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<ArticleSet>
<Article>
<Journal>
				<PublisherName>مؤسسه ژئوفیزیک دانشگاه تهران</PublisherName>
				<JournalTitle>فیزیک زمین و فضا</JournalTitle>
				<Issn>2538-371X</Issn>
				<Volume>47</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2022</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>On the Propagation of VLF Electric Field Emissions Associated with Earthquakes in the Middle Layer of the Earth Crust</ArticleTitle>
<VernacularTitle>On the Propagation of VLF Electric Field Emissions Associated with Earthquakes in the Middle Layer of the Earth Crust</VernacularTitle>
			<FirstPage>1</FirstPage>
			<LastPage>13</LastPage>
			<ELocationID EIdType="pii">81560</ELocationID>
			
<ELocationID EIdType="doi">10.22059/jesphys.2021.298662.1007196</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Sarita</FirstName>
					<LastName>Sharma</LastName>
<Affiliation>Research Scholar, Department of Physics, Institute of Applied Sciences &amp; Humanities, GLA University, Mathura, India</Affiliation>

</Author>
<Author>
					<FirstName>Raj Pal</FirstName>
					<LastName>Singh</LastName>
<Affiliation>Professor, Department of Physics, Institute of Applied Sciences &amp; Humanities, GLA University, Mathura, India</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2020</Year>
					<Month>03</Month>
					<Day>05</Day>
				</PubDate>
			</History>
		<Abstract>An ensemble of elementary radiators is generated on the basement rock because of the applied stresses in the preparation zone of the earthquakes in the earth crust. Considering such an ‘ensemble’ as the source of electromagnetic signals, the strength of the electric field is estimated at different distances and frequencies laying in range (3 – 27 kHz) at three different conductivities of the crustal layers (10&lt;sup&gt;-8&lt;/sup&gt;, 10&lt;sup&gt;-9&lt;/sup&gt;, 10&lt;sup&gt;-10 &lt;/sup&gt;S/m). The results of the computation are presented in this paper. Moreover, propagation distances for the seismogenic VLF emissions have also been calculated in the frequency band (3 – 27 kHz) at the conductivities laying in the range (10&lt;sup&gt;-8 &lt;/sup&gt;- 10&lt;sup&gt;-10 &lt;/sup&gt;S/m) within the limit of detectability of measuring instruments (10&lt;sup&gt;-7&lt;/sup&gt; V/m). It is observed that these distances increase with the decrease of conductivity of the middle layer of crust. Furthermore, theoretical results of computations are verified from the experimental observations of the seismic event that occurred at the distance of 698 km from the observing station at Chaumuhan Mathura (Geographic lat. 27.49&lt;sup&gt;0&lt;/sup&gt;N, long. 77.67&lt;sup&gt;0&lt;/sup&gt;E). In addition to this, the generation and propagation mechanisms of seismo-electromagnetic radiations have also been discussed briefly.</Abstract>
			<OtherAbstract Language="FA">An ensemble of elementary radiators is generated on the basement rock because of the applied stresses in the preparation zone of the earthquakes in the earth crust. Considering such an ‘ensemble’ as the source of electromagnetic signals, the strength of the electric field is estimated at different distances and frequencies laying in range (3 – 27 kHz) at three different conductivities of the crustal layers (10&lt;sup&gt;-8&lt;/sup&gt;, 10&lt;sup&gt;-9&lt;/sup&gt;, 10&lt;sup&gt;-10 &lt;/sup&gt;S/m). The results of the computation are presented in this paper. Moreover, propagation distances for the seismogenic VLF emissions have also been calculated in the frequency band (3 – 27 kHz) at the conductivities laying in the range (10&lt;sup&gt;-8 &lt;/sup&gt;- 10&lt;sup&gt;-10 &lt;/sup&gt;S/m) within the limit of detectability of measuring instruments (10&lt;sup&gt;-7&lt;/sup&gt; V/m). It is observed that these distances increase with the decrease of conductivity of the middle layer of crust. Furthermore, theoretical results of computations are verified from the experimental observations of the seismic event that occurred at the distance of 698 km from the observing station at Chaumuhan Mathura (Geographic lat. 27.49&lt;sup&gt;0&lt;/sup&gt;N, long. 77.67&lt;sup&gt;0&lt;/sup&gt;E). In addition to this, the generation and propagation mechanisms of seismo-electromagnetic radiations have also been discussed briefly.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Attenuation</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">earthquake</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Earth crust</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Radiating dipole</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">VLF waves</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jesphys.ut.ac.ir/article_81560_f54bbcd35bc96dd1b02efd720b67fffd.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>مؤسسه ژئوفیزیک دانشگاه تهران</PublisherName>
				<JournalTitle>فیزیک زمین و فضا</JournalTitle>
				<Issn>2538-371X</Issn>
				<Volume>47</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2022</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>The 2007 Kahak and 2010 Kazerun Earthquakes: Constrained Non-Negative Least-Squares Linear Finite Fault Inversion for Slip Distribution</ArticleTitle>
<VernacularTitle>The 2007 Kahak and 2010 Kazerun Earthquakes: Constrained Non-Negative Least-Squares Linear Finite Fault Inversion for Slip Distribution</VernacularTitle>
			<FirstPage>15</FirstPage>
			<LastPage>30</LastPage>
			<ELocationID EIdType="pii">79633</ELocationID>
			
<ELocationID EIdType="doi">10.22059/jesphys.2021.303882.1007222</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Sonia</FirstName>
					<LastName>Bazargan</LastName>
<Affiliation>M.Sc. Graduated, Department of Seismology, Institute of Geophysics, University of Tehran, Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Zaher Hossein</FirstName>
					<LastName>Shomali</LastName>
<Affiliation>Associate Professor, Department of Seismology, Institute of Geophysics, University of Tehran, Tehran, Iran</Affiliation>
<Identifier Source="ORCID">0000-0001-6254-7560</Identifier>

</Author>
<Author>
					<FirstName>Mehdi</FirstName>
					<LastName>Rezapour</LastName>
<Affiliation>Professor, Department of Seismology, Institute of Geophysics, University of Tehran, Tehran, Iran</Affiliation>
<Identifier Source="ORCID">0000-0002-8112-7083</Identifier>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2020</Year>
					<Month>06</Month>
					<Day>08</Day>
				</PubDate>
			</History>
		<Abstract>Here we study slip distribution of the June 18, 2007 M&lt;sub&gt;w &lt;/sub&gt;5.5 Kahak and September 27, 2010 M&lt;sub&gt;w &lt;/sub&gt;5.9 Kazerun earthquakes by using constrained non-negative least-squares linear slip inversion method for regional broadband seismic data. Hundreds of inversions were carried out to obtain the optimal parameters used in the process, including rupture velocity and rise time. We used the rupture velocity of 2.6 km/s (0.75 Vs) and the rise time of 1.4 s for the first event, and 2.8 km/s (0.75 Vs) and 2.1 s for the second one. Results show the rupture with the peak slip of 8.6 cm and 14.3 cm, and the total seismic moment release of 1.59×10&lt;sup&gt;24&lt;/sup&gt; dyne-cm and 2.80×10&lt;sup&gt;25&lt;/sup&gt; dyne-cm for the Kahak and Kazerun earthquakes, respectively. Owing to the non-uniqueness of the inversion problem, we presented a set of solutions for both events. Furthermore, the sensitivity of the slip models to some influential parameters such as rupture velocity and rise time was explored. Moreover, we used two ways for identifying the main/preferred fault plane, which are compatible with one another: First, discerning the main fault plane by using the slip inversion method; second, distinguishing the main fault plane by the use of aftershocks. To the best of our knowledge, this is the first time to apply the linear finite-fault inversion method to moderate earthquakes in Central Iran and Zagros seismotectonic provinces to model a set of rupture histories at regional distances.</Abstract>
			<OtherAbstract Language="FA">Here we study slip distribution of the June 18, 2007 M&lt;sub&gt;w &lt;/sub&gt;5.5 Kahak and September 27, 2010 M&lt;sub&gt;w &lt;/sub&gt;5.9 Kazerun earthquakes by using constrained non-negative least-squares linear slip inversion method for regional broadband seismic data. Hundreds of inversions were carried out to obtain the optimal parameters used in the process, including rupture velocity and rise time. We used the rupture velocity of 2.6 km/s (0.75 Vs) and the rise time of 1.4 s for the first event, and 2.8 km/s (0.75 Vs) and 2.1 s for the second one. Results show the rupture with the peak slip of 8.6 cm and 14.3 cm, and the total seismic moment release of 1.59×10&lt;sup&gt;24&lt;/sup&gt; dyne-cm and 2.80×10&lt;sup&gt;25&lt;/sup&gt; dyne-cm for the Kahak and Kazerun earthquakes, respectively. Owing to the non-uniqueness of the inversion problem, we presented a set of solutions for both events. Furthermore, the sensitivity of the slip models to some influential parameters such as rupture velocity and rise time was explored. Moreover, we used two ways for identifying the main/preferred fault plane, which are compatible with one another: First, discerning the main fault plane by using the slip inversion method; second, distinguishing the main fault plane by the use of aftershocks. To the best of our knowledge, this is the first time to apply the linear finite-fault inversion method to moderate earthquakes in Central Iran and Zagros seismotectonic provinces to model a set of rupture histories at regional distances.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Kahak earthquake</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Kazerun earthquake</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Seismic Data</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">slip inversion</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">finite-fault modeling</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jesphys.ut.ac.ir/article_79633_c8f337c2aa97e90f58ff344987a53f89.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>مؤسسه ژئوفیزیک دانشگاه تهران</PublisherName>
				<JournalTitle>فیزیک زمین و فضا</JournalTitle>
				<Issn>2538-371X</Issn>
				<Volume>47</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2022</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Groundwater Prospectivity Mapping Using Integrated GIS, Remote Sensing, and Geophysical Techniques; A Case Study From Northeastern Nigeria</ArticleTitle>
<VernacularTitle>Groundwater Prospectivity Mapping Using Integrated GIS, Remote Sensing, and Geophysical Techniques; A Case Study From Northeastern Nigeria</VernacularTitle>
			<FirstPage>31</FirstPage>
			<LastPage>73</LastPage>
			<ELocationID EIdType="pii">81559</ELocationID>
			
