scholarly journals Dynamics and spatio-temporal distribution of geomagnetic disturbances during periods of increased solar activity and magnetic storms

2020 ◽  
Vol 196 ◽  
pp. 02009
Author(s):  
Oksana Mandrikova ◽  
Anastasia Rodomanskay
Keyword(s):  
Cross Correlation ◽  
Temporal Distribution ◽  
Temporal Analysis ◽  
Auroral Zone ◽  
Magnetic Storms ◽  
Magnetic Data ◽  
Geomagnetic Disturbances ◽  
Short Period ◽  
Adaptive Thresholds ◽  
Spatio Temporal

A detailed spatio-temporal analysis of magnetic data was performed during the periods of magnetic storms on October 02, 2013 and September 27, 2019 based on measurements of the station network. In this work, we used a method developed by us for the analysis of magnetic data, based on the use of wavelet transform and adaptive thresholds. The method allows us to identify short-period field disturbances and estimate their intensity from the data of the H-component of the geomagnetic field. The features of the occurrence and propagation of geomagnetic disturbances in the auroral zone and at meridionally located stations have been studied. Dynamic spectra of disturbances of different intensity and duration are obtained. The paper confirms the possibility of occurrence of short-period weak geomagnetic disturbances at stations from high latitudes to the equator, preceding magnetic storms and correlating with fluctuations of the southern Bz-component of the interplanetary magnetic field and increases in the auroral indices of geomagnetic activity. Cross-correlation dependences of the intensity of geomagnetic disturbances on the parameters of the interplanetary medium during magnetic storms were obtained from the data of the network of magnetic stations. A statistically significant influence of the magnitude of the scope of the Bz-component of the IMF and the speed of the solar wind on the development of magnetic storms during the initial and main phases of magnetic storms was revealed.

scholarly journals Analysis of geomagnetic disturbances dynamics during increased solar activity and magnetic storms (according to the measurements of INTERMAGNET station network)

2019 ◽  
Vol 127 ◽  
pp. 02003
Author(s):  
Oksana Mandrikova ◽  
Anastasia Rodomanskay ◽  
Alexander Zaitsev
Keyword(s):  
Geomagnetic Activity ◽  
Geomagnetic Field ◽  
Auroral Zone ◽  
Magnetic Storms ◽  
Magnetic Data ◽  
Field Variation ◽  
Geomagnetic Disturbances ◽  
Station Network ◽  
Ground Station ◽  
Automated Method

We present and describe an automated method for analysis of magnetic data and for detection of geomagnetic disturbances based on wavelet transformation. The parameters of the computational algorithms allow us to estimate the characteristics of non-uniformly scaled peculiar properties in the variations of geomagnetic field that arise during increasing geomagnetic activity. The analysis of geomagnetic data before and during magnetic storms was carried out on the basis of the method according to ground station network. Periods of increasing geomagnetic activity, which precede and accompany magnetic storms, are highlighted. The dynamic of geomagnetic field variation in the auroral zone is considered in detail.

GICS IN THE MAIN TRANSMISSION LINE “NORTHERN TRANSIT” IN RUSSIA AND IN THE MÄNTSÄLÄ FINLAND PIPELINE: A CASE STUDY

2021 ◽  
Vol 44 ◽  
pp. 20-23
Author(s):  
I.V. Despirak ◽  
◽  
P.V. Setsko ◽  
Ya.A. Sakharov ◽  
V.N. Selivanov ◽  
...  
Keyword(s):  
Negative Impact ◽  
Temporal Structure ◽  
Auroral Zone ◽  
Magnetic Data ◽  
Geomagnetically Induced Currents ◽  
Camera System ◽  
Natural Gas Pipeline ◽  
Spatio Temporal ◽  
Using Data

Geomagnetically induced currents (GICs), arising both on power lines and on pipelines, may have strong negative impact on the technological networks up to accidents ("blackouts"). Magnetospheric disturbances are one of the factors in the appearance of GICs, however there is no unambiguous relationship between substorm and presence of currents. In this paper, we consider two intense cases of GIC (15March 2012 and 17 March 2013), registered on two different technological networks: 1) on the "Nothern Transit" power line (Vykhodnoy, Revda and Kondopoga stations) located in the auroral zone, 2) on the Finnish natural gas pipeline near Mäntsälä located in the subauroral zone. Both GIC cases are compared with substorm development in the auroral zone, using data from IMAGE magnetometers network and MAIN camera system in Apatity. We found a good correlation between the GIC appearance and variations of geomagnetic indexes: IL – index, which characterized of westward electrojet intensity on the IMAGE meridian and Wp - index, which describes the wave activity of the substorm. Besides, it was shown also a good correlation between GICs and the thin spatio-temporal structure of the substorm development (the appearance and the propagation to the pole of substorm activations), which is appeared both in the magnetic data and in the all sky camera images.

