A Multiscale Approach to Geomagnetic Storm Morphology Analysis Based on DMA Activity Measures

The article is focused on the approach based on the discrete mathematical analysis conception and continues a series of studies related to the application of the previously developed methodology to geophysical data analysis. The main idea of the study is the modification of earlier conceptions regarding the interpreter’s logic that allows introducing a multiscale approach and performing the time series analysis using the activity measure plots, implying the vertical scale. This approach was used to study the morphology of several intense geomagnetic storms at the final stages of the 23rd and 24th solar activity cycles. Geomagnetic observatory data and interplanetary magnetic field parameters as well as the solar wind flux speed and proton density were analyzed for each of the studied storms using the activity measures. The developed methods, applied to geomagnetic storm morphological analysis, displayed good results in revealing the decreases and increases in various durations and intensities during storms, detecting low-amplitude disturbances, and storm sudden commencement recognition. The results provide an opportunity to analyze any physical data using a unified scale and, in particular, to implement this approach to geomagnetic activity studies.

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Studies of ionospheric F-region response in the Latin American sector during the geomagnetic storm of 21–22 January 2005

Annales Geophysicae ◽

10.5194/angeo-29-919-2011 ◽

2011 ◽

Vol 29 (5) ◽

pp. 919-929 ◽

Cited By ~ 20

Author(s):

Y. Sahai ◽

P. R. Fagundes ◽

R. de Jesus ◽

A. J. de Abreu ◽

G. Crowley ◽

...

Keyword(s):

Geomagnetic Storm ◽

Latin American ◽

Geomagnetic Disturbance ◽

Equatorial Station ◽

Phase Fluctuations ◽

Interplanetary Magnetic Fields ◽

F Region ◽

Storm Sudden Commencement ◽

Reversal Time ◽

Spread F

Abstract. In the present investigation, we have studied the response of the ionospheric F-region in the Latin American sector during the intense geomagnetic storm of 21–22 January 2005. This geomagnetic storm has been considered "anomalous" (minimum Dst reached −105 nT at 07:00 UT on 22 January) because the main storm phase occurred during the northward excursion of the Bz component of interplanetary magnetic fields (IMFs). The monthly mean F10.7 solar flux for the month of January 2005 was 99.0 sfu. The F-region parameters observed by ionosondes at Ramey (RAM; 18.5° N, 67.1° W), Puerto Rico, Jicamarca (JIC; 12.0° S, 76.8° W), Peru, Manaus (MAN; 2.9° S, 60.0° W), and São José dos Campos (SJC; 23.2° S, 45.9° W), Brazil, during 21–22 January (geomagnetically disturbed) and 25 January (geomagnetically quiet) have been analyzed. Both JIC and MAN, the equatorial stations, show unusually rapid uplifting of the F-region peak heights (hpF2/hmF2) and a decrease in the NmF2 coincident with the time of storm sudden commencement (SSC). The observed variations in the F-region ionospheric parameters are compared with the TIMEGCM model run for 21–22 January and the model results show both similarities and differences from the observed results. Average GPS-TEC (21, 22 and 25 January) and phase fluctuations (21, 22, 25, 26 January) observed at Belem (BELE; 1.5° S, 48.5° W), Brasilia (BRAZ; 15.9° S, 47.9° W), Presidente Prudente (UEPP; 22.3° S, 51.4° W), and Porto Alegre (POAL; 30.1° S, 51.1° W), Brazil, are also presented. These GPS stations belong to the RBMC/IBGE network of Brazil. A few hours after the onset of the storm, large enhancements in the VTEC and NmF2 between about 20:00 and 24:00 UT on 21 January were observed at all the stations. However, the increase in VTEC was greatest at the near equatorial station (BELE) and enhancements in VTEC decreased with latitude. It should be pointed out that no phase fluctuations or spread-F were observed in the Latin American sector during the post-sunset pre-reversal time in the geomagnetic disturbance (21 January). The disturbance dynamo electric field possibly resulted in downward drift of the F-region plasma and inhibited the formation of spread-F.