<ELocationID EIdType="doi">10.22059/jesphys.2021.311147.1007253</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Abubakar</FirstName>
					<LastName>Yusuf</LastName>
<Affiliation>Ph.D. Student, School of Physics, University Sains Malaysia, Penang, Malaysia</Affiliation>

</Author>
<Author>
					<FirstName>Hwee San</FirstName>
					<LastName>Lim</LastName>
<Affiliation>Associate Professor, School of Physics, University Sains Malaysia, Penang, Malaysia</Affiliation>
<Identifier Source="ORCID">0000-0002-4835-8015</Identifier>

</Author>
<Author>
					<FirstName>Ismail</FirstName>
					<LastName>Ahmad Abir</LastName>
<Affiliation>Assistant Professor, School of Physics, University Sains Malaysia, Penang, Malaysia</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2020</Year>
					<Month>10</Month>
					<Day>06</Day>
				</PubDate>
			</History>
		<Abstract>An integrated GIS, Remote sensing, and Geophysical techniques have been successfully applied to generate the previously non-available groundwater prospectivity map for the present study area. Selected thematic maps were integrated using the weighted sum tool of the spatial analyst tool of the ArcGIS software. The five thematic maps used are: lithology map, drainage density map, slope map, lineaments density map, and the topographic map of the area. The groundwater prospectivity map generated was reclassified into low, moderate, high, and very high potential zones on the basis of their assigned layer rank, which also depends on their degree of influence on groundwater occurrence. Areas around Gombe, Wuyo, Deba, Alkaleri, Kaltungo, Misau, Nafada, Bajoga towns are the regions that showed very high prospects for groundwater occurrence. Data processing filters such as: horizontal derivatives, Analytic signal processing, 3D-Euler depth estimation was applied on the magnetic data in order to map structures and lithologic contacts before its subsequent integration with other structural lineaments as a thematic layer. Vertical Electrical Sounding (VES) data were used to compute hydraulic conductivity, and Transmisivity etc. for the acquiferous layers identified. The results of the present study showed some regions that are classified as highly prospective to be consistent with high transmisivity and high yield values. The final outcome (groundwater potential map) of this research demonstrated that GIS/remote sensing, and the geophysical technique employed is a very powerful tool for generating groundwater prospectivity map, which is very vital in terms of planning for groundwater exploration and exploitation.</Abstract>
			<OtherAbstract Language="FA">An integrated GIS, Remote sensing, and Geophysical techniques have been successfully applied to generate the previously non-available groundwater prospectivity map for the present study area. Selected thematic maps were integrated using the weighted sum tool of the spatial analyst tool of the ArcGIS software. The five thematic maps used are: lithology map, drainage density map, slope map, lineaments density map, and the topographic map of the area. The groundwater prospectivity map generated was reclassified into low, moderate, high, and very high potential zones on the basis of their assigned layer rank, which also depends on their degree of influence on groundwater occurrence. Areas around Gombe, Wuyo, Deba, Alkaleri, Kaltungo, Misau, Nafada, Bajoga towns are the regions that showed very high prospects for groundwater occurrence. Data processing filters such as: horizontal derivatives, Analytic signal processing, 3D-Euler depth estimation was applied on the magnetic data in order to map structures and lithologic contacts before its subsequent integration with other structural lineaments as a thematic layer. Vertical Electrical Sounding (VES) data were used to compute hydraulic conductivity, and Transmisivity etc. for the acquiferous layers identified. The results of the present study showed some regions that are classified as highly prospective to be consistent with high transmisivity and high yield values. The final outcome (groundwater potential map) of this research demonstrated that GIS/remote sensing, and the geophysical technique employed is a very powerful tool for generating groundwater prospectivity map, which is very vital in terms of planning for groundwater exploration and exploitation.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Multiple criteria</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Analytic Hierarchy Process</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Groundwater</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Geographic Information System</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">thematic maps</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jesphys.ut.ac.ir/article_81559_663a47da77841c1cc7e4ff7cb32a0083.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>مؤسسه ژئوفیزیک دانشگاه تهران</PublisherName>
				<JournalTitle>فیزیک زمین و فضا</JournalTitle>
				<Issn>2538-371X</Issn>
				<Volume>47</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2022</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Frequency Response of Electrical Properties of some Granite Samples</ArticleTitle>
<VernacularTitle>Frequency Response of Electrical Properties of some Granite Samples</VernacularTitle>
			<FirstPage>75</FirstPage>
			<LastPage>86</LastPage>
			<ELocationID EIdType="pii">83550</ELocationID>
			
<ELocationID EIdType="doi">10.22059/jesphys.2021.318321.1007287</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Mohamed M.</FirstName>
					<LastName>Gomaa</LastName>
<Affiliation>Professor, Department of Geophysical Sciences, National Research Centre, Cairo, Egypt</Affiliation>
<Identifier Source="ORCID">0000-0002-8556-4555</Identifier>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2021</Year>
					<Month>02</Month>
					<Day>06</Day>
				</PubDate>
			</History>
		<Abstract>The electrical properties of rock types or channel structures have been the object of intense studies for many years. The main aim of the present work is to show the frequency response of electrical properties of some Granite samples concerning chemical, minor and major composition. This may be used as a fingerprint for the characterization of some Granite rocks. Electrical measurements on Granite samples (surface, Aswan, Egypt) were measured (100 Hz up to 10&lt;sup&gt;7&lt;/sup&gt; Hz). Differences in samples due to changes in texture lead to different changes in electrical properties. The changes at conductivity and dielectric constant are reflections from the texture within grains. Conductivity and dielectric constant values extend from ~10&lt;sup&gt;-8&lt;/sup&gt; to 10&lt;sup&gt;-4&lt;/sup&gt; (S/m) and 24 to 3.5, respectively. With frequency increase, conductivity increases, and dielectric constant decreases (10 kHz), and then it settles down. Differences in electrical properties between samples are small as a direct result of the homogeneity and texture of most samples. There is a high dispersion of dielectric constant for relatively low-frequency values (&lt;10 kHz) and no dispersion at relatively high frequencies. In conclusion, the dielectric constant decreases due to the shrinkage of energy levels for electrons and the increase of hopping particles between different particles.</Abstract>
			<OtherAbstract Language="FA">The electrical properties of rock types or channel structures have been the object of intense studies for many years. The main aim of the present work is to show the frequency response of electrical properties of some Granite samples concerning chemical, minor and major composition. This may be used as a fingerprint for the characterization of some Granite rocks. Electrical measurements on Granite samples (surface, Aswan, Egypt) were measured (100 Hz up to 10&lt;sup&gt;7&lt;/sup&gt; Hz). Differences in samples due to changes in texture lead to different changes in electrical properties. The changes at conductivity and dielectric constant are reflections from the texture within grains. Conductivity and dielectric constant values extend from ~10&lt;sup&gt;-8&lt;/sup&gt; to 10&lt;sup&gt;-4&lt;/sup&gt; (S/m) and 24 to 3.5, respectively. With frequency increase, conductivity increases, and dielectric constant decreases (10 kHz), and then it settles down. Differences in electrical properties between samples are small as a direct result of the homogeneity and texture of most samples. There is a high dispersion of dielectric constant for relatively low-frequency values (&lt;10 kHz) and no dispersion at relatively high frequencies. In conclusion, the dielectric constant decreases due to the shrinkage of energy levels for electrons and the increase of hopping particles between different particles.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">conductivity</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Granite</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Frequency-domain</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">electric</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Dielectric Constant</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jesphys.ut.ac.ir/article_83550_077f67808b3448f8c6c2df510eddecd6.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>مؤسسه ژئوفیزیک دانشگاه تهران</PublisherName>
				<JournalTitle>فیزیک زمین و فضا</JournalTitle>
				<Issn>2538-371X</Issn>
				<Volume>47</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2022</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>DC Electrical Resistance Tomography Inversion</ArticleTitle>
<VernacularTitle>DC Electrical Resistance Tomography Inversion</VernacularTitle>
			<FirstPage>87</FirstPage>
			<LastPage>98</LastPage>
			<ELocationID EIdType="pii">83554</ELocationID>
			
