مجله ژئوفیزیک ایران
سال پانزدهم شماره 2 (پیاپی 51، تابستان 1400)

Thunderstorms often appear with a strong, energetic and short-term air flow. These types of storm are caused by the ascent of hot and humid air in an unstable atmosphere and can lead to heavy rainfall if there is sufficient moisture, and otherwise they will lead to a dust storm. The purpose of this study was to investigate the storms in Khuzestan province, which usually experiences gusty winds, and convective storm events during spring and early summer. With regard to the frequent occurrence of dust storms in Khuzestan in recent years, it has become ever more important to study the convective storms. In order to identify the storm events in Khuzestan, Ahvaz station was selected due to much longer record of data and more accurate information than other stations in the province. A statistical analysis has been carried out on the long-term data of Ahvaz synoptic station between 1981 and 2016. After a thorough analysis of the long-term data, five cases of severe convective storms were selected. The cases include the 16th of October 1981 (case 1), the 27th of August 1985 (case 2), the 18th of December 1985 (case 3), the 24th of April 1992 (case 4) and the 8th of May 2000 (case 5). Finally, the characteristics of the cases were determined by numerical simulations using the Weather Research and Forecasting (WRF) model. The simulations were performed using four nested domains D1 to D4 with horizontal resolutions of 81, 27, 9 and 3km, respectively. The NCEP/NCAR reanalysis data were used for the boundary and initial conditions.Statistical analysis shows a decrease in the intensity and frequency of occurrences of the convective storms with maximum wind speed of greater than 12m/s during the 36-year period. Monthly analysis reveals that the most (least) frequent severe convective storms occur in April (October). Another important finding is that the severe convective storms occur mainly in spring and in the interval between 12UTC and 15UTC. From the early hours of the day until 13:00 UTC, the percentage of events increases, and then until the end hours of the day, the percentage of events decreases as the surface heating is maximized in the afternoon. The low frequency of occurrence in autumn and winter is due to reduced surface heating as a result of reduced solar energy received from the sun. The results of numerical simulations demonstrate that the position of the maximum wind speed is different in the considered cases. The comparison of the results of simulation of the selected cases with observational data shows that the model of simulated storm has a time delay of about 1 to 3 hours with respect to the actual storm occurred in the area. Tracking the storms from 30 min before to 30 min after the occurrence of the maximum wind speed along the path in the fourth domain of the model points out that the cases 1 to 3 evolve in the northeast and the cases 4 and 5 evolve in the northwest of Ahvaz station.

The abrupt topographical change in northern Tehran divides the Eocene rock formation from Quaternary and Plio-Quaternary alluvial deposits situated in the piedmont and the plain. This phenomenon has been interpreted differently by two Geologists in the 70's and 80's. The term North Tehran Fault (NTF) is the first interpretation of rock-alluvium boundary, coined by Tchalenco (1975). According to this interpretation consist the NTF of the fault system, arranged in an en-echelon manner, not necessarily forming the rock-alluvium boundary in northern Tehran. A later interpretation, by joining all the fault systems, as a single line, called North Tehran Thrust (NTT). According to this interpretation forms (NTT) a single line, defining the boundary of rock-alluvium in northern Tehran (Berberian et al., 1983), not confusing with North Tehran Fault (NTF). The mentioned two interpretations of faulting in northern Tehran include two different faulting mechanisms opposing each other diagonally. By time are the two interpretations wrongly melted together as (NTF) and were used by several authors without paying attention to its original meaning interpreted by Tchalenko (1975).In later works (Langraf et al., 2009; Ritz et al., 2012) is (NTF) the main structure responsible for the rising of highly elevated rock formation in the hanging wall of North Tehran Thrust (NTT).The present study deals strictly with the boundary of rock and alluvium in northern Tehran, which was called (NTT). Kinematic study along the contact of rock and alluvium revealed two characteristic features: 1- Rock-Alluvium boundary occurs not along with a single faulting trend, it is rather arranged along NW-, N-S, E-W, and NE-striking faults. 2- Obtained stress direction associated with fault plane solution show different directions.In many places is the NTT covered by rock slides, obscuring the trace of the rock-alluvium boundary. Older rockslides are thrusted over alluvium units of different ages. The contact of such boundaries shows striations compatible with present-day stress direction. The slow deformation rate in northern Tehran is not concentrated along a single fault. Therefore, it seems that absorbed deformation in northern Tehran is distributed over a wide range adjacent to the rock-alluvium boundary. These observations suggest an unrecognized fault, which needs more careful geological and seismological study.Considering the three different trends of NTT, namely NW-, E-W- and NE-trending, no fold axis run parallel to those trends. The results obtained in this study suggest the NTT is not a major fault and in addition, it could not be regarded as a single fault responsible for the rising of the rock formation on the hanging wall of NTT in northern Tehran.

