Content Anomalies Research Articles

A Study of Lithosphere–Ionosphere Seismic Precursors from Detecting Gamma-Ray and Total Electron Content Anomalies Prior to the 2018 ML6.2 Hualien Earthquake in Eastern Taiwan

This study conducts a comprehensive analysis of observations related to the ML6.2 Hualien earthquake that struck eastern Taiwan on February 6, 2018, focusing particularly on gamma-ray emissions and total electron content (TEC) as earthquake precursors. Prior research has shown that significant gamma-ray enhancements are frequently detected at the YMSG (Yangmingshan gamma-ray) station prior to major earthquakes in eastern and northeastern Taiwan, suggesting that gamma-ray anomalies may serve as reliable indicators for identifying seismic precursors in this area. Our findings reveal a significant rise in gamma-ray emissions at the YMSG station from January 19 to February 4, 2018, which corresponds to a precursor period of approximately 18 days before the Hualien earthquake. Positive and negative TEC anomalies were observed in Taiwan on 20–21 January and 5 February, respectively, and may be considered as ionospheric precursors to the earthquake. Additionally, deep-learning techniques applied to TEC data facilitate the detection of ionospheric precursors associated with the Hualien earthquake, enabling forecasts of an approaching seismic event. Collectively, these observations indicate that all identified anomalies are regarded as short-term precursors, explicable through the theoretical framework of lithosphere–ionosphere coupling (LIC).

Analysis of Ionospheric Anomalies before Earthquakes of Mw6.5 and above in Japan from 2011 to 2022

In this study, a TEC variation window value was selected based on the wavelet power spectrum method to analyze the seismic–ionospheric coupling relationship. In the full-time domain, a 27-day periodicity of the wavelet power spectrum was obtained that passed the 95% significance test. The sliding interquartile range method was used to analyze earthquakes above Mw6.5 in Japan from 2011 to 2022, excluding the hybrid effects between earthquakes close to one another. The sunspot number (SSN), 10.7 cm radio flux (F10.7), total solar irradiance (TSI), solar wind velocity (Vsw), geomagnetic activity index in the equatorial region (DST), and global geomagnetic activity index (KP) were used as indices representing solar and geomagnetic activity. After removing solar and geomagnetic interference from ionospheric anomaly changes using the sliding interquartile range method, the TEC anomaly changes before the earthquake were verified as being caused by the earthquake and analyzed. The statistical analysis of ionospheric total electron content (TEC) anomalies showed that earthquake magnitude was positively correlated with the amplitude of TEC anomalies but not linearly. The occurrence time of ionospheric anomalies lagged behind to some extent with the increase in earthquake magnitude. Additionally, abnormal changes on the 29th day (15 February 2022) before the 20th earthquake did not conform to previous research rules. According to the lithosphere–atmosphere–ionospheric coupling (LAIC) mechanism and global ionospheric map (GIM) studies, the TEC anomaly was consistent with the vertical projection of the epicenter with obvious regularity. The results show that these TEC anomalies may be related to earthquakes.

Asymmetric responses of summer soil moisture anomalies to the large-scale teleconnections on the Loess Plateau between 2000 and 2020

Asymmetric responses of summer soil moisture anomalies to the large-scale teleconnections on the Loess Plateau between 2000 and 2020

Definition of springtime easterly wind bursts in the Indian Ocean and their roles in triggering positive IOD events

Using wind reanalysis dataset, we propose a definition for easterly wind bursts (EWBs) occurring in the Indian Ocean and analyze their effects on positive Indian Ocean Dipole (pIOD) events. It was found that there were eight pIOD events during the period from 1980–2020, all of which were accompanied by EWBs occurrence in spring except 2015. The significant impact of EWBs on pIOD events is through the Bjerkness feedback process, strengthening upwelling in the Eastern Indian Ocean (EIO) and triggering a westward zonal current in the equatorial Indian Ocean, both cooling the EIO and in turn strengthening the easterly wind anomalies. Further analysis reveals that the negative upper ocean heat content (OHC) anomalies in EIO, acting as a trigger of Bjerkness feedback process, also plays a critical role in the development of pIOD. Thus, the simultaneous occurrence of EWBs and negative OHC anomalies in spring is an important precursor to pIOD occurrence, although there are possible other triggers.

