Indices Of Geomagnetic Activity Research Articles

Long-term geomagnetic activities and stratospheric winter temperature

In this research, impact of long term solar forcing on stratospheric winter temperature is checked. The 11- year sunspot activity and geomagnetic indices (AE, Kp, Dst) are used as an indicator for solar forcing, as geomagnetic activity indices show good correlation with solar variability. To understand the impact of solar forcing through high latitude, stratospheric winter (November to March) time North Polar Region (60N–90N) temperature anomalies are considered. The findings showed that temperature changes in the stratosphere are significantly correlated with solar activity, as evidenced by a significant positive correlation between the 11-year moving mean of stratospheric (10 hPa) temperature anomalies and sunspot number. Approximately from 1970 to 2000, the North Polar Region saw positive anomalous stratospheric winter temperatures. During the same time, the geomagnetic activity also showed a substantial increase. The year-to-year correlation between stratospheric pole temperature and geomagnetic activity is significant (about 0.5). The Empirical Mode Decomposition analysis reveals a highly significant correlation (around 0.9) between the long-term component of stratospheric winter temperature (IMF-4) and the long-term component of geomagnetic activity (IMF-3 and IMF-4). One of the reasons for the increase in lower stratospheric temperature is an increase in ozone concentration during the same period when geomagnetic activity is higher. Empirical orthogonal function (EOF) and correlation analysis of stratospheric winter temperature with large-scale circulation patterns are also carried out. The spatial correlation is checked for stratospheric winter temperature at North Pole and lower atmospheric levels (250 hPa and 850 hPa) followed by pre-monsoon and monsoon season. This study includes statistical analysis, however, also highlights the necessity of in-depth dynamical analysis to improve our understanding of how solar activity impacts Earth's atmospheric layers, which may be helpful in predicting the weather and climate.

Forecasting Geoffective Events from Solar Wind Data and Evaluating the Most Predictive Features through Machine Learning Approaches

This study addresses the prediction of geomagnetic disturbances by exploiting machine learning techniques. Specifically, the Long Short-term Memory recurrent neural network, which is particularly suited for application over long time series, is employed in the analysis of in situ measurements of solar wind plasma and magnetic field acquired over more than one solar cycle, from 2005 to 2019, at the Lagrangian point L1. The problem is approached as a binary classification aiming to predict 1 hr in advance a decrease in the SYM-H geomagnetic activity index below the threshold of −50 nT, which is generally regarded as indicative of magnetospheric perturbations. The strong class imbalance issue is tackled by using an appropriate loss function tailored to optimize appropriate skill scores in the training phase of the neural network. Beside classical skill scores, value-weighted skill scores are then employed to evaluate predictions, suitable in the study of problems, such as the one faced here, characterized by strong temporal variability. For the first time, the content of magnetic helicity and energy carried by solar transients, associated with their detection and likelihood of geoeffectiveness, were considered as input features of the network architecture. Their predictive capabilities are demonstrated through a correlation-driven feature selection method to rank the most relevant characteristics involved in the neural network prediction model. The optimal performance of the adopted neural network in properly forecasting the onset of geomagnetic storms, which is a crucial point for giving real warnings in an operational setting, is finally showed.

Lower Thermospheric Temperature Response to Geomagnetic Activity at High Latitudes

AbstractThe magnetosphere‐ionosphere‐thermosphere system is externally driven by the energy input from the solar wind. A part of the solar wind energy deposited in the magnetosphere during geomagnetically active periods dissipates into the thermosphere. Previous studies have reported temperature perturbations in the lower thermosphere during geomagnetic storms. The present study aims to assess the climatological spatial pattern of the lower thermospheric response to geomagnetic activity at high latitudes based on 21 years of temperature measurements by the SABER (Sounding of the Atmosphere using Broadband Emission Radiometry) instrument onboard the TIMED (Thermosphere Ionosphere Mesosphere Energetics and Dynamics) satellite and their comparison with the recently developed half‐hourly geomagnetic activity index Hp30. The temperature response to geomagnetic activity, evaluated at different seasons and altitudes, is better organized in magnetic coordinates than in geographic coordinates. At 110 km, the temperature increases with Hp30 at all magnetic local times, but with a prominent dusk‐dawn asymmetry in the magnitude. That is, the temperature variation per unit Hp30 is larger in the dusk sector than in the dawn sector. At 106 km, the response in the dawn sector is further reduced or even negative. These results provide observational evidence to support earlier theoretical predictions; according to which, both storm‐induced vertical wind and Joule heating contribute to the temperature increase in the dusk sector, while in the dawn sector, the vertical wind acts to cool the air and thus counteracts Joule heating.