<ELocationID EIdType="doi">10.22059/jesphys.2021.323911.1007321</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Mahdi</FirstName>
					<LastName>Fallah Safari</LastName>
<Affiliation>Ph.D. Graduated, Department of Earth Physics, Institute of Geophysics, University of Tehran, Tehran, Iran</Affiliation>
<Identifier Source="ORCID">0009-0008-6449-0463</Identifier>

</Author>
<Author>
					<FirstName>Reza</FirstName>
					<LastName>Ghanati</LastName>
<Affiliation>Assistant Professor, Department of Earth Physics, Institute of Geophysics, University of Tehran, Tehran, Iran</Affiliation>
<Identifier Source="ORCID">0000-0003-1138-7442</Identifier>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2021</Year>
					<Month>05</Month>
					<Day>19</Day>
				</PubDate>
			</History>
		<Abstract>Direct current electrical resistivity imaging is provided by measuring the vertical and horizontal electrical potential variations of subsurface structures using surface and borehole records. To recover the resistivity tomograms from the observed data, a non-linear inverse problem is required to be iteratively solved. A 2.5-dimensional forward modeling based on the finite-difference method with rectangular meshes is also formulated. The two-dimensional reconstruction of earth resistivity data is implemented using a smoothness constrained inversion algorithm (i.e. Occam’s method), wherein a Gauss-Newton technique for updating the sensitivity function is proposed. After verifying the accuracy and efficiency of the forward modeling and the sensitivity function calculation, the inversion algorithm is tested on synthetic data from both geometrically simple and complicated bodies and a real data set. A stopping criterion based on the noise level, roughly estimated using the method of reciprocal resistance measurements, is also provided leading to preventing over-or under-interpreted structure during the inversion process. The numerical experiments reveal that the proposed inversion algorithm provides stable inversion results and an acceptable representation of the main features and structure of the models without producing spurious effects. Furthermore, to deal with the reliability of the recovered models, a model sensitivity analysis is implemented using the resolution density distribution. All used formulations and concepts are part of a Matlab source code developed during this study.</Abstract>
			<OtherAbstract Language="FA">Direct current electrical resistivity imaging is provided by measuring the vertical and horizontal electrical potential variations of subsurface structures using surface and borehole records. To recover the resistivity tomograms from the observed data, a non-linear inverse problem is required to be iteratively solved. A 2.5-dimensional forward modeling based on the finite-difference method with rectangular meshes is also formulated. The two-dimensional reconstruction of earth resistivity data is implemented using a smoothness constrained inversion algorithm (i.e. Occam’s method), wherein a Gauss-Newton technique for updating the sensitivity function is proposed. After verifying the accuracy and efficiency of the forward modeling and the sensitivity function calculation, the inversion algorithm is tested on synthetic data from both geometrically simple and complicated bodies and a real data set. A stopping criterion based on the noise level, roughly estimated using the method of reciprocal resistance measurements, is also provided leading to preventing over-or under-interpreted structure during the inversion process. The numerical experiments reveal that the proposed inversion algorithm provides stable inversion results and an acceptable representation of the main features and structure of the models without producing spurious effects. Furthermore, to deal with the reliability of the recovered models, a model sensitivity analysis is implemented using the resolution density distribution. All used formulations and concepts are part of a Matlab source code developed during this study.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Electrical Resistivity Tomography</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">2.5-D non-linear inversion</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Resolution density</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jesphys.ut.ac.ir/article_83554_0550714c3e235b68738544e32831d9d0.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>مؤسسه ژئوفیزیک دانشگاه تهران</PublisherName>
				<JournalTitle>فیزیک زمین و فضا</JournalTitle>
				<Issn>2538-371X</Issn>
				<Volume>47</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2022</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>3D Electromagnetic Low Induction Number Modeling using Integral Equations</ArticleTitle>
<VernacularTitle>3D Electromagnetic Low Induction Number Modeling using Integral Equations</VernacularTitle>
			<FirstPage>99</FirstPage>
			<LastPage>110</LastPage>
			<ELocationID EIdType="pii">83552</ELocationID>
			
<ELocationID EIdType="doi">10.22059/jesphys.2021.325291.1007330</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Ramin</FirstName>
					<LastName>Varfinezhad</LastName>
<Affiliation>Ph.D. Graduated, Department of Earth Physics, Institute of Geophysics, University of Tehran, Tehran, Iran</Affiliation>
<Identifier Source="ORCID">0000-0001-9360-4978</Identifier>

</Author>
<Author>
					<FirstName>Saeed</FirstName>
					<LastName>Parnow</LastName>
<Affiliation>Ph.D. Graduated, Department of Earth Physics, Institute of Geophysics, University of Tehran, Tehran, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2021</Year>
					<Month>06</Month>
					<Day>13</Day>
				</PubDate>
			</History>
		<Abstract>In this paper, a code for 3D forward modeling of electromagnetic low induction number (EM-LIN) data is developed based on the linear integral equations (IE). At first, the code is manipulated for a resistive block immersed in a homogenous background, and the obtained results have RMS errors of 2% comparing with the previously standard published results, which demonstrates the productivity of &lt;sub&gt;the&lt;/sub&gt; 3D forward modeling code. Then, a model composed of two conductive anomalies with different depth ranges and conductivities in a resistive background is considered. IE Forward reposes shows that the shallower block produce larger values in spite of having less conductivity.&lt;br /&gt;Since the forward modeling is linear, the productivity of the forward modeling code depends on the efficiency of the forward operator. Furthermore, linear forward operator plays the key role in the linear inversion procedure, therefore, a real data set of a thick dyke in Bloemfontein Nature Reserve region in South Africa is manipulated. Weighted damped minimum length solution is utilized for the inversion procedure and the inverted model is demonstrative of the forward operator efficiency in practical applications.</Abstract>
			<OtherAbstract Language="FA">In this paper, a code for 3D forward modeling of electromagnetic low induction number (EM-LIN) data is developed based on the linear integral equations (IE). At first, the code is manipulated for a resistive block immersed in a homogenous background, and the obtained results have RMS errors of 2% comparing with the previously standard published results, which demonstrates the productivity of &lt;sub&gt;the&lt;/sub&gt; 3D forward modeling code. Then, a model composed of two conductive anomalies with different depth ranges and conductivities in a resistive background is considered. IE Forward reposes shows that the shallower block produce larger values in spite of having less conductivity.&lt;br /&gt;Since the forward modeling is linear, the productivity of the forward modeling code depends on the efficiency of the forward operator. Furthermore, linear forward operator plays the key role in the linear inversion procedure, therefore, a real data set of a thick dyke in Bloemfontein Nature Reserve region in South Africa is manipulated. Weighted damped minimum length solution is utilized for the inversion procedure and the inverted model is demonstrative of the forward operator efficiency in practical applications.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Conductivities</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">EM-LIN</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">EM-34</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">3D forward modeling</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">IE</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">inversion</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jesphys.ut.ac.ir/article_83552_c751f1edd12f09b3cefe86cd7d2e6e76.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>مؤسسه ژئوفیزیک دانشگاه تهران</PublisherName>
				<JournalTitle>فیزیک زمین و فضا</JournalTitle>
				<Issn>2538-371X</Issn>
				<Volume>47</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2022</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>MLP, Recurrent, Convolutional and LSTM Neural Networks Detect Seismo-TEC Anomalies Potentially Related to the Iran Sarpol-e Zahab (Mw=7.3) Earthquake of 12 November 2017</ArticleTitle>
<VernacularTitle>MLP, Recurrent, Convolutional and LSTM Neural Networks Detect Seismo-TEC Anomalies Potentially Related to the Iran Sarpol-e Zahab (Mw=7.3) Earthquake of 12 November 2017</VernacularTitle>
			<FirstPage>111</FirstPage>
			<LastPage>124</LastPage>
			<ELocationID EIdType="pii">83545</ELocationID>
			