scholarly journals Arabian Sea Tropical Cyclones: A Spatio-Temporal Analysis in Support of Natural Hazard Risk Appraisal in Oman

2021 ◽  
Author(s):  
Suad Al-Manji ◽  
Gordon Mitchell ◽  
Amna Al Ruheili
Keyword(s):  
High Risk ◽  
Tropical Cyclones ◽  
Natural Hazard ◽  
Temporal Distribution ◽  
Storm Surges ◽  
Temporal Analysis ◽  
The North ◽  
Risk Areas ◽  
Spatio Temporal ◽  
Extreme Winds

Tropical cyclones [TCs] are a common natural hazard that have significantly impacted Oman. Over the period 1881–2019, 41 TC systems made landfall in Oman, each associated with extreme winds, storm surges and significant flash floods, often resulting in loss of life and substantial damage to infrastructure. TCs affect Omani coastal areas from Muscat in the north to Salalah in the south. However, developing a better understanding of the high-risk regions is needed, and is of particular interest in disaster risk reduction institutions in Oman. This study aims to find and map TC tracks and their spatio-temporal distribution to landfall in Oman to identify the high-risk areas. The analysis uses Kernel Density Estimation [KDE] and Linear Direction Mean [LDM] methods to better identify the spatio-temporal distribution of TC tracks and their landfall in Oman. The study reveals clear seasonal and monthly patterns. This knowledge will help to improve disaster planning for the high-risk areas.

scholarly journals Spatial-temporal analysis and visualization of scarlet fever in mainland China from 2004 to 2017

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Wei-tong Li ◽  
Rui-hua Feng ◽  
Tong Li ◽  
Yan-bing Du ◽  
Nan Zhou ◽  
...  
Keyword(s):  
Surface Analysis ◽  
Scarlet Fever ◽  
Spatial Clustering ◽  
National Level ◽  
Mainland China ◽  
Temporal Distribution ◽  
Temporal Analysis ◽  
Trend Surface Analysis ◽  
Trend Surface ◽  
Spatio Temporal

This study retrospectively analyzed the spatio-temporal distribution and spatial clustering of scarlet fever in mainland China from 2004 to 2017. In recent years, the incidence of scarlet fever is increasing. Previous studies on the spatial distribution of scarlet fever in China are mainly focused at the provincial and municipal levels, and there is few systematic report on the spatial and temporal distribution characteristics of scarlet fever on the national level. Based on the incidence information of scarlet fever in mainland China between 2004 and 2017 collected from the China Center for Disease Control, this paper systematically explored the Spatio-temporal distribution of scarlet fever by three methods, contains spatial autocorrelation analysis, Spatio-temporal scanning analysis, and trend surface analysis. The results demonstrate that the incidence of scarlet fever varies by seasons, which is in line with double-peak distribution.The first peak generally occurs from May to June and the second one from November to December, while February and August is the lowest period of incidence. Trend surface analysis indicates that the incidence of scarlet fever in northern China is higher than the south, slightly higher in western compared to the east, and lower in the central part. Additionally, the results show that the clustering regions of scarlet fever centrally distributed in the northeast, northwest, north china and some provinces in the east, such as Zhejiang, Shanghai, Shandong, and Jiangsu.       

Spatio-temporal analysis of colorectal cancer using a geographic information system in the Iranian military community during the period 2007–2016

2019 ◽  
Vol 166 (E) ◽  
pp. e8-e12
Author(s):  
Alireza Khoshdel ◽  
M Alimohammadi ◽  
M Sepandi ◽  
Y Alimohamadi ◽  
P Jalali ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Disease Prevention ◽  
Temporal Distribution ◽  
Temporal Analysis ◽  
Individual Risk ◽  
Cancer Type ◽  
North West ◽  
Prevention Programmes ◽  
Military Community ◽  
Spatio Temporal

IntroductionColorectal cancer (CRC) is one of the most prevalent cancers among Iranian people. The study of spatio-temporal distribution of disease has an important role in the design of disease prevention programmes. The purpose of the current study was to describe the spatio-temporal distribution of CRC in the Iranian military community as a sample of the Iranian population.MethodsIn the current ecological study, all registered cancer cases in the Iranian military community during the period 2007–2016 were considered. To identify hotspots, Getis-Ord Gi statistics were used. All analyses were performed using ArcGIS 10.5 and Excel 2010.ResultsThe highest incidences of CRC in 2007–2008, 2009–2010 and 2011–2012 were recorded in Kermanshah province. The highest incidences of CRC in 2013–2014 were seen in Kermanshah, Ghilan, Tehran and North Khorasan. In 2007–2008 and 2009–2010, hotspots were detected in West Azarbayjan. In 2011–2012, hotspots were detected in Zanjan and Qazvin. In 2013–2014, a hotspot was detected in Qazvin. Finally, West Azerbaijan was the hotspot for CRC in 2015–2016.ConclusionsThe incidence of CRC in men was higher than in women. Also it appeared that North and North West Iran were risk areas for this disease, and so these areas should be considered in the design of disease prevention programme for this cancer type. Additionally, the determination of individual risk factors in the aforementioned geographical areas can play an important role in the prevention of this type of cancer.