Impact of geomagnetic activity on stratosphere and upper troposphere

During active geomagnetic conditions, a large amount of energy is deposited in the polar atmosphere in the form of particle precipitation that leads to Joule heating creating circulation of intense currents in the auroral region. It can affect the existing background pressure fluctuations in the stratospheric and tropospheric heights, leading to anomalous changes in the vertical temperature (T), zonal (u) and meridional (v) wind. In this study, we demonstrate the effect of active geomagnetic conditions on these atmospheric variables in different longitudinal regions. The investigation involves daily, monthly and seasonal variation of active geomagnetic conditions. Active geomagnetic conditions are selected using geomagnetic activity indices like auroral activity index |AL|>1000 nT, Disturbed Storm time index Dst < -150 and polar cap index PC > 5. Events are identified during November to March for 1990 to 2020 period. Among them 99 active geomagnetic conditions occurred in the month of March which are considered for further investigation. Composite analysis of T, u and v reflects that the temperature shows an increase in the entire atmospheric column; the anomalies in u (u′) and v (v′) show a regional dependence and strengthen in their amplitudes. It is seen from the monthly investigation of March that the Western Pacific, Canadian and East Pacific sectors respond to the active geomagnetic conditions at upper atmospheric pressure levels (approximately 40–70 km altitude) in the polar region. This is indicative of a vertical translation of energy to lower atmosphere during active geomagnetic conditions.

Forecasting ionospheric TEC using least squares support vector machine and moth-flame optimization methods in China

The total electron content (TEC) of the ionosphere is an important parameter to describe the ionosphere, and it is a great significance to monitor and predict it accurately. In this paper, a hybrid ionospheric TEC prediction model based on the least squares support vector machine (LSSVM) and the Moth-Flame Optimization (MFO) algorithm is proposed. The parameters of the LSSVM model are optimized by the MFO algorithm. We use observation data of 15 GNSS stations from the Crustal Movement Observation Network of China (CMONOC) to extract ionospheric TEC from 2012 to 2019. The ionospheric TEC is forecasted using solar and geomagnetic activity indices in both the low solar activity year (2019) and the high solar activity year (2015). The results show that the prediction performance of the MFO_LSSVM model is significantly better than that of the IRI model, SVM model, and LSSVM model. Compared with the other three models, there are more stable prediction results in the low and high solar activity years. At the same time, the predicted value of the MFO_LSSVM model has a good correlation with the measured value, and it also has good prediction potential in areas with active geomagnetic activity. The comparison with the Long Short-Term Memory (LSTM) model shows that the MFO_LSSVM model has better performance than the single LSTM model. In conclusion, the MFO_LSSVM model can accurately predict ionospheric TEC in China, and has better accuracy than traditional long-term and short-term models.

Tidal Composition Analysis of Global Sq Current System

AbstractIn this study, we examine the spatiotemporal variability of the global equivalent ionospheric current system estimated from geomagnetic Solar‐quiet (Sq) variations at 124 mid‐ to low‐latitude ground‐based magnetometer stations during 1–31 May 2020. In this period, geomagnetic activity was particularly low, that is, the hourly geomagnetic activity index Hp60 did not exceed 4o. The spherical harmonic analysis is performed on the Sq variations to estimate the equivalent current function at each universal time hour. Hourly maps of the global Sq current system are used to evaluate, for the first time, the tidal composition of mid‐latitude Sq currents and its temporal evolution. Although tides are known to be an important driver of Sq currents, the tidal composition analysis was difficult in previous studies that focused on Sq currents at particular longitude sectors. Our results show that the migrating tidal components (DW1, SW2, and TW3) are predominant in both hemispheres. This is as expected from the strong day‐night contrast in ionospheric conductivities. The day‐to‐day variations of the migrating tidal components are, however, not strongly correlated between the two hemispheres, suggesting that these variations arise not only from the global effect of solar radiation on ionospheric conductivities but also from the local effect of neutral winds. Variations associated with non‐migrating tides are also found. Especially, eastward‐propagating diurnal and semidiurnal tides with zonal wavenumber 1 (DE1 and SE1) are the largest non‐migrating components. Their production mechanisms remain to be understood.