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Total electron content responses to HILDCAAs and geomagnetic storms over South America

Annales Geophysicae ◽

10.5194/angeo-35-1309-2017 ◽

2017 ◽

Vol 35 (6) ◽

pp. 1309-1326 ◽

Cited By ~ 5

Author(s):

Patricia Mara de Siqueira Negreti ◽

Eurico Rodrigues de Paula ◽

Claudia Maria Nicoli Candido

Keyword(s):

Solar Wind ◽

South America ◽

Total Electron Content ◽

Geomagnetic Storm ◽

Electric Fields ◽

Geomagnetic Storms ◽

Time Variability ◽

Electron Content ◽

Quiet Time ◽

Total Electron

Abstract. Total electron content (TEC) is extensively used to monitor the ionospheric behavior under geomagnetically quiet and disturbed conditions. This subject is of greatest importance for space weather applications. Under disturbed conditions the two main sources of electric fields, which are responsible for changes in the plasma drifts and for current perturbations, are the short-lived prompt penetration electric fields (PPEFs) and the longer-lasting ionospheric disturbance dynamo (DD) electric fields. Both mechanisms modulate the TEC around the globe and the equatorial ionization anomaly (EIA) at low latitudes. In this work we computed vertical absolute TEC over the low latitude of South America. The analysis was performed considering HILDCAA (high-intensity, long-duration, continuous auroral electrojet (AE) activity) events and geomagnetic storms. The characteristics of storm-time TEC and HILDCAA-associated TEC will be presented and discussed. For both case studies presented in this work (March and August 2013) the HILDCAA event follows a geomagnetic storm, and then a global scenario of geomagnetic disturbances will be discussed. Solar wind parameters, geomagnetic indices, O ∕ N2 ratios retrieved by GUVI instrument onboard the TIMED satellite and TEC observations will be analyzed and discussed. Data from the RBMC/IBGE (Brazil) and IGS GNSS networks were used to calculate TEC over South America. We show that a HILDCAA event may generate larger TEC differences compared to the TEC observed during the main phase of the precedent geomagnetic storm; thus, a HILDCAA event may be more effective for ionospheric response in comparison to moderate geomagnetic storms, considering the seasonal conditions. During the August HILDCAA event, TEC enhancements from ∼  25 to 80 % (compared to quiet time) were observed. These enhancements are much higher than the quiet-time variability observed in the ionosphere. We show that ionosphere is quite sensitive to solar wind forcing and considering the events studied here, this was the most important source of ionospheric responses. Furthermore, the most important source of TEC changes were the long-lasting PPEFs observed on August 2013, during the HILDCAA event. The importance of this study relies on the peculiarity of the region analyzed characterized by high declination angle and ionospheric gradients which are responsible for creating a complex response during disturbed periods.

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Ionospheric Responses to the June 2015 Geomagnetic Storm from Ground and LEO GNSS Observations

Remote Sensing ◽

10.3390/rs12142200 ◽

2020 ◽

Vol 12 (14) ◽

pp. 2200

Author(s):

Chao Gao ◽

Shuanggen Jin ◽

Liangliang Yuan

Keyword(s):

Geomagnetic Storm ◽

Geomagnetic Storms ◽

Low Earth Orbit ◽

Horizontal Gradient ◽

Electron Content ◽

Vertical Total Electron Content ◽

Total Electron ◽

Leo Satellites ◽

The Impact ◽

Gnss Observations

Geomagnetic storms are extreme space weather events, which have considerable impacts on the ionosphere and power transmission systems. In this paper, the ionospheric responses to the geomagnetic storm on 22 June 2015, are analyzed from ground-based and satellite-based Global Navigation Satellite System (GNSS) observations as well as observational data of digital ionosondes, and the main physical mechanisms of the ionospheric disturbances observed during the geomagnetic storm are discussed. Salient positive and negative storms are observed from vertical total electron content (VTEC) based on ground-based GNSS observations at different stages of the storm. Combining topside observations of Low-Earth-Orbit (LEO) satellites (GRACE and MetOp satellites) with different orbital altitudes and corresponding ground-based observations, the ionospheric responses above and below the orbits are studied during the storm. To obtain VTEC from the slant TEC between Global Positioning System (GPS) and LEO satellites, we employ a multi-layer mapping function, which can effectively reduce the overall error caused by the single-layer geometric assumption where the horizontal gradient of the ionosphere is not considered. The results show that the topside observations of the GRACE satellite with a lower orbit can intuitively detect the impact caused by the fluctuation of the F2 peak height (hmF2). At the same time, the latitude range corresponding to the peak value of the up-looking VTEC on the event day becomes wider, which is the precursor of the Equatorial Ionization Anomaly (EIA). However, no obvious response is observed in the up-looking VTEC from MetOp satellites with higher orbits, which indicates that the VTEC responses to the geomagnetic storm mainly take place below the orbit of MetOp satellites.