<ELocationID EIdType="doi">10.22059/jesphys.2021.326054.1007332</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Mehdi</FirstName>
					<LastName>Akhoondzadeh</LastName>
<Affiliation>Associate Professor, Department of Photogrammetry and Remote Sensing, School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Benyamin</FirstName>
					<LastName>Hosseiny</LastName>
<Affiliation>Ph.D. Student, Department of Photogrammetry and Remote Sensing, School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Nafise</FirstName>
					<LastName>Ghasemian</LastName>
<Affiliation>Ph.D. Student, Department of Photogrammetry and Remote Sensing, School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2021</Year>
					<Month>06</Month>
					<Day>27</Day>
				</PubDate>
			</History>
		<Abstract>A strong earthquake () (34.911&lt;sup&gt;° &lt;/sup&gt;N, 45.959&lt;sup&gt;° &lt;/sup&gt;E, ~19 km depth) occurred on November 12, 2017, at 18:18:17 UTC (LT=UTC+03:30) in Sarpol-e Zahab, Iran. Six different Neural Network (NN) algorithms including Multi-Layer Perceptron (MLP), Recurrent Neural Network (RNN), Gated Recurrent Unit (GRU), Convolutional Neural Network (CNN), Long-Short Term Memory (LSTM) and CNN-LSTM were implemented to survey the four months of GPS Total Electron Content (TEC) measurements during the period of August 01 to November 30, 2017 around the epicenter of the mentioned earthquake. By considering the quiet solar-geomagnetic conditions, every six methods detect anomalous TEC variations nine days prior to the earthquake. Since time-series of TEC variations follow a nonlinear and complex behavior, intelligent algorithms such as NN can be considered as an appropriate tool for modelling and prediction of TEC time-series. Moreover, multi-methods analyses beside the multi precursor’s analyses decrease uncertainty and false alarms and consequently lead to confident anomalies.</Abstract>
			<OtherAbstract Language="FA">A strong earthquake () (34.911&lt;sup&gt;° &lt;/sup&gt;N, 45.959&lt;sup&gt;° &lt;/sup&gt;E, ~19 km depth) occurred on November 12, 2017, at 18:18:17 UTC (LT=UTC+03:30) in Sarpol-e Zahab, Iran. Six different Neural Network (NN) algorithms including Multi-Layer Perceptron (MLP), Recurrent Neural Network (RNN), Gated Recurrent Unit (GRU), Convolutional Neural Network (CNN), Long-Short Term Memory (LSTM) and CNN-LSTM were implemented to survey the four months of GPS Total Electron Content (TEC) measurements during the period of August 01 to November 30, 2017 around the epicenter of the mentioned earthquake. By considering the quiet solar-geomagnetic conditions, every six methods detect anomalous TEC variations nine days prior to the earthquake. Since time-series of TEC variations follow a nonlinear and complex behavior, intelligent algorithms such as NN can be considered as an appropriate tool for modelling and prediction of TEC time-series. Moreover, multi-methods analyses beside the multi precursor’s analyses decrease uncertainty and false alarms and consequently lead to confident anomalies.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Earthquake Precursor</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">anomaly</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Ionosphere</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">GPS-TEC</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">neural network</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jesphys.ut.ac.ir/article_83545_f196959db6f8b6b1281bb1d79f9d7c1c.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>مؤسسه ژئوفیزیک دانشگاه تهران</PublisherName>
				<JournalTitle>فیزیک زمین و فضا</JournalTitle>
				<Issn>2538-371X</Issn>
				<Volume>47</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2022</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Fuzzy Partitioning of Radon Domain for Estimation of Water Reverberation Energy</ArticleTitle>
<VernacularTitle>Fuzzy Partitioning of Radon Domain for Estimation of Water Reverberation Energy</VernacularTitle>
			<FirstPage>125</FirstPage>
			<LastPage>132</LastPage>
			<ELocationID EIdType="pii">85435</ELocationID>
			
<ELocationID EIdType="doi">10.22059/jesphys.2022.331240.1007366</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Meysam</FirstName>
					<LastName>Zarei</LastName>
<Affiliation>Ph.D. Student, Department of Earth Physics, Institute of Geophysics, University of Tehran, Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Hosein</FirstName>
					<LastName>Hashemi</LastName>
<Affiliation>Assistant Professor, Department of Earth Physics, Institute of Geophysics, University of Tehran, Tehran, Iran</Affiliation>
<Identifier Source="ORCID">0000-0002-6734-9317</Identifier>

</Author>
<Author>
					<FirstName>Majid</FirstName>
					<LastName>Bagheri</LastName>
<Affiliation>Assistant Professor, Department of Earth Physics, Institute of Geophysics, University of Tehran, Tehran, Iran</Affiliation>
<Identifier Source="ORCID">0000-0003-2059-0194</Identifier>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2021</Year>
					<Month>10</Month>
					<Day>02</Day>
				</PubDate>
			</History>
		<Abstract>The radon transform has a wide application in seismic processing for each project in different areas. Multiple attenuation is mostly summarized in the use of radon analysis in practice, especially in marine data processing. The definition of mute function is the major challenge in parabolic radon transform. In this paper, a method for segmentation of the radon transform by fuzzy inference system is introduced to separate energy parts in the radon domain. We applied a fuzzy inference system based on the property of energy distribution and its attribute in the radon domain. The result of clustering is the partitioning of the radon domain in three major classes: 1- random noise, 2- multiple, and 3- primary and multiple. The result of applying the new method on real data has shown the applicability of the new method for separation of multiple class from other classes that can assist the processor to define the mute function in the absence of other events in the radon domain.</Abstract>
			<OtherAbstract Language="FA">The radon transform has a wide application in seismic processing for each project in different areas. Multiple attenuation is mostly summarized in the use of radon analysis in practice, especially in marine data processing. The definition of mute function is the major challenge in parabolic radon transform. In this paper, a method for segmentation of the radon transform by fuzzy inference system is introduced to separate energy parts in the radon domain. We applied a fuzzy inference system based on the property of energy distribution and its attribute in the radon domain. The result of clustering is the partitioning of the radon domain in three major classes: 1- random noise, 2- multiple, and 3- primary and multiple. The result of applying the new method on real data has shown the applicability of the new method for separation of multiple class from other classes that can assist the processor to define the mute function in the absence of other events in the radon domain.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Fuzzy inference system</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">multiple attenuation</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Radon transform</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">fuzzy partitioning</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Fuzzy C-Mean Clustering</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jesphys.ut.ac.ir/article_85435_f2bee0cbf0dd86a98f0fedd9e13c17e4.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>مؤسسه ژئوفیزیک دانشگاه تهران</PublisherName>
				<JournalTitle>فیزیک زمین و فضا</JournalTitle>
				<Issn>2538-371X</Issn>
				<Volume>47</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2022</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>ANFIS Rules Driven Integrated Seismic and Petrophysical Facies Analysis</ArticleTitle>
<VernacularTitle>ANFIS Rules Driven Integrated Seismic and Petrophysical Facies Analysis</VernacularTitle>
			<FirstPage>133</FirstPage>
			<LastPage>141</LastPage>
			<ELocationID EIdType="pii">85624</ELocationID>
			
<ELocationID EIdType="doi">10.22059/jesphys.2022.331894.1007370</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Marzieh</FirstName>
					<LastName>Mirzakhanian</LastName>
<Affiliation>Ph.D. Student, Department of Earth Physics, Institute of Geophysics, University of Tehran, Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Hosein</FirstName>
					<LastName>Hashemi</LastName>
<Affiliation>Assistant Professor, Department of Earth Physics, Institute of Geophysics, University of Tehran, Tehran, Iran</Affiliation>
<Identifier Source="ORCID">0000-0002-6734-9317</Identifier>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2021</Year>
					<Month>10</Month>
					<Day>17</Day>
				</PubDate>
			</History>
		<Abstract>Different learning methods have been used to recognize seismic facies and reservoir characterization using seismic attributes. One of the significant issues in automatic facies analysis is to relate the seismic data to facies properties using the well data. According to previous studies, the role of attributes is more significant than the learning method for automatic classification. The proposed method uses supervised selection of seismic attributes for automatic facies analysis.&lt;br /&gt;Extended Elastic Impedances (EEI) at different angles as seismic attributes are being increasingly utilized in both seismic facies analysis and reservoir characterization. They are representative of elastic parameters of rocks appropriately. In the presented method, proper EEI seismic attributes are selected after a feasibility study using petro-physical logs, and EEI template analysis of the well data. Adaptive Neuro-Fuzzy Inference System (ANFIS) is applied to the fuzzy coded data of the well facies to train an automatic model to predict facies from the seismic data. Subsequently, the same particular EEI attributes are prepared. The EEI attributes from the seismic data are inputs for the trained ANIFIS model to perform seismic facies analysis. In this method, the seismic facies and the well facies are compatible. Only one well data can be sufficient for the well analysis stage and well facies clustering.&lt;br /&gt;The proposed method is applied on 3D prestack seismic data located in Abadan plain to discriminate hydrocarbon interval of Sarvak Formation. The results reveal that the supervised selection of attributes and fuzzy concepts present remarkable ability in dealing with imprecise seismic facies analysis and reservoir characterization.</Abstract>
			<OtherAbstract Language="FA">Different learning methods have been used to recognize seismic facies and reservoir characterization using seismic attributes. One of the significant issues in automatic facies analysis is to relate the seismic data to facies properties using the well data. According to previous studies, the role of attributes is more significant than the learning method for automatic classification. The proposed method uses supervised selection of seismic attributes for automatic facies analysis.&lt;br /&gt;Extended Elastic Impedances (EEI) at different angles as seismic attributes are being increasingly utilized in both seismic facies analysis and reservoir characterization. They are representative of elastic parameters of rocks appropriately. In the presented method, proper EEI seismic attributes are selected after a feasibility study using petro-physical logs, and EEI template analysis of the well data. Adaptive Neuro-Fuzzy Inference System (ANFIS) is applied to the fuzzy coded data of the well facies to train an automatic model to predict facies from the seismic data. Subsequently, the same particular EEI attributes are prepared. The EEI attributes from the seismic data are inputs for the trained ANIFIS model to perform seismic facies analysis. In this method, the seismic facies and the well facies are compatible. Only one well data can be sufficient for the well analysis stage and well facies clustering.&lt;br /&gt;The proposed method is applied on 3D prestack seismic data located in Abadan plain to discriminate hydrocarbon interval of Sarvak Formation. The results reveal that the supervised selection of attributes and fuzzy concepts present remarkable ability in dealing with imprecise seismic facies analysis and reservoir characterization.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">seismic attributes</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Extended elastic impedance</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Facies analysis</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Adaptive neuro- fuzzy inference system</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jesphys.ut.ac.ir/article_85624_0d8b4467ea3ef9c0065214e1fcc912f1.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>مؤسسه ژئوفیزیک دانشگاه تهران</PublisherName>
				<JournalTitle>فیزیک زمین و فضا</JournalTitle>
				<Issn>2538-371X</Issn>
				<Volume>47</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2022</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Contribution of Source Emissions in the Air Pollution Modeling - a WRF/Chem
Case Study</ArticleTitle>
<VernacularTitle>Contribution of Source Emissions in the Air Pollution Modeling - a WRF/Chem Case Study</VernacularTitle>
			<FirstPage>143</FirstPage>
			<LastPage>156</LastPage>
			<ELocationID EIdType="pii">81756</ELocationID>
			
