ORIGINAL_ARTICLE
Investigation of mode osculation phenomenon in MASW and MALW methods
There are two types of seismic waves: those that can propagate inside a medium (body waves) and those traveling along the Earth’s surface (surface waves). In the last decades, a number of papers dealing with surface waves have been published but it must be recalled that their theoretical description and first applications date back to almost a century ago. Surface waves have been in fact used for a number of applications since 1920s: nondestructive testing (even for medical applications, geotechnical studies and crustal seismology). Recently the interest toward their applications has increased both for the increasing demand for efficient methodologies to apply in engineering projects and because the recent regulations addressing the assessment of the seismic hazard (for instance the Eurocode8) that are giving the necessary emphasis to the determination of shear-wave velocity vertical profile. This parameter is commonly used in geotechnical studies for classifying soil types.Among various methods for estimating shear-wave velocity profile, MASW and MALW methods are most popular because of their fast performance, low cost and their nondestructive nature. These methods are based on analyzing dispersive properties of Rayleigh and Love waves. In surface wave methods a correct identification of the modes is essential to avoid serious errors in building near surface shear wave velocity model. Here we consider the case of higher-mode misidentification known as “osculation” where the energy peak shifts at low frequencies from the fundamental to the first higher mode. This jump occurs around a well-defined frequency where the two modes get very close to each other. This problem is known to take place in complex subsurface situations, for example in inversely dispersive sites or in presence of a strong impedance contrast, such as a soil layer resting on top of the bedrock. This phenomenon can cause a misleading interpretation of dispersion curve by the operator, which is completely hazardous for engineering projects.In this paper we investigated mode osculation phenomenon for both MASW and MALW methods using synthetic and real datasets. We showed that MALW has a far better performance facing this problem, while it is a main drawback for the MASW method. Generally, when we encounter a low-velocity layer in the subsurface, the identification of Rayleigh wave’s fundamental mode (MASW method) becomes almost impossible, while at the same time dispersion modes of Love waves (MALW method) are well separated, even in extreme conditions. In addition, we showed that performing single-station microtremor ellipticity analysis can also be quite useful. It can warn against the presence of a strong impedance contrast, it indicates the critical frequency at which mode osculation takes place, and also the HVSR data can be used as a constraint in the inversion process of surface wave data. So performing HVSR method alongside MASW and MALW methods not only can predict mode osculation frequency and strong impedance contrasts presence, but also can help us with joint-inversion of the surface wave data, resulting in a more solid Vs profile. We evaluated the performances of the proposed methods on real and synthetic seismic data and results were satisfying.
https://jesphys.ut.ac.ir/article_81507_17823dbdbc9144fd511cbd33834aed43.pdf
2021-11-22
409
420
10.22059/jesphys.2021.304373.1007223
MASW
MALW
Shear wave velocity profile
HVSR
Joint-inversion
Hossein
Kazemnezhadi
h.kazemnezhadi@alumni.ut.ac.ir
1
M.Sc. Graduated, Department of Earth Physics, Institute of Geophysics, University of Tehran, Tehran, Iran
AUTHOR
Hamid Reza
Siahkoohi
hamid@ut.ac.ir
2
Professor, Department of Earth Physics, Institute of Geophysics, University of Tehran, Tehran, Iran
LEAD_AUTHOR
Aki, K. and Richards, P. G., 2002, Quantitative seismology. Sausalito, California, University Science Books.
1
Ampuero, J. P., 2008, SEM2DPACK a spectral element method tool for 2Dwave propagationand earthquake source dynamics. https://geodynamics.org/cig/software/specfem2d/.
2
Antipov, V. V. and Ofrikhter,V. G., 2019, Field estimation of deformation modulus of the soils by multichannel analysis of surface waves.Data in Brief, 24, 2352-3409.
3
Boaga, J., Cassiani, G., Strobbia, C. L. and Vignoli, G., 2013, Mode misidentification inRayleigh waves. Geophysics,78, 4, EN17–EN28.
4
Dalmoro,G., 2015, Surface Wave Analysis for Near Surface Applications. Elsevier books.
5
Jakka, R. S. and Roy, N., 2018, Uncertainties in Site Characterization Using Surface Wave Techniques and Their Effects on Seismic Ground Response, In: Krishna A., Dey A., Sreedeep S. (eds), Geotechnics for Natural and Engineered Sustainable Technologies. Developments inGeotechnicalEngineering. Springer, Singapore.
6
Krishna, A, Jakka, R. S. and Roy, N., 2018, Uncertainties in Site Characterization Using Surface Wave Techniques and Their Effects on Seismic Ground Response, In:. Dey A., Sreedeep S. (eds), Geotechnics for Natural and Engineered Sustainable Technologies. Developments inGeotechnicalEngineering. Springer, Singapore.
7
Luo, Y., Xia, J., Liu, J., Liu, Q. and Xu, S., 2007, Joint inversion of high-frequency surface waves with Fundamental and higher modes. J. Appl. Geophysics. 62, 375–384.
8
Luo, Y., Xia, J., Xu, Y., Zeng, C. and Liu, J., 2010, Finite-difference modeling and dispersion analysis of high frequency Love waves for near-surface applications. Pure Appl Geophys, 167(12), 1525–1536.
9
Mi, B., Xia, J., Bradford, J. H. and Shen, C., 2020, Estimating Near-Surface Shear-Wave-Velocity Structures Via Multichannel Analysis of Rayleigh and Love Waves: An Experiment at the Boise Hydrogeophysical Research Site. Surv Geophys, 41, 323–341. https://doi.org/10.1007/s10712-019-09582-4.
10
Nazarian, S., Prajwol, T., Azari, H. and Yuan, D., 2017, Implementation of spectral analysis of surface waves approach for characterization of railway track substructure., Transportation Geotechnics, 12, 101-111.
11
Nogoshi, M. and Igarashi, T., 1971, On the amplitude characteristics of Microtremor (part 2). Jour. Seismol. Soc. Jpn, 24, 26–40, (Japanese with English abstract).
12
Yudi, P., Xia, J., Xu, Y. and Gao, L., 2016, Multichannel analysis of Love waves in a 3D seismic acquisition system, GEOPHYSICS 81, EN67-EN74.
13
Park, C. B. and Miller, R. D., 1999, Multichannel analysis of surface waves. Geophysics, 64, 800–808.
14
Prodehl, C., Kennett, B. and Artemieva, I.andThybo, H., 2013, 100 years of seismic research on the Moho. Tectonophysics, 609, 9-44.
15
Safani, J., O’Neill, A., Matsuoka, T. and Sanada, Y., 2005, Applications of Love wave dispersion for improved shear-wave velocity imaging. J Environ Eng Geophys, 10(2), 135–150.
16
Safani, J., O’Neill, A. and Matsuoka, T., 2006, Love wave modeling and inversion for low velocity layer cases. In: Proceedings of the symposium on the application of geophysics to engineering and environmental problems (SAGEEP). Annual meeting of the environmental and engineering geophysical society (EEGS) Seattle, WA, 1181–1190.
17
Socco, L. V., Foti, S. and Boiero, D., 2010, Surface-wave analysis for building near-surface velocity models — Established approaches and new perspectives. Geophysics, 75, 75A83-75A102.
18
Socco, L. V, Boiero, D., Maraschini, M., Vanneste, M., Madshus, C., Westerdahl, H., Duffaut, K. and Skomedal, E., 2011, On the use of NGI’s prototype seabed-coupled shear wave vibrator for 1 shallow soil characterization— Part II: Joint Inversion of multi-modal Love and Scholte surface waves. Geophys J Int, 185, 237–252.
19
Socco, L. V., Comina, C. and KhosroAnjom, F., 2017, Time-average velocity estimation through surface-wave analysis: Part 1 — S-wave velocity. Geophysics, 82, U49-U59.
20
Socco, L. V., Foti, S., Hollender, F. and Garofalo, F., 2018, Guidelines for the good practice of surface wave analysis: a product of the InterPACIFIC project. Bull. Earthquake Eng, 16, 2367–2420.
21
Strobbia, C., Foti, S., Rix, G. J. and Lai, C. G., 2015, Surface Wave Methods for Near-Surface Site Characterization. CRC Press, Taylor & Francis Group.
22
Tavasoli, O. and Ghazavi, M., 2018, Wave propagation and ground vibrations due to non-uniform cross-sections piles driving. Computers and Geotechnics, 104, 13-21.
23
Xia, J., Xu, Y., Luo, Y. and Miller, D., 2012, Advantages of Using Multichannel Analysis of Love Waves (MALW) to Estimate Near-Surface Shear-Wave Velocity. Surv Geophys, 33, 841–860. https://doi.org/10.1007/s10712-012-9174-2.
24
ORIGINAL_ARTICLE
Reservoir porosity modelling using support vector regression based on Gaussian kernel in an oil field of Iran
Permeability, porosity and sedimentary facies are the main factors of reservoir characteristics. Porosity indicates the ability of a rock to store fluids. So far, many approaches including linear / nonlinear regressions have been developed to predict porosity. Neural networks have received a lot of attention in recent years, and various types of learning machines based on neural networks have been introduced. Multilayer perceptron neural network (MLP) is one of these networks that proven its ability, but each of these methods has disadvantages. In this research, the support vector machine (SVM) method has been used as the main method for regression and estimation of the reservoir porosity in one of the hydrocarbon reservoirs. This method has been compared with the multilayer perceptron method and the results of each have been investigated.The best way to get accurate values of physical properties of reservoir is to measure them directly in the laboratory. However, this method has disadvantages: high cost, time consuming, lack of access to the entire depth of the well. For these reasons, geologists extract core from a number of wells and from a specific range. Geologists generally use a statistical approach involving multiple linear or nonlinear regressions to relate reservoir characteristics to each other (eg, porosity and permeability). In these contexts, a linear or non-linear relationship is assumed between porosity and other reservoir characteristics. However, these techniques are insufficient for certain issues, such as heterogeneous reservoirs. Recently, geoscientists have used artificial intelligence (AI) methods, especially neural networks (NNs), to predict reservoir parameters. Neural networks have been widely used in various fields of science and engineering.To build a three-dimensional model of a reservoir, a thorough knowledge of permeability, porosity and sedimentary facies is required. Well logs and core information are local measurements that do not reflect the behavior of the reservoir as a whole. In addition, well information does not cover the entire field area, while 3D seismic information covers a larger area. Changes in lithology and fluids cause changes in amplitude, wavelet shape, coherence coefficient, and other seismic attributes. These attributes can provide information for building a repository model.The main purpose of this research is to analyze training machines developed by computer scientists to predict reservoir characteristics such as porosity in vertical and lateral directions with the help of well logs and seismic attributes. The aim is to achieve the following steps to estimate a reliable porosity model of the reservoir:Development of a multilayer perceptron (MLP) to estimate the porosity using well logs.Development of a support vector machine (SVM) to estimate the porosity using well logs.Comparing the proposed methods and choosing the best.Estimation of porosity based on seismic attributes using the selected algorithm.Making a three-dimensional model of the reservoir porosity based on the training machine.As it was expected, these computational intelligence approaches overcome the weakness of the standard regression techniques. Generally, the results show that the performances of Support Vector Machine outperform that Multilayer Perceptron neural networks. In addition, Support Vector Regression (SVR) is more robust, easier and quicker to train. Therefore, it could be concluded that the use of SVM technique will be valuable and powerful for geoscientists to model the reservoir properties.
