IRANIAN JOURNAL OF GEOPHYSICS
Year:2018 | Volume:12 | Issue:2 |Papers Count:13

Dust storms are significant phenomenon in south west Asian countries like Iraq, Syria and Iran. Mineral dust is generated by wind erosion over arid and semiarid land surfaces and is transported locally and over vast distances, causing adverse environmental and weather problems. Recent draughts over dust sources in Iraq and Syria have remarkably increased dust events in the area particularly over west of Iran. Real time prediction of dust storms especially quantitative forecasting of dust concentration has become highly desirable to alleviate its damaging consequences. In this study the impact of the assimilation of satellite radiance, prepbufr and GPSro data in the wind speed and dust load forecasts of WRF-Chem model using WRFDA system are investigated. Prepbufr data are a collection of surface and upper air observations and GPSro data are GPS radio occultation data. These data are operationally collected by the National Centers for Environmental Prediction (NCEP). Data assimilation is applied to two dust events starting from Iraq and Syria borders on August 31st 2015 and June 15th 2016. For each case, two experiments are conducted. An experiment assimilating above mentioned data with three dimensional variational (3D-Var) intermittent assimilation method and a control simulation with no assimilation. The assimilation cycles in the intermittent method consist of three subsequent analyses at 00, 06 and 12 UTC. After the last assimilation cycle, the model is integrated for 48 hours in the future. In variational data assimilation a key element to get a qualified analysis is the accurate specification of error statistics for the background forecast. For the calculation of background error, the model with the same specification for the experiments is run for the whole January 2014 at 0000 and 1200 UTC and the 12-and 24-h forecasts are used to calculate the background error using the National Meteorological Center (NMC) method with CV5 option. The horizontal resolution of the domain is 21 km with 142×130 grid points covering Iran and western neighboring countries. The model has 41 vertical levels with the model top at 25 hPa. Initial and boundary conditions are taken from NCEP Global Forecast System (GFS) model with the horizontal resolution of 0. 5º ×0. 5º . Results show that the agreement between spatial distribution of dust load prediction of the model and Meteosat-10 satellite RGB images is improvedusing data assimilation especially in first forecast hours. Quantitative comparison of 10 m, 850 hPa and 700 hPa model wind speed with surface observation data and ERA-Interim ECMWF reanalysis data show up to 11% improvement in RMSE especially in first forecast hour times. The positive impact of data assimilation is decreased as the forecast length increases.

We detect the downward planetary wave reflection from the stratosphere back to the troposphere in the Northern hemisphere extended winter season (November-March), using ECMWF (ERA-Interim) reanalysis data (1979-2014). In the previous studies, the wave activity is defined as departure from a long-term time mean. However, we demonstrate some of the shortcomings of the above-mentioned definition. For instance, negative values of the heat flux at the lower stratosphere does not necessarily show the downward wave propagation, but a lower upward wave propagation. Perlwitz-Harnik index of reflection is used to categorize the stratospheric wind regimes into the two distinct states: reflective and non-reflective. Negative and positive values of this index indicate a reflective and non-reflective (either absorptive or propagative) stratospheric states, respectively. Our results show that the negative values of this index during early winter (November-December) suggests that the downward wave coupling is less likely to happen in early winter and most of the direct downward wave coupling occurs during mid-winter and early spring (January-March), which is in agreement with previous studies. Furthermore, 10 stratospheric winter states (out of 34) are reflective, while the remaining states (24 winters) are non-reflective winters. Winters whose their stratosphere experiences a major Sudden Stratospheric Warming (SSW) event is identified to detect the absorptive states of the stratosphere. Our analysis suggests that only in the %33 of the winters with reflective stratosphere a SSW can occur. In the %62 and %38 of the winters with nonreflective stratosphere, a SSW event can occur or Rossby waves can propagate upward freely to the upper stratosphere, respectively. Analysis of the heat flux at the lower stratosphere (50 hPa) using two different definitions (wave as a deviation from the time mean and as a deviation from the zonal mean) provides some useful information. If the waves are defined as a deviation from the zonal mean (V T ), during the reflective years, this quantity is negative (indicating a downward reflection of wave activity from the stratosphere to the troposphere). Similarly, during non-reflective years, this quantity has positive values (suggesting either upward wave propagation or absorption by the mean flow). While the above-mentioned definition is in harmony with our expectation, the definition of the wave as a deviation from the long-term time mean (V*T* ) results in an oscillation curve around zero line, without any useful information either about the upward wave propagation or a downward wave reflection. In order to understand the role of mean flow in influencing the upward wave propagation, we calculate the Rossby wave refractive index (or vertical wavenumber alternatively). Our analysis show some of the problematic features (for instance, a very noisy structure) of this index in understanding the differences of reflective and non-reflective stratospheric states. This is most probably due to the overlapping of very large or very small values of the refractive index which cancel each other and results in a noisy structure. To overcome this problem, we use a modified diagnostic tool (compared to the refractive index), probability of favorable propagation condition for Rossby waves. This index has some clear advantages over the traditional refractive index. Analysis of this index shows that during the non-reflective stratospheric states, Rossby waves are more likely to propagate upward (with higher values of the probability), in comparison to the reflective stratospheric regimes which is a superior demonstration of the influences of the basic mean flow on the upward wave propagation over the traditional refractive index.