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Statistics of the largest geomagnetic storms per solar cycle (1844-1993)

Annales Geophysicae ◽

10.1007/s00585-997-0719-5 ◽

1997 ◽

Vol 15 (6) ◽

pp. 719-728 ◽

Cited By ~ 13

Author(s):

D. M. Willis ◽

P. R. Stevens ◽

S. R. Crothers

Keyword(s):

Statistical Analysis ◽

Solar Cycle ◽

Geomagnetic Storm ◽

Extreme Values ◽

Geomagnetic Storms ◽

Extreme Value ◽

Extreme Value Statistics ◽

Relative Dispersion ◽

Solar Cycles ◽

Aa Index

Abstract. A previous application of extreme-value statistics to the first, second and third largest geomagnetic storms per solar cycle for nine solar cycles is extended to fourteen solar cycles (1844–1993). The intensity of a geomagnetic storm is measured by the magnitude of the daily aa index, rather than the half-daily aa index used previously. Values of the conventional aa index (1868–1993), supplemented by the Helsinki Ak index (1844–1880), provide an almost continuous, and largely homogeneous, daily measure of geomagnetic activity over an interval of 150 years. As in the earlier investigation, analytic expressions giving the probabilities of the three greatest storms (extreme values) per solar cycle, as continuous functions of storm magnitude (aa), are obtained by least-squares fitting of the observations to the appropriate theoretical extreme-value probability functions. These expressions are used to obtain the statistical characteristics of the extreme values; namely, the mode, median, mean, standard deviation and relative dispersion. Since the Ak index may not provide an entirely homogeneous extension of the aa index, the statistical analysis is performed separately for twelve solar cycles (1868–1993), as well as nine solar cycles (1868–1967). The results are utilized to determine the expected ranges of the extreme values as a function of the number of solar cycles. For fourteen solar cycles, the expected ranges of the daily aa index for the first, second and third largest geomagnetic storms per solar cycle decrease monotonically in magnitude, contrary to the situation for the half-daily aa index over nine solar cycles. The observed range of the first extreme daily aa index for fourteen solar cycles is 159–352 nT and for twelve solar cycles is 215–352 nT. In a group of 100 solar cycles the expected ranges are expanded to 137–539 and 177–511 nT, which represent increases of 108% and 144% in the respective ranges. Thus there is at least a 99% probability that the daily aa index will satisfy the condition aa < 550 for the largest geomagnetic storm in the next 100 solar cycles. The statistical analysis is used to infer that remarkable conjugate auroral observations on the night of 16 September 1770, which were recorded during the first voyage of Captain Cook to Australia, occurred during an intense geomagnetic storm.

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Neural network applications in geomagnetic storm prognosis based on the pre-storm occurrence of magnetic islands in the solar wind

10.5194/egusphere-egu2020-1848 ◽

2020 ◽

Author(s):

Mikhail Fridman

Keyword(s):