Reconstruction of Carrington Rotation Means of Open Solar Flux over the Past 154 Years

We generate reconstructions of signed open solar flux (OSF) for the past 154 years using observations of geomagnetic activity. Previous reconstructions have been limited to annual resolution, but this is here increased by a factor of more than 13 by using averages over Carrington rotation (CR) intervals. We use two indices of geomagnetic activity, the homogeneous aa index, aaH, and the IDV(1d) index; a combination of the two is fitted to OSF estimates from near-Earth interplanetary satellite data. For 1995 – 2022, these are corrected for excess flux (i.e. orthogardenhose flux and switchbacks) using strahl electrons. For 1970 – 2022, we also use the absolute values of the radial component of the near-Earth interplanetary magnetic field 〈|〈Br〉τ|〉CR\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}${\\langle }|{\\langle }B_{r}{\\rangle }_{\ au }|{\\rangle }_{CR}$\\end{document}, where the excess flux is allowed for by adopting the optimum averaging interval τ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}${\ au }$\\end{document} of 20 h. However, in the interval 1970 – 1995, data gaps in the interplanetary data are a serious problem. The errors that these missing data cause in CR averages of OSF are evaluated by synthetically masking data for CRs that have a full complement, using the same number and time series of data gaps as for the CR in question. Given the potential for missing data to generate large errors, we use the near-continuous 1995 – 2022 data to derive the best-fit combination of the geomagnetic data and employ the 1970 – 1995 data for testing in which we can readily allow for the errors caused by data gaps. Errors caused by inaccuracies in the geomagnetic data are shown to be considerably smaller than the uncertainties due to the polynomial fitting. It is shown that the new reconstructions are consistent with the previous annual estimates and that there is considerable variability in the OSF values from one CR to the next; in particular, in high-activity solar cycles, there can be individual CRs in which the OSF exceeds that for adjacent CRs by a factor as large as two.

Periodic Behavior of Selected Solar, Geomagnetic and Cosmic Activity Indices during Solar Cycle 24

In this study, we performed periodicity analyses of selected daily solar (flare index, coronal index, number of coronal mass ejections), geomagnetic (planetary equivalent range index, disturbance storm time index, interplanetary magnetic field) and cosmic ray indices for the last Solar Cycle 24 (from December 2008 to December 2019). To study the periodic variation of the above-listed datasets, the following analysis methods were applied; multi-taper method, Morlet wavelet, cross-wavelet transform and wavelet coherence analysis. The outcome of our analyses revealed the following. (i) The 25–33 days solar rotation periodicities exist in all datasets without any exception in the MTM power spectra. (ii) Except for the solar rotation periodicity, all periods show data preference, and they appear around the investigated cycle’s maximum phase. (iii) When comparing the phase relations between periodicities in the used datasets, they exhibit a gradual transition from small to large periods. For short-term periodicities, there are no phase relations but a mixed phase, whereas for high periodicities, there are complete phase/antiphase transitions. (iv) All identified flare index periodicities are common to all other datasets examined in this investigation.

Analysis of ionospheric anomalies before the Fukushima Mw 7.3 earthquake of March 16, 2022

Abstract In order to study the coupling relationship between earthquakes and ionospheric disturbances, TEC data during the Mw 7.3 earthquake that occurred near Fukushima, Japan on March 16, 2022, were processed using global ionospheric data provided by the Center for Orbit Determination in Europe (CODE). In this paper, the sliding quartile interval method is used to eliminate solar activity in a 27-day window, including sunspot number (SSN), F10.7 cm radio flux (F10.7), total solar irradiation (TSI), solar wind velocity (Vsw) and geomagnetic activity. The impact of disturbance storm time index (DST) and global geomagnetic activity index (KP) on TEC anomaly disturbance can obtain more accurate TEC anomaly information. The results indicate that when the solar and geomagnetic activity cycles are inconsistent with the TEC anomalies on fifth day before the earthquake, the TEC anomalies above the epicenter are significantly greater than those observed in other regions, and the corresponding magnetic conjugate region is accompanied by anomalies, which is the characteristic of TEC anomalies caused by earthquakes. This means that the detected TEC anomalies can be used as a potential ionospheric precursors, indicating that the Fukushima earthquake is imminent.

