Geomagnetic Index Kp Research Articles

Empirical Model of SSUSI‐Derived Auroral Ionization Rates

AbstractWe present an empirical model for auroral (90–150 km) electron–ion pair production rates, ionization rates for short, derived from Special Sensor Ultraviolet Spectrographic Imager electron energy and flux data. Using the Fang et al. (2010, https://doi.org/10.1029/2010gl045406) parametrization for mono‐energetic electrons, and the NRLMSISE‐00 neutral atmosphere model (Picone et al., 2002, https://doi.org/10.1029/2002ja009430), the calculated ionization rate profiles are binned in 2‐hr magnetic local time and 3.6°geomagnetic latitude to yield time series of ionization rates at 5‐km altitude steps. We fit each of these time series to the geomagnetic indices Kp, PC, and Ap, the 81‐day averaged solar radio flux index, and a constant term. The resulting empirical model can easily be incorporated into coupled chemistry–climate models to include particle precipitation effects.

Unusual Forbush Decreases and Geomagnetic Storms on 24 March, 2024 and 11 May, 2024

As the current solar cycle 25 progresses and moves towards solar maxima, solar activity is increasing and extreme space weather events are taking place. Two severe geomagnetic storms accompanied by two large Forbush decreases in galactic cosmic ray intensity were recorded in March and May, 2024. More precisely, on 24 March 2024, a G4 (according to the NOAA Space Weather Scale for Geomagnetic Storms) geomagnetic storm was registered, with the corresponding geomagnetic indices Kp and Dst equal to 8 and −130 nT, respectively. On the same day, the majority of ground-based neutron monitor stations recorded an unusual Forbush decrease. This event stands out from a typical Forbush decrease because of its high amplitude decrease phase and rapid recovery phase, i.e., 15% decrease and an extremely rapid recovery of 10% within 1.5 h, as recorded at the Oulu neutron monitor station. Furthermore, on 10–13 May 2024, an unusual G5 geomagnetic storm (geomagnetic indices Kp = 9 and Dst = −412 nT) was registered (the last G5 storm had been observed in 2003). In addition, the polar neutron monitor stations recorded a Ground Level Enhancement (GLE74) during the recovery phase of a large Forbush decrease of 15%, which started on 10 May 2024. In this study, a detailed analysis of these two severe events in regard to the accompanying solar activity, interplanetary conditions and solar energetic particle events is provided. Moreover, the results of the NKUA “GLE Alert++ system”, the NKUA/IZMIRAN “FD Precursory Signals” method and the NKUA “ap Prediction tool” concerning these events are presented.

Comparing Influences of Solar Wind, ULF Waves, and Substorms on 20 eV–2 MeV Electron Flux (RBSP) Using ARMAX Models

AbstractElectron fluxes (20 eV–2 MeV, RBSP‐A satellite) show reasonable simple correlation with a variety of parameters (solar wind, IMF, substorms, ultralow frequency (ULF) waves, geomagnetic indices) over L‐shells 2–6. Removing correlation‐inflating common cycles and trends (using autoregressive and moving average terms in an ARMAX analysis) results in a 10 times reduction in apparent association between drivers and electron flux, although many are still statistically significant (p < 0.05). Corrected influences are highest in the 20 eV–1 keV and 1–2 MeV electrons, more modest in the midrange (2–40 keV). Solar wind velocity and pressure (but not number density), IMF magnitude (with lower influence of Bz), SME (a substorm measure), a ULF wave index, and geomagnetic indices Kp and SymH all show statistically significant associations with electron flux in the corrected individual ARMAX analyses. We postulate that only pressure, ULF waves, and substorms are direct drivers of electron flux and compare their influences in a combined analysis. SME is the strongest influence of these three, mainly in the eV and MeV electrons. ULF is most influential on the MeV electrons. Pressure shows a smaller positive influence and some indication of either magnetopause shadowing or simply compression on the eV electrons. While strictly predictive models may improve forecasting ability by including indirect driver and proxy parameters, and while these models may be made more parsimonious by choosing not to explicitly model time series behavior, our present analyses include time series variables in order to draw valid conclusions about the physical influences of exogenous parameters.