Investigating ultra-low frequency emissions and total electron content anomalies as earthquake precursors in Sumatra (2019–2020)

Investigating ultra-low frequency emissions and total electron content anomalies as earthquake precursors in Sumatra (2019–2020)

Composite vertical structures and spatiotemporal characteristics of abnormal eddies in the Japan/East Sea: a synergistic investigation using satellite altimetry and Argo profiles

Mesoscale eddies are omnipresent and play an important role in regulating Earth’s climate and ocean circulation in the global ocean. Here using the combination of satellite altimetry products and Argo float profile data, two types of abnormal eddies are investigated: WCEs(warm cyclonic eddies) and CAEs(cold anticyclonic eddies) with different cores than conventional eddies in the Japan/East Sea. By applying a classification method based on the calculation of the heat content anomalies in the upper ocean, it was found that 10% of the eddies that captured the Argo float profiles exhibited obvious abnormal features. Subsequently, their spatiotemporal distributions and characteristics were analyzed statistically. Three-dimensional structures of abnormal eddies were obtained via the composite analysis method, showing that the warm/cold and light/dense core of the composite WCE/CAE is confined to the upper 100 m of the ocean with a maximum temperature anomaly of approximately +1.0(-1.1)°C. The composite WCE had a double-core salinity structure with a salty core above 50 m and an inferior fresh core. Meanwhile composite CAE had a fresh single-core with a maximum magnitude of -0.05 psu. Abnormal eddies are pervasive in the Japan/East sea, a revaluation of the role of these eddies in ocean circulation and climate systems, such as heat and salt transport, air and sea interaction, and variability in mixed layer depth, is of great importance.

A Method for Detecting Ionospheric TEC Anomalies before Earthquake: The Case Study of Ms 7.8 Earthquake, February 06, 2023, Türkiye

The ionospheric anomalies before an earthquake may be related to earthquake preparation. The study of the ionospheric anomalies before an earthquake provides potential value for earthquake prediction. This paper proposes a method for detecting ionospheric total electron content (TEC) anomalies before an earthquake, taking the MS 7.8 earthquake in Türkiye on 6 February 2023 as an example. First, the data of four ground-based GNSS stations close to the epicenter were processed by using the sliding interquartile range method and the long short-term memory (LSTM) network. The anomaly dates detected by the two methods were identified as potential pre-earthquake TEC anomaly dates after eliminating solar and geomagnetic interference. Then, by using the sliding interquartile range method to process and analyze the CODE GIM (Center for Orbit Determination in Europe, Global Ionospheric Map) data from a global perspective, we further verified the existence of TEC anomalies before the earthquake on the above TEC anomaly days. Finally, the influence of the equatorial ionospheric anomaly (EIA) on the TEC anomaly disturbance was excluded. The results show that the ionospheric TEC anomalies on January 20, January 27, February 4, and February 5 before the Türkiye earthquake may be correlated with the earthquake.

Ionospheric Total Electron Content (TEC) Anomalies as Earthquake Precursors: Unveiling the Geophysical Connection Leading to the 2023 Moroccan 6.8 Mw Earthquake

The study delves into the relationship between ionospheric total electron content (TEC) anomalies and seismic activity, with a focus on Morocco’s 6.8 Mw earthquake on 8 September 2023, lying within a tectonically active region at the convergence of the African and Eurasian Plates. To enhance the reliability of our findings, we incorporate space weather conditions, utilizing indices (Dst, Kp, and F10.7) to pinpoint periods of stable space weather. This minimizes the possibility of erroneously attributing natural ionospheric fluctuations to seismic events. Notably, our TEC analysis unveils positive and negative anomalies, with some occurring up to a week before the earthquake. These anomalies, exceeding predefined thresholds, provide compelling evidence of significant deviations from typical ionospheric conditions. Spatial mapping techniques employing both station-specific vTEC data and pseudorandom noise codes (PRNs) from multiple global navigation satellite system (GNSS) stations highlight a strong correlation between ionospheric anomalies and the earthquake’s epicenter. The integration of PRNs enhances coverage and sensitivity to subtle anomalies. Additionally, the analysis of satellite imagery and ground displacement data using Sentinel-1 confirms significant ground uplift of approximately 15 cm following the earthquake, shedding light on surface responses to seismic events. These findings underscore the potential of ionospheric science in advancing earthquake early warning systems and deepening our understanding of earthquake precursors, thus contributing to the mitigation of seismic event impacts and the protection of lives and infrastructure.