https://jesphys.ut.ac.ir/article_83551_5ca6c99687f8b609da4dc079eb4afd0e.pdf
2021-11-22
421
432
10.22059/jesphys.2021.315671.1007270
Porosity
Regression
Multilayer Perception Neural Network
Support vector machine
seismic attributes
Well logs
Mehdi
Rafei
hmehdirafee@gmail.com
1
M.Sc. Student, Department of Earth Physics, Institute of Geophysics, University of Tehran, Tehran, Iran
AUTHOR
Majid
Bagheri
majidbagheri@ut.ac.ir
2
Assistant Professor, Department of Earth Physics, Institute of Geophysics, University of Tehran, Tehran, Iran
LEAD_AUTHOR
Majid
Nabi-Bidhendi
mnbhendi@ut.ac.ir
3
Professor, Department of Earth Physics, Institute of Geophysics, University of Tehran, Tehran, Iran
AUTHOR
AL-Bazzaz, W. H, Al-Mehanna, Y. W. and Gupta, A., 2007, Permeability Modeling Using Neural-Networks Approach for Complex Mauddud-Burgan Carbonate Reservoir SPE 105337.
1
Ali, K, 1994, Neural Networks: A New Tool for the Petroleum Industry, SPE.
2
Aminzadeh, F. and Brouwer, F. 2006, Integrating Neural Networks and Fuzzy Logic for Improved Reservoir Property Prediction and Prospect Ranking. SEG New Orleans 2006 Annual Meeting.
3
Balan, B., Mohaghegh, S. and Ameri, S., 1995, State-of-the-Art in Permeability Determination from Well Log Data: Part I. Comparative study, model development. SPE Eastern Regional Conference and Exhibition, West Virginia, 17–21.
4
Bean M. and Jutten C., 2000, Neural Networks in Geophysical Applications, Geophysics, 65, 1032-1047.
5
Bolandi, V., Kadkhodaie, A. and Farzi, R., 2017, Analyzing organic richness of source rocks from well log data by using svm and ann classifiers: A case study from the kazhdumi formation, the persian gulf basin, offshore iran.
6
Cortes, C. and Vapnik, V., 1995, Support-Vector Networks. Machine Learning, 20, 273-297.
7
Leiphart, D. J. and Hart, B. S., 2001, Case History Comparison of Linear Regression and Probabilistic Neural Network to Predict Porosity from 3-D seismic Attributes in Lower Brushy Canyon Channel Sandstones, Southeast New Mexico, Geophysics, 66(5), 1349-1358.
8
Doyen, P. M., 1998, Porosity from seismic data -A geostatistical approach: Geophysics, 3, 1263-1275.
9
Eshafei, M. and Gharib, M., 2007, Neural Network Identification of Hydrocarbon Potential of Shaly Sand Reservoirs, Technical Symposium SPE.
10
Gholami, A. and Ansari, H. R., 2017, Estimation of porosity from seismic attributes using a committee model with bat-inspired optimization algorithm. J Pet Sci Eng 152:238–249.
11
Hommel, J., Coltman, E. and Holger, C., 2018, Porosity – permeability relations for evolving pore space: a review with a focus on (bio-)geochemically altered porous media. Transp Porous Med. 124(2):589–629.
12
Hosseini, E., Gholami, R. and Hajivand, F., 2019., Geostatistical modeling and spatial distribution analysis of porosity and permeability in the Shurijeh-B reservoir of Khangiran gas field in Iran. J Pet Explor Prod Technol, 9, 1051–1073.
13
Kumar, R., Das, B., Chatterjee, R. and Sain, K., 2016, A methodology of porosity estimation from inversion of post stack seismic data. Journal of Natural Gas Science and Engineering, 28, 356–364.
14
Linqi, Z., Zhang, C. and Guo, C., 2018, Calculating the total porosity of shale reservoirs by combining conventional logging and elemental logging to eliminate the effects of gas saturation. Petrophysics, 59(2), 162–84.
15
Mori, T. and Leite, E. P., 2018, Porosity Prediction of a Carbonate Reservoir in Campos Basin Based on the Integration of Seismic Attributes and Well Log Data. (2018).
16
Perrin, C., Rafik, M., Akbar, M. and Jain, S., 2007, Integration of Borehole Image to Enhance Conventional Electrofacies Analysis in Dual Porosity Carbonate Reservoirs, SPE, 11622, International Petroleum Technology Conference, Dubai, UAE 6-4 December.
17
Saggaf, M. M., Toksöz, M. N. and Marhoon, M. I., 2003, Seismic Facies Classification and Identification by Competitive Neural Networks, Geophysics, 68(6), 1984-1999.
18
Schutz, P. S., Hattori, M. and Corbett, C., 1994, Seismic guided estimation of log properties, parts 1,2, and 3: The Leading Edge,13,305-310,674-678, and 770-776.
19
Sippel, M., 2003, Reservoir Characterization from Seismic and Well Control with Intelligent Computing Software, AAPG Annual Convention, Salt Lake City, Utah, May 11-14.
20
Soto, R.B., Bernal, M.C. and Silva, B., 2000, How to Improve Reservoir Characterization using Intelligent Systems. SPE 62938.
21
Soto, R., Torres, B.F., Arango, S. and Cobaleda, G., 2001, Improved Reservoir Permeability Models from Flow Units and Soft Computing Techniques. A Case Study, Suria and Reforma-Libertad, SPE 69625.
22
Wang, L., 2005, Support Vector Machines: Theory and Applications, STUDFUZZ, volume 177.
23
Xie, M., Mayer, KU., Claret, F., Alt-Epping, P., Jacques, D., Steefel, C., Chiaberge, C. and Simunek, J., 2015, Implementation and evaluation of permeability-porosity and tortuosity-porosity relationships linked to mineral dissolution-precipitation. Comput Geo Sci., 19(3), 655–71.
24
ORIGINAL_ARTICLE
The induced seismicity after Alborz Dam impoundment: implications to the active tectonic in northern Iran
The study of induced earthquakes is important in different aspects. One of the most important aspects of reservoir-induced seismicity is the possibility of the triggering of a strong ground motion after reservoir impoundment. This study aims at finding a relationship between the ML5.2 Babolkenar earthquake of 2012 January 11 and the Alborz dam’s impoundment. The Alborz dam is located on the northern flank of the Alborz Mountains. The Alborz dam is an embankment dam and its capacity is 8.6 million cubic meters. Its ridge lies on the tectonized Early Tertiary rocks. The 5.2 ML Babolkenar earthquake of 2012 January 11 is assessed with the use of waveforms provided by different seismic stations. The analyses of waveformes show the centroid depth of 20km and epicenter located at 36.357N, 52.788E. Its thrust fault focal mechanism is in agreement with the fault kinematics inversion implying the reactivation of one of segments of the Khazar fault. Although the event in question could be considered as an ordinary tectonic earthquake, some lines of existing evidence associated with the reservoir impounding data encouraged the authors to consider it as anthropogenic seismicity. Firstly the reservoir is located in the area between two very active thrust fault that contains fractured and permeable rocks. Secondly is the drastic change of seismicity after the onset of reservoir impoundment represents the change of the b-value before, during, and after reservoir impoundment. Thirdly the trigger of the event just after a lowering of the water level. In these cases, earthquake rupture may be interpreted by two different mechanisms: 1) an immediate, undrained, elastic response to the reservoir load and/or an instantaneous pore pressure change in the vicinity of the reservoir due to an undrained response )Skempton, 1954(. The governing equation to explain the undrained response is . In this equation, the change of the undrained compression is related to the Skempton coefficient (B) and the average normal stress at a point located on the fracture ( ). Although the lowering of the reservoir’s water table may change rapidly , the B-coefficient on the other hand, could not change immediately. Therefore the pore pressure is increased even if the water level is decreased leading to satisfying the Coulomb failure criteria. 2) A delayed and/or undrained response due to diffusion of pore pressure. The curve of the accumulative of the seismicity versus the time history of the reservoir impoundment shows two cycles of rising and lowering the water level. Each cycle starts with a gently linear increase of seismicity corresponding to the rising of the water table and ends with a period of increase of the seismicity in response to the water level drawdown. The authors think the diffusion of pore pressure is responsible for the increasing of the seismicity after reservoir impoundment. Given the r=25km as the maximum distance between dam and centroid depth and ∆t=12 months as average time elapsed between the time of that water level increase and the time of the earthquake, the hydraulic diffusivity c=4.95 m^2/sec is estimated by . By the other approach in which the area is affected by the after shakes (here ~100km2) is considered as the r2 in the above-mentioned equation, the c-value takes 0.8 m^2/sec. This c-value discrepancy may be raised by lack of data especially due to lack of local seismic network to the survey of microearthquakes and also unavailable bore-hole to install piezometers measuring the water pore pressure versus time. The c-coefficient may be a useful parameter that is applicable to predict the same reservoir-induced or triggered seismicity in future times. Finally, as mentioned above, the b-value decreased just before the event. This may be in an analogy to the decreasing of the b-value in the other anthropogenic seismic activity i.e. mining tremors, usually called rockburst, and a strong ground motion governed by tectonic activity. The b-value after the event M5.2 increased. Finally, the authors strongly recommend the government plan detailed geological, geophysical and geotechnical studies before and after the impoundment of a new water reservoir to monitor the induced seismicity in the northern flank of Alborz. This may help to mitigate the damages due to the probable triggering of the active faults within this very seismically active belt.
https://jesphys.ut.ac.ir/article_83578_0214f08e0ab9160bf44de22a3fe85e5c.pdf
2021-11-22
433
451
10.22059/jesphys.2021.319525.1007299
Induced Seismicity
Active fault
water pore pressure
impoundment
diffusivity
Zaman
Malekzade
z_malekzadeh@pnu.ac.ir
1
Assistant Professor, Department of Geology, Payame Noor University, Sari, Iran
LEAD_AUTHOR
Zeinab
Rokni
zeinab.rokni@yahoo.com
2
M.Sc. Graduated, Department of Geology, Payame Noor University, Tehran, Iran
AUTHOR
رسولی، ر.، و هوشمندان، ح.، 1389، بررسی روند تغییرات فشار آب منفذی در بدنه و پی سد البرز با استفاده از نتایج ابزار دقیق و مقایسه آن با نتایج تحلیلی، اولین همایش ملی سازه – زلزله-ژئوتکنیک آذر 1389، مازندران-بابلسر.