Inertia– gravity waves (IGWs) play an important role in transporting energy and momentum, in making and shaping turbulence and mixing, and in influencing the mean circulation and thermal structure of the atmosphere. They cause perturbations in the main dynamical fields, such as pressure, temperature and wind. Therefore, knowledge of their sources and analysis of their characteristics are very important. Given that there has been no study to identify and simulate IGWs that may have occurred over Tehran during the last few decades, the current research aims to investigate IGWs in the lower troposphere based on the long-term data of Mehr-Abad meteorological station during the period from 1960 to 2015. One method for detecting IGWs is checking the large amplitude hourly surface pressure changes. At first, hourly surface pressure observations for Tehran in a 55-yr period have been used to find the distribution of large hourly pressure changes defined as falls or rises in excess of 3 hPa per hour. After making careful checks, 101 cases were identified as potential candidates of IGWs occurrences. In the second part of the paper, we constructed composite maps of mean sea level pressure, 1000-500 hPa thickness, 500 hPa geopotential height, and 850 hPa, 500 hPa and 200 hPa wind. The cyclone-related IGW composite showed that the IGW events clustered poleward of the estimated position of the surface warm front, northeastward of the surface cyclone center, downstream and within the poleward exit region of a jet streak that was upstream of a ridge. By analyzing the synoptic-scale environments in which IGWs evolve, the probable candidates for IGWs were reduced to 17, among which 13 events were associated with convection and 4 events were related to cyclone development. In order to evaluate our analysis and to obtain the IGWs characteristics, the Weather Research and Forecasting (WRF) model was used. We determined the position of wave packets and their propagation during the time evolution by drawing the horizontal velocity divergence. The horizontal and vertical wavelength, intrinsic frequency, the period, horizontal and vertical velocity and the group velocity were determined by drawing the cross sections of horizontal velocity divergence and making use of the dispersion relation for hydrostatic waves, as well as the relations for the horizontal and vertical components of group velocity and the intrinsic phase speed. Then we drew time series of the horizontal velocity divergence and sea level pressure, and evaluated the correlation between these two quantities. By checking the horizontal velocity divergence at 800 hPa which is near the surface of the earth, it was observed that negative/positive divergence is associated with pressure rise/fall. On the other hand, the strength or weakness of wave’ s amplitude was investigated by using the time series of horizontal divergence at different pressure levels. The numerical simulation results not only confirmed the validity of the method employed to analyze and identify IGWs, but also determined the connection between the IGWs sources, their propagation as well as their effects on meteorological fields such as pressure, temperature and wind over Tehran, especially at Mehr-Abad meteorological station.