Analysis of Ionospheric Anomalies before the Tonga Volcanic Eruption on 15 January 2022

In this paper, GNSS stations’ observational data, global ionospheric maps (GIM) and the electron density of FORMOSAT-7/COSMIC-2 occultation are used to study ionospheric anomalies before the submarine volcanic eruption of Hunga Tonga–Hunga Ha’apai on 15 January 2022. (i) We detect the negative total electron content (TEC) anomalies by three GNSS stations on 5 January before the volcanic eruption after excluding the influence of solar and geomagnetic disturbances and lower atmospheric forcing. The GIMs also detect the negative anomaly in the global ionospheric TEC only near the epicenter of the eruption on 5 January, with a maximum outlier exceeding 6 TECU. (ii) From 1 to 3 January (local time), the equatorial ionization anomaly (EIA) peak shifts significantly towards the Antarctic from afternoon to night. The equatorial ionization anomaly double peak decreases from 4 January, and the EIA double peak disappears and merges into a single peak on 7 January. Meanwhile, the diurnal maxima of TEC at TONG station decrease by nearly 10 TECU and only one diurnal maximum occurred on 4 January (i.e., 5 January of UT), but the significant ionospheric diurnal double-maxima (DDM) are observed on other dates. (iii) We find a maximum value exceeding NmF2 at an altitude of 100~130 km above the volcanic eruption on 5 January (i.e., a sporadic E layer), with an electron density of 7.5 × 105 el/cm3.

Global High-Resolution Random Forest Regression Maps of Ocean Heat Content Anomalies Using In Situ and Satellite Data

Abstract The ocean, with its low albedo and vast thermal inertia, plays key roles in the climate system, including absorbing massive amounts of heat as atmospheric greenhouse gas concentrations rise. While the Argo array of profiling floats has vastly improved sampling of ocean temperature in the upper half of the global ocean volume since the mid-2000s, they are not sufficient in number to resolve eddy scales in the oceans. However, satellite sea surface temperature (SST) and sea surface height (SSH) measurements do resolve these scales. Here we use random forest regressions to map ocean heat content anomalies (OHCA) using in situ training data from Argo and other sources on a 7-day × 1/4° × 1/4° grid with latitude, longitude, time, SSH, and SST as predictors. The maps display substantial patterns on eddy scales, resolving variations of ocean currents and fronts. During the well-sampled Argo period, global integrals of these maps reduce noise relative to estimates based on objective mapping of in situ data alone by roughly a factor of 3 when compared to time series of CERES (satellite data) top-of-the-atmosphere energy flux measurements and improve correlations of anomalies with CERES on annual time scales. Prior to and early on in the Argo period, when in situ data were sparser, global integrals of these maps retain low variance, and do not relax back to a climatological mean, avoiding potential deficiencies of various methods for infilling data-sparse regions with objective maps by exploiting temporal and spatial patterns of OHCA and its correlations with SST and SSH. Significance Statement We use a simple machine learning technique to improve maps of subsurface ocean warming by exploiting the relationships between subsurface ocean temperature both sea surface temperature and sea level. Mapping ocean warming is important because it contributes to sea level rise through thermal expansion; impacts marine life through marine heatwaves and changes in mixing, oxygen, and carbon dioxide levels; increases energy available to tropical cyclones; and stores most of the energy building up in Earth’s climate system owing to the accumulation of anthropogenic greenhouse gases in the atmosphere. Our new estimates generally have lower noise energy and higher correlations than other products when compared with global energy fluxes at the top of the atmosphere measured by satellite.