1
Alavi, M., 1996, Tectonostratigraphic synthesis and structural style of the Alborz mountain system in northern Iran. Journal of Geodynamics 21, 1–33.
2
Aziz Zanjani, A., Ghods, A., Sobouti, F., Bergman, E., Mortezanejad, G., Priestley, k., Saeed Madanipour, S. and Rezaeian, M., 2013, Seismicity in the western coast of the South Caspian Basin and the Talesh Mountains. Geophys. J. Int. https://doi.org/10. 1093/gji/ggt299.
3
Bell, M.L. and Nur, A., 1978, Strength changes due to reservoir-induced pore pressure and stresses and application to Lake Oroville. J. Geophys. Res. 83, 4469 – 4483.
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Carey-Gailhardis, E. and Mercier, J.-L., 1987, a numerical method for determining the state of stress using focal mechanisms of earthquake populations: application to Tibetan teleseisms and microseismicity of Southern Peru, earth planet. Sci. Lett. 82, 165–179.
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Carder, D. S., 1970, Reservoir loading and local earthquakes in engineering seismology the works of man. In: W.M. Adams (Editor), Engineering Geology Case Histories, No. 8. Geological Society of America, Denver, Colo., 51-61.
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Doloei, J. and Roberts, R., 2003, Crustal and uppermost mantle structure of Tehran region from teleseismic P-waveform receiver function analysis, Tectonophysics, 364, 115–133.
7
Gupta, H., K. and Rastogi, B., K., 1976, Dams and Earthquake, Elsevier, the Netherlands, 229pp.
8
Gupta, H. K., 2002, a review of recent studies of triggered earthquakes by artifcial water reservoirs with special emphasis on earthquakes in Koyna, India. Earth-Science Reviews 58(3–4), 279–310.
9
Jackson, J., Priestley, K., Allen, M. and Berberian, M., 2002, Active tectonics of the South Caspian Basin, Geophys. J. Int., 148(2), 214–245.
10
Kaviani, A., 2004, La chaine de collision continentale du Zagros (Iran): structure litospherique par analyse De donees sismologiques, PhD Thesis, University of Joseph Fourier-Grenoble I.
11
Maa, Xu., Westmana, E., Slakera, B., Thibodeaub, D. and Counter, D., 2018, The b-value evolution of mining-induced seismicity and mainshock occurrences at hard-rock mines, International Journal of Rock Mechanics and Mining Sciences 104.
12
Malekzade, Z., 2018, Block rotation induced by the change from the collision to subduction: 1333 Implications for active deformations within the areas surrounding South Caspian Basin. 1334 Marin Geology 404, 111-129.
13
Nuannin, P., 2006, The Potential of b-value Variations as Earthquake Precursors for Small and Large Events. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology 183.
14
Pavlou, K., Drakatos, G., Kouskouna, V., Makropoulos, K. and Kranis, H., 2016, Seismicity study in Pournari reservoir area (W. Greece) 1981–2010.
15
Ritz, J.-F., Nazari, H., Ghassemi, A., Salamati, R., Shafei, A., Soleymani, S. and Vernant, P., 2006, Active transtension inside Central Alborz: a new insight into northern Iran—southern Caspian geodynamics, Geology, 34, 477–480.
16
Ruiz-Barajas, S., Santoyo, M. A., BenitoOterino, M. B., Alvarado, G. E. and Climent, A., 2021, Stress transfer patterns and local seismicity related to reservoir water-level variations. A case study in central Costa Rica.
17
Simpson, D. W., Leith, W. S. and Scholz, C. H., 1988, Two types of reservoir induced seismicity, Bull. Seism. Soc. Am. 78, 2025–2040.
18
Skempton, A. W., 1954, The pore pressure coefficients A and B, Geotechnique 4, 143–147.
19
Tatar, M., 2001, Etude siesmotectonique de deux zones de collision continentale: Le Zagros Central et l’Alborz (Iran), PhD Thesis, University of Joseph Fourier-Grenoble I.
20
Tatar, M., Jackson, J., Hatzfeld, D. and Bergman, E.A., 2007, The 28 May 2004 Baladeh earthquake (Mw 6.2) in the Alborz, Iran: implications for the geology of the south Caspian basin margin and for the seismic hazard of Tehran, Geophys J. Int., 170, 249–261.
21
Talwani, P., 1997, on the nature of reservoir-induced seismicity, Pageoph 150, 473–492.
22
Talwani, P., L. Chen, and K. Gahalaut, 2007, Seismogenic permeability, ks, J. Geophys. Res., 112, B07309, doi:10.1029/ 2006JB004665.
23
Trifu, C., 2002, the Mechanism of Induced Seismicity; Springer RaseI AG.
24
Valoroso, L., Improta, L., Chiaraluce, L., Di Stefano, R., Ferranti, L., Govoni, A. and Chiarabba, C., 2009, Active faults and induced seismicity in the Val d’Agri area (Southern Apennines, Italy). Geophysical Journal International 178 (1), 488e502.
25
Williams-Stroud S., 2014, A geological approach to seismicity b-values: implications for hazard assessment. SEG SEG International Exposition and 87th Annual Meeting.
26
Wyss, M., and Wiemer, S., ZMAP, 2001, A tool for analyses of Seismicity Pattern. ZMAP cook book, ETH, Zurich.
27
ORIGINAL_ARTICLE
Investigation of a suitable geometric design for the CONT14 observation network to improve the accuracy of EOPs by construction of VLBI stations in Iran
Very long baseline interferometry (VLBI) has been used since the mid-1960s as a spatial geodetic tool for accurately determining coordinates on the ground, determining the Earth's rotational axis with very high accuracy and extracting important parameters related to earth. The most important products of VLBI data processing are Earth Orientation Parameters (EOPs) and International Celestial Reference Frames (ICRFs). Other important parameters can be determined by VLBI are International Terrestrial Reference Frames (ITRFs), light deflection parameter, motion parameters of tectonic plates, Love and Shida numbers and ionospheric and tropospheric parameters. The basic principle of VLBI is measuring the time difference between the arrival time of a radio wave in two or more antennas, which is referred to as the time delay. To achieve this purpose, first the atomic clock must be used and secondly the clocks in the antennas must be synchronous. Earth orientation parameters (EOPs) are a set of parameters that describe irregularities in the Earth's rotation. The VLBI method can be used to derive EOPs. These parameters can be used for transformation between international terrestrial reference frame (ITRFs) and celestial reference frame (ICRFs) or vice versa. This transformation takes place through a sequence of rotations related to precession/nutation (NUTX, NUTY), earth rotation (Dut1) and polar motion (XPO, YPO). The geophysical effects of the Earth as well as the effects of celestial bodies such as the Moon or the Sun on the Earth's rotation, lead to changes in the EOPs; therefore, changes in geophysical parameters of the earth can be obtained from changes in the EOPs. The purpose of this study is to investigate the accuracy of the EOPs after adding new observation stations to the CONT14 observation network. These observation stations are artificially constructed in Iran and the accuracy of EOPs before and after adding new station to the network is investigated. CONT sessions are one of the most famous and important sessions in which the stations collect data continuously for two weeks. On average, the CONT sessions take place every three years. Due to the large amount of data in these sessions, the EOPs are determined with high accuracy. Due to the importance of CONT sessions, we will investigate the effect of constructing stations in Iran on the accuracy of the EOPs in one of the CONT sessions, which will be added to the CONT14 observation network. Due to the high cost of constructing a VLBI observation station and to approaching reality, we will add five stations to the network in maximum case. The local network resulting from the five new stations covers the whole of Iran and the locations of these five stations have been chosen arbitrarily. With analyzing the data that collected by the CONT14 session, the accuracy of the EOPs is obtained. After adding new observation stations to CONT14 network and performing the new session, the collected data is processed again and the accuracy of the EOPs is obtained. A comparison of the accuracy obtained in the new mode with accuracy obtained in CONT14 session shows the degree of improvement of EOPs accuracy. By comparing EOPs precision in all possible observation networks, we came to the conclusion that if four observation stations are constructed in Tabriz, Ahvaz, Chabahar and Mashhad and add them to the CONT14 observation network we can improve CONT14 EOPs accuracy by about 13.28%.
https://jesphys.ut.ac.ir/article_81508_d8ff5e0d8d786836d945dda1d1b709f8.pdf
2021-11-22
453
465
10.22059/jesphys.2021.320576.1007303
Very long baseline interferometry (VLBI)
Earth orientation parameters (EOP)
Station
CONT14
Iran
Asghar
Rastbood
arastbood@tabrizu.ac.ir
1
Assistant Professor, Department of Surveying, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran
LEAD_AUTHOR
Mohsen
Sahebi Ilekhchi
mohsensahebi98@ms.tabrizu.ac.ir
2
M.Sc. Student, Department of Surveying, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran
AUTHOR
Clark, B., 2003, A review of the history of VLBI, Radio astronomy at the fringe, 1.
1
Heinkelman, R., 2013, VLBI geodesy, observations, analysis, and results, Geodetic sciences–observations, modeling and applications, S. Jin (ed.), InTech open, doi, 10, 127-156.