Main time characteristics of cosmic ray variations and related parameters in magnetic clouds

The behavior of the main parameters of the interplanetary medium, cosmic rays, and geomagnetic activity during the passage of magnetic clouds past the Earth (465 events over the period from 1967 to 2021) has been studied. Time distributions of these parameters inside magnetic clouds are considered. It is shown that the maximum values of the solar wind velocity, interplanetary magnetic field strength, and geomagnetic activity indices are more often recorded at the beginning of the magnetic cloud, while the minimum values of the temperature index, cosmic ray density and equatorial component of anisotropy can be observed in any part of the structure under study.

Experiment on long-term forecasting of geomagnetic activity based on nonlocal correlations

The experiment was performed on the use of advanced macroscopic nonlocal correlations to forecast slow random fluctuations of the Dst index of geomagnetic activity. The global maximum correlation of Dst with the signal of the electrode detector reaches 0.97, which is sufficient for the forecast, and its time shift corresponds to the advance of the detector signal relative to Dst by 329 days. The large magnitude of the time shift is due to the slow diffusion mechanism of entanglement swapping between the detector and the source. At the same time, the position of the global maximum of the correlation function coincides with the position of the global minimum of the entropy independence function, which confirms its undistorted by possible nonlinearity of the relationship and determines the optimal lead time of the forecast. Long series of test forecasts Dst have been calculated using data from a nonlocal correlation detector with a fixed lead time using three methods: current regression, current impulse transient response and current neural network. The accuracy of the forecasts is sufficient for all practical purposes.

A Floor in the Sun's Photospheric Magnetic Field: Implications for an Independent Small-scale Dynamo

Clette recently showed that F 10.7 systematically approaches a quiet Sun daily value of 67 solar flux units (sfu) at solar minima as the number of spotless days on the Sun increases. Previously, a floor of ∼2.8 nT had been proposed for the solar wind (SW) magnetic field strength (B). F 10.7, which closely tracks the Sun's unsigned photospheric magnetic flux, and SW B exhibit different relationships to their floors at 11 yr solar minima during the last ∼50 yr. While F 10.7 approaches 67 sfu at each minimum, the corresponding SW B is offset above ∼2.8 nT by an amount approximately proportional to the solar polar field strength—which varied by a factor of ∼2.5 during this interval. This difference is substantiated by ∼130 yr of reconstructed F 10.7 (via the range of the diurnal variation of the East-component (rY) of the geomagnetic field) and SW B (based on the interdiurnal variability geomagnetic activity index). For the last ∼60 yr, the contribution of the slow SW to SW B has exhibited a floor-like behavior at ∼2 nT, in contrast to the contributions of coronal mass ejections and high-speed streams that vary with the solar cycle. These observations, as well as recent SW studies based on Parker Solar Probe and Solar Dynamics Observatory data, suggest that (1) the Sun has a small-scale turbulent dynamo that is independent of the 11 yr sunspot cycle; and (2) the small-scale magnetic fields generated by this nonvarying turbulent dynamo maintain a constant open flux carried to the heliosphere by the Sun's floor-like slow SW.

Forecasting Ionospheric foF2 Using Bidirectional LSTM and Attention Mechanism

AbstractThe critical frequency of ionospheric F2 layer (foF2) is an important ionospheric characteristic parameter. In this paper, a deep learning model based on Bidirectional long short‐term memory (BiLSTM) and attention mechanism is implemented for predicting the foF2 parameter. The inputs of models are the foF2 of globally available ionospheric ionosonde stations, geographic longitude and latitude, world time (UT), geomagnetic activity index, and solar activity index from 2015 to 2017. The superiority of the model is analyzed from different latitudes, seasons, and geomagnetic conditions. The results show that the prediction performance of the Bidirectional long short‐term memory model based on attention mechanism (BiLSTM‐Attention) is better than other models. The performance of the prediction model is optimal at high latitudes. The root mean square error (RMSE) and correlation coefficient (R) of the BiLSTM‐Attention model are 0.539 MHZ and 0.908 MHz at high latitudes, respectively. In terms of RMSE, it is 25.243%, 18.209%, and 11.203% lower than those of the international reference ionosphere (IRI), LSTM, and BiLSTM models, respectively. The prediction results of the four seasons show that the models are more applicable in winter. Compared with the IRI model, the RMSE of the BiLSTM‐Attention model in spring, summer, autumn, and winter is reduced by 24.344%, 21.181%, 25.058%, and 30.948%, respectively. The prediction effect of the BiLSTM‐Attention model is improved in the magnetic quiet period, the magnetic moderate period and the magnetic storm period. Also, the improvement effect is more obvious in the magnetostatic day, and the RMSE is reduced by 27.462% compared with the IRI model.