Statistical analysis of ionospheric vertical total electron content anomalies before global Mw≥6.0 shallow earthquakes during 2000–2020

To quantitatively investigate the relationship between earthquakes and ionospheric anomalies, this paper presents a statistical study of pre-earthquake vertical total electron content (VTEC) variations. A total of 1522 shallow (≤60 km) strong (Mw≥6.0) earthquakes in the global area during 2000-2020 are selected, and classified according to different magnitudes, latitudes and focal depths. A quartile-based process with different lengths of sliding windows, equaling 10 days, 15 days and 27 days, respectively, has been utilized to detect VTEC anomalies. The abnormal level is first defined, and then VTEC anomalies occurrence probabilities (Po) and occurrence rates (PE) within 1-10 days before 1522 earthquakes have been calculated. Besides, VTEC anomalies occurrence rates of the background days (PN) are also calculated. The results show that the significant correlation between Po and epicentral latitudinal locations could be observed within 1-10 days before earthquakes. The values of Po increase with larger magnitudes in the equatorial and low-latitude regions, but decrease with greater magnitudes in the mid- and high-latitude regions to some degree. Within 1-5 days before earthquakes, the overall trend of PE shows an increase with larger magnitudes, but the correlation between the values of PE and magnitudes is relatively weak in the southern mid- and high-latitude regions. There is no evident causality between PN and the magnitude, and most of the values of PE/PN are larger than 1, indicating that VTEC anomalies within a few days before earthquakes are probably related with the forthcoming earthquakes. Moreover, when the abnormal level exceeds 60%, different sliding window lengths have a significant impact on the values of Po and PE in the mid- and high-latitude regions. In particular, there are obvious systematic deviations between the values of Po obtained from different sliding windows in the southern mid- and high-latitude regions. However, the selection of the optimal sliding window needs to be further studied.

Global Variability of Density Contrast Across the 660‐km Discontinuity

AbstractThis study investigates lateral variations in density contrast across the 660‐km discontinuity, which is critical for understanding mantle convection and composition. We produce a global map of density jump, with values ranging from 3.8% to 9.3%, at the mineralogical phase boundary by applying inversions of amplitude variations with offset to underside S reflections. Our observations reveal a global average velocity jump of 4.1% and a density jump of 5.3%, favoring a pyrolitic bulk composition. Near major subduction zones, most notably the western Pacific and South America, we identify reduced density jumps in regions of depressed 660‐km discontinuity, consistent with basalt fractions greater than 30% in a mechanically mixed mantle. The causal association between density jump and compositional changes is further supported by a moderate correlation between lateral variations in density jump and those of water content anomalies.

Integrated observations on crustal strain-ionosphere total electron content anomalies before the earthquake

Integrated observations on crustal strain-ionosphere total electron content anomalies before the earthquake

Contextual analysis of scholarly communications to identify the source of disinformation on digital scholarly platforms

PurposeScholarly communications, particularly, questions and answers (Q&A) present on digital scholarly platforms provide a new avenue to gain knowledge. However, several studies have raised a concern about the content anomalies in these Q&A and suggested a proper validation before utilizing them in scholarly applications such as influence analysis and content-based recommendation systems. The content anomalies are referred as disinformation in this research. The purpose of this research is firstly, to assess scholarly communications in order to identify disinformation and secondly, to help scholarly platforms determine the scholars who probably disseminate such disinformation. These scholars are referred as the probable sources of disinformation.Design/methodology/approachTo identify disinformation, the proposed model deduces (1) content redundancy and contextual redundancy in questions (2) contextual nonrelevance in answers with respect to the questions and (3) quality of answers with respect to the expertise of the answering scholars. Then, the model determines the probable sources of disinformation using the statistical analysis.FindingsThe model is evaluated on ResearchGate (RG) data. Results suggest that the model efficiently identifies disinformation from scholarly communications and accurately detects the probable sources of disinformation.Practical implicationsDifferent platforms with communication portals can use this model as a regulatory mechanism to restrict the prorogation of disinformation. Scholarly platforms can use this model to generate an accurate influence assessment mechanism and also relevant recommendations for their scholars.Originality/valueThe existing studies majorly deal with validating the answers using statistical measures. The proposed model focuses on questions as well as answers and performs a contextual analysis using an advanced word embedding technique.