2
Kareinen, N., 2016, Geodetic Analysis for the Very Long Baseline Interferometry Global Observing System, Chalmers Tekniska Hogskola (Sweden).
3
Nilsson, T., Heinkelmann, R., Karbon, M., raposo-pulido, V., Soja, B. and Schuh, H., 2014, Earth orientation parameters estimated from VLBI during the CONT11 campaign, Journal of Geodesy, 88, 491-502.
4
Nothnagel, A., Artz, T., Behrend, D. and Malkin, Z., 2021, Continuous VLBI Campaign 2014 www.ivscc.gsfc.nasa.gov/ program/cont14.
5
Thompson, R., Moran, J. and Swenson, G., 2017, Interferometry and synthesis in radio astronomy, Springer Nature, p11-13.
6
Schartner, M. and Böhm, J., 2019, VieSched++: a new VLBI scheduling software for geodesy and astrometry. Publications of the Astronomical Society of the Pacific, 131, 084501.
7
Schartner, M., Böhm, J. and Nothnagel, A., 2020, Optimal antenna locations of the VLBI Global Observing System for the estimation of Earth orientation parameters, Earth, Planets and Space, 72, 1-14.
8
Schuh, H. and Behrend, D., 2012, VLBI: A fascinating technique for geodesy and astrometry, Journal of Geodynamics, 61, 68-80.
9
Seidelmann, P., 1982, 1980 IAU theory of nutation: The final report of the IAU working group on nutation, Celestial mechanics, 27, 79-106.
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Sovers, O. J., Fanselow, J. L. and Jacobs, C. S., 1998, Astrometry and geodesy with radio interferometry: experiments, models, results. Reviews of Modern Physics, 70, 1393.
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Vondrak, J., 2009, Geophysical contributions in precessionnutation, Proc. VI Serbian-Bulgarian Astronomical Conference, Publ. Astr. Soc. Rudjer Bošković, 143-153.
12
Whitney, A., 2000, How Do VLBI Correlators Work?, International VLBI Service for Geodesy and Astrometry 2000 General Meeting Proceedings, 187-205.
13
ORIGINAL_ARTICLE
Retracking Sentinel-3A SAR waveforms to monitor the water level of a small inland water body (Case study: Doroudzan Dam Reservoir, Shiraz, Iran)
In inland water bodies, the water level obtained from the Level-2 data of the altimetry missions is not often correct. Therefore, to correct the water level measured in these areas, it is necessary to retrack the return waveforms. In this study, data from level-2 and level-1 SRAL altimeter of Sentinel-3A mission, measured in SAR mode, in the period from March 2016 to November 2019 to monitor the water level of Doroudzan Dam, has been used. The threshold retracking algorithm with different thresholds has also been used to retrack the waveforms in the level one data. The results showed that the OCOG retracker in L-2 data with an RMSE value of 38.23 cm and a correlation of 99.23% with in situ gauge data compared to other retrackers in L-2 data from Doroudzan dam has higher accuracy in estimating the time series of the water level. The Ocean retracker also has results close to those of the OCOG retracker, indicating that these two retrackers perform well in restoring water levels. After obtaining the water level time series from the retrackers in the L-2 data and selecting the optimal level two retracker, the return waveforms from the L-1 data were first retracked using the threshold algorithm. Then the time series of the water level for different thresholds were obtained and compared with in situ gauge data, which showed that the threshold of 60% with a value of RMSE 37.73 cm and a correlation of 99.30% improved %1.3 in accuracies and increase of %0.07 correlation with in situ gauge data has been optimized for the time series of water level obtained from L-2 retracker. Also, the results showed that, especially in the period from 2017 to 2018, the difference in water levels results from the retracking of the return waveforms with the optimal threshold algorithm (60%) with in situ gauge data less than the optimal L-2 retracker (OCOG). The average water level of Doroudzan Dam from the threshold of 60% was analyzed. Results showed the highest growth in water level with 4.09 m from March 6 to April 2, 2019, which corresponds to usually rainy months. The most significant decrease in the water level with 2.80 meters occurred from April 29, 2019, to May 26, 2019, which are usually low rainfall months. The results also showed that during the study period a slight increase in the water level of Doroudzan Dam was observed. Due to the hard, challenging shape, and topography of Doroudzan Dam and its confused waveforms, therefore, in the above study area, it is not possible to expect high accuracy from both the retrackers in the L-2 data and the results of the waveform retracking. Therefore, the proximity of RMSE results and correlation goes back to the shape and topography of the Doroudzan Dam reservoir. The results of this study show high suitability of the Sentinel-3 mission in monitoring the water level from inland water bodies, which is still a challenging area for satellite altimetry to monitor. Indeed, for a better understanding of the performance of this mission, more samples need to be analyzed.
https://jesphys.ut.ac.ir/article_81509_d7747acd7f97afed146fa7f31875ba0a.pdf
2021-11-22
467
483
10.22059/jesphys.2021.322322.1007311
Satellite altimetry
Sentinel-3
Waveforms Retracking
water level
Doroudzan Dam
Arash
Tayfeh Rostami
a.tayfehrostami@email.kntu.ac.ir
1
M.Sc. Student, School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran
LEAD_AUTHOR
Ali Reza
Azmoudeh Ardalan
ardalan@ut.ac.ir
2
Professor, School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran
AUTHOR
Shirzad
Roohi
roohi.sh77@gmail.com
3
Assistant Professor, Department of Geodesy, South Tehran Branch, Islamic Azad University, Tehran, Iran
AUTHOR
Amir Hossein
Pourmina
pourmina@email.kntu.ac.ir
4
Ph.D. Student, Department of Geodesy, College of Geodesy & Geomatics Engineering, K. N. Toosi University of Technology, Tehran, Iran
AUTHOR
Biancamaria, S., Frappart, F., Leleu, A.-S., Marieu, V., Blumstein, D., Desjonquères, J.-D., Boy, F., Sottolichio, A. and Valle-Levinson, A., 2017, Satellite radar altimetry water elevations performance over a 200 m wide river: Evaluation over the Garonne River. Adv. Space Res., 59 (1), 128-146.
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Birkett, C. M., 1995, The contribution of Topex/Poseidon to the global monitoring of climatically sensitive lakes. J. Geophys. Res. 100 (C12), 25179_25204.
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Brooks, R. L., 1982, Lake Elevation from Satellite Radar Altimetry from a Validation Area in Canada. Report. Geoscience Research Corporation, Salibury, MD.
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EUMETSAT, 2017, Sentinel-3 SRAL Marine User Handbook, EUMETSAT.
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Frappart, F., Calmant, S., Cauhope, M., Seyler, F. and Cazenave, A., 2006, Preliminary results of ENVISAT RA-2-derived water levels validation over the Amazon basin. Remote Sens. Environ. 100, 252_264.
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Ganguly, D., Chander, S., Desai, S. and Chauhan, P., 2015., A subwaveform-based retracker for multipeak waveforms: a case study over Ukai dam/reservoir. Marine Geodesy 38(sup1), 581-596.
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Jain, M., Andersen, O. B., Dall, J. and Stenseng, L., 2015, Sea surface height determination in the Arctic using Cryosat-2 SAR data from primary peak empirical retrackers. Advances in Space Research 55(1), 40-50.
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Jinyum, G., Cheiway, H., Xiaotao, C. and Yuting L., 2006, Improved threshold retracker for satellite altimeter waveform retracking over coastal sea. Progress in Natural Science 16(7), 732-738.
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Koblinsky, C. J., Clarke, R. T., Brenner, A. C. and Frey, H., 1993, Measurement of river level variations with satellite altimetry. Water Resour. Res. 29 (6), 1839_1848.
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Kouraev, A.V., Zakharova, E. A., Samain, O., Mognard, N.M. and Cazenave, A., 2004. Ob’ river discharge from TOPEX/Poseidon satellite altimetry (1992_2002). Remote Sens. Environ. 93, 238_245.
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Leon, J.G., Calmant, S., Seyler, F., Bonnet, M.-P., Cauhopé, M., Frappart, F., Filizola, N. and Fraizy, P., 2006, Rating curves and estimation of average water depth at the upper Negro River based on satellite altimeter data and modeled discharges. J. Hydrol. 328, 481_496.
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Mercier, F., Cazenave, A. and Maheu, C., 2002, Interannual lake level fluctuations (1993_1999) in Africa from Topex/Poseidon: connections with ocean_atmosphere interactions over the Indian ocean. Glob. Planet. Change 32, 141_163.
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Morris, C. S. and Gill, S. K., 1994, Variation of Great Lakes waters from geosat altimetry. Water Resour. Res. 30, 1009_1017.
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Nielsen, K., Stenseng, L., Andersen, O.B. and Knudsen, P., 2017, The Performance and Potentials of the CryoSat-2 SAR and SARIn Modes for Lake Level Estimation. Water, 2017. 9(6), 374.
23
Roohi, S., 2017, Performance evaluation of different satellite radar altimetry missions for monitoring inland water bodies, in Institute of Geodesy. University of Stuttgart. p. 141.
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Santos da Silva, J., Calmant, S., Seyler, F., Rotunno Filho, O.C., Cochonneau, G. and Mansur, W.J., 2010. Water levels in the Amazon basin derived from the ERS 2 and ENVISAT radar altimetry missions. Remote Sens. Environ. 114, 2160_2181.
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27
Tarpanelli, A., Barbetta, S., Brocca, L. and Moramarco, T., 2013, River discharge estimation by using altimetry data and simplified flood routing modeling. Remote Sens. 5 (9), 4145_4162.
28
Tarpanelli, A., Benveniste, J., 2019, Chapter Eleven - On the potential of altimetry and optical sensors for monitoring and forecasting river discharge and extreme flood events, Editor(s): Viviana Maggioni, Christian Massari, Extreme Hydroclimatic Events and Multivariate Hazards in a Changing Environment, Elsevier, P. 267-287, ISBN 9780128148990.
29
Tayfehrostami, A., Azmoudeh Ardalan, A. R., Roohi, S. and Pourmina, A. H., 2021, Dams Surface Area Monitoring from VV and VH Polarization of Sentinel-1 Mission SAR Images (Case study: Doroudzan Dam, Shiraz, Iran). JGST., 10(4),103-116.