The high-energy tail of energetic electron precipitation: solar wind drivers and geomagnetic responses

Compositional NOx changes caused by energetic electron precipitation (EEP) at a specific altitude and those co-dependent on vertical transport are referred to as the EEP direct and indirect effect, respectively. The direct effect of EEP at lower mesospheric and upper stratospheric altitudes is linked to the high-energy tail of EEP (≳ 300 keV). The relative importance of this direct effect on NOx, ozone, and atmospheric dynamics remains unresolved due to inadequate particle measurements and scarcity of polar mesospheric NOx observations. An accurate parameterization of the high-energy tail of EEP is, therefore, crucial. This study utilizes EEP flux data from MEPED aboard the POES/Metop satellites from 2004–2014. Data from both hemispheres (55–70° N/S) are combined in daily flux estimates. 164 peaks above the 90th percentile of the ≳ 30 keV flux are identified. These peaks are categorized into absolute E1 and E3 events representing weak and strong ≳ 300 keV responses, respectively. A subset of absolute E1 and E3 events with similar ≳ 30 keV responses is termed overlapping events. Additionally, relative E1 and E3 events are determined by the relative strength of the ≳ 300 keV response, scaled by the initial ≳ 30 keV flux. A comparison between E1 and E3 events aims to identify solar wind and geomagnetic conditions leading to high-energy EEP responses and to gain insight into the conditions that generate a high-energy tail, independent of the initial ≳ 30 keV flux level. Superposed epoch analysis of mesospheric NO density from SOFIE confirms an observable direct impact on lower mesospheric chemistry associated with the absolute E3 events. A probability assessment based on absolute events identifies specific thresholds in the solar wind-magnetosphere coupling function (epsilon) and the geomagnetic indices Kp*10 and Dst, capable of determining the occurrence or exclusion of absolute E1 and E3 events. Elevated solar wind speeds persisting in the recovery phase of a deep Dst trough appear characteristic of overlapping and relative E3 events. This study provides insight into which parameters are important for accurately modeling the high-energy tail of EEP.

Analysis of GPS TEC anomalies associated with Mw > 7 earthquakes in Japan

The Global Positioning System (GPS) provides insights into the Earthquakes (EQs) ionospheric anomalies. Different space-and-ground parameters are used to observe EQ precursors. This paper uses the Total Electron Content (TEC) from nearby operating GPS stations to detect perturbation in the ionosphere before and after four EQs in Japan in 2011. In addition, the TEC variations in relation to the depth and magnitude of the EQs are noticed. The analysis shows significant variations in TEC to depth and magnitude in association with each main shock. TEC value abruption starts on 8 March and continues for 6 days in March. In April, TEC abnormalities start 5 days before and after the man shock. The geomagnetic Kp index is higher than four from March 10 to 12. The anomalies in this study are clearly associated with geomagnetic storms, as the Kp index is active. Moreover, the Dst index is below the negative 50 (nT) in the seismic period of March and April. The ionosphere parameters will define the severity of seismic activity in future.

Geomagnetic Anomaly in the Growth Response of Peat Moss Sphagnum riparium to Temperature.

Temperature plays an essential role in a plant's life. The current investigation reveals that photoreceptors, whose activity is affected by the geomagnetic field, are a critical element of its perception. This knowledge suggests that plants' responses to temperature could shift in different geomagnetic conditions. To test this hypothesis, we studied the change in the growth response of the peat moss Sphagnum riparium to temperature with a gradual increase in the geomagnetic Kp index. Growth data for this species were collected from Karelian mires by detailed monitoring over eight full growing seasons. The growth of 209,490 shoots was measured and 1439 growth rates were obtained for this period. The analysis showed a strong positive dependence of sphagnum growth on temperature (r = 0.58; n = 1439; P = 1.7 × 10-119), which is strongest in the Kp range from 0.87 to 1.61 (r = 0.65; n = 464; P = 4.5 × 10-58). This Kp interval is clearer after removing the seasonal contributions from the growth rate and temperature and is preserved when diurnal temperature is used. Our results are consistent with the hypothesis and show the unknown contribution of the geomagnetic field to the temperature responses of plants.