Neural Network ◽

Solar Wind ◽

Particle Acceleration ◽

Geomagnetic Storm ◽

High Speed ◽

Geomagnetic Storms ◽

Pattern Search ◽

Small Scale ◽

Magnetic Islands ◽

Solar Wind Density

So far, the problem of a short-term forecast of geomagnetic storms can be considered as solved. Meanwhile, mid-term prognoses of geomagnetic storms with an advance time from 3 hours to 3 days are still unsuccessful (see &#160;https://www.swpc.noaa.gov/sites/default/files/images/u30/Max%20Kp%20and%20GPRA.pdf).&#160;This fact suggests a necessity of looking for specific&#160;processes&#160;in the solar wind preceding geomagnetic storms. Knowing that magnetic cavities filled with magnetic islands and current sheets are formed in front of high-speed streams of any type (Khabarova et al., 2015, 2016, 2018; Adhikari et al., 2019), we have performed an analysis of the corresponding ULF variations in the solar wind density observed at the Earth's orbit from hours to days before the arrival of a geoeffective stream or flow. The fact of the occurrence of ULF-precursors of geomagnetic storms was noticed a long time ago (Khabarova 2007; Khabarova & Yermolaev, 2007) and related&#160;prognostic methods were recently developed (Kogai et al. 2019), while the problem of automatization of the prognosis remained unsolved.&#160;A new geomagnetic storm forecast method, which employs a Recurrent Neural Network (RNN) for an automatic pattern search, is proposed. An ability of self-teaching and extracting deeply hidden non-linear patterns is the main advantage of Deep Neural Networks (DNNs) with multiple layers over traditional Machine Learning methods. We show a success of the&#160;RNN&#160;method, using either the unprocessed solar wind density data or Wavelet analysis coefficients as the input parameter for a DNN to perform an automatic mid-term prognosis of geomagnetic storms.&#160;&#160;Adhikari, L., et al. 2019, The Role of Magnetic Reconnection&#8211;associated Processes in Local Particle Acceleration in the Solar Wind, ApJ, 873, 1, 72,&#160;https://doi.org/10.3847/1538-4357/ab05c6 Kogai T.G. et al., Pre-storm ULF variations in the solar wind density and interplanetary magnetic field as key parameters to build a mid-term prognosis of geomagnetic storms. &#8220;GRINGAUZ 100: PLASMA IN THE SOLAR SYSTEM&#8221;, IKI RAS, Moscow, June 13&#8211;15, 2018, 140-143, ISBN 978-5-00015-043-6.&#160;https://www.researchgate.net/publication/327781146_Pre-storm_ULF_variations_in_the_solar_wind_density_and_interplanetary_magnetic_field_as_key_parameters_to_build_a_mid-term_prognosis_of_geomagnetic_storms &#160;Khabarova O. V., et al. 2018, &#160;Re-acceleration of energetic particles in large-scale heliospheric magnetic cavities, Proceedings of the IAU, 76-82,&#160;https://doi.org/10.1017/S1743921318000285&#160; Khabarova O.V., et al. Small-scale magnetic islands in the solar wind and their role in particle acceleration. II. Particle energization inside magnetically confined cavities. 2016, ApJ, 827,&#160;122,&#160;http://iopscience.iop.org/article/10.3847/0004-637X/827/2/122 Khabarova O., et al. Small-scale magnetic islands in the solar wind and their role in particle acceleration. 1. Dynamics of magnetic islands near the heliospheric current sheet. 2015, ApJ, 808, 181,&#160;https://doi.org/10.1088/0004-637X/808/2/181Khabarova O.V., Current Problems of Magnetic Storm Prediction and Possible Ways of Their Solving. Sun&Geosphere, &#160;http://sg.shao.az/v2n1/SG_v2_No1_2007-pp-33-38.pdf&#160;, 2(1), 33-38, 2007Khabarova O.V. & Yu.I.Yermolaev, Solar wind parameters' behavior before and after magnetic storms, JASTP, 70, 2-4, 2008, 384-390,&#160;http://dx.doi.org/10.1016/j.jastp.2007.08.024

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Studying the Ionospheric Responses Induced by a Geomagnetic Storm in September 2017 with Multiple Observations in America

10.5194/egusphere-egu2020-1906 ◽

2020 ◽

Author(s):

Yang Liu ◽

Zheng Li ◽

Jinling Wang

Keyword(s):