Atmospheric blocking is an important large-scale weather phenomenon at mid-high latitudes in the atmosphere which has a profound effect on local and regional climates in the immediate blocking domain as well as in regions upstream and/or downstream of the blocking event.Commonly used definitions can be divided into four categories of methods to identify blocking. All of the definitions of blocking do not wholly address dipole-type blocking, so new criteria for identifying dipole-type blocking have to be established. In this research, diagnostic case of dipole-type blocking life in the Middle East region for the period time from 13 to 20 November 2019 was studied. Several basic features of the dipole-type blocking, along with the calculation of the thermal wind, are introduced to identify and distinguish the dipole-type blocking from the other blockings.The results showed that the dipole-type blocking event usually occurs at lower-tropospheric pressure levels compared to the upper-tropospheric pressure as they have weaker westerly winds. The life time of the blocking event considered was made shorter by increasing of the westerly winds on higher pressure levels. For the occurrence of a blocking event, the wind must reach the minimum at the mid-tropospheric pressure levels of the atmosphere and the flow must be split into two branches. However, with the reduction of the thermal wind, the geostrophic wind as well as the total are weakened, resulting in the formation of split flow and blocking event. It was observed that the magnitude of the thermal wind at the time of the formation of the blocking tends to zero. The thermal wind and its westerly and easterly parts over the dipole were determined at the 500 hPa pressure level. At the time of the event, a dipole-type blocking of at least one closed contour with 4 geopotential decameters interval, simultaneously occurred for both high and low centers. Moreover, examining the westerly winds over the blocking entrance showed that during the time of this event, the speed of westerly winds decreased to a minimum amount. For the dipole-type blocking, unlike the cut-off low single-pole type, there is no sign of a fairly intense wind at the entrance of blocking. During the life cycle, the movement of blocking is less than 10 degrees per day. Furthermore, the high of blocking rests in a latitude above . The computed blocking index is also no lower than 20 m/s. The use of some features blocking and the calculation of thermal wind during the life time of a typical case of dipole-type blocking illustrates the utility of this method for identifying dipole-type blocking. The analysis, however, needs to be extended to several other cases for a more definite conclusion.

This research has investigated the possibility of predicting the direction and speed of Gusty wind by using the information of Mehrabad Airport runway automatic station during the period of January 2013 to June 2013, the Metar report of Mehrabad Synoptic Station in the period of 2013, and regression method.The data of the automatic station is taken from three sensors located in the band with a length of 4000 meters and a width of 45 meters, in southeast-northwest direction.The sensor number 29 and the sensor number 11, are at the northwestern end of the band and southeast edge of the band respectively. The Mid sensor location is at the middle of the band which distance from the band is 600 meters to the north direction.    First, all data (except the data of Gusty wind direction and speed measured by the sensors) was normalized to intervals 0.1-0.9. Second, all the data of sensors were randomly divided into three unequal parts: 70% of the data was stored for training, 50% of the remaining data was used for testing and the rest was used for validation. During the calculations, they were used instead of the original data. Third, the quantities were processed by using the three methods of feature selection: Sequential Forward Feature Selection(SFS); Backward(SBS) and Mutual Information(MI) with the method of the Maximum-Relevance and Minimum-Redundancy criterion. At this stage, selective features by every method were separately used in the linear regression method to predict the speed and direction of Gusty wind in the winter and spring seasons. The results were then compared with each other.The results show that the selected features by SBS method for wind speed in winter are similar to spring, but their wind direction is slightly different. Selected features for winter Gusty wind with SFS method are a subset of the set of the selected features for spring. Selected features with MI are similar for the two seasons but with different weights. The performance of the selected features for wind speed are better than for wind direction. The SFS method is optimal for selecting features of Gusty wind in the Mid runway. On runway 11, the SBS method and the SFS are optimized for predicting the Gusty wind speed and direction respectively. On runway 29, the SBF method is very suitable for selecting features related to Gusty wind speed and direction.Finally, by examining the output of the models for each of the runways, an equation is provided to predict the direction and speed of the Gusty wind in each runway.The quantity of predicted wind direction in runway 29 and 11 depends on the mean wind direction in 2 minutes, the minimum and mean direction in 10 minutes and the wind speed component along the runway, but the quantity of predicted wind speed depends on the maximum wind speed in 10 minutes on the runway, the instantaneous pressure of the station, and the pressure of the station relative to sea level.  The quantity of predicted wind direction in Mid runway depends on the minimum and mean wind direction in 2 minutes, minimum, mean and maximum wind direction in 10 minutes in runway Mid, maximum wind speed in 2 minutes and components of wind direction along with the runway 11. The quantity of predicted wind speed depends on the maximum and minimum wind speed in 10 minutes on the runway, deviation of wind direction during the last 10 minutes in the runways 29, Mid and 11.

