure index are obtained as about 4m and 0.8, respectively using ELW method; also the depth is estimated at about 4.4m using model vision software. It is worthy to note that the depth of anomaly has been reported 4.5m by drilling. The parameters obtained from the introduced method for the anomalies show that the enhanced local wavenumber method and its introduced Matlab code can be a powerful tool in the studies of local anomalies. Because this method is automatic and quick, it can be used for large data sets like vast area or airborne data. This method is also used on airborne data of Damghan region in another paper.

The lack of reliable and updated precipitation datasets is the most important limiting factor in studying many climatological and hydrological topics including climate change and temporal variability of precipitation in many data sparse areas around the globe. This is particularly valid for Iran that encompasses vast deserts and un-settled hyper-arid climate areas (central-eastern Iran) that hinders establishing an adequate network of rain-gauge stations required for climatological studies. Similarly, the high elevation areas of mountainous regions of western and northern Iran suffer from limited representative stations. Using the gridded or reanalysis precipitation datasets could be one of the possible solutions to overcome this obstacle; knowing that the representativeness of these datasets that has been already proved for many different parts of the world. Amongst many available gridded precipitation datasets are the Global Precipitation Climatology Center (GPCC) and the Tropical Rainfall Measuring Mission (TRMM) that have been widely used in many researches; indicating their accurate estimation of precipitation values and intra-annual variation for the regions studied. The reanalysis precipitation dataset which is a product of the Numerical Weather Prediction (NWP) models is an alternative source of precipitation data that is widely used in the literature and many authors have pointed to the relatively accurate precipitation prediction of reanalysis for many parts of the word. The two widely used reanalysis datasets are NCEP/NCAR and different products of ECMWF, namely ERA-15, ERA-40 and ERA-Interim reanalysis. ERA-Interim which is used in the present study is produced with T255 spectral resolution (about 80 km) and covers the period from January 1979 to present, with product updates at approximately 1 month delay from real-time (Dee et al., 2011; Balsamo et al., 2015). The ERA-Interim atmospheric reanalysis is built upon a consistent assimilation of an extensive set of observations (typically tens of millions daily) distributed worldwide (from satellite remote sensing, in situ, radio sounding, profilers, etc.). To develop the reanalysis, the analysis step combines the observations with a prior estimate of the atmospheric state (first-guess fields) produced with a global forecast model in a statistically optimal manner (Balsamo et al., 2015). The representativeness and performance of ERA-Interim in forecasting precipitation amount at 45 Iranian synoptic stations distributed across the country is herein examined. Spatial resolution of ERA-Interim dataset used in this study is 0.125 × 0.125 in latitude and longitude. For each station, the closest grid point of ERA-Interim to the station coordinates was chosen for a statistical comparison analysis. To evaluate the performance of the considered dataset when compared to the observed precipitation records at the considered locations we have used R squared, the Nash–Sutcliffe model efficiency coefficient (EF), RMSE, Bias, B slope of the regression and the standardized RMSE indicators. The performance of the dataset was also graphically represented through scatter plots of the established regression between ERA-Interim and observation at the selected stations. The results of the statistical indicators were represented through plotting the indicators over the map of Iran to ease displaying spatial tendency of the indicators and explaining the possible geographical role in controlling the spatial variation of the indicators. The results indicate that the ERA-Interim performs well in majority of the studied stations with strong correlation coefficient. However, it was found that the ERA-Interim underestimates precipitation in most of the stations located in the coastal areas of the Caspian Sea as well as in some stations along the Persian Gulf and the Oman Sea, suggesting that ERA-Interim is somewhat inefficient in adequately forecasting precipitation in the coastal areas; very likely due to not properly taking into account the complex topography of the region in its model parameterization or not being able to adequately differentiate between land and sea characteristics for the stations very close to the sea. It should be noted that the ERA-Interim is less efficient in accurately forecasting extreme precipitation in the Caspian Sea region. Nevertheless, we found very high agreement between observations and ERA-Interim in this region when some extreme precipitation events were excluded from the analysis. Contrarily, the results suggest an over-estimation for most of the stations located in northwestern and northeastern mountainous areas of the country; once again due to perhaps improper representation of topography of these regions in the model.