The aim of the present study is detecting the moisture sources of the heavy floods in the western and southern parts of Iran using hydrometeorological analysis. For this purpose, two heavy floods happened during 28th to 31th October and 10th to 12th November 2015 in the western and southern parts of Iran were selected. The Integrated Vapor Transport (IVT) algorithm was used to study the transfer path of the tropical moisture to the mid-latitudes region. This algorithm is also useful for detecting the moisture source of the heavy rainfall and floods. In midlatitude locations, most of the heavy precipitation and flood events are related to intense vertically integrated horizontal water vapor transport. The Integrated Vapor Transport algorithm is in the base of accumulated atmospheric moisture transport from 1000 hPa to 300 hPa levels which is computed using the Global Forecast System (GFS) analyzed data with 0. 5° 0. 5° resolution for all days of October to November from 2007 to 2015. Then threshold values of the IVT were computed for the selected western and southern flood events separately as median value of the maximum IVT along a meridional line at 45E between 20N to 45N for the western flood case and a diagonal line between 42E, 23N and 52E, 33N for the southern flood event one. To detecting the role of humidity associated with the Persian Gulf in the southern flood event, an additional diagonal line was also considered in the northern parts of the Persian Gulf between 56. 5E, 25N and 47E, 34. 5N. To detect the source and path of the moisture for the selected floods, the IVT algoritm (as mentioned in the main text) is used. In addition to the IVT, the zonal and meridional components of integrated vertical moisture flux vector were computed and analyzed to determine the direction of the moisture flux in all grid points. The results showed that the IVT algorithm is a useful tool for finding the atmospheric moisture sources of the floods and the path of the moisture for the studied area. The algorithm indicated that the Red Sea and the Indian Ocean participate equally in moisture supply for the studied flood in the western parts of Iran. But for the peak rainfalls, the results showed that the center of the Red Sea is the main moisture source. For the selected heavy rainfall and flood in the southern parts of Iran, the IVT analysis showed that in days before the flood, the end edge of the moisture path is located over south of the Red Sea but in day with heavy rainfall and flood, the moisture path is limited to the Persian Gulf and surrounding area. So, it seems that for the selected southern flood, the main source of the moisture is the Persian Gulf and the other moisture sources have lesser role in the moisture supply.

The analysis of seismic facies is a technique for mapping geological features and properties using seismic data. To analyze seismic facies, seismic attributes are categorized and classified using machine learning algorithms to identify different seismic facies. Seismic facies analysis due to the nature of seismic data, which always has a degree of uncertainty, can produce different results with even small changes in input parameters of the analyzing method. For this reason, it is necessary to select the different stages of analysis, including the selection of input parameters and algorithm of machine learning, with high accuracy with regard to the objective of the seismic facies analysis. In this study, an interactive method with the supervision of interpreter is proposed for producing seismic facies map, using the optimal selection of the input parameters and the the proper selection of clustering and classification algorithms. In this method, the interpreter in a recursive and rotational process can compare the results of the analysis and generate thr optimal results by changing the input parameters. The method presented in this article is implemented in SeisART software. SeisART has a complete environment for data initialization (importing seismic data and well data). A user-friendly interactive environment allows the user to implement several methods and monitor the corresponding result in 2D and 3D. SeisART software makes the possibility of the interpreter contribution in the whole stages of seismic facies analysis procedure. The interpreter can select the input attributes and chose the proper methods of pattern recognition to reach the best possible result. In the software, various evaluation utilities have been provided in each stage of seismic facies analysis. These utilities allow the interpreter to monitor the results of each method quantitatively and qualitatively. In the unsupervised system, clustering quality factors are used. The interpreter calculates the validation indices for different methods of clustering and identifies the proper method which has been more successful in discovering the natural grouping of patterns in the data set. Afterward, if there is structural geology information about the horizon of interest, the interpreter can decide on the clustering result with more accuracy. In the supervised system, the most proper method is feasible using minimization of training data and validation data errors. In this case, the interpreter can use geological knowledge and well data information to verify obtained results. In this method, the interpreter can obtain different results by changing the input parameters. Comparing these results, and taking into account the path leading to this result, the interpreter gains more knowledge of existing facies. This method has been applied to the MSF4 horizons of the 3D seismic data of the North Sea F3 and has been shown which method is more efficient for different purposes.