scholarly journals Spatio-Temporal Analysis of Rainfall Variability and its Prediction in Al-Qassim Region Using (1987-2017): التحليل المكاني والزماني لتباين التهاطل المطري والتنبؤ به في منطقة القصيم (2017-1987)

2020 ◽  
Vol 4 (4) ◽  
Author(s):  
Aljazy Khalid Alturki, Ahmad Abdullah Aldughairi
Keyword(s):  
Urban Areas ◽  
Rainfall Variability ◽  
Temporal Distribution ◽  
Temporal Analysis ◽  
Seasonal Rainfall ◽  
Economic Activities ◽  
Systems Software ◽  
Distance Weighted ◽  
Spatio Temporal ◽  
The Stability

This study aimed to analyze the indicators of spatial and temporal distribution of daily, monthly, and seasonal rainfall measurements. It is looking for the possibility of the stability or change of precipitation properties by using the data of the present. Also, it is working with the most important factors that effects on the rainfall, Moreover, many of some statistical methods applied in this study. Using inverted distance weighted Inverse Distance Weighting (IDW) method to generates rain interpolation surface that is tool approves in geographic information systems software. Rain is an important element of many economic activities. Therefore, the importance of predicting the spatial distribution of precipitation that is important from water rain resources. This study presents an analysis of spatiotemporal variation of the daily, monthly and seasonal rainfall in Qassim region, based on data seven weather stations, that is including, Buraidah, Unaizah, Al Rasa, and the General Authority for Meteorology and Environmental Protection, also Prince Nayef Airport Station between (2017-1987) which period included 31 years for the accuracy of the results. The study reached to several recommendations that can be used in geographical fields, whether environmental or human, which are related to water resources and torrents, rainwater drainage projects and urban areas to avoid disasters.

scholarly journals Epidemiology of Dengue viral infection in Nepal: 2006-2019

2020 ◽  
Author(s):  
Komal Raj Rijal ◽  
Bipin Adhikari ◽  
Bindu Ghimire ◽  
Binod Dhungel ◽  
Uttam Raj Pyakurel ◽  
...  
Keyword(s):  
High Risk ◽  
Temporal Distribution ◽  
Temporal Analysis ◽  
Emerging Diseases ◽  
Standard Deviation Increase ◽  
First Report ◽  
Vector Borne Diseases ◽  
Dengue Outbreak ◽  
Epidemiological Trend ◽  
Spatio Temporal

AbstractBackgroundDengue is one of the newest emerging diseases in Nepal with increasing burden and geographic spread over the last 14 years. The main objective of this study was to explore the spatio-temporal epidemiological patterns of Dengue since its first report (2006) till 2019 in Nepal.MethodsThis study is a retrospective analysis of dengue data available from the Epidemiological Disease Control Division (EDCD) of Government of Nepal. The data in this study cover the last 14 years (2006-2019) of reported dengue cases in Nepal. Epidemiological trend and spatio-temporal analyses were performed. Maps of reported case incidence were created using QGIS version 3.4.ResultsSince the first report of dengue in a foreigner in 2004, Nepal reported a total of 17,992 dengue cases in 68 districts of Nepal in 2019. The incidence was approximately five times higher in 2018 (Incidence Rate Ratio (IRR): 4.8; 95% CI: 1.5 – 15.3) and over 140 times higher in 2019 (IRR: 141.6; CI: 45.8 – 438.4). Population density was not a statistically significant predictor of case incidence. Mean elevation had a negative association with case incidence. A one standard deviation increase in elevation was associated with a 90% decrease in reported case incidence (IRR: 0.10; CI: 0.01 – 0.20). However, the association with mean elevation varied across the years. In comparison to 2016, incidence was greater at higher elevations in 2018 (IRR: 22.7; CI: 6.0 - 86.1) and 2019 (IRR: 9.6; CI: 2.6 - 36.1).ConclusionThere is a high risk of dengue outbreak in the Terai region with increasing spread towards the mid-mountains and beyond as seen over the last 14 years. Urgent measures are required to increase the availability of diagnostics and resources to mitigate future dengue epidemics. Findings from this study can inform the spatio-temporal distribution of dengue and can help in resource allocation and priority setting for future epidemic.Author summaryDengue in humans is caused by four different serotypes (DENV-1, DENV-2, DENV-3 & DENV-4). Globally it is the most pervasive vector borne diseases with increasing number of cases in recent years. Dengue is one of the youngest emerging diseases in Nepal with increasing cases and spread from the tropical lowland to the highland (hilly) regions. We conducted a spatio-temporal analysis of national data to consolidate the information using QGIS to measure the dengue incidence at district levels of Nepal. Spatio-temporal analysis exploring the incidence and distribution of dengue cases aids in identification of high-risk areas which can ultimately enable national dengue programme to mobilize and allocate resources for the control and treatment. This study shows, the persistent high risk of dengue outbreak in lowland Terai region with annual rise in the risk of spread towards the mid-mountains and beyond. Urgent measures are required to increase the diagnostics and resources to mitigate the epidemic burden of dengue in Terai and peripheral regions.