30
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32
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33
ORIGINAL_ARTICLE
Multifractal analysis of daily precipitation of selected stations in the west - southwest of Iran
The area of this study, which has covered large parts of the western-southwestern of Iran, has a special topographic and climatic variety. As this area is exposed to geomorphological features such as mountain and plain. In this regard, western and southwestern rainfall systems entering the area, show different reactions to these mid-scale phenomenon (Jahanbakhsh et al; 2020) that such a process has caused the scale behavior and more complex dynamic structure of the rainfall signal in the area. Therefore, on one hand to cover the whole area and on the other hand in order to have long-term daily rainfall statistics, six synotic stations including Khorramabad, Kermanshah, Sanandaj, Dezful, Ahvaz and Abadan stations were selected that have long-term statistics with 1961-2018 as representatives of this area. Also, in order to identify the scale behavior and the dynamics of the structure of the temporal series of rainfall in the western-southwestern of Iran, the fractal and multifractal changed fluctuation analysis method was used (DAF2, MF-DFA2). By using fractal-multifractal analysis of receding fluctuations on daily rainfall signal, it was shown that the rain of all the stations has a scale behavior. In this regard, three different scale periods were identified for records. So that, the fitting of the fluctuation function of DFA2 against different scales show that there are two cross over points that separate three different rainy regimes in the fluctuation function of the stations. These two crossover points are based on a temporal scale of 180 (6 months) and 550 days (approximately 2 years); Therefore, there are three different scale periods including small-scale (less than 6 months), mid-scale (from 6 months to 2 years) and large-scale (more than 2 years) in the rainy temporal series of the stations with different stability and dynamic rainy structure at these three temporal periods. Lovejoy and Mandelbrot, 1985; Matsoukas et al., 2000; Gan et al., 2007; Tan and Gan, (2017) claimed that the existence of cross over points in rainy temporal series, are different mechanisms of raining because temporal scales different. The values of scale exponent in these three periods showed that large-scale rainfalls do not follow a specific spatial pattern and show relatively homogeneous behavior. Although, small-scale raining period has a spatial behavior, in the way that the rain of southwestern stations shows more instability and short-term memory than western stations. Also the results of MF-DFA2 showed that these two cross over points are present in all fluctuations, so that different scale periods are also shown in small to large fluctuations and are not limited to medium period fluctuations. The results of MF-DFA2 showed that the generalized Hurst exponent (hq) has been converged with increasing rainy temporal scale, as the difference between the small fluctuations and large fluctuations , the small-scale temporal series is larger than the large-scale temporal series; Thus, on a small scale, periods with large fluctuations can be clearly distinguished from periods with small fluctuations. Other multifractal properties, including a decreasing hq with increasing the rank of fluctuation (q), nonlinearity of mass signal in relation to q indicate the multifractal nature and multiple scale behavior and nonlinear memory of the rainy signal of the studied stations (Adresh et al. 2020; Shimizu et al., 2002 ; Bunde et al., 2012; Tan and Gan, 2017).On one hand, the comparison of the parameters of the singularity spectrum of the stations shows that all the singularity parameters are similar in the area, but have different intensities. In this regard, the singularity spectrum of all stations in the area is asymmetric and has long left tails. Such a tendency in the singularity spectrum indicates the predominant role of large fluctuations in the multifractal structure of the rainy signal (Telesca and Lovallo, 2011). Thus, the shape of the singularity spectrum reveals that the rainy temporal series in the area has such a multifractal structure which is sensitive to local fluctuations with large values (Kalamaras et al., 2017). In this regard, the rainy temporal series in Khorramabad, Kermanshah and Dezful stations were more complex than other temporal series and Abadan and Ahvaz stations showed a very unstable and noisy structure. On the other hand, the extreme rainfall of southwestern stations including Abadan, Ahvaz and Dezful are much more unstable than the western stations and show heavy rainfall. In this regard, although the structure of Sanandaj station rainfall series is highly sensitive to extreme rainfall, but the intensity of its instability rainfall is lower than the limit rainfall of southwestern stations such as Dezful, which are less sensitive to that of Sanandaj. Its scale exponent is equal to 0.67 with the scale exponent of Khorramabad and Kermanshah stations. In general, such results indicate complexities of temporal series s of rainfall that have very strong local fluctuations.
https://jesphys.ut.ac.ir/article_83556_c00295a96fd455b3f984bcb495239043.pdf
2021-11-22
485
499
10.22059/jesphys.2021.314941.1007267
singular spectrum
fluctuation
hurst exponent
presipitation signal
Multifractal
Hamid
Mirhashemi
climate90@yahoo.com
1
Assistant Professor, Department of Geography, Faculty of Literature and Human Sciences, Lorestan University, Khorramabad, Iran
LEAD_AUTHOR
Dariush
Yarahmadi
d.yarahmadi@gmail.com
2
Associate Professor, Department of Geography, Faculty of Literature and Human Sciences, Lorestan University, Khorramabad, Iran
AUTHOR
Adarsh, S., Nourani, V., Archana, D. and Dharan, D. S., 2020, Multifractal description of daily rainfall fields over India, Journal of Hydrology, 589, 124913.
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2
Baranowski, P., Krzyszczak, J., Slawinski, C., Hoffmann, H., Kozyra, J., Nieróbca, A., Siwek, K. and Gluza, A., 2015, Multifractal analysis of meteorological time series to assess climate impacts, Climate Research, 65, 39-52.
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Matsoukas, C., Islam, S. and Rodriguez‐Iturbe, I., 2000, Detrended fluctuation analysis of rainfall and streamflow time series, Journal of Geophysical Research: Atmospheres, 105, 29165-29172.
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32
Shimizu, Y., Thurner, S. and Ehrenberger, K., 2002, Multifractal spectra as a measure of complexity in human posture, Fractals, 10, 103-116.
33
Tan, X. and Gan, T. Y., 2017, Multifractality of Canadian precipitation and streamflow, International Journal of Climatology, 37, 1221-1236.
34
Taqqu, M. S., Teverovsky, V. and Willinger, W., 1995, Estimators for long-range dependence: an empirical study, Fractals, 3, 785-798.
35
Tessier, Y., Lovejoy, S., Hubert, P., Schertzer, D. and Pecknold, S., 1996, Multifractal analysis and modeling of rainfall and river flows and scaling, causal transfer functions, Journal of Geophysical Research: Atmospheres, 101, 26427-26440.
36
Valencia, J., Requejo, A. S., Gascó, J. and Tarquis, A., 2010, A universal multifractal description applied to precipitation patterns of the Ebro River Basin, Spain, Climate Research, 44, 17-25.
37
Walther, G.-R., Post, E., Convey, P., Menzel, A., Parmesan, C., Beebee, T. J., Fromentin, J.-M., Hoegh-Guldberg, O. and Bairlein, F., 2002, Ecological responses to recent climate change, Nature, 416, 389-395.
38
Yu, Z.-G., Leung, Y., Chen, Y. D., Zhang, Q., Anh, V. and Zhou, Y., 2014, Multifractal analyses of daily rainfall time series in Pearl River basin of China, Physica A: Statistical Mechanics and its Applications, 405, 193-202.
39
Zhang, Q., Xu, C.-Y. and Yang, T., 2009, Scaling properties of the runoff variations in the arid and semi-arid regions of China: a case study of the Yellow River basin, Stochastic Environmental Research and Risk Assessment, 23, 1103-1111.
40
Zhang, X., Zhang, G., Qiu, L., Zhang, B., Sun, Y., Gui, Z. and Zhang, Q., 2019, A Modified Multifractal Detrended Fluctuation Analysis (MFDFA) Approach for Multifractal Analysis of Precipitation in Dongting Lake Basin, China, Water, 11, 891.
41
ORIGINAL_ARTICLE
Dust Storms Trajectories and Identification of the Internal Sources over Hormozgan Province: A Case Study on Kohestak- Bandar Abbas, south of Iran
Today, the existence of numerous sources of dust production is one of the environmental challenges of Hormozgan province. Remote sensing and using MODIS data is one of the effective methods for the detection and mapping of dust storms. At first, meteorological data of all synoptic stations in the study area were collected and analyzed. According to the results, the highest frequency of dust occurrence is related to the three months of July, August, and May, which are in spring and summer. October, December and November have the lowest occurrence of dust storms in the study area. Also, autumn with 12.5% has the lowest occurrence of dust storms in all stations in the study area, and spring with 34.4%, and then summer with 33.6% has been recorded as the highest occurrence of the dust storms. This research monitors and evaluates four detecting algorithms for identification of plume and dust source and dust storm emission in the Kostak- Bandar Abbas area in the Hormozgan Province using MODIS satellite data and the HYSPLIT model. Ackerman’s model, Normalized Difference Dust Index (NDDI), Thermal-infrared Dust Index (TDI), and thermal Infrared Integrated Dust Index (TIIDI) were four Algorithm methods for dust source and plume identification using MODIS Level 1B and MODIS Level 2 data. The results show that all of the algorithms except NDDI were successful in detecting dust plumes, but the most effective algorithm for plumes identification varied from event to event. In addition, TDI is the best algorithm comparing its results with those of other three algorithms. The results show that there are a lot of dust sources in the study area that have many negative effects on other populated areas in the Hormozgan province and its neighboring areas. The results indicate that the Flood Plains Deposits (Qal3), Natural Levee Deposits (Qal2), and Coastal Dunes (Qdune) play the most important role in dust production in the study area. The HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) model was used to trace wind flow backward and forward to the study area. The results of the HYSPLIT model show that the dust particles are mainly transported to the study area from three main paths, namely, Northeastern, the West, and the Southwestern part of the study area. The results also, show that dust plumes lifted and dispersed towards different directions including the north and northeast with 30%, the south with 25%, and the east with 20% of the total events in the study period 2000 to 2018. In addition, the results show that the study area has a high potential for the occurrence of dust storms during the year as many dust hotspots have been identified in this area. Also, the occurrence of more than a decade of drought, the presence of erosion-sensitive formations, and the presence of erosion-sensitive sedimentary units in the study area and its surrounding areas, especially in the seasonal wetland Jazmourian has provided conditions to aggravate this situation. Due to the economic and tourism importance of cities such as Bandar Abbas, Qeshm, and Minab, and especially the industrial and economic region west of Bandar Abbas and the existence of active dust sources around this region, the need for executive operations and watershed management activities is highly recommended.
https://jesphys.ut.ac.ir/article_83558_27e8e2cde1078ce0e963290a641c3384.pdf
2021-11-22
501
518
10.22059/jesphys.2021.316614.1007275
Algorithm detector
HYSPLIT
MODIS
Minab
trajectory
Mahmood
Damizadeh
damizadeh@yahoo.com
1
Assistant Professor, Soil Conservation & Watershed Management Research Institute (SCWMRI), Tehran, Iran
LEAD_AUTHOR
Morteza
Miri
mmiri@ut.ac.ir
2
Assistant Professor, Soil Conservation & Watershed Management Research Institute (SCWMRI), Tehran, Iran
AUTHOR
Mehran
Zand
mehran.lashanizand@gmail.com
3
Associate Professor, Soil Conservation & Watershed Management Research Institute (SCWMRI), Tehran, Iran
AUTHOR
جبالی، ع.، اختصاصی، م. و جعفری، ر.، 1398، ارزیابی عملکرد الگوریتمهای آشکارساز طوفانهای گردوغبار در مناطق خشک (مطالعه موردی استان یزد). مجله علمی پژوهشی مهندسی اکوسیستم بیابان، سال هشتم، شماره 23، 85-105.