In this study, the seasonal changes of plankton in the north of Oman Sea have been investigated using the three-dimensional Regional Ocean Modeling System (ROMS) model. The initial conditions of the model follow the preliminary conditions as in WOA5 data with a horizontal resolution of 0.25 degrees and a time step of 300 seconds for one year. Vertical coordinate data were for 30 layers sigma levels by interpolations in the vertical direction of temperature and salinity. Due to the greater sub-model compatibility, ROMS model is coupled with Nutrient-Phytoplankton-Zooplankton-Detritus (NPZD) model. The simulation results showed that: (1) Temperature change is one of the main factors in the frequency of phytoplankton and zooplankton blooms; (2) Clock and counterclockwise Eddies, which represent the phenomenon of extra down or upwells in the Sea of Oman and the Strait of Hormuz, causes the transfer of chlorophyll from the south to the north; (3) The amount of chlorophyll is higher during winter compared to summer. It can be due to the presence of seasonal thermocline layer which prevents blooming despite the availability of nutrients; (4) The phytoplankton cncenteration changes in a period of one year shows that their maximum value is in late March and early spring, and April is the peak of zooplankton due to the increase in phytoplankton population. Moreover, the density of plankton depends mainly on mineral nutrients, therefore, the availability of minerals is often considered as a key factor in their growth and metabolism; (5) Chlorophyll content shows a positive correlation with water surface temperature in winter (r = 0.965), while a negative one in summer (r = -0.549). There is a significant difference between chlorophyll density in winter and summer (p <0.05). There was a positive correlation between amount of chlorophyll and nitrate in winter (r = 0.268) and summer (r = 0.794), which suggests a significant difference between winter and summer (for p <0.05); (6) There were good agreements between satellite observations of temperature and chlorophyll and the values measured in numerical modeling in majority of the cases.

In this study, deterministic forecasts of 10-meter wind speed for the next 24, 48 and 72 hours have been produced and analyzed over Iran using BMA and EMOS methods for post-processing of raw outputs of the ensemble systems. The main purpose of this article is to compare deterministic forecasts based on these two methods with each raw ensemble members and the mean of the raw ensemble members. The applied ensemble system consists of eight members with different boundary layer schemes in the Weather Research and Forecasting (WRF) model. Other physical schemes remained the same in the ensemble members. For each ensemble member, the 24, 48 and 72-hour forecasts of 10-meter wind speed have ben conducted over Iran, with a horizontal resolution of 21 km. The Global Forecast System (GFS) is used for initial and boundary conditions of forecasts starting at 1200 UTC for each case. Observational data of 31 synoptic meteorological stations located in provincial capitals have been used for model evaluation, in which model outputs are interpolated to the locations of these stations by a bilinear method. The WRF model is run from 1 March to 31 August 2017, but the results from 11 April to 31 August 2017 are considered as the spin-up period. Indeed, after careful examination of the forecast errors using different spin-up periods, the first 30 days of the simulation are considered as the spin-up for both BMA and EMOS methods. Verification is performed by different methods (accuracy: PC, TS and OR; reliability and resolution: FAR, POFD and POD; skill: CSS, HSS, PSS, GSS and Q; statistical errors: RMSE and MAE) for 10-meter wind speed thresholds less than 3 m/s and more than 5, 10 and 15 m/s for both methods for all forecast lead times. Results indicate significant improvements in accuracy scores (300%), reliability and resolution scores (220%), skill scores (340%). Statistical error scores are also reduced by 24%. Furthermore, applying verification for different climatic regions of Iran (cold, semi-arid, hot-dry, hot-humid and moderate-rainy climate) indicates that in all climatic regions, the best performance in terms of RMSE is for BMA and EMOS methods, with the average reduction of error by 21% and 23% ,respectively. Particularly, in hot and humid climates,  these two methods better improve predictions, and hence, are more promisingas they reduce the error by 44% and 46%, respectively.