Models for magnetospheric mass density and average ion mass including radial dependence

Analytical models for magnetospheric mass density, ρm, and average ion mass, M, were created from a database of ρm and electron density, ne, values from six spacecraft missions by making use of the Eureqa nonlinear genetic regression algorithm. All values of ρm were determined from Alfvén frequencies, and the values of ne were determined from plasma wave or spacecraft potential data. Models of varying complexity are listed. The most complex models appearing in this paper are capable of modeling ρm within a factor of 1.81, and M within a factor of 1.34 if ne is used as an input parameter, or within a factor of 1.45 if ne is not used. The most important parameters for modeling ρm are L, the solar EUV index F10.7, magnetic local time, MLT, the geomagnetic activity index Kp, and the solar wind dynamic pressure, Pdyn. The very simplest model for M depends on Kp. In more complex models for M including ne, the most important parameters are ne with L, F10.7, and Pdyn or Kp. In more complex models for M not including ne, the most important parameters are Kp, MLT, F10.7, L, and the auroral electrojet index, AE. Explanations for most of the dependencies are given. We also demonstrate the danger of calculating spatial dependence without taking account of different conditions sampled in different regions. Here we avoid that problem by using multivariant models.

Forecasting the Geomagnetic Activity Several Days in Advance Using Neural Networks Driven by Solar EUV Imaging

AbstractMany models of the near‐Earth's space environment (radiation belts, ionosphere, upper atmosphere, etc.) are driven by geomagnetic indices, representing the state of disturbance of the Earth's magnetosphere. Over the past decade, machine learning‐based methods for forecasting geomagnetic indices from near‐Earth solar wind parameters have become popular in the space weather community. These methods often prove to be very accurate and skilled. However, these approaches have the notable drawback of being effective in an operational context only for limited forecasting horizons (often up to a couple of hours ahead at best). In order to increase this prediction horizon, we introduce SERENADE, a novel deep learning‐based proof‐of‐concept model using images delivered by the Atmospheric Imaging Assembly instrument onboard the Solar Dynamics Observatory spacecraft to directly provide probabilistic forecasts of the daily maximum of the geomagnetic index Kp up to a few days ahead. We show in particular that SERENADE is able to capture information on the geomagnetic dynamics from solar imaging alone. In addition, despite it being a prototypical model, our model is more accurate in most situations than three empirical baseline models. However, the model still shows some strong limitations inherent to its structure and the used data set, which could be the focus of future works. This opens the way to a better mid‐to‐long term data‐driven magnetospheric modeling within space weather and geophysical pipelines.

Geomagnetic Activity Index Hpo

AbstractThe geomagnetic activity index Kp is widely used but is restricted by low time resolution (3‐hourly) and an upper limit. To address this, new geomagnetic activity indices, Hpo, are introduced. Similar to Kp, Hpo expresses the level of planetary geomagnetic activity in units of thirds (0o, 0+, 1−, 1o, 1+, 2−, …) based on the magnitude of geomagnetic disturbances observed at subauroral observatories. Hpo has a higher time resolution than Kp. 30‐min (Hp30) and 60‐min (Hp60) indices are produced. The frequency distribution of Hpo is designed to be similar to that of Kp so that Hpo may be used as a higher time‐resolution alternative to Kp. Unlike Kp, which is capped at 9o, Hpo is an open‐ended index and thus can characterize severe geomagnetic storms more accurately. Hp30, Hp60 and corresponding linearly scaled ap30 and ap60 are available, in near real time, at the GFZ website (https://www.gfz-potsdam.de/en/hpo-index).