An earthquake of local magnitude 5. 2 which occurred in Malard recently, was accompanied by four earthquakes with local magnitudes largerthan 4. 0 These events can be considered as a manifestation of the state of Tehran, a mega-city with more than 13 million inhabitants, in last decade. For this reason, we tried to do a comprehensive seismic study on Tehran and surrounded area using all available data. In order to do this, we used three independent datasets belonged to Iranian Seismological Center (IRSC), International Institute of Earthquake Engineering and Seismology (IIEES) and Tehran Disaster and Mitigation Organization (TDMMO). We merged these three datasets to get a uniform one, using 3D cells gridding technique and then explosions or outliers were removed. The final dataset included 2000 events. Using 310 selected events based on horizontal and depth errors, azimuthal gap, RMS and minimum number of recording stations, we calculated 1D velocity model by utilizing Particle Swarm Optimization (PSO) method. The calculated model consists of three layers. The thickness and P velocity of layers are 4. 0 km and 5. 4 km/s, 6. 0 km and 5. 8 km/s and 5. 0 km and 6. 05 km/s for the first, second and third layer, respectively. The final layer is a half-space with a P velocity of 6. 5 km/s. The computed Vp/Vs is 1. 71. Then all events were relocated using our new velocity model utilizing fully non-linear probabilistic method to get as much as possible accurate locations. The results show that 40% of all relocated events have uncertainties less than 2. 5 km and 5. 0 km in horizontal and vertical direction, respectively. The final calculated mean RMS is ~ 0. 24 s. In order to define the geometry of the active faults, three different subsets of events were selected based on their location uncertainties, azimuthal gap, RMS and minimum number of recording stations. This helped us to use well-located events for better defining of the fault traces on map view and in depth cross-sections. We plotted four cross-sections perpendicular to the strike of the main faults in the region. The focal mechanism solutions for 38 selected events were also computed based on P-wave first polarity method. The final results show that the eastern part of the study region is more active than the western part, at least in the last decade, and surprisingly, the Malard earthquake occurred in a region without any major activity from three months before the main shock. Stress field study also reveals that the maximum stress axis is N36E and the main seismotectonic regime is left lateral structures. These results are very consistent with the main trends of the North Tehran fault.

On 20 December 2010, an earthquake with Mw 6. 5 occurred in Rigan, a small town in the desert south of Bam city. The earthquake epicenter was in a low population area so, luckily, it caused only few casualties. Five days later 76 aftershocks reported by Iranian Seismological Center (ISC). On 27 January 2011, another earthquake (Mw 6. 2) stroke an area at ~ 20 km southwest of the first earthquake. Bam earthquake Mw 6. 6 occurred in 2003 with 40, 000 victims is one of the deadliest earthquakes in Iran which is located in shear zones at southeast Iran. Considering the active faults distribution of the region and aftershocks of the 2010 Rigan earthquake encouraged us to better investigate and model the post-seismic deformation related to the 2010 earthquake. Post-seismic syudying provides information about rheology of the surrounding region and improves our knowledge about the strain release after the earthquake. In this study, COSMO-SkyMed (from Italian Space Agency, ASI) images spanning the temporal interval between 27 January 2011 and 15 July 2011 are used to investigate the postseismic deformation following both earthquakes. We applied the Small Baseline Subset (SBAS) algorithm for images to obtain the post-seismic mean velocity map and the relative deformation time series. 109 interferograms, post-seismic mean velocity map and the relative deformation time series obtained Mean velocity map shows that displacements of post-seismic phase are right lateral strike slip same as co-seismic mechanism. Time series analysis reveals a clear post-seismic signal exponentially increasing with time until reaching the rate of more than 8 mm/year which indicates the end of post-seismic phase and following inter-seismic phase, starts with steady stress accumulation. Later, we modeled the post seismic signal considering a dislocation on a finite fault in an elastic and homogeneous half-space that are the assumptions for the Okada (1985) model. Post-seismic results modeled by adopting a two-step approach: (1) a non-linear inversion performed to constrain the fault geometry parameters and considering a uniform slip, then (2) a linear inversion performed to retrieve the slip distribution on the fault plane previously obtained. The fault plane is split into 1×1 km patches along strike and down-dip. Determining fault parameters and slip distribution by Okada model, indicates that the slip is concentrated in downdip of the coseismic depth with 1. 2 m slip and also at the edges of the coseismic asperity. This slip distribution indicates that “ afterslip” is the mechanism for post-seismic deformation of the Rigan earthquake.