<ELocationID EIdType="doi">10.22059/jesphys.2021.299733.1007204</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Amir Hosein</FirstName>
					<LastName>Nikfal</LastName>
<Affiliation>Ph.D. Student, Atmospheric Science and Meteorological Research Center (ASMERC), Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Abbas</FirstName>
					<LastName>Ranjbar Saadat Abadi</LastName>
<Affiliation>Associate Professor, Atmospheric Science and Meteorological Research Center (ASMERC), Tehran, Iran</Affiliation>
<Identifier Source="ORCID">0000-0003-2239-0786</Identifier>

</Author>
<Author>
					<FirstName>Mehdi</FirstName>
					<LastName>Rahnama</LastName>
<Affiliation>Assistant Professor, Atmospheric Science and Meteorological Research Center (ASMERC), Tehran, Iran</Affiliation>
<Identifier Source="ORCID">0000-0003-1644-8822</Identifier>

</Author>
<Author>
					<FirstName>Sahar</FirstName>
					<LastName>Tajbakhsh Mosalman</LastName>
<Affiliation>Assistant Professor, Atmospheric Science and Meteorological Research Center (ASMERC), Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Mohammad</FirstName>
					<LastName>Moradi</LastName>
<Affiliation>Associate Professor, Atmospheric Science and Meteorological Research Center (ASMERC), Tehran, Iran</Affiliation>
<Identifier Source="ORCID">0000-0002-5356-8578</Identifier>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2021</Year>
					<Month>03</Month>
					<Day>21</Day>
				</PubDate>
			</History>
		<Abstract>We investigate the capability of the WRF/Chem model in the simulation of some criteria air pollutants, during a major air pollution episode between 16 and 21 December 2017. In this study, by employing the EDGAR-HTAP_v2 global emissions data in the WRF/Chem model, we evaluate the simulations of the surface mixing ratios of NO&lt;sub&gt;2&lt;/sub&gt;, SO&lt;sub&gt;2&lt;/sub&gt;, and CO. The RADM2 chemical mechanism with MADE-SORGAM aerosol scheme has been used as the chemical option of the WRF/Chem model, to simulate the meteorology-chemistry interactions. The variations of the time series of the pollutants and the comparisons of the results in Tehran with the measurement data showed that although the WRF/Chem simulations in Tehran presented considerable over-estimations, but the model’s performance with regard to the time variations of the concentrations of the gaseous agents over the polluted episode is acceptable, and therefore, could be considered in the operational air quality systems. Since emission data are not available for many metropolitan areas over Iran, the HTAP_v2 global dataset could be used as the emissions data with reliable accuracy for the numerical air quality models.</Abstract>
			<OtherAbstract Language="FA">We investigate the capability of the WRF/Chem model in the simulation of some criteria air pollutants, during a major air pollution episode between 16 and 21 December 2017. In this study, by employing the EDGAR-HTAP_v2 global emissions data in the WRF/Chem model, we evaluate the simulations of the surface mixing ratios of NO&lt;sub&gt;2&lt;/sub&gt;, SO&lt;sub&gt;2&lt;/sub&gt;, and CO. The RADM2 chemical mechanism with MADE-SORGAM aerosol scheme has been used as the chemical option of the WRF/Chem model, to simulate the meteorology-chemistry interactions. The variations of the time series of the pollutants and the comparisons of the results in Tehran with the measurement data showed that although the WRF/Chem simulations in Tehran presented considerable over-estimations, but the model’s performance with regard to the time variations of the concentrations of the gaseous agents over the polluted episode is acceptable, and therefore, could be considered in the operational air quality systems. Since emission data are not available for many metropolitan areas over Iran, the HTAP_v2 global dataset could be used as the emissions data with reliable accuracy for the numerical air quality models.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">WRF/Chem</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">HTAP_v2 datast</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">global emissions</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">criteria air pollutants</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Numerical Modeling</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jesphys.ut.ac.ir/article_81756_1694c0072e36db25bdbff63b41216335.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>مؤسسه ژئوفیزیک دانشگاه تهران</PublisherName>
				<JournalTitle>فیزیک زمین و فضا</JournalTitle>
				<Issn>2538-371X</Issn>
				<Volume>47</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2022</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Detection of Aircraft Icing Threat Pixels Using Cloud Properties of MSG Satellite Products Case Study: Tehran-Urmia Flight Route</ArticleTitle>
<VernacularTitle>Detection of Aircraft Icing Threat Pixels Using Cloud Properties of MSG Satellite Products Case Study: Tehran-Urmia Flight Route</VernacularTitle>
			<FirstPage>157</FirstPage>
			<LastPage>175</LastPage>
			<ELocationID EIdType="pii">79586</ELocationID>
			
<ELocationID EIdType="doi">10.22059/jesphys.2021.303519.1007216</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Hashem</FirstName>
					<LastName>Rostamzadeh</LastName>
<Affiliation>Assistant Professor, Department of Climatology, Faculty of Planning and Environmental Sciences, University of Tabriz, Tabriz, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Ali Mohammad</FirstName>
					<LastName>Khorshiddoust</LastName>
<Affiliation>Professor, Department of Climatology, Faculty of Planning and Environmental Sciences, University of Tabriz, Tabriz, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Mohammad Reza</FirstName>
					<LastName>Azizzadeh</LastName>
<Affiliation>Ph.D. Student, Department of Climatology, Faculty of Planning and Environmental Sciences, University of Tabriz, Tabriz, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2020</Year>
					<Month>06</Month>
					<Day>07</Day>
				</PubDate>
			</History>
		<Abstract>In the present study, the meteorological conditions of the plane crash on the Tehran-Urmia route on 01/19/2011 were investigated. The ultimate goal of this study is to detect icing threatening pixels in aircraft. To achieve this goal, using the products of Meteosat satellite, the physical properties of the cloud in the northwest were evaluated. First, cloud products were received in Netcdf4 format in 15 minutes. Then, a regular network of geographical coordinates with a spatial resolution of 101×165 was prepared. After the data networking process, cloud characteristics (cloud cover, cloud type, cloud phase, cloud optical depth and cloud temperature) were extracted for the study day in a period of 15 minutes. Finally, by combining cloud characteristics (temperature cloud less than 273 and cloud liquid phase and optical depth less than one) through FIT algorithm, icing mask was modeled for the study area. Examination of cloud characteristics maps shows that the cloud temperature and the cloud phase (liquid state) have played the most important role in creating icing conditions. According to the Aviation Authorities, there are icing pixels on the flight path and at the crash location. Examination of synoptic maps also showed unstable weather conditions with severe convection at the time of the accident in the study area. Finally, under such conditions and with access to moisture sources in the upper layers of the atmosphere and the strengthening of super-cold water vapor, it has provided icing conditions.</Abstract>
			<OtherAbstract Language="FA">In the present study, the meteorological conditions of the plane crash on the Tehran-Urmia route on 01/19/2011 were investigated. The ultimate goal of this study is to detect icing threatening pixels in aircraft. To achieve this goal, using the products of Meteosat satellite, the physical properties of the cloud in the northwest were evaluated. First, cloud products were received in Netcdf4 format in 15 minutes. Then, a regular network of geographical coordinates with a spatial resolution of 101×165 was prepared. After the data networking process, cloud characteristics (cloud cover, cloud type, cloud phase, cloud optical depth and cloud temperature) were extracted for the study day in a period of 15 minutes. Finally, by combining cloud characteristics (temperature cloud less than 273 and cloud liquid phase and optical depth less than one) through FIT algorithm, icing mask was modeled for the study area. Examination of cloud characteristics maps shows that the cloud temperature and the cloud phase (liquid state) have played the most important role in creating icing conditions. According to the Aviation Authorities, there are icing pixels on the flight path and at the crash location. Examination of synoptic maps also showed unstable weather conditions with severe convection at the time of the accident in the study area. Finally, under such conditions and with access to moisture sources in the upper layers of the atmosphere and the strengthening of super-cold water vapor, it has provided icing conditions.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Aircraft icing</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Icing mask</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Supercooled Liquid Water</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Cloud Physical Properties</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Meteosat (MSG) Products</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jesphys.ut.ac.ir/article_79586_222b56aae2f098322c7a9bda1a6da90c.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>مؤسسه ژئوفیزیک دانشگاه تهران</PublisherName>
				<JournalTitle>فیزیک زمین و فضا</JournalTitle>
				<Issn>2538-371X</Issn>
				<Volume>47</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2022</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Application of Siemens Index of Green Cities for Selected Areas in Iraq</ArticleTitle>
<VernacularTitle>Application of Siemens Index of Green Cities for Selected Areas in Iraq</VernacularTitle>
			<FirstPage>177</FirstPage>
			<LastPage>185</LastPage>
			<ELocationID EIdType="pii">79580</ELocationID>
			
