Wavelet analysis of the ionospheric response at mid-latitudes during the April 200 storm using magnetograms and vTEC from GPS

In this work we pursue the idea of computing a parameter that allows us to estimate the local ionospheric response to a geospheric event that triggers an ionospheric storm. For that, wavelet technique has been chosen because of its ability to analyze non-stationary signals. The advantage of the time-frequency analysis method called Wavelet Transform resides in providing information not only about the frequencies of the event but also about its location in the time series. Specifically, we compute the Scale Average Wavelet Power (SAWP) of two parameters that describe the local geomagnetic field variation at the Earth surface caused by a geospheric storm and ionospheric response to the storm event. In particular, we propose the time delay between the maximum values of SAWP applied to the vTEC (vertical Total Electron Content) and the horizontal component of the geomagnetic field (H) variations as parameters to characterize the local behavior of the ionospheric storm. We applied the parameter to the geomagnetic and ionospheric disturbances caused by a coronal mass ejection (CME) that took place on April 4, 2000. We used vTEC values computed from GPS observations and H at the surface of the Earth, measured in stations near to each GPS station chosen. The vTEC values used came from the GPS permanent stations belonging to the global IGS (International GNSS Service) network. We chose stations located at magnetic mid-latitudes. Moreover, three-longitude bands representing the ionospheric behavior at different local times (LT) were studied. Because the April 2000 storm has been extensively studied for many authors, the results are compared with those in the literature and we found a very good agreement as expected.En este trabajo perseguimos la idea de estimar un parámetro que nos permita calcular la respuesta ionosférica local a un evento geosférico desencadenante de una tormenta ionosférica. Para ello, se eligió la aplicación de la técnica ondeleta debido a su capacidad para analizar señales no estacionarias. La ventaja del método de análisis en tiempo y frecuencia llamada Transformada Ondeleta reside en el hecho de que provee información, no sólo acerca de las frecuencias del evento, sino también sobre su ubicación en la serie de tiempo. En concreto, se calcula el promedio por escalas de la potencia de la transformada ondeleta (SWAP, de su sigla en inglés Scale Average Wavelet Power) para dos parámetros que describen la respuesta local de la magnetosfera y la ionosfera a una tormenta. En particular, se propone el retraso de tiempo entre los valores máximos de SAWP aplicadas al vTEC (Contenido Electrónico Total en dirección Vertical) y la componente horizontal del campo geomagnético (H), como parámetros cuyas variaciones caracterizan el comportamiento local de la tormenta ionosférica. El parámetro propuesto se aplicó a las perturbaciones geomagnética e ionosférica causadas por una eyección de masa coronal (CME, Coronal Mass Ejection), que tuvo lugar el 4 de abril de 2000. Se utilizaron valores vTEC calculados a partir de las observaciones GPS y H en la superficie de la Tierra, medida en las estaciones cercanas a cada estación de GPS elegida. Los valores de vTEC utilizados provinieron de las estaciones GPS permanentes que pertenecen a la red del servicio internacional IGS (International GNSS Service). Entre todas, elegimos estaciones situadas en latitudes magnéticas medias. Por otra parte, estudiamos tres bandas de longitud que representan el comportamiento de la ionosfera a distintas horas locales (LT). Debido a que la tormenta de abril de 2000 ha sido ampliamente estudiada por muchos autores, los resultados se comparan con los de la literatura y nos encontramos con un muy buen acuerdo entre los datos publicados y nuestros resultados, tal y como se esperaba.Fil: Fernandez, Laura Isabel. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Meza, Amalia Margarita. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; ArgentinaFil: Van Zele, Maria Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias Geológicas; Argentin

Geomagnetism : review 2010

The Geomagnetism team measures, records, models and interprets variations in the Earth’s natural magnetic fields, across the world and over time. Our data and expertise help to develop scientific understanding of the evolution of the solid Earth and it’s atmospheric, oceanic and space environments. We also provide geomagnetic products and services to industry and academics and we use our knowledge to inform and educate the public, government and the private sector

Geomagnetic control of the spectrum of traveling ionospheric disturbances based on data from a global GPS network

In this paper an attempt is made to verify the hypothesis on the role of geomagnetic disturbances as a factor determining the intensity of traveling ionospheric disturbances (TIDs). To improve the statistical validity of the data, we have used the based on the new GLOBDET technology method involving a global spatial averaging of disturbance spectra of the total electron content (TEC). To characterize the TID intensity quantitatively, we suggest that a new global index of the degree of disturbance should be used, which is equal to the mean value of the rms variations in TEC within the selected range of spectral periods (of 20-60 min in the present case). It was found that power spectra of daytime TEC variations in the range of 20-60 min periods under quiet conditions have a power-law form, with the slope index k = -2.5. With an increase of the level of magnetic disturbance, there is an increase in total intensity of TIDs, with a concurrent kink of the spectrum caused by an increase in oscillation intensity in the range of 20-60 min. It was found that an increase in the level of geomagnetic activity is accompanied by an increase in total intensity of TEC; however, it correlates not with the absolute level of Dst, but with the value of the time derivative of Dst (a maximum correlation coefficient reaches -0.94). The delay of the TID response of the order of 2 hours is consistent with the view that TIDs are generated in auroral regions, and propagate equatorward with the velocity of about 300-400 m/s.Comment: LaTeX2.09, 16 pages, 5 figures, 1 table, egs.cls, egs.bst (the style files