Cutoff Latitudes of Solar Proton Events Measured by GPS Satellites

AbstractSolar energetic particles (SEPs), one of the main causes of particle radiation in interplanetary space, can disrupt radio communication, induce spacecraft failures and change the heating and cooling rates in the atmosphere among others. To investigate the impact of SEPs and more specifically solar proton events (SPEs), we established a cutoff latitude database based on energetic particle data from Combined X‐ray Dosimeters (CXDs) on board the Global Positioning System (GPS) spacecraft. Introducing a novel normalization method involving proton fluxes from the Geostationary Operational Environmental Satellites enabled us to include the CXD data from its introduction (2001) onwards. The database contains 5714 cutoff latitudes divided over six energies between 18 and 115 MeV which occur during 58 SPEs from 2001 to 2015. Based on the database, a cutoff latitude parameterization as a function of solar wind dynamic pressure and geomagnetic indices Kp and Dst is created for each energy. Moreover, comparisons to previous studies on energetic particle data from the Polar Orbiting Environmental Satellites have been performed to put the GPS data into perspective. A 1–2° poleward offset is found for the GPS based cutoff latitude models, for which several causes are discussed. Furthermore, the limitation of GPS data to geomagnetic latitudes above 60° should be considered. All in all, the usage of the long time span of GPS data in this study combined with its recent release (2016) opens up a new range of studies involving GPS energetic particle data such as investigating long‐term trends with respect to our solar cycle or magnetospheric trends.

A Study of Possible Correlations between Seismo-Ionospheric Anomalies of GNSS Total Electron Content and Earthquake Energy

In this study, we conduct a correlation analysis between the daily occurrence times of the increase and decrease anomalies in the global total electron content (TEC) in the ionosphere, and the daily earthquake energy release within 110–130°E longitude over the following three latitude regions: A: 13°S–0.5°S (22.3°S–10°S geomagnetic), B: 0.5°S–19.5°N (10°S–10°N geomagnetic), and C: 19.5°N–32.1°N (10°N–22.5°N geomagnetic). The TEC data from global ionosphere maps (GIMs) during earthquake events of M ≥ 2.5 that occurred in 2015–2018 are used in this study. The time series of daily seismic wave energy releases within the three regions and the daily occurrence times of the TEC anomalies in each GIM grid are computed. By time-shifting the time series, the correlations are calculated and compared globally, and the temporal characteristics are also examined. The disturbance storm time (Dst) index, planetary geomagnetic index Kp, and daily observed 10.7 cm solar flux (F10.7) are used to remove data associated with space weather variations. Although the seismo-ionospheric precursor is not confirmed by the statistical investigations, the greater occurrence times of TEC decrease anomalies are observed in the southeast in Region A, and the conjugate point 13 days prior to a M6.9 earthquake in Region A, which occurred on 5 August 2018, in accordance with the statistical results. Therefore, it is required to apply more parameters to understand the causes of the ionospheric TEC variations and investigate whether ionospheric variations are caused by earthquakes.

Examination of Radiation Belt Dynamics During Substorm Clusters: Activity Drivers and Dependencies of Trapped Flux Enhancements

AbstractDynamical variations of radiation belt trapped electron fluxes are examined to better understand the variability of enhancements linked to substorm clusters. Analysis is undertaken using the Substorm Onsets and Phases from Indices of the Electrojet substorm cluster algorithm for event detection. Observations from low earth orbit are complemented by additional measurements from medium earth orbit to allow a major expansion in the energy range considered, from medium energy energetic electrons up to ultra‐relativistic electrons. The number of substorms identified inside a cluster does not depend strongly on solar wind drivers or geomagnetic indices either before, during, or after the cluster start time. Clusters of substorms linked to moderate (100 nT < AE ≤ 300 nT) or strong AE (AE ≥ 300 nT) disturbances are associated with radiation belt flux enhancements, including up to ultra‐relativistic energies by the strongest substorms (as measured by strong southward Bz and high AE). These clusters reliably occur during times of high speed solar winds streams with associated increased magnetospheric convection. However, substorm clusters associated with quiet AE disturbances (AE ≤ 100 nT) lead to no significant chorus whistler mode intensity enhancements, or increases in energetic, relativistic, or ultra‐relativistic electron flux in the outer radiation belts. In these cases the solar wind speed is low, and the geomagnetic Kp index indicates a lack of magnetospheric convection. Our study clearly indicates that clusters of substorms occurring outside of high speed wind streams are not by themselves sufficient to drive acceleration, which may be due to the lack of pre‐cluster convection.