<ELocationID EIdType="doi">10.22059/jesphys.2021.308430.1007240</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Safaa</FirstName>
					<LastName>Al-Swaiedi</LastName>
<Affiliation>Ph.D. Graduated, Department of Atmospheric Sciences, College of Science, Al-Mustansiriya University, Baghdad, Iraq</Affiliation>

</Author>
<Author>
					<FirstName>Amani</FirstName>
					<LastName>Altmimi</LastName>
<Affiliation>Assistant Professor, Department of Renewable Energy, College of Energy and Environmental Sciences, Al-Karkh University of Science, Baghdad, Iraq</Affiliation>

</Author>
<Author>
					<FirstName>Ammar</FirstName>
					<LastName>Alkhalidi</LastName>
<Affiliation>Assistant Professor, Department of Energy Engineering, School of Natural Resources Engineering and Management, German Jordanian University, Amman, Jordan</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2020</Year>
					<Month>08</Month>
					<Day>22</Day>
				</PubDate>
			</History>
		<Abstract>Irregular urban design and use of traditional resources to provide energy have a major impact on people&#039;s lives and climate in the future. The goal of this paper is to determine the best place to design a sustainable city, based on the Siemens Index for Green Cities and Comfort Factor. Four sites were selected in Iraq based on the geographical location and weather variables for each site, namely Um Qasr, Baghdad, Anah and Sulaymaniyah. Weights and percentages were distributed on the categories of the Siemens index, which are renewable energy, water and air quality, in addition to the comfort factor, and then analyzed and evaluated at each site. With regard to the renewable energy category represented by solar and wind energy, the best evaluation of the energy category was found at Um Qasr by 60.88%. As for the evaluation of the water resources category, it was found that the Anah site possesses the highest percentage of available water quantities in the study sites by 85%. As for the air quality category represented by the percentage of pollutants for each site, which are CO&lt;sub&gt;2&lt;/sub&gt;, SO&lt;sub&gt;2&lt;/sub&gt;, NO&lt;sub&gt;2&lt;/sub&gt;, and Particulate Matter in the air, it was found that Sulaymaniyah site has the lowest percentage of pollutants in the study sites by 24.86%. Finally, the comfort factor category represented by the Temperature Humidity Index and Wind Chill Factor shows Sulaymaniyah&#039;s location with the highest percentage of the comfort factor value at 94%. After distributing the weights and percentages and collecting them for each site, the results showed that it was the best site for designing a sustainable city in Iraq, by 72% due to the abundance of water and renewable energy sources, in addition to high air quality.</Abstract>
			<OtherAbstract Language="FA">Irregular urban design and use of traditional resources to provide energy have a major impact on people&#039;s lives and climate in the future. The goal of this paper is to determine the best place to design a sustainable city, based on the Siemens Index for Green Cities and Comfort Factor. Four sites were selected in Iraq based on the geographical location and weather variables for each site, namely Um Qasr, Baghdad, Anah and Sulaymaniyah. Weights and percentages were distributed on the categories of the Siemens index, which are renewable energy, water and air quality, in addition to the comfort factor, and then analyzed and evaluated at each site. With regard to the renewable energy category represented by solar and wind energy, the best evaluation of the energy category was found at Um Qasr by 60.88%. As for the evaluation of the water resources category, it was found that the Anah site possesses the highest percentage of available water quantities in the study sites by 85%. As for the air quality category represented by the percentage of pollutants for each site, which are CO&lt;sub&gt;2&lt;/sub&gt;, SO&lt;sub&gt;2&lt;/sub&gt;, NO&lt;sub&gt;2&lt;/sub&gt;, and Particulate Matter in the air, it was found that Sulaymaniyah site has the lowest percentage of pollutants in the study sites by 24.86%. Finally, the comfort factor category represented by the Temperature Humidity Index and Wind Chill Factor shows Sulaymaniyah&#039;s location with the highest percentage of the comfort factor value at 94%. After distributing the weights and percentages and collecting them for each site, the results showed that it was the best site for designing a sustainable city in Iraq, by 72% due to the abundance of water and renewable energy sources, in addition to high air quality.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Air Quality</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Anah</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">renewable energy</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Siemens index</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">sustainability</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">water resources</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jesphys.ut.ac.ir/article_79580_8e3b66b7b9f65122f6963d413fe11f68.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>مؤسسه ژئوفیزیک دانشگاه تهران</PublisherName>
				<JournalTitle>فیزیک زمین و فضا</JournalTitle>
				<Issn>2538-371X</Issn>
				<Volume>47</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2022</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>A Study on the Effects of Solar Protons on the NOy by Magnetic Storm Events from 2003 to 2012: A Comparison between the Southern and Northern Hemispheres</ArticleTitle>
<VernacularTitle>A Study on the Effects of Solar Protons on the NOy by Magnetic Storm Events from 2003 to 2012: A Comparison between the Southern and Northern Hemispheres</VernacularTitle>
			<FirstPage>187</FirstPage>
			<LastPage>200</LastPage>
			<ELocationID EIdType="pii">81522</ELocationID>
			