Electron Density ◽

Geomagnetic Storm ◽

Geomagnetic Storms ◽

Ionospheric Irregularities ◽

Electron Content ◽

High Latitudes ◽

Total Electron ◽

Multiple Observations ◽

The Usa ◽

Plasma Depletions

A series of studies have suggested that a geomagnetic storm can accelerate the formation of plasma depletions and the generation of ionospheric irregularities. Using observation data from the Continuously Operating Reference Stations (CORS) network in the USA, the responses of the ionospheric total electron content (TEC) to the geomagnetic storm on September 8, 2017 are studied in detail. A mid-latitude trough was discovered from 01:00 UT to 06:00 UT in the USA with a length exceeding 5000 km. The probable causes are the combination of a classic negative storm response with increments in the neutral composition and the expansion of the auroral oval, pushing the mid-latitude trough equatorward. &#160;Super-scale plasma depletion was observed by SWARM data accompanied by the expansion of mid-latitude trough. Both PPEF from high latitudes and pole-ward neutral wind are responsible for the large-scale ionospheric irregularities. Medium-scale travelling ionospheric disturbances (MSTID) with wavelengths of 600&#8211;700 km were generated accompanied by a drop and perturbation in the electron density. The intensity of the MSTID fluctuations reached over 2.5 TECU, which were discovered by filtering the differential TEC. The evolution of plasma depletions were associated with the MSTID propagating from high latitudes to low latitudes. SWARM spaceborne observations also showed a drop in the electron density from 105&#160;to 103&#160;compared to the background values at 28&#176; N, 96&#176; W, and 25&#176; N, 95&#176; W. This research investigates super-scale plasma depletions generated by geomagnetic storms using both CORS GNSS and spaceborne observations. The proposed work is valuable for better understanding the evolution of ionospheric depletions during geomagnetic storms.

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Geoeffectiveness of the ‘Battle of Grunwald day’ in 2012

10.5194/egusphere-egu2020-8326 ◽

2020 ◽

Author(s):

Agnieszka Gil ◽

Renata Modzelewska ◽

Szczepan Moskwa ◽

Agnieszka Siluszyk ◽

Marek Siluszyk ◽

...

Keyword(s):

Geomagnetic Storm ◽

Transmission Lines ◽

Geomagnetic Storms ◽

Activity Cycle ◽

Solar Activity Cycle ◽

Solar Origin ◽

Electric Transmission Lines ◽

Cycle 24 ◽

Ap Index ◽

Halo Coronal Mass Ejection

During the solar activity cycle 24, which started at the end of 2008, Sun was behaving silently and there were not many spectacular geoeffective events. Here we analyze the geomagnetic storm which happened on July 15 of 2012 in the 602 anniversary of the famous Polish Battle of Grunwald. According to the NOAA scale, it was G3 geomagnetic storm with Bz heliospheric magnetic field component dropping up to -20 nT, Dst index below -130 nT, AE index greater than 1300 nT and ap index being above 130 nT. It was proceeded by the solar flare of X1.4 class on 12 of July. This geomagnetic storm was accompanied by the fast halo coronal mass ejection 16:48:05 on 12 of July-the first C2 appearance, with the apparent speed 885 km/s and space speed 1405 km/s. This geomagnetic storm was classified as the fourth of the strongest geomagnetic storms from SC 24. Around that time in Polish electric transmission lines infrastructure, there was observed a significant growth of the number of failures that might be of solar origin.Acknowledgments: the Polish National Science Centre, grant number 2016/22/E/HS5/00406.

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Statistical Study of Geomagnetic Storms during Year 1996-2007

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.433-440.268 ◽

2012 ◽

Vol 433-440 ◽

pp. 268-271

Author(s):

Balveer S. Rathore ◽

Subhash C. Kaushik ◽

K.K. Parashar ◽

Rammohan S. Bhadoria ◽

Dinesh C. Gupta

Keyword(s):

Magnetic Field ◽

Solar Cycle ◽

Geomagnetic Storm ◽

Statistical Study ◽

Geomagnetic Storms ◽

Sunspot Cycle ◽

Solar Wind Plasma ◽

Strongly Correlated ◽

Minimum Phase ◽

Solar Cycle 23

A geomagnetic storm is a global disturbance in Earth’s magnetic field usually occurred due to abnormal conditions in the interplanetary magnetic field (IMF) and solar wind plasma emissions caused by various solar phenomenon. A study of 220 geomagnetic storms associated with disturbance storm time (Dst) decreases of more than -50 nT to -300 nT, observed during 1996-2007, the span of solar cycle 23. We have analyzed and studied them statistically. We find yearly occurrences of geomagnetic storm are strongly correlated with 11-year sunspot cycle, but no significant correlation between the maximum and minimum phase of solar cycle-23 have been found. It is also found that solar cycle-23 is remarkable for occurrence of Intense geomagnetic storm during its declining phase. The detailed results are discussed in this paper.