Probabilistic hazard assessment: Application to geomagnetic activity

Probabilistic Hazard Assessment (PHA) provides an appropriate methodology for assessing space weather hazards and their impact on technology. PHA is widely used in geosciences to determine the probability of exceedance of critical thresholds, caused by one or more hazard sources. PHA has proved useful with limited historical data to estimate the likelihood of specific impacts. PHA has also driven the development of empirical and physical models, or ensembles of models, to replace measured data. Here we aim to highlight the PHA method to the space weather community and provide an example of how it could be used. In terms of space weather impact, the critical hazard thresholds might include the Geomagnetically Induced Current in a specific high voltage power transformer neutral, or the local pipe-to-soil potential in a particular metal pipe. We illustrate PHA in the space weather context by applying it to a twelve-year dataset of Earth-directed solar Coronal Mass Ejections (CME), which we relate to the probability that the global three-hourly geomagnetic activity index Kp exceeds specific thresholds. We call this a “Probabilistic Geomagnetic Hazard Assessment”, or PGHA. This provides a simple but concrete example of the method. We find that the cumulative probability of Kp > 6−, > 7−, > 8− and Kp = 9o is 0.359, 0.227, 0.090, 0.011, respectively, following observation of an Earth-directed CME, summed over all CME launch speeds and solar source locations. According to the historical Kp distribution, this represents an order of magnitude increase in the a priori probability of exceeding these thresholds. For the lower Kp thresholds, the results are somewhat distorted by our exclusion of coronal hole high-speed stream effects. The PHGA also reveals useful probabilistic associations between solar source location and subsequent maximum Kp for operational forecasters.

OBSERVATION OF ULF ELECTROMAGNETIC EMISSIONS BEFORE THE M 7.8 NEW ZEALAND EARTHQUAKE OF NOVEMBER 13, 2016

We analyzed the ground geomagnetic data obtained from a 3-component fluxgate magnetometer at the Eyrewell Geomagnetic Observatory (New Zealand) (43.474 °S, 172.393 °E) from October 1 to December 31, 2016. The study aimed to investigate electromagnetic precursors associated with the M 7.8 New Zealand earthquake of November 13, 2016. This earthquake occurred 54 km northeast of Amberley (New Zealand). Its epicenter was located 158 km from the Eyrewell Observatory. We used three methods focused on the polarization ratio, fractal dimension and principal component analysis to identify anomalies in the geomagnetic data. The time series showed an enhanced polarization ratio at two times, October 20 and October 30, 2016, i.e. before the occurrence of the New Zealand earthquake, and a value ~1 or more during these instances. Since the global geomagnetic indices Kp and Dst were normal in these cases, the enhanced polarization ratio may be related to the preparation phase of the New Zealand earthquake. To further classify them, we applied the principal component analysis to the magnetic data on component H. The first three principal components showed more than 90 % of the variance of the original ultra-low frequency (ULF) magnetic field time series. The first principal component was found to be well correlated with the storm index (Dst) recorded during this period. Again, the second principal component was dominated by daily variations, which were the periodic component of the recorded ULF magnetic field. The temporal variation of the third principal component was analyzed to verify a possible correlation between the ULF emissions and the occurrence of the earthquake. The fractal dimension of components D and Z of the magnetic data decreased initially and sharply increased three days before the New Zealand earthquake.