Based on the report by Islamic Republic of Iran Meteorological Organization (IRIMO) published as part of a greater report on the state of the world climate in 2011 by the American Meteorological Society (Blunden and Arndt, 2012), large parts of Iran, from central to northern and northeastern areas, have experienced significant negative anomalies of surface temperature together with positive anomalies of precipitation in autumn 2011. The temperature and precipitation anomalies have been determined with respect to the climatological mean values over the period 1960 to 2010. As the establishment of a prolonged period of cold weather in Aban 1390 (23rd Oct. to 21st of Nov.2011) together with abundant precipitation in the form of both rain and snow played a great role in shaping the climate anomalies of autumn 2011 in Iran, this study aims to investigate the large-scale dynamical processes involved in the climate anomalies of this period. Such studies are particularly important, when the increase in the frequency of extreme climate anomalies in recent years and its possible link with global warming is noted. To this end, the NCEP/NCAR reanalysis data are used for the concerned period and the long-term mean fields (from 1950 to 2010). The main analysis tools used are the analysis of the anomalies of geopotential height and temperature in the lower and middle troposphere, jet speed and relative vorticity in the upper troposphere, the computation of the blocking index (BI) introduced by Wiedenmann et al. in 2002, and the energy diagnostics. The latter includes the eddy kinetic energy, ageostrophic geopotential flux and its convergence, total flux and its convergence, baroclinic generation, baroclinic conversion, and barotropic conversion. The results for the year 2011 indicate the action of two consecutive blocking systems, which extended their central ridges over Europe with their troughs stretched over the North Atlantic and the west of Asia. The two blocking systems were peaked in the 3rd and 21st of Aban 1390, with respectively moderate and high intensities as measured by BI. In addition, the obtained results show that a branch of Siberian high-pressure system extended to the west of Asia associated with a positive relative vorticity anomaly in the north of Iran, lead to vigorous cold air advection to the North and Northwest of Iran. The increase in eddy kinetic energy over a band stretched from the North Atlantic to the Mediterranean and Black Seas in Aban 1390 was associated with an increase in the strength as well as the zonal and meridional extensions of the subtropical jet. Concerning energy diagnostics, the positive anomalies of the ageostrophic and total flux convergence over Iran indicate that the country was a favorable region for receiving large amounts of energy. Also, the flux vectors demonstrate that the main passage of this energy to Iran was through a north–south extent that included an emission area over the Black Sea. This was further confirmed by the analysis of baroclinic generation, which showed a positive anomaly over the Black Sea. The analysis also shows that the low-frequency phenomena and teleconnection patterns, including the positive phases of the North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO), and the positive phase of the East Atlantic–West Russia (EA–WR) may have played a part in shaping the climate anomaly over Iran in Aban 1390.

                Tidal observations have been widely used for a variety of applications. Realistic functional and stochastic models of tidal observation are then required. The functional model is complete if one knows the tide characteristics such as tidal frequencies (M2 and S2 for instance). The stochastic model is complete if we know noise characteristics of tidal observations. There is always a prediction error between the predicted values and the observed tide heights. This can be investigated when taking the noise characteristics of tidal time series observations. Functional model identification is however the subject of discussion in the present contribution. Tidal data are frequently used for different applications such as safe navigation. Real tidal gauge data can be expressed by their tidal constituents (frequencies) and a noise structure. Using tidal frequencies and tidal observations one can employ the functional model to predict tide. Therefore identifying tidal frequencies is an important issue for tidal analysis. So far, most of the available methods to determine tidal frequencies have been based on theory, and sea level height observations have not seriously been used to extract tidal frequencies. The theory-based methods usually apply the ephemeris of Moon, Sun and other planets to extract tidal frequencies without the use of tidal observations. Following-up the study by Amiri-Simkooei et al. (2014), we further focus on extracting tidal frequencies using tidal observations. For this purpose, we apply the least squares harmonic estimation (LS-HE) to the multivariate tidal time series. As a generalization of the Fourier spectral analysis, LS-HE is neither limited to evenly spaced data nor to integer frequencies. We may also note that the main tidal constituents may change from one area to another area. In this contribution, we use the data sets of eight coastal tide gauge stations in the Persian Gulf and Oman Sea between 1999 and 2010 with a sampling rate of 30 min using a multivariate analysis. In multivariate analysis, the frequencies contributed in tide structure are more obvious than in the univariate analysis. Such signals can thus simply be detected in the multivariate analysis. Using the above-mentioned data, 414 main tidal constituents have been extracted. Our extracted lists of frequencies (of the Persian Gulf and Oman Sea) are compared with the two lists of frequencies consisting of 50 and 121 frequencies by the study of Amiri-Simkooei et al. (2014), which was applied to UK tide gauge stations. In the present contribution, new frequencies that belong to the tide gauge stations of the Persian Gulf and Oman Sea have been identified. Finally, a six-month prediction is performed for all stations using the two lists of main frequencies obtained in the two studies. The prediction results of the two studies are then compared using the estimated root mean squared error (RMSE). The RMSE difference of our predicted data show a reduction ranging from 2 cm to 7 cm compared to that predicted using the frequency lists of Amiri-Simkooei et al. (2014). The estimated RMSE of tide prediction using the frequencies obtained in this study ranges from 9 to 16 cm.