Geomagnetism : review 2009

The Geomagnetism team measures, records, models and interprets variations in the Earth’s natural magnetic fields, across the world and over time. Our data and expertise help to develop scientific understanding of the evolution of the solid Earth and its atmospheric, ocean and space environments. We also provide geomagnetic products and services to industry and academics and we use our knowledge to inform and educate the public, government and the private sector

A density-temperature description of the outer electron radiation belt during geomagnetic storms

Bi-Maxwellian fits are made to energetic-electron flux measurements from seven satellites in geosynchronous orbit, yielding a number density (n) and temperature (T) description of the outer electron radiation belt. For 54.5 spacecraft years of measurements the median value of n is 3.7 × 10−4 cm−3, and the median value of T is 148 keV. General statistical properties of n, T, and the 1.1–1.5 MeV flux F are investigated, including local-time and solar-cycle dependencies. Using superposed-epoch analysis where the zero epoch is convection onset, the evolution of the outer electron radiation belt through high-speed-stream-driven storms is investigated. The number-density decay during the calm before the storm, relativistic-electron dropouts and recoveries, and the heating of the outer electron radiation belt during storms are analyzed. Using four different “triggers” (sudden storm commencement (SSC), southward interplanetary magnetic field (IMF) portions of coronal mass ejection (CME) sheaths, southward-IMF portions of magnetic clouds, and minimum Dst) a selection of CME-driven storms are analyzed with superposed-epoch techniques. For CME-driven storms, only a very modest density decay prior to storm onset is found. In addition, the compression of the outer electron radiation belt at the time of SSC is analyzed, the number-density increase and temperature decrease during storm main phase are characterized, and the increase in density and temperature during storm recovery phase is determined. During the different phases of storms, changes in the flux are sometimes in response to changes in the temperature, sometimes to changes in the number density, and sometimes to changes in both. Differences are found between the density-temperature and flux descriptions, and it is concluded that more information is available using the density-temperature description

Short term Variability of the Sun Earth System: An Overview of Progress Made during the CAWSES II Period

This paper presents an overview of results obtained during the CAWSES II period on the short term variability of the Sun and how it affects the near Earth space environment. CAWSES II was planned to examine the behavior of the solar terrestrial system as the solar activity climbed to its maximum phase in solar cycle 24. After a deep minimum following cycle 23, the Sun climbed to a very weak maximum in terms of the sunspot number in cycle 24 (MiniMax24), so many of the results presented here refer to this weak activity in comparison with cycle 23. The short term variability that has immediate consequence to Earth and geospace manifests as solar eruptions from closed field regions and high speed streams from coronal holes. Both electromagnetic (flares) and mass emissions (coronal mass ejections, CMEs) are involved in solar eruptions, while coronal holes result in high speed streams that collide with slow wind forming the so called corotating interaction regions (CIRs). Fast CMEs affect Earth via leading shocks accelerating energetic particles and creating large geomagnetic storms. CIRs and their trailing high speed streams (HSSs), on the other hand, are responsible for recurrent small geomagnetic storms and extended (days) of auroral zone activity, respectively. The latter lead to the acceleration of relativistic magnetospheric killer electrons. One of the major consequences of the weak solar activity is the altered physical state of the heliosphere that has serious implications for the shock-driving and storm causing properties of CMEs. Finally, a discussion is presented on extreme space weather events prompted by the 2012 July 23 super storm event that occurred on the backside of the Sun. Many of these studies were enabled by the simultaneous availability of remote-sensing and in situ observations from multiple vantage points with respect to the Sun Earth line.Comment: 85 pages, 30 figures, 2 tables, Accepted for publication in Progress in Earth and Planetary Science on April 13, 201

Deep learning for face detection using matlab

This project report presents face detection using Convolutional Neural Network algorithm and Deep Learning combination (DCT / DL) throughout MATLAB simulation and modeling. It reveals that the research project has successfully managed to establish an accurate accurate human face detection and crystal-clear human face recognition systems. The system will annul the face image that are tilted, the images on non-human faces as well as the images of human faces that have watermarks. The test results on face tracking when the image has watermarks. Under this condition, it looks like the CNN and deep learning could not identify the image correctly and wrong result is showing for the second image. This indicates that there is a limitation for the CNN and deep learning algorithm. The disadvantage is, it cannot detects the watermark image, as this image is protected. This process will proceed to Convolutional Neural Network algorithm to identify the human face from a given image. If the image belongs to human features then there will be a tracking box marking clearly the appointed face with a yellow square. This marker will be clearly pointing and shaping a yellowish box of the appointed and selected face or image.The novelty of this research project is that the CNN and deep learning (CNN / DL) methods to trace, scan and detect the human face in a very successful and effective manners taking into account the following distinguished features: the face of the human facing to the front view and not tilted or the face does not make any angles unless angels within 5 to 10 degrees only. The face must not be hiding or nor recognizable or positioned on another object. The face must be real and is not printed on any object like wood or plastic. The water mark must not be printed on the face image picture, otherwise the CNN / DL will not recognize it as human face. The working of the algorithm depends on the deep learning where the system needs to learn the image, identify the faces and store the images into database. By creating a folder called image folder, it will be easy for the MATLAB access into the folder to find the images that content human face and none human face. High resolution for face detection was approximately 85%. The algorithm was able to distinguish between human and non-human faces. By doing this we saved a lot of time in almost half