1
خیراندیش، ز.، بداق جمالی، ج. و رایگانی، ب.، 1397، شناسایی بهترین الگوریتم تشخیص گردوغبار با کمک دادههای مودیس، مجله مخاطرات محیط طبیعی، دوره هفتم، شماره 15، 205-218.
2
دمیزاده، م.، مهدوی، ر.، نوروزی، ع.، حلیساز، ا. و غلامی، ح.، 1400، آشکارسازی و واکاوی گردوغبار در استان هرمزگان، مجله مهندسی و مدیریت آبخیز،دوره 13، شماره 1، صص 111-124.
3
سبحانی، ب.، صفریان، ز.، و. و فیضالهزاده، س.، 1399، مدلسازی و پیشبینی گردوغبار در غرب ایران، پژوهشهای جغرافیای طبیعی، دورۀ 25 ، شمارۀ 1.
4
رایگانی، ب. و خیراندیش، ز.، 1396، بهرهگیری از سری زمانی دادههای ماهوارهای بهمنظور اعتبارسنجی کانونهای شناسایی شده تولید گردوغبار استان البرز، نشریه تحلیل فضایی مخاطرات طبیعی، سال چهارم شماره4، 18-1.
5
کارگر، ا.، بداقجمالی، ج.، رنجبرسعادتآبادی، ع.، معینالدینی، م. و گشتاسب، ح.، 1395، شبیهسازی و تحلیل عددی طوفان گردوغبار شدید شرق ایران، نشریه تحلیل فضایی مخاطرات محیطی، شماره4، 101-119.
6
قادرینسب، ف. و راهنما، م. ب.، 1397، آشکارسازی گردوغبار در حوضه آبریز جازموریان با استفاده از تکنیکهای چند طیفی در تصاویر سنجنده مودیس، مجله پژوهشهای جغرافیایی، دوره5 شماره 3، 545-562.
7
مهرابی، ش.، جعفری، ر.، سلطانیکویانی، س.، 1394، بررسی کارایی شاخص NDDI در پهنهبندی طوفان گردوغبار (مطالعۀ موردی: استان خوزستان)، مجله علمی پژوهشی مهندسی اکوسیستم بیابان، سال چهارم، شماره 8، 1-10.
8
ملکوتی، ح.، باباحسینی، س.، نوحهگر، ا.، آزادی، م. و محمدپور، م.، 1392، مطالعه همدیدی و عددی نشر، انتقال و شناسایی چشمه یک طوفان گردوغبارسنگین در منطقه خاورمیانه. فصلنامه علمی –پژوهشی پژوهشهای فرسایش محیطی سال سوم، شماره 12، 69-80.
9
Ackerman, S. A., 1997, Remote sensing aerosols using satellite infrared observations. Journal of Geophysical Research: Atmospheres 102(D14), 17069-17079.
10
Ackerman, S., Strabala, K., Menzel, W., Frey, R., Moeller, C., Gumley, L., Baum, B., Seemann, S. and Zhang, H., 2002, Discriminating clear-sky from cloud with MODIS—algorithm theoretical basis document. (MOD35), ATBD Reference Number: ATBD-MOD-06. Goddard Space Flight Center.
11
Baddock, M. C., Bullard, J. E. and Bryant, R. G., 2009, Dust source identification using MODIS: A comparison of techniques applied to the Lake Eyre Basin, Australia. Remote Sensing of Environment 113(7), 1511-1528.
12
Darmenov, A. and Sokolik, I. N., 2005, Identifying the regional thermal-IR radiative signature of mineral dust with Modis, Geophisical Research Letters, 32, 16803, doi: 10.1029/2005GL023092.
13
Hamish, M. and Andrew, C., 2008, Identification of dust transport pathways from Lake Eyre, Australia using Hysplit, Atmospheric Environment 42 (29) 6915-6925, doi.org/10.1016/j.atmosenv.2008.05.053
14
Ganbat, G. and Jugder, D., 2019, Observations and transport modeling of dust storm event over Northeast Asia using HYSPLIT.E3S Web of Conferences; Les Ulis Vol. 99, doi.org/10.1051/e3sconf/20199902002.
15
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16
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17
Karimi, K., Moridnejad, A., Golian, S., Mohammad Vali Samani, J., Karimi, D. and Javadi, S., 2012, Comparison of dust source identification techniques over land in the Middle East region using MODIS data. Canadian Journal of Remote Sensing, 38, 5, 586_599.
18
Khalidy, R., Salmabadi, H. and Saeedi, M., 2019, Numerical Simulation of a Severe Dust Storm over Ahvaz Using the HYSPLIT Model. International Journal of Environmental Research, 13, 161–174.
19
Lee, Y. C., Yang, X. and Wenig, M., 2010, Transport of dusts from East Asian and non-East Asian sources to Hong Kong during dust storm related events 1996- 2007. Atmospheric Environment. Vol. 44, 3728-3738.
20
Liu, Y. and Liu, R., 2011, A thermal index from modis data for dust detection, 2011 IEEE International Geoscience and Remote Sensing Symposium, Vancouver, BC, Canada.
21
Miller, S. D., 2003, A consolidated technique for enhancing desert dust storms with MODIS, Geophysical Research Letters 30(20).
22
Mohamed, F. Y., Sarah K. A. and Ali A. H., 2018, Dust storms backward Trajectories' and source identification over Kuwait. Atmospheric Research, Vol. 212, 158-171.
23
Qu, J. J., Hao, X., Kafatos, M. and Wang, L., 2006, Asian dust storm monitoring combining Terra and Aqua MODIS SRB measurements. IEEE Geoscience and Remote Sensing Letters 3(4), 484-486.
24
Rajaee, T., Rohani, N., Jabbari, E. and Mojaradi, B., 2020, Tracing and assessment of simultaneous dust storms in the cities of Ahvaz and Kermanshah in western Iran based on the new approach. Arabian Journal of Geosciences,13,461.
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26
Sarikhani, A., Dehghani, M., Karimi-Jashni, A. and Saadat, S., 2020, A New Approach for Dust Storm Detection Using MODIS Data. Iranian Journal of Science and Technology, Transactions of Civil Engineering.
27
Sugimoto, N., Shimizu, A., Nishizawa1, T., Jin, Y. and Yumimoto, K., 2020, Long-Range-Transported Mineral Dust from Africa and Middle East to East Asia Observed with the Asian Dust and Aerosol Lidar Observation Network (AD-Net). The 29th International Laser Radar Conference (ILRC 29), 237, https://doi.org/10.1051/epjconf/202023705009
28
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29
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30
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31
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32
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33
ORIGINAL_ARTICLE
The general circulation of the atmosphere in the North Atlantic and Pacific and its relationship with development and strengthening the Azores and Hawaiian subtropical anticyclones
Subtropical anticyclones are among the large-scale atmospheric centers of action in the northern hemisphere in the east of the oceans. Clockwise flow and high surface pressure are two prominent features of these systems. These systems have an annual trend and usually achieve maximum flow and surface pressure in the summer, especially in July. Understanding the factors influencing the development and intensification of these anticyclones has been the favorite of many researchers. One of these factors has been the general circulation of the atmosphere. In this study, a climatological study of the general atmospheric circulation, including the Hadley and Walker circulations, has been performed. Their role in the development and strengthening of subtropical anticyclones has been investigated. The research has been done in three parts; 1- Mean Meridian Circulation, 2- meridional circulation in the North Atlantic and Pacific, and 3- Walker circulation in the North Atlantic and Pacific. In this study, the meridional component of wind, vertical velocity (omega), and horizontal wind divergence have been used. Data at 27 pressure levels with a horizontal resolution of 0.25 × 0.25 ° were extracted from the European Center for Medium Weather Forecasting (ECMWF) and the ERA5 version. The monthly mean of the data used was conducted over 40 years, from 1979 to 2018. The Mass Stream Function (MSF) method has been used to quantify the meridional and walker circulation.The Mean Meridian Circulation showed that the meridional circulation in the equinox months consists of a pair of Hadley cells in which air rises in the tropics and subsides in the subtropics. Also, a solstitial cell is found with the ascent in the outer tropics of the summer hemisphere and subsidence in the outer tropics of the winter hemisphere. Although the Mean Meridional Circulation showed that mass transfer takes place in the summer of the Northern Hemisphere to the Southern Hemisphere and the Hadley circulation could not explain and justify the maximum activity of the subtropical anticyclones, but the meridional circulation at smaller cross-sections in the East Atlantic and Pacific showed that the Hadley cells play a vital role in mass transfer to the subtropics and mid-latitudes. The mean walker circulation (20-40 ° N) showed that the source of this circulation is only the latent heat released over the waters and the lands of the western oceans that have no role in mass transfer to the east. Westerly and southwesterly winds also form mass transfer in the Walker circulation to the northeast of the oceans. Heating in northwestern Africa and North America is another phenomenon that plays a role in subsidence in the North Atlantic and Pacific. The subsidence induced from heating on African lands is much more severe than that in North America. This may depend on the climate and extent of these areas. Therefore, as a result of this research, it can be said that three processes: Hadley circulation, Walker circulation, and heating on the lands adjacent to the eastern oceans, are effective in mass transfer and subsidence in the east Atlantic and Pacific. These conditions form strong northerly winds in the eastern oceans and trade winds in the tropics and effectively develop and strengthen subtropical anticyclones.