Uncertainty in Preindustrial Global Ocean Initialization Can Yield Irreducible Uncertainty in Southern Ocean Surface Climate

Abstract How do ocean initial states impact historical and future climate projections in Earth system models? To answer this question, we use the 50-member Canadian Earth System Model (CanESM2) large ensemble, in which individual ensemble members are initialized using a combination of different oceanic initial states and atmospheric microperturbations. We show that global ocean heat content anomalies associated with the different ocean initial states, particularly differences in deep ocean heat content due to ocean drift, persist from initialization at year 1950 through the end of the simulations at year 2100. We also find that these anomalies most readily impact surface climate over the Southern Ocean. Differences in ocean initial states affect Southern Ocean surface climate because persistent deep ocean temperature anomalies upwell along sloping isopycnal surfaces that delineate neighboring branches of the upper and lower cells of the global meridional overturning circulation. As a result, up to a quarter of the ensemble variance in Southern Ocean turbulent heat fluxes, heat uptake, and surface temperature trends can be traced to variance in the ocean initial state, notably deep ocean temperature differences of order 0.1 K due to model drift. Such a discernible impact of varying ocean initial conditions on ensemble variance over the Southern Ocean is evident throughout the full 150 simulation years of the ensemble, even though upper ocean temperature anomalies due to varying ocean initial conditions rapidly dissipate over the first two decades of model integration over much of the rest of the globe.

Phase-Locked Impact of the 11-Year Solar Cycle on Tropical Pacific Decadal Variability

Abstract As an important external forcing, the effect of the 11-yr solar cycle on the tropical Pacific decadal variability is an interesting question. Here, we systematically investigate the phase-locking of the atmosphere and ocean covariations to the solar cycle in the tropical Pacific and propose a new mechanism to explain these decadal covariations. In both observation/reanalysis datasets and a solar cycle forced sensitivity experiment (named the SOL experiment), the ocean heat content anomalies (OHCa; 300 m) resemble a La Niña–like pattern in the solar cycle ascending phase, and the Walker circulation shifts westward. In the declining phase, the opposite is true. The accumulative solar irradiation directly contributes to this coherent decadal variability via changing the warm water volume and the solar-related heat is redistributed by the ocean dynamic processes. During the 11-yr solar cycle, the Pacific Walker circulation anomalies maintain the OHCa in the western equatorial Pacific and work as negative feedback for the eastern Pacific to help the OHCa phase transition. In addition, oceanic meridional heat transport via the subtropical cells and the propagation of off-equatorial Rossby waves also provide a lagged negative feedback to the OHCa phase transition according to the 11-yr solar cycle. The decadal coupled responses of the tropical Pacific climate system are 2 years more lag in the SOL experiment than in the observation/reanalysis. Significance Statement Here, we propose a new mechanism that the heating effect of the accumulative solar irradiation during the 11-yr solar cycle can be “integrated” into the tropical Pacific OHC and then provide a bottom-up effect on the atmosphere at decadal time scales. The strongly coupled processes in this region amplify the decadal phase-locking of the covariations to the 11-yr solar cycle. Our study demonstrates the role of the 11-yr solar cycle in the tropical Pacific decadal variability and provides a new explanation for the “bottom-up” mechanism of the solar cycle forcing. Our results update the understanding of the tropical Pacific decadal variability and may help to improve climate predictions at decadal time scales.

Analysis of the Anomalous Environmental Response to the 2022 Tonga Volcanic Eruption Based on GNSS

On 15 January 2022, a violent eruption and tsunami of the Hunga Tonga-Hunga Ha’apai (HTHH) volcano in Tonga, South Pacific, caused widespread international concern. In order to detect the anomalous environmental response caused by the HTHH volcanic eruption based on GNSS ionospheric data, GNSS tropospheric data and GNSS coordinate time series, a new method combining the zenith non-hydrostatic delay difference method and the extreme-point symmetric mode decomposition (ESMD) method, was proposed to detect tropospheric anomalies. The moving interquartile range method and the ESMD method were introduced to detect ionospheric anomalous and coordinate time series anomalies, respectively. The results showed that 9–10 h before the eruption of the Tonga volcano and 11–12 h after the eruption of the Tonga volcano, obvious total electron content (TEC) anomalies occurred in the volcanic eruption center and its northeast and southeast, with the maximum abnormal value of 15 TECU. Significant tropospheric anomalies were observed on the day of the HTHH volcano eruption as well as 1–3 days and 16–17 days after the eruption, and the abnormal intensity was more than 10 times that of normal. The coordinate time series in direction E showed very significant anomalies at approximately 2:45 p.m. on 14 January, at approximately 4:30 a.m.–5:40 a.m. on 15 January, and at approximately 3:45 a.m. on 16 January, with anomalies reaching a maximum of 7–8 times daily. The abnormality in the direction north (N) is not obvious. Very prominent anomalies can be observed in the direction up (U) at approximately 4:30 a.m.–5:40 a.m., with the intensity of the anomalies exceeding the normal by more than 10 times. In this study, GNSS was successfully used to detect the anomalous environmental response during this HTHH volcano eruption.