<ELocationID EIdType="doi">10.22059/jesphys.2021.314620.1007264</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Nasim</FirstName>
					<LastName>Farzanegan</LastName>
<Affiliation>M.Sc. Graduated, Department of Space Physics, Institute of Geophysics, University of Tehran, Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Mohammad Javad</FirstName>
					<LastName>Kalaee</LastName>
<Affiliation>Associate Professor, Department of Space Physics, Institute of Geophysics, University of Tehran, Tehran, Iran</Affiliation>
<Identifier Source="ORCID">0000-0002-2424-9172</Identifier>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2020</Year>
					<Month>12</Month>
					<Day>08</Day>
				</PubDate>
			</History>
		<Abstract>In the study of solar-terrestrial relationships, magnetic storms and solar activity play important roles. In this paper, the intense magnetic storms in company with solar proton events occurred in October and November 2003, January 2005, December 2006, January and March 2012 have been considered. The variation of the odd nitrogen (&lt;em&gt;NO&lt;sub&gt;y&lt;/sub&gt;&lt;/em&gt;) oxides and ozone in the stratospheric layer is investigated by the effects of energetic particle precipitation. Anomaly percentage of the odd nitrogen (&lt;em&gt;NO&lt;sub&gt;y&lt;/sub&gt;&lt;/em&gt;) oxides and ozone are calculated separately for the Southern and the Northern hemispheres and geographic latitude from 60 to 80 degrees. The analyzed results of the observational data showed that the intense magnetic storms, which consist of more than 500 (particles/cm&lt;sup&gt;2 &lt;/sup&gt;s sr) solar energetic proton (E&gt;10MeV), gave rise to the increase of the odd nitrogen (&lt;em&gt;NO&lt;sub&gt;y&lt;/sub&gt;&lt;/em&gt;) oxides in the stratosphere, from level 1 mb to 200 mb. Also, the results showed that in November 2003, January 2005, December 2006, January and March 2012 the odd nitrogen (&lt;em&gt;NO&lt;sub&gt;y&lt;/sub&gt;&lt;/em&gt;) oxides, which consist of over 500 (particles/cm&lt;sup&gt;2&lt;/sup&gt; s sr) increased in the Northern hemisphere but decreased a little in the Southern hemisphere . Among the events of the magnetic storms in the autumn and winter seasons, the only event on the October 2003, showed that the odd nitrogen (&lt;em&gt;NO&lt;sub&gt;y&lt;/sub&gt;&lt;/em&gt;) oxides increased in the Southern hemisphere. The results showed that the increase in the odd nitrogen (&lt;em&gt;NO&lt;sub&gt;y&lt;/sub&gt;&lt;/em&gt;) oxides caused a decrease of ozone in the altitude below the odd nitrogen (&lt;em&gt;NO&lt;sub&gt;y&lt;/sub&gt;&lt;/em&gt;) with a delay.</Abstract>
			<OtherAbstract Language="FA">In the study of solar-terrestrial relationships, magnetic storms and solar activity play important roles. In this paper, the intense magnetic storms in company with solar proton events occurred in October and November 2003, January 2005, December 2006, January and March 2012 have been considered. The variation of the odd nitrogen (&lt;em&gt;NO&lt;sub&gt;y&lt;/sub&gt;&lt;/em&gt;) oxides and ozone in the stratospheric layer is investigated by the effects of energetic particle precipitation. Anomaly percentage of the odd nitrogen (&lt;em&gt;NO&lt;sub&gt;y&lt;/sub&gt;&lt;/em&gt;) oxides and ozone are calculated separately for the Southern and the Northern hemispheres and geographic latitude from 60 to 80 degrees. The analyzed results of the observational data showed that the intense magnetic storms, which consist of more than 500 (particles/cm&lt;sup&gt;2 &lt;/sup&gt;s sr) solar energetic proton (E&gt;10MeV), gave rise to the increase of the odd nitrogen (&lt;em&gt;NO&lt;sub&gt;y&lt;/sub&gt;&lt;/em&gt;) oxides in the stratosphere, from level 1 mb to 200 mb. Also, the results showed that in November 2003, January 2005, December 2006, January and March 2012 the odd nitrogen (&lt;em&gt;NO&lt;sub&gt;y&lt;/sub&gt;&lt;/em&gt;) oxides, which consist of over 500 (particles/cm&lt;sup&gt;2&lt;/sup&gt; s sr) increased in the Northern hemisphere but decreased a little in the Southern hemisphere . Among the events of the magnetic storms in the autumn and winter seasons, the only event on the October 2003, showed that the odd nitrogen (&lt;em&gt;NO&lt;sub&gt;y&lt;/sub&gt;&lt;/em&gt;) oxides increased in the Southern hemisphere. The results showed that the increase in the odd nitrogen (&lt;em&gt;NO&lt;sub&gt;y&lt;/sub&gt;&lt;/em&gt;) oxides caused a decrease of ozone in the altitude below the odd nitrogen (&lt;em&gt;NO&lt;sub&gt;y&lt;/sub&gt;&lt;/em&gt;) with a delay.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Magnetic storms</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">solar proton</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">solar activity</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">odd nitrogen oxides</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">energetic particles</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jesphys.ut.ac.ir/article_81522_9cb9aa0ba3c0d66f244cfa4ff5e5ce66.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>مؤسسه ژئوفیزیک دانشگاه تهران</PublisherName>
				<JournalTitle>فیزیک زمین و فضا</JournalTitle>
				<Issn>2538-371X</Issn>
				<Volume>47</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2022</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Autumn and Winter Extreme Precipitation Events and their Relationship with ENSO, NAO and MJO Phases over the West of Iran</ArticleTitle>
<VernacularTitle>Autumn and Winter Extreme Precipitation Events and their Relationship with ENSO, NAO and MJO Phases over the West of Iran</VernacularTitle>
			<FirstPage>201</FirstPage>
			<LastPage>218</LastPage>
			<ELocationID EIdType="pii">83549</ELocationID>
			
<ELocationID EIdType="doi">10.22059/jesphys.2021.316961.1007280</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Toraj</FirstName>
					<LastName>Jamshidi Khezeli</LastName>
<Affiliation>Ph.D. Student, Atmospheric Science and Meteorological Research Center (ASMERC), Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Abbas</FirstName>
					<LastName>Ranjbar Saadat Abadi</LastName>
<Affiliation>Associate Professor, Department of Weather Hazards Warning, Atmospheric Science and Meteorological Research Center (ASMERC), Tehran, Iran</Affiliation>
<Identifier Source="ORCID">0000-0003-2239-0786</Identifier>

</Author>
<Author>
					<FirstName>Mohammad Ali</FirstName>
					<LastName>Nasr-Esfahany</LastName>
<Affiliation>Assistant Professor, Department of Water Engineering, Shahrekord University, Shahrekord, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Sahar</FirstName>
					<LastName>Tajbakhsh Mosalman</LastName>
<Affiliation>Assistant Professor, Department of Atmospheric Prospecting, Atmospheric Science and Meteorological Research Center (ASMERC), Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Ali Reza</FirstName>
					<LastName>Mohebalhojeh</LastName>
<Affiliation>Professor, Department of Space Physics, Institute of Geophysics, University of Tehran, Tehran, Iran</Affiliation>
<Identifier Source="ORCID">0000-0002-5906-8486</Identifier>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2021</Year>
					<Month>01</Month>
					<Day>11</Day>
				</PubDate>
			</History>
		<Abstract>Some extreme precipitations have occurred in Iran in recent years. This paper is devoted to the study of extreme precipitations in the west of Iran, affected by combination of atmospheric pressure patterns in the period of 1987–2016. At first, monthly precipitations for seven synoptic stations of the west of Iran in autumn and winter with positive anomalies greater than 100% were identified. Then, for statistical-dynamical analysis, the El-Nino Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Madden–Julian Oscillation (MJO) indices were used. Results showed that the extreme precipitations had occurred during moderate to strong El-Nino, while MJO was critical and strong, in phases 2 and 8, and NAO was in positive phase. The anomalies of the MJO index in case studies had positive values. The NAO for case studies has entered a positive phase from a strong negative phase a few days before extreme precipitation. Analyzing the relationship between the NAO and the MJO with lagged composites showed when the MJO leads the NAO, significant positive NAOs are found for phases 2, and negative NAOs for phases 8, indicating a significant influence of the MJO on NAO. The synoptic-dynamic analysis showed that three low pressure and one high pressure were the dominant systems that have been effective in producing extreme precipitation. Examination of the moisture fluxes revealed that the main humidity sources of the heavy precipitation were the Arabian Sea due to easterly winds that travel a long distance over the north west of Indian Ocean to the Arabian Sea.</Abstract>
			<OtherAbstract Language="FA">Some extreme precipitations have occurred in Iran in recent years. This paper is devoted to the study of extreme precipitations in the west of Iran, affected by combination of atmospheric pressure patterns in the period of 1987–2016. At first, monthly precipitations for seven synoptic stations of the west of Iran in autumn and winter with positive anomalies greater than 100% were identified. Then, for statistical-dynamical analysis, the El-Nino Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Madden–Julian Oscillation (MJO) indices were used. Results showed that the extreme precipitations had occurred during moderate to strong El-Nino, while MJO was critical and strong, in phases 2 and 8, and NAO was in positive phase. The anomalies of the MJO index in case studies had positive values. The NAO for case studies has entered a positive phase from a strong negative phase a few days before extreme precipitation. Analyzing the relationship between the NAO and the MJO with lagged composites showed when the MJO leads the NAO, significant positive NAOs are found for phases 2, and negative NAOs for phases 8, indicating a significant influence of the MJO on NAO. The synoptic-dynamic analysis showed that three low pressure and one high pressure were the dominant systems that have been effective in producing extreme precipitation. Examination of the moisture fluxes revealed that the main humidity sources of the heavy precipitation were the Arabian Sea due to easterly winds that travel a long distance over the north west of Indian Ocean to the Arabian Sea.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">extreme precipitation</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">pressure patterns</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">ENSO</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">MJO</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">NAO</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">West of Iran</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jesphys.ut.ac.ir/article_83549_374f2327afac1b1aea38528f055ca331.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>مؤسسه ژئوفیزیک دانشگاه تهران</PublisherName>
				<JournalTitle>فیزیک زمین و فضا</JournalTitle>
				<Issn>2538-371X</Issn>
				<Volume>47</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2022</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Some Physical Properties of Mesoscale Eddies in the Caspian Sea Basins Based on Numerical Simulations</ArticleTitle>
<VernacularTitle>Some Physical Properties of Mesoscale Eddies in the Caspian Sea Basins Based on Numerical Simulations</VernacularTitle>
			<FirstPage>219</FirstPage>
			<LastPage>230</LastPage>
			<ELocationID EIdType="pii">81510</ELocationID>
			
<ELocationID EIdType="doi">10.22059/jesphys.2021.318928.1007290</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Abdolsamad</FirstName>
					<LastName>Rahnemania</LastName>
<Affiliation>Ph.D. Graduated, Department of Space Physics, Institute of Geophysics, University of Tehran, Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Abbas Ali</FirstName>
					<LastName>Aliakbari-Bidokhti</LastName>
<Affiliation>Professor, Department of Space Physics, Institute of Geophysics, University of Tehran, Tehran, Iran</Affiliation>
<Identifier Source="ORCID">0000-0003-4841-2218</Identifier>