https://jesphys.ut.ac.ir/article_81513_8bc0e361fdcc71e40142d92a914c007a.pdf
2021-11-22
519
536
10.22059/jesphys.2021.318963.1007291
General Circulation
Hadley Cell
Mass Stream Function
Subtropical Anticyclone
Walker circulation
Ali Akbar
Garmsiri Mahvar
amahvar@ut.ac.ir
1
Ph.D. Student, Department of Physical Geography, Faculty of Geography, University of Tehran, Tehran, Iran
AUTHOR
Ghasem
Azizi
ghazizi@ut.ac.ir
2
Professor, Department of Physical Geography, Faculty of Geography, University of Tehran, Tehran, Iran
LEAD_AUTHOR
Hosein
Mohammadi
hmmohammadi@ut.ac.ir
3
Professor, Department of Physical Geography, Faculty of Geography, University of Tehran, Tehran, Iran
AUTHOR
Mostafa
Karimi Ahmadabad
mostafakarimi.a@ut.ac.ir
4
Assistant Professor, Department of Physical Geography, Faculty of Geography, University of Tehran, Tehran, Iran
AUTHOR
حجازیزاده، ز.، 1372، بررسی نوسانات فشار زیاد جنبحاره در تغییر فصل ایران، رساله دکتری جغرافیای طبیعی، دانشگاه تربیت مدرس.
1
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2
علیپور، ی.، حجازیزاده، ز.، اکبری، م. و سلیقه، م.، 1397، بررسی تغییرات پرفشار جنبحاره تراز 500 هکتوپاسکال نیوار ایران با رویکرد تغییر اقلیم، م. مخاطرات محیط طبیعی، 18(7)، 1-16.
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لشکری، ح.، متکان، ع. ا.، آزادی، م. و محمدی، ز. 1396، تحلیل همدیدی نقش پرفشار جنبحارهای عربستان و رودباد جنبحارهای در خشکسالیهای شدید جنوب و جنوب غرب ایران، م. پژوهشهای دانش زمین، 2(8)، 141-163.
5
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6
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Chang, E. K., 1995, The influence of Hadley circulation intensity changes on extratropical climate in an idealized model. Journal of the atmospheric sciences, 52(11), 2006-2024.
9
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10
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11
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12
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13
Dima, I. M., 2005, An observational study of the tropical tropospheric circulation (Doctoral dissertation).
14
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15
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16
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19
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20
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21
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27
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28
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Oort, A. H. and Yienger, J. J., 1996, Observed interannual variability in the Hadley circulation and its connection to ENSO. Journal of Climate, 9(11), 2751-2767.
32
Peixoto, J. P. and Oort, A. H., 1992, Physics of climate, 520pp., Am. Inst. of Phys., New York.
33
Rodwell, M. J. and Hoskins, B. J., 2001, Subtropical anticyclones and summer monsoons. Journal of Climate, 14(15), 3192-3211.
34
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35
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37
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40
ORIGINAL_ARTICLE
Calculating magnetic activity cycle of M-type dwarf stars using GLS technique and index-H_α; Proxima Centauri
The study of the existence of life or habitable zone somewhere in the universe, beyond the Earth, has been one of the important research areas in the field of astronomy and astrophysics in the last few decades. Countless studies have been done and are being done theoretically and experimentally.Proxima Centauri () with visual magnitude of 11.01 and at a distance of 1.3 pc is the closest star to Earth after the Sun and is especially important for our knowledge of very cool stars. This M5.5V spectral type star is the faintest member of the Alpha Centauri ternary star system, located about 1400 astronomical units closer to Earth than the other members. The physical characteristics of this star, including radius (), mass (, rotational periodicity (1.5 35) and its age, which is about 4.85 billion years old, are well determined. Despite its old age, Proxima Centauri is an active star, and like the sun it has activity cycle (the activity cycle of the sun is about 11 years).Generally, M-type stars are hard to study due to their optical faintness. But Studying Proxima Centauri can improve our knowledge of very cool stars as its proximity lets us to observe it with great accuracy. Moreover, its similarity to the sun and the possibility of having a system of planets around it and consequently the study of life on these planets is of particular importance.This paper aims to determine the activity cycle of Proxima Centauri star using spectral line and to evaluate the generalized Lamb-Scargel periodogram technique (GLS) to determine the period of active dwarf stars, including Proxima Centauri.The GLS is an extension to the Lomb-Scargle periodogram which takes into account the measurement of errors and also is more suitable for time series with non-zero average. GLS tries to fit the sinusoidal equation to the time series and find the power spectrum for frequencies. We consider a given periodogram peak, derived from GLS, significant when it exceeds the one present “false alarm probability” level (FAP), which means there is 99% confidence that it is real and could not be simulated by Gaussian noise. FAP levels are calculated by performing random permutations of the data with similar times of observations.For this purpose, we used HARPS spectroscopic data over a period from 2004 to 2017. HARPS, the High Accuracy Radial velocity Planet Searcher at the European Southern Observatory La Silla 3.6m Cassegrain telescope is dedicated to the discovery of extrasolar planets. It is a fibre-fed high resolution echelle spectrograph. This instrument is used to accurately measure radial velocities of the order of 1 m/s in extrasolar planet research. The spectral area is 378-691 nm and its resolution 115,000. Therefore, from this point of view, we can say that our analysis is more accurate than others.The magnetic activity period of Proxima Centauri is obtained as 2349 days, which is in good agreement with the results obtained from other methods. Therefore, our results confirm the efficiency and superiority of the generalized Lamb-Scargel periodogram technique in determining the period of active cool dwarf stars.
https://jesphys.ut.ac.ir/article_81515_aa7e7473f270a730a433447975fcd903.pdf
2021-11-22
537
545
10.22059/jesphys.2021.318861.1007292
Cool dwarfs
Active star
Period
Periodogram technique
Proxima Centauri
Fatemeh
Azizi
f.azizi@pnu.ac.ir
1
Assistant Professor, Department of Physics, Payame Noor University, Tehran, Iran
LEAD_AUTHOR
Rahimeh
Foroughi
r.froghi@gmail.com
2
M.Sc. Graduated, Department of Physics, Payame Noor University, Tehran, Iran
AUTHOR
عزیزی، ف. و میرترابی، م. ت.، ۱۳۹۸، محاسبه دورهتناوب ستارههای متغیر دلتا اسکوتی با استفاده از تکنیک تناوبنگار لمب-اسکارگل تعمیمیافته، م. فیزیک زمین و فضا، ۴۵، ۸۸-۸۱.
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36
ORIGINAL_ARTICLE
The Effect of Jet Stream Width on the Growth of Baroclinic Waves
In this study, the effect of jet width on baroclinic instability is discussed, while a baroclinic instability problem is solved using a quasi-geostrophic (QG) model on a β-plane. To solve the QG equations on the β-plane, the finite difference method is applied in the vertical and meridional directions. Boundary conditions in this problem are considered for both vertical and meridional directions. Indeed, two hard boundaries at the surface of the Earth and tropopause are chosen for the vertical, with non-flux conditions at the upper and lower boundaries along the meridian. After discretization along both meridian and vertical directions, the equation takes the form of Sturm–Liouville, particularly the eigenvalue of the resulting Sturm – Liouville equation is the imaginary part of the phase velocity. Using the Matlab software, the eigenvalue instability equation can be solved. In this study, the effect of jet stream width on baroclinic instability is investigated. In addition, jet streams with different widths are defined and the growth rate of atmospheric waves is calculated.The jet stream equation has a sinusoidal shape in the meridional direction, but an exponential form in the vertical, in which the jet width is adjusted using the sine-wave parameter. Once built according to the desired width, the problem is solved and the rate of the growth of atmospheric waves is obtained. The jet has a limited effect on the growth of atmospheric waves. The effect of the jet on the baroclinic instability is such that a disturbance with meridional wavenumber is imposed on the problem. The meridional wavenumber causes a decrease of the growth rate at the desired zonal wavenumber. For this reason, we conclude that the jet has a limited effect on the growth rate of baroclinic instability. The effect of the width on baroclinic instability is identified in a two-dimensional model, in which the vertical extent is an independent variable in the problem, such that the solution is very similar to the combination of Eady (1949) and Charney (1947) models. Using a quasi-terrestrial linear model, they concluded that jet streams width, increases the growth rate of waves. Their results are inconsistent with ours due to application of one-dimensional model in their study. They noted that jet stream introduces increasing or decreasing wind shear, and with increasing wind shear, an increasing growth rate of baroclinic instability is observed. However, this result cannot be generalized for a two-dimensional problem, in which for a range of latitudes, which is called a channel, the jet velocity at the bottom of the channel starts from a minimum, but increases to the maximum value in the middle of the channel and again decreases to the same value at the top of the channel. However, in a one-dimensional problem, only the jet stream core is considered, such that baroclinic instability is solved only on the vertical direction in the jet core. Thus, the effect of jet stream on baroclinic instability in a two-dimensional framework is conducted here. The instability problem is solved using the jet stream shown in Figure 1. According to Lindzen (1993), in the presence of a jet stream, the meridional wavenumber is equivalent to the inverse of the width of the jet, which increases as the jet width decreases, such that an increase in the meridional wavenumber is associated with a slowdown of the jet stream, following Eady (1949). Initially, by reducing the jet width to 2400 kilometers, the growth rate also decreases. However, reduction of the jet width to a certain extent (i.e., 3240 km) results in a decrease of the growth rate, while further decrease of the jet width is associated with an increase of the growth rate (e.g., for jet stream with widths of 2400 and 1710 km). Thus, the widest jet stream is associated with the maximum growth rate for wavenumbers between 6 and 13, while the narrowest jet stream is associated with the maximum growth rate for wavenumbers between 13 and 20.The relationship between the jet bandwidth and velocity of the jet center based on observational data over the Pacific is discussed below. A linear relationship (34) is obtained between velocity of the jet core and the observed jet width. Velocity of the jet core increases with the decline of the jet width (Table 4). Width and velocity of the jet in Table 4 are plotted in the numerical scheme, in which real and imaginary parts of the phase velocity are calculated when the jet core velocity is increased following a decrease of the jet width, which results in an enhancing of the growth of atmospheric waves. Therefore, under real conditions, in which width and velocity of the jet core are represented in Table 3, a meridional constraint can no longer be introduced.