High‐Energy Electron Flux Enhancement Pattern in the Outer Radiation Belt in Response to the Interplanetary Coronal Mass Ejections

AbstractThe high‐energy electron flux enhancement pattern in the outer radiation belt is observed under the influence of the Interplanetary Coronal Mass Ejections (ICMEs). Ten events were selected during the Van Allen Probes era, with the high‐energy electron flux enhancement starting close to L* = 4. A schematic diagram of the main physical processes responsible for this kind of high‐energy electron flux enhancement is presented, considering the energy deposited in the inner magnetosphere under the influence of ICMEs. Superposed Epoch Analysis is applied to the interplanetary medium parameters, the magnetopause standoff distance, the storm‐time geomagnetic activity indices, the Ultra‐Low Frequency (ULF) waves, and the whistler‐mode chorus waves. A compressed magnetopause, Bz component preferentially southward and storm indices considerably high are observed at the beginning of the electron flux enhancements. The modeled parameters of the chorus waves at the dayside/nightside sectors show the high acceleration efficiency at the beginning of the electron flux enhancement pattern II. These results suggest that the local acceleration driven by chorus waves is essential to these electron flux enhancements at low L*. In contrast, although the ULF waves are detected at the beginning of the studied electron flux enhancements, their contribution is insignificant.

Hysteresis effect between geomagnetic activity indices (Ap, Dst) and interplanetary medium parameters in solar activity cycles 21–24

We have studied the relationship of geomagnetic activity indices (Ap, Dst) on time intervals, equal to solar cycles (∼11 years), with solar activity indicators and heliospheric parameters. It is shown that the plots of the Ap and Dst indices versus solar activity indicators, as well as versus heliospheric parameters, i.e. solar wind and IMF parameters in the ascending and descending phases of solar activity cycles 21–24 do not coincide, which is indicative of the hysteresis phenomenon. The Ap and Dst indices form hysteresis loops with all parameters we analyze during cycles 21–24. The shape and area of the hysteresis loops, as well as the direction of rotation, clockwise or counterclockwise, depend significantly on indicators of solar activity, heliospheric parameters and change from cycle to cycle. We have found a tendency for the extension and area of the hysteresis loops to decrease from cycle 21 to cycle 24. Analysis of the variability in the shape and size of the hysteresis loops formed by the Ap and Dst indices with solar indicators and heliospheric parameters gives reason to believe that the obtained loops reflect the long-term evolution of the solar wind energy flux, which determines global geomagnetic activity and the magnetospheric ring current intensity in the ascending and descending phases of solar activity cycles 21‒24.

Variations in Pulsating Aurora Emission in 337 nm and 391 nm Nitrogen Spectral Lines during Geomagnetic Substorms

Spectroscopic measurements of aurora emissions provide valuable insights into the altitude of electron atmospheric penetration and their maximum energy. To achieve this, the photometers used in the PAIPS (Pulsating Aurora Imaging Photometers System) project are equipped with spectrometers. These spectrometers enable the measurement of auroral emissions in narrow spectral lines with a temporal resolution of milliseconds. In this study, we present two cases of PsA (Pulsating Aurora) measurements in the 337 nm and 391 nm spectral lines. We demonstrate that during quiet geomagnetic conditions the ratio of night sky emissions in these bands is close to one and significantly increases during substorms. We propose and implement a special procedure for estimating this ratio. Our findings reveal that the intensity of emissions in both spectral lines correlates with the AL index of geomagnetic activity. However, the ratio between the emissions fluctuates around constant values over time and does not undergo significant changes throughout the entire PsA event, which can last for more than an hour.