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Magnetospheric chaos and dynamical complexity response during storm time disturbance

10.5194/npg-2020-47 ◽

2020 ◽

Author(s):

Irewola Aaron Oludehinwa ◽

Olasunkanmi Isaac Olusola ◽

Olawale Segun Bolaji ◽

Olumide Olayinka Odeyemi ◽

Abdullahi Ndzi Njah

Keyword(s):

Time Series ◽

Solar Wind ◽

Geomagnetic Storm ◽

Time Series Data ◽

Geomagnetic Storms ◽

Approximate Entropy ◽

Series Data ◽

Dynamical Complexity ◽

Significant Difference ◽

Dynamical Features

Abstract. In this study, we examine the magnetospheric chaos and dynamical complexity response in the disturbance storm time (Dst) and solar wind electric field (VBs) during different categories of geomagnetic storm (minor, moderate and major geomagnetic storm). The time series data of the Dst and VBs are analyzed for the period of nine years using nonlinear dynamics tools (Maximal Lyapunov Exponent, MLE, Approximate Entropy, ApEn and Delay Vector Variance, DVV). We found a significant trend between each nonlinear parameter and the categories of geomagnetic storm. The MLE and ApEn values of the Dst indicate that chaotic and dynamical complexity response are high during minor geomagnetic storms, reduce at moderate geomagnetic storms and declined further during major geomagnetic storms. However, the MLE and ApEn values obtained in VBs indicate that chaotic and dynamical complexity response are high with no significant difference between the periods that are associate with minor, moderate and major geomagnetic storms. The test for nonlinearity in the Dst time series during major geomagnetic storm reveals the strongest nonlinearity features. Based on these findings, the dynamical features obtained in the VBs as input and Dst as output of the magnetospheric system suggest that the magnetospheric dynamics is nonlinear and the solar wind dynamics is consistently stochastic in nature.

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ESTIMASI BADAI GEOMAGNET BERDASARKAN PERILAKU PARAMETER ANGIN SURYA DAN MEDAN MAGNET ANTARPLANET SEBELUM BADAI GEOMAGNET (THE ESTIMATION OF GEOMAGNETIC STORM BASED ON SOLAR WIND PARAMETERS AND INTERPLANETARY MAGNETIC FIELD BEHAVIOR BEFORE GEOMAGNETIC STOR

Jurnal Sains Dirgantara ◽

10.30536/j.jsd.2016.v14.a2327 ◽

2017 ◽

Vol 14 (2) ◽

pp. 17

Author(s):

Anwar Santoso ◽

Mamat Rahimat ◽

Rasdewita Kesumaningrum ◽

Siska Filawati

Keyword(s):

Magnetic Field ◽

Solar Wind ◽

Geomagnetic Storm ◽

Space Weather ◽

Geomagnetic Storms ◽

Storm Events ◽

Science Center ◽

Solar Wind Parameters ◽

The Impact ◽

The Imf

Space weather research is the principal activity at the Space Science Center, Lapan to learn characteristics and generator source of the space weather so that can mitigate its the impact on the Earth's environment as mandated in Law No. 21 Year 2013. One of them is the phenomenon of geomagnetic storms. Geomagnetic storms caused by the entry of solar wind together with the IMF Bz that leads to the south. The behavior of the solar wind parameters together with the IMF Bz before geomagnetic storms can determine the formation of geomagnetic storms that caused it. In spite that, by the solar wind parameters and IMF Bz behavior before geomagnetic storm can be estimated its intensity through the equation Dst * = 1.599 * Ptotal - 34.48. The result of this equation is obtained that the Dst minimum deviation between the raw data and the output of this equation to the geomagnetic storm events on March 17, 2013 is about of -2.51 nT or 1.9% and on the geomagnetic storm events on February 19, 2014 is about of 2.77 nT or 2, 5%. Thus, the equation Dst * = 1.599 * Ptotal - 34.48 is very good for the estimation of geomagnetic storms.

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