</Author>
<Author>
					<FirstName>Javad</FirstName>
					<LastName>Babagoli Matikolaei</LastName>
<Affiliation>M.Sc. Graduated, Department of Space Physics, Institute of Geophysics, University of Tehran, Tehran, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2021</Year>
					<Month>02</Month>
					<Day>15</Day>
				</PubDate>
			</History>
		<Abstract>This paper investigates the mechanism of the eddy’s formation and their locations in the Caspian Sea using numerical simulations. The HYCOM model is used to simulate the evolutions of eddies. The model ran for 18 years from 1992 to 2009 while river runoff and atmospheric forcing are applied in the model as input files. The model output is appropriately compared to some observation data. The results indicate that one cyclonic eddy in the middle and two cyclonic and anticyclonic eddies in the southern basin of the Caspian Sea are the main eddies in this closed sea. Herein we prepare a comprehensive map to show the exact location of eddies with their important features like scales of them in all months using model simulation outputs. Topographic steering seems to be very important in the formation of mesoscale deep basin size eddies.</Abstract>
			<OtherAbstract Language="FA">This paper investigates the mechanism of the eddy’s formation and their locations in the Caspian Sea using numerical simulations. The HYCOM model is used to simulate the evolutions of eddies. The model ran for 18 years from 1992 to 2009 while river runoff and atmospheric forcing are applied in the model as input files. The model output is appropriately compared to some observation data. The results indicate that one cyclonic eddy in the middle and two cyclonic and anticyclonic eddies in the southern basin of the Caspian Sea are the main eddies in this closed sea. Herein we prepare a comprehensive map to show the exact location of eddies with their important features like scales of them in all months using model simulation outputs. Topographic steering seems to be very important in the formation of mesoscale deep basin size eddies.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">HYCOM</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">numerical modelling</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Mesoscale eddies</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Caspian Sea</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jesphys.ut.ac.ir/article_81510_2281696efe1bb9dce95822a3e4b5c378.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>مؤسسه ژئوفیزیک دانشگاه تهران</PublisherName>
				<JournalTitle>فیزیک زمین و فضا</JournalTitle>
				<Issn>2538-371X</Issn>
				<Volume>47</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2022</Year>
					<Month>01</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Spatio-Temporal Distribution of Various Types of Dust Events in the Middle East during the Period 1996-2015</ArticleTitle>
<VernacularTitle>Spatio-Temporal Distribution of Various Types of Dust Events in the Middle East during the Period 1996-2015</VernacularTitle>
			<FirstPage>231</FirstPage>
			<LastPage>248</LastPage>
			<ELocationID EIdType="pii">83547</ELocationID>
			
<ELocationID EIdType="doi">10.22059/jesphys.2021.321010.1007306</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Parisa</FirstName>
					<LastName>Fattahi Masrour</LastName>
<Affiliation>Ph.D. Student, Department of Marine and Atmospheric Science (Non-Biologic), Faculty of Marine Science and Technology, University of Hormozgan, Bandarabbas, Iran</Affiliation>
<Identifier Source="ORCID">0000-0002-2829-4018</Identifier>

</Author>
<Author>
					<FirstName>Maryam</FirstName>
					<LastName>Rezazadeh</LastName>
<Affiliation>Assistant Professor, Department of Marine and Atmospheric Science (Non-Biologic), Faculty of Marine Science and Technology, University of Hormozgan, Bandarabbas, Iran</Affiliation>
<Identifier Source="ORCID">0000-0002-7329-8368</Identifier>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2021</Year>
					<Month>04</Month>
					<Day>03</Day>
				</PubDate>
			</History>
		<Abstract>In recent years, an increase in the frequency of dust storms in the Middle East has been experienced. Identifying the potential sources of dust is essential to manage the hazardous consequences of dust storms. In addition, the relation between dust events and meteorological factors such as wind speed and horizontal visibility in the Middle East is lacking. The relation between dust events and topographical features such as soil texture in the Middle East is also unclear. In this study, dust events in the Middle East were classified based on horizontal visibility and the present weather reports during the period 1996-2015. Frequencies of different types of dust events, including blowing dust, dust in suspension, dust storm and severe dust storm, were estimated. The average concentrations of dust particles in the Middle East were also estimated based on horizontal visibility. Wind speed makes a critical contribution to dust events in the Middle East, thus wind speeds were also analyzed over the regions with relatively high frequency of dust events. In addition, maps of soil texture, elevation of landforms and the vegetation cover percentage, which have been obtained by the Weather Research and Forecasting (WRF) preprocessing system (WPS), were evaluated. The highest frequency of dust events is observed in five domains, which include Sudan, Saudi Arabia, Iraq, the United Arab Emirates (UAE), Afghanistan, Pakistan and Iran. Dust in suspension has the highest frequency among all types of the dust events studied here, particularly in southeastern Iran and central and eastern Iraq. Seasonal variations in dust event activity are directly related to wind speed, such that the frequency of dust events is the highest in June and July when winds are strongest, and lowest in January when winds are weakest. Maximum dust concentrations are observed in Saudi Arabia, Yemen and Iraq. The maximal frequency of dust storms in the Middle East occurs in May, June and July. Due to the differences in soil texture, elevation and vegetation cover, the dust emission in the Middle East is characterized by significant spatial heterogeneity. Our numerical analysis shows that sources of dust in the Middle East are mostly topographical lows with heights below 400 m, including sources in Sudan, northeastern and eastern Saudi Arabia, Iraq and Pakistan. Nevertheless, in the southwestern Arabian Peninsula, the height of sources of dust reaches to approximately 1200-2400 m. The upper surface texture of soil in region A (northeastern Sudan) is loam and sandy loam, in region B (Yemen and the southwestern Arabian Peninsula) is loamy sand and loam, in region C (northeastern Saudi Arabia, eastern Iraq and western Iran) is clay loam and loam, in region D (the UAE) is sand, sandy loam and loam, and in region E (Afghanistan, Pakistan and southeastern Iran) is loam clay and loam. The upper surface texture of soil in areas with the highest dust frequency is sandy loam and clay loam. The spatial distributions of the vegetation cover percentage show a sharp decline (below 1%) in Sudan, Saudi Arabia, Iraq, Central and Southern Iran and Pakistan.</Abstract>
			<OtherAbstract Language="FA">In recent years, an increase in the frequency of dust storms in the Middle East has been experienced. Identifying the potential sources of dust is essential to manage the hazardous consequences of dust storms. In addition, the relation between dust events and meteorological factors such as wind speed and horizontal visibility in the Middle East is lacking. The relation between dust events and topographical features such as soil texture in the Middle East is also unclear. In this study, dust events in the Middle East were classified based on horizontal visibility and the present weather reports during the period 1996-2015. Frequencies of different types of dust events, including blowing dust, dust in suspension, dust storm and severe dust storm, were estimated. The average concentrations of dust particles in the Middle East were also estimated based on horizontal visibility. Wind speed makes a critical contribution to dust events in the Middle East, thus wind speeds were also analyzed over the regions with relatively high frequency of dust events. In addition, maps of soil texture, elevation of landforms and the vegetation cover percentage, which have been obtained by the Weather Research and Forecasting (WRF) preprocessing system (WPS), were evaluated. The highest frequency of dust events is observed in five domains, which include Sudan, Saudi Arabia, Iraq, the United Arab Emirates (UAE), Afghanistan, Pakistan and Iran. Dust in suspension has the highest frequency among all types of the dust events studied here, particularly in southeastern Iran and central and eastern Iraq. Seasonal variations in dust event activity are directly related to wind speed, such that the frequency of dust events is the highest in June and July when winds are strongest, and lowest in January when winds are weakest. Maximum dust concentrations are observed in Saudi Arabia, Yemen and Iraq. The maximal frequency of dust storms in the Middle East occurs in May, June and July. Due to the differences in soil texture, elevation and vegetation cover, the dust emission in the Middle East is characterized by significant spatial heterogeneity. Our numerical analysis shows that sources of dust in the Middle East are mostly topographical lows with heights below 400 m, including sources in Sudan, northeastern and eastern Saudi Arabia, Iraq and Pakistan. Nevertheless, in the southwestern Arabian Peninsula, the height of sources of dust reaches to approximately 1200-2400 m. The upper surface texture of soil in region A (northeastern Sudan) is loam and sandy loam, in region B (Yemen and the southwestern Arabian Peninsula) is loamy sand and loam, in region C (northeastern Saudi Arabia, eastern Iraq and western Iran) is clay loam and loam, in region D (the UAE) is sand, sandy loam and loam, and in region E (Afghanistan, Pakistan and southeastern Iran) is loam clay and loam. The upper surface texture of soil in areas with the highest dust frequency is sandy loam and clay loam. The spatial distributions of the vegetation cover percentage show a sharp decline (below 1%) in Sudan, Saudi Arabia, Iraq, Central and Southern Iran and Pakistan.</OtherAbstract>
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			<Param Name="value">Dust distribution</Param>
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			<Param Name="value">Dust frequency</Param>
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<ArchiveCopySource DocType="pdf">https://jesphys.ut.ac.ir/article_83547_dbdf29da04ddbdb0e4315390c3c01a98.pdf</ArchiveCopySource>
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