The Madden-Julian Oscillation (MJO) and El Niñ o Southern Oscillation (ENSO) are known as the primary modes of large-scale climate variability in the equatorial parts of the Indian and Pacific Oceans, respectively. The present study has made an effort to analyze interactions of these two oscillations during boreal autumn and the feedback of these interactions on the occurrence of dry or wet periods in Fars province. Cold and warm phases of ENSO (La Niñ a and El Niñ o, respectively) are then classified according to the size of the SOI. Then positive and negative phases of the MJO were defined according to the algebraic sign of the real-time multivariate MJO series 1 (RMM1). Daily values of October-December precipitation data of 9 synoptic stations of Fars province were obtained for the 1974-2013 period. Precipitation amount and the occurrence probability of precipitation were investigated for La Niñ a, El Niñ o MJO positive phase, MJO negative phase and other four combinations of these phases. Since the impacts of ENSO or MJO phases on precipitation variability had been studied previously, the present study mainly motivated to investigate precipitation characteristics for the episodes that El Nino or La Nina events were concurrent with the MJO positive phase (El-P or La-P, respectively) or MJO negative phase (El-N and La-N, respectively). The characteristics of atmospheric circulation and vapor transport over the ocean waters and the Middle East are then investigated to justify the obtained results. Some parameters including precipitation, intensity and occurrence probability of a rainy day were computed for all phases, separately. The ratio between these parameters during opposite phases was computed and spatially mapped to evaluate the effects of the interactions. The results indicated that the frequency of the positive and negative MJO phases is significantly associated with the ENSO condition. Differences between the frequency of the positive and negative MJO phases during the El Niñ o events were found to be insignificant. Contrariwise, during the El Niñ o events, the frequency and occurrence probability of the positive MJO phase are about twice than corresponding statistics during the MJO negative phase. It was found that ENSO and MJO have a significant influence on autumnal precipitation in Fars province. During El Niñ o or negative MJO phase, the mean occurrence probability and intensity of precipitation were significantly greater than the corresponding values during La Nina or positive MJO in Fars. For almost entire parts and for the periods of El Nino, precipitation has significantly enhanced or suppressed during the negative and positive MJO phase, respectively. On the other hand, such differences are not significant when the opposite phases of the MJO have concurred with the La Nina events. Compare to El-P, mean precipitation during El-N has increased by about 300% in the southeast and about 70% in the eastern districts. When the El-N phase has prevailed, the autumnal precipitation intensity has increased about 40-110% and 4-40% over the southern and northern area of Fars, respectively.

In general, the southwest Asia is one of the regions with positive anomalous values of tropopause folding frequency compared to the annual average of the northern hemisphere. The frequency of folding in this region in warm seasons is higher than in cold seasons. This research was carried out with the aim of statistical and dynamical analysis of the atmospheric processes associated with the tropopause folds in the southwest Asia during 2000– 2015. Identification of tropopause folding is based on the algorithm developed by Sprenger et al. (2003) and Gray (2003) and refined by Š kerlak et al. (2014). The detected folds are divided into three categories as shallow, medium, and deep based on their vertical extensions. The time series analysis of all types of tropopause folds shows that the frequency of folding events has an increasing trend during the period of study. The most frequent folding type is as shallow or medium in the summer season but as deep in the winter. The geographical distribution of the correlation coefficients between the monthly mean folding frequencies and some relevant dynamical quantities indicates that baroclinic instability mechanism plays the main role in the occurrences of tropopause foldings in the winter, while the effects of thermodynamic factors are dominant in the summer. Dynamical study of tropopause folds in both winter and summer seasons was conducted using January 2001 and 2004 as well as June 2007 and 2015 data sets. Results show that the winter tropopause foldings are associated with the formation of intense baroclinic waves in mid-levels of troposphere, strengthening of jet streams in upper levels and subsequently the formation of surface cyclones. Also, together with the seasonal displacement of the jet, the positions of tropopause folds are moving about 10 to 15 degrees latitudinally. The analysis of horizontal wave activity flux in January 2004, reveals the presence of a strong wave source (divergence of wave activity flux) in the Western Mediterranean and, at the same time, a wave sink (convergence of flux) over Europe. In January 2001, the wave activity flux was weakened and divided into two branches, one located in middle latitudes and the other in subtropical regions that transmitted wave energy to the southwest Asia. Furthermore, the strong equatorward wave propagation in this month indicates the anticyclonic wave breaking. In the two June months, as the baroclinic waves were weakened, the intensities of wave activity flux as well as the convergence and divergence centers in the southwest Asia were decreased compared to the January cases. Comparing the above results, it can be deduced that in winter, intense baroclinic wave packets in middle latitudes cause the strength of the subtropical jet, and consequently intensification of wave breaking which are associated with the occurrences of deep tropopause folds in the southwest Asia. In summer, the weakening of baroclinic activities leads to the reduction of deep folding frequency and the folds are formed mainly as shallow type at high levels.