In this research, a deterministic forecast of 24, 48 and 72 hours of 10-meter wind speed has been produced over Iran, using BMA and EMOS methods for post-processing of raw output of ensemble systems. The main purpose of this article is to compare the deterministic forecasts obtained by using these two methods with each raw ensemble members and the mean of the raw ensemble members. The used ensemble system consists of eight different physical configurations, with changes in the boundary layer scheme of the WRF model. Other physical models in ensemble system are the same for all ensemble members. Each ensemble member includes 24, 48 and 72-hour forecasts of 10-meter wind speed with a resolution of 21 kilometers over Iran. GFS forecasts are used for the initial and boundary conditions, and the forecast start time is 12 UTC per day. Observation data of 31 synoptic meteorological stations located in the provincial capitals have been used and the corresponding values of the predictions on these stations have been interpolated by bilinear method. The model is run from 1 March to 31 August 2017, and the results from 11 April to 31 August 2017 are considered as the test period. After calculating the forecast errors with different training periods, 30 days are considered as the length of training period for prediction in both BMA and EMOS methods. Verification was performed by different methods (accuracy: PC, TS and OR; reliability and resolution: FAR, POFD and POD; skill: CSS, HSS, PSS, GSS and Q; statistical errors: RMSE and MAE) for 10-meter wind speed thresholds less than 3 and more than 5, 10 and 15 m/s for both methods in all forecast ages. The results show a 3 times improvement in accuracy scores, 2.2 times improvement in reliability and resolution scores, 3.4 times improvement in skill scores and 24% reduction in statistical error scores relative to the mean of ensemble members. Furthermore, the verification results for different climatic regions (cold, semi-arid, hot-dry, hot-humid and moderate-rainy climate) in the country separately showed that in all climates, RMSE measurement has the best performance for BMA and EMOS methods and reduces the error by 21% and 23% ,respectively. In hot and humid climates, compared to the mean of ensemble members errors, these two methods were more powerful to improve the prediction system. They reduced the error by 44% and 46%, respectively.

Although hydrogeophysics application in studying the groundwater systems has been significantly increased over the two recent decades, the solute concentration quantities obtained from geophysical modeling are of high uncertainty. This is mostly attributed to (1) the regularization procedure in geoelectrical inverse models, particularly in complex geological settings such as heterogeneous aquifers, and (2) the use of petrophysical relationships.The primary goal of this study is to model the spatio-temporal evolution of the injected salt contaminant in a heterogeneous loamy sand aquifer through the prediction-focused approach (PFA) and resistivity data, circumventing the need for classical geoelectric inversion. The primary advantage of the PFA method is that it does not need any regularization step used in the deterministic geoelectric inversion. This methodology only needs to generate the prior dataset without suffering from any spatial bias, spatially and temporally varying resolution or uncertainty in the post inversion petrophysical transformation.In this research, a synthetic heterogeneous two-dimensional aquifer with 30m´30m is generated through a sequential Gaussian simulation. Then, 500 heterogeneous hydraulic conductivity (K) fields with mean of logK = -4.6 are generated. Accordingly, 500 models of flow and solute transport are carried out for each of six time steps of 0.05, 0.1, 0.2, 0.5, 1, and 5 years. Subsequently, 500 corresponding apparent resistivity datasets are generated through forward geoelectrical modeling (dipole-dipole array) for each of six steps using a MATLAB code. After preparing the large 3D matrices of resistivity and concentration variables as inputs for the PFA, canonical correlation analysis is used to explore the relationship between the apparent resistivity (data) and the solute concentrations (forecast variables) in their reduced dimension space. We selected only 12 and 8 first components for the resistivity and saline concentration variables which they both explain more than 99.5 percent of the variance. The principal component analysis and canonical correlation analysis are used on the reduced datasets to maximize the correlation between the components of the resistivity and solute concentration data. Since a linear relationship is established between the data and forecast, the posterior distribution of the solute concentration is directly sampled using a Gaussian process regression. Finally, the reduced dimension space is back-transformed to the original space. Results demonstrate that the modeled contaminant plumes, in addition to their spatio-temporal distributions, are highly consistent with the maximum and minimum concentration values of the reference images. This signifies the robustness of the PFA for hydrogeophyscical investigation.