For calculating the acoustic pressure due to sound propagation at sea using usual methods (pressure variations signals), knowing the density distribution and consequently, changes the speed of sound in the environment is very important. Many environmental factors affect the distribution of the density at sea, depending on environmental conditions and geographic locations and the weaknesses of each of them are different. One of them is internal waves which usually cause temporal and spatial changes and consequently affect the acoustic wave propagation in the ocean. Internal waves can be generated by tidal currents over sea floor sloping that is very common in the stratified oceans. Results of study in some researches showed that internal waves can affect the sound waves in two ways: 1-Internal waves can decrease sound level up to 25 dB due to sound mode coupling in an exact frequency.2- Internal waves can focus and defocus sound waves because of sound speed fluctuation. The purpose of this study is a laboratory investigation of internal waves caused by oscillation of a cylinder in a stratified glass channel with 3 meters long, 0.5 meter width and 1 meter height, on the sound waves propagation. In this study, using the double bucket and filling box method for generating stratification that is measured by one pair of salinity and temperature meters fixed on a rail that can move up and down. Using the usual methods of setting up internal waves and using acoustical transducers in 53 kHz frequency, internal wave's effects on the propagation of sound waves, were investigated. In this study with usual optical method (Synthetic Schlieren) the internal waves generated in the tank can be detected. In this method internal wave generated in the glass tank change optical index of water layers and cased deviation of the image straight lines designed on the back of tank. Laboratory results showed that sound waves can be focused and defocused due to the normal modes of internal waves. Some 9 experiments were done mainly in cases with vertical linear density stratified fluid. As the modal structure of internal waves in the water tank change due to the waves, constant density surfaces change slopes, hence changing the sound ray's paths and the amount of signals reaching the receivers. Similar results of numerical simulation also show similar behavior in the strength of the acoustic signal. The numerical simulation were done by AcTUP v2.2L software that use KERAKENC method based on normal mode method. The acoustic signal can be weakened up to 54 per cent depending on the degree of sound ray divergence. We can conclude that in the laboratory tank in this study internal waves can affect the sound waves by focusing and defocusing and not by mode coupling. Similar behaviors can be expected in the open ocean as the existence of internal waves is ubiquitous. For this goal dimensionless numbers should be use. Bowen (1993) showed that for simulating a sound waves interaction with a phenomenon in laboratory scale we can use ka=k' a'. With this formula we can compare laboratory results with real results in oceans.

Two single and multi-site statistical downscaling methods of Statistical Downscaling Model–Decision Centric (SDSM–DC) for daily temperature and precipitation are evaluated at nine stations located in the mountainous region of Iran’s Midwest. SDSM is best described as a single-site model, but it can be extended to multi-site applications via conditional resampling (CR-SDSM, Wilby et al.2003; Harpham and Wilby 2005). SDSM–DC (Wilby and Dawson 2013) is a hybrid of the stochastic weather generator and transfer function methods. Predictor selection is based on empirical relationships between GCM-scale predictors and single-site predictand variables. (Farajzadeh et al.2015). Applying SDSM to multi-site daily rainfall downscaling includes two steps: (1) the daily rainfall and temperature at a “marker” site (in this study, the area average amounts) is first downscaled by the single-site SDSM; (2) Daily rainfall amounts are then “resampled from the empirical distribution of area averages, conditional on the large-scale atmospheric forcing and the stochastic error term. The actual daily rainfall is determined by mapping the modeled normal cumulative distribution value onto the observed cumulative distribution of amounts at the marker site” (Wilby et al.2003; Liu et al.2013). Ultimately, the marker site rainfall is resampled to the constituent amount falling on the same day from each station in the multi-sites array (Harpham and Wilby 2005). Thus, if the marker series is based on an unweighted average of all sites, the conditional resampling will preserve both the areal average of the marker series and the spatial covariance of the multi-site rainfall (Wilby et al.2003). Additionally, using area average, instead of individual sites as the marker series, reduces the risk of employing a nonhomogeneous/non-representative record and increases the signal to noise ratio of the predictand (Wilby et al.2003; Liu et al.2013). To downscale temperature, the same steps are applied but unconditionally using transfer function methods. For statistical downscaling, two sets of data are generally required: (1) observational data for model calibration and validation, as predictands; and (2) synoptic-scale climate data from GCM and/or reanalysis, as predictors. In order for a better assessment of climate variability and change on local and regional scale, long-term time series of reliable climate data at fine-scale resolution are required (Vincent et al 2002; Mekis and Vincent 2011; Menne et al 2012). As mentioned before, for the Midwest of Iran, we selected nine synoptic stations with nearly complete data coverage for 1981–2010. We used station data for two decades (1981–2000) for calibration and from one decade (2001–2010) for validation of daily values of minimum and maximum temperature, and total daily precipitation. To assess the accuracy and homogeneity of the observational data, we used different methods for