https://jesphys.ut.ac.ir/article_83557_147a3bf4b19070dc5125e417d5d784dd.pdf
2021-11-22
547
560
10.22059/jesphys.2021.319124.1007294
jet stream
meridional wavenumber
β-plane
baroclinic instability
Sturm-Liouville equation
Ahmad
Zadegh Abadi
amirabbas7463@yahoo.com
1
Ph.D. Student, Department of Marine and Atmospheric Science (Non-Biologic), Faculty of Marine Science and Technology, University of Hormozgan, Bandarabbas, Iran
AUTHOR
Maryam
Rezazadeh
rezazadeh@hormozgan.ac.ir
2
Assistant Professor, Department of Marine and Atmospheric Science (Non-Biologic), Faculty of Marine Science and Technology, University of Hormozgan, Bandarabbas, Iran
LEAD_AUTHOR
Ali
Mohammadi
ali.mohammadi1964@gmail.com
3
Assistant Professor, Department of Marine Science, Imam Khomeini University of Marine Sciences, Noshahr, Iran
AUTHOR
Chang, E. K. M., 2001, GCM and observational diagnoses of the seasonal and interannual variations of the Pacific storm track during the cool season, J. Atmos. Sci., 58, 1784–1800.
1
Charney, J. G., 1947, The dynamics of long waves in a baroclinic westerly current, Journal of Meteorology., 4,136-162.
2
Eady, E. T., 1949, Long waves and cyclone waves, Tellus, 1, 33-52.
3
Grotjahn, R., 2003, Baroclinic instability. Encyclopedia of Atmospheric Sciences, 419, 467.
4
Harnik, N. and Chang, E.K., 2004, The effects of variations in jet width on the growth of baroclinic waves: Implications for midwinter Pacific storm track variability, J. Atmos. Sci., 61, 23-40.
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12
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13
ORIGINAL_ARTICLE
Projected consecutive dry and wet days in Iran based on CMIP6 bias‐corrected multi‐model ensemble
Climate change with changes in precipitation patterns around the world can cause significant changes in the frequency, intensity and duration of precipitation events. In the context of climate change and with the increase of extreme climate events, irreparable consequences are imposed on the environment and the economy. Therefore, it is necessary to have an appropriate understanding of the frequency, intensity and spatial distribution of these extreme events in order to take a fundamental step in preventing damage caused by them. The purpose of this study is to analyze the characteristics of consecutive dry/wet days during 1975-2014 and 2021-2100 based on the output of CMIP6 models. In this regard, the evaluation of CMIP6 models against gauge precipitation data has been done in Iran.In this study, historical precipitation (1975-2014) and scenarios-based output of CMIP6 models under shared socioeconomic pathways (SSPs) in the two future periods (2021-2060 and 2061-2100) were used. Basic statistics of r, RMSE, MBE and receiver operating characteristic (ROC) were used to validate the precipitation output of selected models (GFDL-ESM4, IPSL-CM6A-LR, MPI-ESM1-2-HR, MRI-ESM2-0, UKESM1-0-LL). Then, consecutive dry and wet days were calculated using the CDD and CWD indices of the Expert team on climate change detection and indices (ETCCDI). After examining each individual model, an ensemble model is applied with independent weighted mean (IWM) method.The results showed that among the five CMIP6 models, the IPSL-CM6A-LR model has the most underestimation and the UKESM1-0-LL has the most overestimation for Iran precipitation. The average amount of precipitation bias in the whole country for GFDL-ESM4 (2.56), IPSL-CM6A-LR (2.29), MPI-ESM1-2-HR (2.89), MRI-ESM2-0 (2.18), and UKESM1-0-LL (2.53) mm were calculated. The skill score is improved significantly by applying the multi model ensemble (MME). Consecutive dry days in Iran will increase by a maximum of 26.4 days under the SSP5-8.5 scenario in the period 2061-2100 for the Caspian Sea and Lake Urmia basins. In contrast, consecutive wet days will decrease in these two basins.Validation results for the period of 1975-2014 showed that (compared to observations), CMIP6 models have a high performance in estimating precipitation in Iran. However, despite the uncertainties in precipitation change, the CMIP6 results provide evidence that the anomaly of consecutive dry and wet periods is an indicator for short-term droughts under increasing climate change conditions. Consecutive dry days will increase significantly in the north and northwest of Iran in the future.The maximum changes related to CDD and CWD indices are observed under SSP5–8.5 scenario, while the lowest frequency for both indices is under SSP1–2.6 scenario. Examination of CDD and CWD anomalies showed that even in the optimistic scenario (SSP1-2.6), drought responses to climate change are significant. Consecutive dry periods are increasing in most of the northern, northwestern and northeastern regions of Iran. It is urgent to consider these changes in the hydrological cycle as a tool to improve water management, especially in the northern and northwestern regions of Iran. Also, in some areas, such as the southeast and the coasts of the Persian Gulf, there is a significant decrease in consecutive dry periods, which indicates an increase in precipitation on a seasonal and inter-annual scale in the future.
https://jesphys.ut.ac.ir/article_81514_07c61dfa8e459a5a9fce4745f2603d00.pdf
2021-11-22
561
578
10.22059/jesphys.2021.319270.1007295
Precipitation
CMIP6
SSP Scenarios
consecutive dry and wet days
Azar
Zarrin
zarrin@um.ac.ir
1
Assistant Professor, Department of Geography, Ferdowsi University of Mashhad, Mashhad, Iran
LEAD_AUTHOR
Abbas Ali
Dadashi-Roudbari
a-dadashi@um.ac.ir
2
Post-Doc Researcher, Department of Geography, Ferdowsi University of Mashhad, Mashhad, Iran
AUTHOR
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Ahmadi, H., Rostami, N. and Dadashi-roudbari, A., 2020, Projected climate change in the Karkheh Basin, Iran, based on CORDEX models. Theoretical and Applied Climatology, 142(1), 661-673.
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10
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Bai, H., Xiao, D., Wang, B., Liu, D. L., Feng, P. and Tang, J., 2020, Multi‐model ensemble of CMIP6 projections for future extreme climate stress on wheat in the North China Plain. International Journal of Climatology.
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Bishop, C. H. and Abramowitz, G., 2013, Climate model dependence and the replicate Earth paradigm. Climate dynamics, 41(3-4), 885-900.
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Brown, P. J., Bradley, R. S. and Keimig, F. T., 2010, Changes in extreme climate indices for the northeastern United States, 1870–2005. Journal of Climate, 23(24), 6555-6572.
15
Duan, Y., Ma, Z. and Yang, Q., 2017, Characteristics of consecutive dry days variations in China. Theoretical and Applied Climatology, 130(1-2), 701-709.
16
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J. and Taylor, K. E., 2016, Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geoscientific Model Development, 9(5), 1937-1958.
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ORIGINAL_ARTICLE
Troposphere Electromagnetic Intensification in Enhancing Percipitation
Decreased precipitation and water scarcity are some of the important challenges in most parts of Iran in recent years and need a cost-effective solution based on high technical knowledge and equipment; To improve the meteorological conditions with modern technologies, one can use the high voltage injection air ionization equipment. The result efficiently can increase cloud-water vapor concentration nuclei due to generate duplex clouds. Recent theoretical and experimental work suggests that a charged atmosphere will have a lower nucleation barrier and will also help stabilize embryonic particles. This allows nucleation to occur at lower vapor concentrations and demonstrates that charged particle and molecular clusters, condensing around natural air ions can grow significantly faster than corresponding neutral clusters. The theoretical dynamic locating of the injection model also indicates that the nucleation rate of particles in the non-charged regions (without injection) is limited by the ion production rate from other sources such as cosmic rays. Thus, stable charged particle concentration by injection resulting from condensation and growth can survive long after ion injection and ionization. Theoretical study of dynamic locating of injection model establishes a relationship between the dynamic locating electromagnetic region of changing point ionization and precipitation microphysics. Mechanism troposphere ionization and the Earth electromagnetic field properties cannot be excluded and there are established electrical effects on precipitation microphysics. Building on the relationship between changing points and ion injection the observations are extended to the realm of electromagnetic field microphysics by exploring this model. The injection produces positive /negative ions and free electrons. Many of these ions will be quickly lost to ion-ion recombination. Some of the ions escape recombination or reduced ion concentrations because the ionization produced by the electric field often is decreased because of the dust storm or wind that are generated in fixed changing points. As we presented in this article, dynamic locating of injection in the troposphere is very important to provide additive effects increasing cloud concentrations and generating precipitation, which is the main achievement of this analytical-simulation work. In this analytical-simulation study, which is based on real and experimental data taken from the western and southwestern regions of Iran, we first review the background of the results obtained from the injection process and the effect of generating clouds in the troposphere. Then we obtain the results of the same data with the theoretical effect of dynamic locating and simulation with injection at the electromagnetic changing points. The results of the previous data assuming maximization of utility have been recalculated and compared. The injection results are optimized by a dynamic locating technique that affects utility indices of maximum electromagnetic changing field between troposphere-ground the earth thickness. Due to the increased generation of rainy clouds and maximization of their concentrations and increased local precipitation by the dynamic locating method at the injection site and the optimal operation of the equipment is investigated. The theoretical model that is presented shows that the theoretical dynamic locating of injection model by increasing in ionizing effect leads to a 15-20% increase in precipitation, decrease of 11% in temperature, increase of 10% in humidity.
https://jesphys.ut.ac.ir/article_81537_fb4fefb2216d0f3c17e1d7d7fa467bbf.pdf
2021-11-22
579
593
10.22059/jesphys.2021.321569.1007310
Electromagnetic Intensification
Precipitation
Cloud Generating
Electromagnetic Injection
Dynamic Locating
Arezu
Jahanshir
aresuj@gmail.com
1
Assistant Professor, Department of Physics and Engineering Sciences, Imam Khomeini International University, Buein Zahra Higher Education Centre of Engineering and Technology, Buein Zahra, Iran
LEAD_AUTHOR
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