scholarly journals Spatial distribution of temperature during geomagnetic disturbances

2018 ◽  
Vol 4 (4) ◽  
pp. 59-62 ◽  
Author(s):  
Ашхен Караханян ◽  
Ashhen Karakhanyan ◽  
Сергей Молодых ◽  
Sergey Molodykh
Keyword(s):  
Solar Activity ◽  
Geomagnetic Activity ◽  
Lower Troposphere ◽  
Temporal Analysis ◽  
Reanalysis Data ◽  
Tropospheric Temperature ◽  
Geomagnetic Disturbances ◽  
Temperature Variations ◽  
Activity Effect ◽  
Spatio Temporal

We propose an index of efficiency of the solar activity effect on the tropospheric temperature, which takes into account the spatial irregularity of the response to this effect. As a proxy of solar activity we take the PC index of geomagnetic activity, designed to monitor the geomagnetic field at high latitudes. Using NCEP/NCAR reanalysis data, we carry out a comparative analysis of variations in the proposed index and lower-troposphere temperature variations during geomagnetic disturbances. We identify the presence of a high degree of correlation between the temperature in the 925–700 hPa layer and the proposed index of solar activity effect. The spatio-temporal analysis of the index and temperature variations shows that the index of effi-ciency of the solar activity effect describes well both the value and the sign of the observed variations in the spa-tial distribution of the lower-troposphere temperature as compared to the frequently used index of geomagnetic activity.

scholarly journals Spatio-Temporal Distribution of Flash Floods in Slovenia

Dela ◽  
2016 ◽  
pp. 5-39 ◽  
Author(s):  
Tajan Trobec
Keyword(s):  
Spatial Distribution ◽  
Temporal Distribution ◽  
Temporal Analysis ◽  
Flash Floods ◽  
Seasonal Distribution ◽  
Flash Flooding ◽  
Hilly Area ◽  
Spatio Temporal

This paper examines the spatial distribution of frequency of flash floods along with their seasonal distribution. The spatio-temporal analysis of past flash flooding covered 124 flash floods affecting areas of Slovenia between 1550 and 2015. Flash floods are most common in the mountainous and hilly area of northern Slovenia, which consists of alpine and a large part of subalpine landscapes. Autumnal flash floods occur across most of the country, while summer flash floods are seen mainly in the east. In most parts of the country autumnal flash floods predominate.

User Driven Query Framework of Social Networks for Geo-Temporal Analysis of Events of Interest

2015 ◽  
pp. 224-249 ◽  
Author(s):  
Gloria Bordogna ◽  
Simone Sterlacchini ◽  
Paolo Arcaini
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Clustering Algorithm ◽  
Temporal Distribution ◽  
Temporal Analysis ◽  
Local Scale ◽  
Temporal Clustering ◽  
Temporal Query ◽  
Spatio Temporal ◽  
Alternative Routes

In this chapter we propose a framework for collecting, organizing into a database and querying information in social networks by the specification of content-based, geographic and temporal conditions to the aim of detecting periodic and aperiodic events. Our proposal could be a basis for developing context aware services. For example to identify the streets and their rush hours by analyzing the messages in social media periodically sent by queuing drivers and to report these critical spatio-temporal situations to help other drivers to plan alternative routes. Specifically, we rely on a focused crawler to periodically collect messages in social networks related with the contents of interest, and on an original geo-temporal clustering algorithm in order to explore the geo-temporal distribution of the messages. The clustering algorithm can be customized so as to identify aperiodic and periodic events at global or local scale based on the specification of geographic and temporal query conditions.

Sign in / Sign up

Export Citation Format

Share Document