quality control: the R packages RHtestsV3 (Wang and Feng 2010) and RHtests_dlyPrcp (Wang et al.2010), based on penalized maximal t and F tests (Wang et al.2007; Wang 2008b) that are embedded in a recursive testing algorithm (Wang 2008a); the R package Climatol (Guijarro 2012), which applies a type II linear regression model; and SDSM (Wilby and Dawson 2012, 2013) based on reanalysis predictor variables. Missing values are filled in by using the sequential k-nearest neighbor imputation method (Kim and Yi 2008) and homogeneity tests are applied both before and after infilling to assess infilling performance. Predictor fields are extracted from the National Centers for Environmental Prediction (NCEP) Reanalysis (Kalnay et al.1996) archives at resolutions of 2.5°×2.5°. As mentioned earlier, SDSM has its own methodology for predictor selection in which EOFs of NCEP reanalysis data over the domain (30° N, 42° E) and (40° N, 52° E) are screened separately for temperature and for precipitation. (Farajzadeh et al.2015). Results indicate that the methods are of widely varying complexity, with input requirements that range from single point predictors of temperature and precipitation to multivariate synoptic-scale fields. The period 1981-2000 is used for model calibration and 2001–2010 for validation, with performance assessed in terms of 27 Climate Extremes Indices (CLIMDEX). The sensitivity of the methods to large-scale anomalies and their ability to replicate the observed data distribution in the validation period are separately tested for each index by Pearson correlation and Kolmogorov–Smirnov (KS) tests, respectively. Combined tests are used to assess overall model performances. Single (multi) -site method of SDSM, passing 76% (81%), 16% (7%) and 14% (5%) of the Kolmogorov–Smirnov (KS), the Pearson correlation and the combined tests, performed well in terms of temperature and precipitation downscaling. Single-site method performed better than multi-site one at single sites; however, multisite method performance is better at regional downscaling. Correlation tests were passed less frequently than KS tests. Both methods downscaled temperature indices better than precipitation indices. Some indices, notably R20, R25, SDII, CWD, and TNx, were not successfully simulated by any of the methods. Model performance varied widely across the study region.

Shallow water equations are for modelixy the behavior of a single-layer of fluid with constant density, that the hydrostatic approximation applies. These equations for the motion of a dry and inviscid atmosphere with constant density include the momentum and the continuity equations. In addition, the shallow water equations are often used as a testbed to assess the performance of new numerical algorithms. In recent years, the trend toward increasing the accuracy of the numerical simulations of the atmospheric and oceanic motions has increased due to the inherent complexity in these motions. In recent researches, the compact schemes have been notable because of their remarkable performance in the numerical simulation of fluid flows in other branches of fluid dynamics. This work is devoted to the application of the fourth-order compact MacCormack scheme to the numerical solution of the conservative form of the two dimensional shallow water equations. The compact MacCormack method is formulated in form of a two-point scheme. Two versions of the fourth-order compact MacCormack scheme have been introduced and called as 4.2 and 4.4. The first order spatial derivative operators have implicit forms in both schemes (4.2 and 4.4), for one-sided forward and backward operators. The Mac Cormack scheme uses two time-marching methods: The first is the original two-stage method and the other one is the Runge-Kutta-type (RK2, RK4 and LDDRK4-6) method. In the present work first, we solve a simple linear (advection) equation with an analytical solution, using the second-order and the fourth-order compact Mac Cormack-type schemes (with the original and the Runge-Kutta time-marching methods) and compare their global errors. The results show that when the fourth-order compact Mac Cormack schemes with the original time-marching are used, the 4.2 formulation has better results than the 4.4 formulation, but when these schemes use the Runge-Kutta time-marching, the results of the 4.4 formulation are better than those in the 4.2 formulation. According to these results and the magnitude of the global errors, we used four Mac Cormack-type methods to solve the shallow water equations. The methods are the second-order scheme with the original time-marching, the 4.2 type of fourth order compact scheme with both the original and the RK4 time-marching, and the 4.4 type of fourth order compact scheme with the RK4 time-marching. In the following, we solved the conservative form of the one-dimensional shallow water equations with those four mentioned schemes. The results were compared with a test case with known analytical solution. Finally, we solved the conservative form of the two-dimensional shallow water equations. To perform the simulations two well know test cases are used. To assess the numerical accuracy, we estimated conservative quantities such as energy, enstrophy and mass along the simulation process in all time steps. The estimated results indicate that the fourth-order compact Mac Cormack schemes retain the conservation of these quantities better than the second-order Mac Cormack scheme. In comparison with the other applied schemes in this work, while the 4.4 formulation with the RK4 time-marching shows more accurate results, the numerical stability condition of this scheme is less than the other schemes. In the second test case, we point out that the computational time of the code for each numerical solution, which utilizes the fourth-order compact schemes, is longer than the computational time of the solution using second-order scheme; but their implementation is reasonable because their numerical accuracy is higher than that of the second-order scheme.