Эффект гистерезиса между индексами геомагнитной активности (Ap, Dst) и параметрами межпланетной среды в 21-24 циклах солнечной активности

We have studied the relationship of geomagnetic activity indices (Ap, Dst) on time intervals, equal to solar cycles (∼11 years), with solar activity indicators and heliospheric parameters. It is shown that the plots of the Ap and Dst indices versus solar activity indicators, as well as versus heliospheric parameters, i.e. solar wind and IMF parameters in the ascending and descending phases of solar activity cycles 21–24 do not coincide, which is indicative of the hysteresis phenomenon. The Ap and Dst indices form hysteresis loops with all parameters we analyze during cycles 21–24. The shape and area of the hysteresis loops, as well as the direction of rotation, clockwise or counterclockwise, depend significantly on indicators of solar activity, heliospheric parameters and change from cycle to cycle. We have found a tendency for the extension and area of the hysteresis loops to decrease from cycle 21 to cycle 24. Analysis of the variability in the shape and size of the hysteresis loops formed by the Ap and Dst indices with solar indicators and heliospheric parameters gives reason to believe that the obtained loops reflect the long-term evolution of the solar wind energy flux, which determines global geomagnetic activity and the magnetospheric ring current intensity in the ascending and descending phases of solar activity cycles 21‒24.

Исследование влияния геомагнитной активности на функционирование систем железнодорожной автоматики в Арктической зоне России

The authors study the possible influence of geomagnetic activity of railway automatics in the Russian Arctic. For the analysis they use the indices of global and regional geomagnetic activity along with the archive of failures on the Northern section of the Oktyabrskaya railway in 2001—2006. The geomagnetic activity is found to be higher for days with failures than for days without the ones. This effect manifests itself in different types of geomagnetic disturbances, including magnetic storms, characterized by the storm index Dst, auroral activations, quantified in AE and EI indices, as well as in local index WY indicating spectral power of geomagnetic variations in milliHerz frequency range. The maximum differences for days with and without failures are obtained for index values averaged over 2—4 days. At the same time, the researchers have found no significant differences between failures for which a cause not related to geomagnetic disturbance is a priori indicated, and those for which such a cause is not identified.

Parametrization of Energetic Ion and Electron Fluxes in the Near‐Earth Magnetotail

AbstractThe near‐Earth plasma sheet region is the main source of energetic (tens to hundreds keV) ion and electron populations transported by convection and injections into the inner magnetosphere. Energetic ions from the plasma sheet contribute to the ring current, whereas energetic electrons contribute to the radiation belt seed population for further acceleration to relativistic energies. Near‐Earth plasma sheet energetic fluxes have been traditionally used to set boundary conditions for radiation belt and ring current models. This study provides an empirical parametrization for ∼75 keV flux intensity as a function of the geomagnetic activity index auroral electrojet and the equatorial magnetic field Bz. Such parametrization includes the dynamic magnetic field configuration in the near‐Earth plasma sheet and may be merged with empirical magnetic field models. We also provide models extending this parametrization to the [20, 300] keV of electron energy range and [75, 300] keV of ion energy range. The parametrization is developed based on THEMIS and Geostationary Operational Environmental Satellite measurements, and verified by comparison with MMS measurements in the near‐Earth plasma sheet. This parametrization incorporates meso‐scale transient flux variations associated with Bz perturbations into ring current and radiation belt simulations.

Understanding Quiet and Storm Time EMIC Waves—Van Allen Probes Results

AbstractGeomagnetic indices have been used as a proxy for studying electromagnetic ion cyclotron (EMIC) wave occurrences under different geomagnetic conditions. However, the drivers of EMIC waves are different during non‐storm, storm time and during individual storm phases. Using ∼7 years of data from the twin Van Allen Probes, we demonstrate that the occurrence probability of EMIC waves are not well captured by a specific geomagnetic activity index alone, but is rather well manifested by considering individual storm phases. We show EMIC wave occurrence statistics during different storm phases (pre‐onset, main and recovery) for geomagnetic activity indices Sym‐H, AE, and Kp and solar wind dynamic pressure Pdyn, illustrating that the occurrence rates vary significantly during different storm phases even for a given geomagnetic index. We also utilize this large database to show EMIC wave occurrence distribution, and how various wave and plasma parameters behave under different geomagnetic conditions. EMIC waves occur 2.9 times more often during geomagnetic storms than during non‐storm times. The majority (72%) of storm time EMIC waves occur during the recovery phase due to long recovering time, while the highest occurrence rates are in the pre‐onset phase, followed by main and recovery phases. EMIC waves in the main phase have occurrence peaks in the dusk to pre‐midnight sectors while recovery phase events spread to more Magnetic Local Time (MLT) sectors with peaks in the morning sector. Wave amplitudes are found to be evenly distributed across different MLT sectors during all geomagnetic conditions.