Modeling of Anisotropy Dynamics of the Proton Pitch Angle Distribution in the Earth’s Magnetosphere

Last years the attention to research of anisotropy of the charged particle pitch angle distribution has considerably increased. Therefore for research of anisotropy dynamics of the proton pitch angle distribution is used the two-dimensional Phenomenological Model of the Ring Current (PheMRC 2-D), which includes the radial and pitch angle diffusions with consideration of losses due to wave-particle interactions. Experimental data are collected on the Polar/MICS satellite during the magnetic storm on October 21–22, 1999. Solving the non-stationary two-dimensional equation of pitch angle and radial diffusions, numerically was determined the proton pitch angle distribution anisotropy index (or parameter of the proton pitch angle distribution) for the pitch angle of 90 degrees during the magnetic storm, when the geomagnetic activity Kp-index changed from 2 in the beginning of a storm up to 7+ in the end of a storm. Dependence of the perpendicular proton pitch angle distribution anisotropy index with energy E = 90 keV during the different moments of time from the McIlwain parameter L (2.26 < L < 6.6) is received. It is certain at a quantitative level for the magnetic storm on October 21–22, 1999, when and where on the nightside of the Earth’s magnetosphere (MLT = 2300) to increase in the geomagnetic activity Kp-index there is a transition from normal (pancake) proton pitch angle distributions to butterfly proton pitch angle distributions. That has allowed to determine unequivocally and precisely the anisotropy dynamics of the proton pitch angle distribution in the given concrete case. It is shown, that with increase of the geomagnetic activity Kp-index the boundary of isotropic proton pitch angle distribution comes nearer to the Earth, reaching L ≈ 3.6 at Kp = 7+

Persistent perturbations of ionosphere at diminution of solar and geomagnetic activity during 21–24 solar cycles

Moderate ionospheric disturbances combined with storm signatures are characterized by the positive ionospheric index (WU), the negative index (WL), and the range (WE = WU – WL). We assign weights to these indices as a function of the magnitude of the W-index, the observation latitude of the critical frequency of the F2 layer, foF2 (the F2 layer peak electron density, NmF2) or total electron content (TEC). It is shown that moderate ionospheric irregularities (W = ±2) occur more than 20% of the time, while ionospheric storms (W = ±3 and ± 4) are observed in about 5% of Global Ionosphere Maps (GIM-TEC) observations for the period 1994–2020. The response of WU, WL and WE indices are provided for the intense storm on 14–15 December 2006 measured by solar wind and interplanetary magnetic field parameters, and geomagnetic Kp, ap, aa and Dst-indices. Sustained perturbations in WU, WL and WE indices are observed with GIM-TEC observations from 1994 to 2020 in contrast to the geomagnetic Kp-index depletion. The sustained perturbations are also observed with foF2-based 3-h local ionospheric indices WUf, WLf, and WEf at Moscow, Slough-Chilton and Canberra from 1945 to 2020, despite the trends of decreasing in solar activity, Kp, ap, aa and Dst-indices, and GIM-TEC-based ionospheric storms. These persistent irregularities appear to be due to moderate-level ionospheric perturbations, a fact that did not receive sufficient attention within the research community so far.

The Geomagnetic Kp Index and Derived Indices of Geomagnetic Activity

AbstractThe geomagnetic Kp index is one of the most extensively used indices of geomagnetic activity, both for scientific and operational purposes. This article reviews the properties of the Kp index and provides a reference for users of the Kp index and associated data products as derived and distributed by the GFZ German Research Centre for Geosciences. The near real‐time production of the nowcast Kp index is of particular interest for space weather services and here we describe and evaluate its current setup.