Determining the petrophysical properties of a reservoir is of great importance. The most important of these properties are the porosity and permeability of the reservoir sections. The petrophysical properties of a reservoir are usually obtained by methods including core analysis and well testing techniques which require spending a very high time and cost. Furthermore, the results of determining these parameters by the mentioned methods are not of good quality due to the lack of sufficient cores, lithological changes and heterogeneity of reservoir rock. Therefore, the optimal method is to use advanced evaluations of petrophysical diagrams in advanced software environments such as Geolog. The results of petrophysical assessments can be compared and calibrated with the results obtained from the core.Usually, porosity is estimated based on the one of the neutron logs, density logs, sound logs or combination of two logs in-site. Moreover, it can be calculated by laboratory methods which give different evaluations of porosity, of course. Experience has also shown that estimation of porosity using one type of log is not accurate due to the response of each log to certain parameters of a formation.Another method to estimate the porosity is to use longitudinal and transverse wave velocities and the ratio of these velocities. This method uses surface wave data and Vertical Seismic Profiling (VSP) surveys. Using the empirical relations between the porosity and seismic velocities, a proper estimation of porosity could be provided. In this research, porosity has been estimated using the VSP data and also some other petrophysical logs in a well in the Persian Gulf and the results have been compared with other methods.The results show that the porosity values obtained from VSP data are closer to the core analysis than acoustic log results. One of the advantages of porosity estimation using VSP data is the insignificant effectiveness of shale contents on this method.The well wall caving, especially at the bottom of the well, causes error in the reading of some logs and affects the amount of porosity calculated by petrophysical logs. However, well caving has little effect on VSP data readings and results in the estimated porosity values to be more accurate than the Vp/Vs velocity ratios in these areas.The porosity obtained from the dynamic method shows only the initial porosity of the rock and is not able to calculate the total porosity. Furthermore, the studies conducted in this research showed that the porosity achieved by acoustic method does not conform well to the helium gas in neutron log and density log methods (as a reliable method), and also does not have the necessary validity. For these reasons, in this study, a method was proposed to determine the porosity by combining the ratio of the longitudinal wave velocity to shear wave velocity (Vp/Vs) and rock density. Comparison of the results presented in this study with other available methods showed a good consistency and suggests that the proposed empirical equation provides a more realistic calculation for rock porosity.As a recommendation, we suggest that VSP data be acquired for the whole well column because extracting the compressional and shear wave velocities in all surveyed depths and calculating the ratio of them, will make it possible to estimate the amount of different porosities in all existing formations.

In this study, an improved picture of the ongoing crustal deformation field for the Zagros as an evolving foreland fold and thrust belt is presented by using an extensive combination of geodetic and seismic analysis. The significant amount of oblique Arabia–Eurasia convergence is currently absorbed within the Zagros. Part of the total available energy is used in seismic deformations and part of it is stored in faults as potential energy. The remaining energy is consumed by the creeps and aseismic processes. Estimation of moment rate is comparatively reckoned as a new method for investigation of tectonic activities rate in different regions. In this research, geodetic moment rate (based on the GPS data) and seismic moment rate (based on the historical and instrumental earthquake data) are estimated for Zagros block in S-SW of Iran. Each approach has its own limitations. In all parts of the Zagros belt, the maximum estimated moment rate belongs to geodetic moment rate which is almost equal to 7.441×1019 Nm/yr. The seismic moment rate in Zagros belt is almost equal to 3.438×1018 Nm/yr. In this study, different parts of the Zagros Mountain range are investigated using three methods (structural, tectonosedimentary and 1°×1° grid) and the results are compared and analyzed. The seismic moment rate of simply-folded belt, high Zagros and Khuzestan plain are 1.56 × 1018 Nm/yr, 1.45 × 1018 Nm/yr and 6.24 × 1016 Nm/yr, respectively. It means that the maximum (minimum) released energy belongs to simply-folded belt (Khuzestan plain). In Izeh, Central Lorestan, interior Fars and Bandar Abbas hinterland sub-zones, the maximum amount of energy has been released during the earthquakes. The ratio of the seismic moment rate to geodetic moment rate is near 0 (0.0429) which indicates that the aseismic processes dominate the deformation, or stress accumulation is underway which can increase the level of the seismic hazard. Such aseismic deformation is probably related to the presence of the weak evaporitic Hormuz Series that prevents the occurrence of very large aseismic motion. According to the values of geodetic moment rates in the Zagros sub-zones and based on the value of the released seismic energy in the north and northeast part of the study area, it seems that in the future, the most of the seismic potential energy and seismic hazard are in the southeastern part of Zagros belt in Fars and Bandar Abbas hinterland and a part of Khuzestan sub-zone. Our study has implications for better comprehending the current seismotectonic pattern of Zagros fold and thrust belt as an evolving deformation area.