Analysis of Relationship Between Ionospheric and Solar Parameters Using Graphical Models

AbstractFor the investigation of time variations of critical frequency (foF2), solar radiation flux at 10.7 cm wavelength (F10.7 index) and geomagnetic activity index Kp, we use conditional independence graphical models which describe and transparently represent the structure of relationships in the time series. We employ multivariate statistic methods applied to daily observational data obtained from midlatitude ionosondes within the period 1994–2009 (23rd Solar Cycle). It is demonstrated that conditional independence graphical models represent a robust method of multivariate statistical analysis, useful for finding a relation between one of the main ionospheric parameters and space weather conditions. This method appears to be more appropriate than correlation analysis between foF2 and the main geomagnetic and solar indices, especially for long‐term data for which the model characteristics may change or time series can be interrupted. We compare the results obtained by the graphical models method with cross‐correlation analysis. We found that the method is suitable for the analysis of the dependence between foF2 values and time‐shifted F10.7 time series. In particular, we clearly identified +0 day shift in all cases, and +1‐, +2–3‐, and +4–5‐day shifts in European, American, and East Asia sector, respectively. The conditional independence graphs method can be applied even in the case when classical parametric methods are not convenient.

Periodic variations of the geomagnetic activity indices Ap and Kp

Yearly averages of geomagnetic activity indices Kp and Ap for the years 1984 to 2018 be compared to the relevant averages of VxBs, where V is the solar wind velocity and Bs is the southward interplanetary magnetic field (IMF) component. The correlation of both quantities is known to be rather good. Comparing the averages of Ap and Kp with V and Bs separately. We found that, during the declining phase of solar cycle, V and during the ascending phase Bs have more influence on Ap and Kp indices. According to this observation the 27 days and semiannual, Ap and Kp variations be analysed discretely for years after and before sunspot minima. The time intervals prior to sunspot minima with a significant 27-day recurrent period of the IMF structure and those intervals after sunspot minima with a significant 28 to28.5 day recurrent phase of the structure be used. The averaged spectra of the two Ap and Kp data sets obviously show a period of 27 days before and a period of 28 to 29 days after sunspot minimum.

The interconnection and phase asynchrony between the geomagnetic indices’ periodicities: A study based on the interplanetary magnetic field polarities 1967–2018 utilizing a cross wavelet analysis

In this article, we investigate the interconnection and phase asynchrony between the periodicities of geomagnetic activity indices Kp, Ap, aa, and Dst according to the interplanetary magnetic field (IMF) polarities, toward (T) or away (A), during the time interval 1967–2018. For this purpose, the daily data of Kp, Ap, aa, and Dst indices during the considered period have been sorted into two groups (T and A) according to the IMF polarities. The wavelet transform (WT), the cross-wavelet transform (XWT), and the wavelet coherence (WTC) have been applied on the monthly averages of T and A groups for each geomagnetic index. Moreover, the correlation analyses (linear and running correlations) between the annual averages of T and A groups of each geomagnetic index have been investigated. The results of XWT and WTC revealed the existence of a long-term periodicity in the frequency range 8–16 yr for the monthly averages of T and A groups for aa, Kp, and Ap indices existed during the entire period. In contrast, the Dst index revealed this periodicity during the period 1980–2018. In addition, during this frequency band, both T and A groups of each geomagnetic index revealed a highly positive correlation and nearly in-phase relationship behavior. Furthermore, during the frequency band 4–8 yr, the XWT displayed a prominent periodicity that occurred for the monthly averages of T and A groups of each geomagnetic index, revealing a phase change during some time intervals. Periodicity in the range 2–4 yr for the monthly averages of T and A groups of aa, Kp,Ap, and Dst occurred in the intervals; 1967–2009 for aa and Kp, 1967–2007 for Ap, and 1976–1995 for Dst. The annual periodicity is also identified for all considered indices. Both T and A groups of Dst shared a semiannual periodicity (~187 days) during different intervals in the entire period. On the other hand, a periodicity around 0.25-yr (~90 days) appeared only near the times of solar activity maxima in the case of the T and A groups of aa, Kp, and Ap indices.