Investigation of Displacement and Ionospheric Disturbance during an Earthquake Using Single-Frequency PPP

Currently, it is still challenging to detect earthquakes by using the measurements of Global Navigation Satellite System (GNSS), especially while only adopting single-frequency GNSS. To increase the accuracy of earthquake detection and warning, extra information and techniques are required that lead to high costs. Therefore, this work tries to find a low-cost method with high-accuracy performance. The contributions of our research are twofold: (1) an improved earthquake-displacement estimation approach by considering the relation between earthquake and ionospheric disturbance is presented. For this purpose, we propose an undifferenced uncombined Single-Frequency Precise Point Positioning (SF-PPP) approach, in which both the ionospheric delay of each observed satellite and receiver Differential Code Bias (DCB) are parameterized. When processing the 1 Hz GPS data collected during the 2013 Mw7.0 Lushan earthquake and the 2011 Mw9.0 Tohoku-Oki earthquake, the proposed SF-PPP method can provide coseismic deformation signals accurately. Compared to the results from GAMIT/TRACK, the accuracy of the proposed SF-PPP was not influenced by the common mode errors that exist in the GAMIT/TRACK solutions. (2) Vertical Total Electron Content (VTEC) anomalies before an earthquake are investigated by applying time-series analysis and spatial interpolation methods. Furthermore, on the long-term scale, it is revealed that significant positive/negative VTEC anomalies appeared around the earthquake epicenter on the day the earthquake occurred compared to about 4–5 days before the earthquake, whereas, on the short-term scale, positive/negative VTEC anomalies emerged several-hours before or after an earthquake.

Revisiting the 2003–18 Deep Ocean Warming through Multiplatform Analysis of the Global Energy Budget

Abstract Recent estimates of the global warming rates suggest that approximately 9% of Earth’s excess heat has been cumulated in the deep and abyssal oceans (below 2000-m depth) during the last two decades. Such estimates assume stationary trends deducted as long-term rates. To reassess the deep ocean warming and potentially shed light on its interannual variability, we formulate the balance between Earth’s energy imbalance (EEI), the steric sea level, and the ocean heat content (OHC), at yearly time scales during the 2003–18 period, as a variational problem. The solution is achieved through variational minimization, merging observational data from top-of-atmosphere EEI, inferred from Clouds and the Earth’s Radiant Energy System (CERES), steric sea level estimates from altimetry minus gravimetry, and upper-ocean heat content estimates from in situ platforms (mostly Argo floats). Global ocean reanalyses provide background-error covariances for the OHC analysis. The analysis indicates a 2000-m–bottom warming of 0.08 ± 0.04 W m−2 for the period 2003–18, equal to 13% of the total ocean warming (0.62 ± 0.08 W m−2), slightly larger than previous estimates but consistent within the error bars. The analysis provides a fully consistent optimized solution also for the steric sea level and EEI. Moreover, the simultaneous use of the different heat budget observing networks is able to decrease the analysis uncertainty with respect to the observational one, for all observation types and especially for the 0–700-m OHC and steric sea level (more than 12% reduction). The sensitivity of the analysis to the choice of the background time series proved insignificant. Significance Statement Several observing networks provide complementary information about the temporal evolution of the global energy budget. Here, satellite observations of Earth’s energy imbalance (EEI) and steric sea level and in situ–derived estimates of ocean heat content anomalies are combined in a variational analysis framework, with the goal of assessing the deep ocean warming. The optimized solution accounts for the uncertainty of the different observing networks. Furthermore, it provides fully consistent analyses of global ocean heat content, steric sea level, and EEI, which show smaller uncertainty than the original observed time series. The deep ocean (below 2000-m depth) exhibits a significant warming of 0.08 ± 0.04 W m−2 for the period 2003–18, equal to the 13% of the total ocean warming.

The Conjugated Ionospheric Anomalies Preceding the 2011 Tohoku-Oki Earthquake

We present the conjugated ionospheric total electron content (TEC) anomalies prior to the 2011 Mw9.0 Tohoku-oki earthquake, Japan, observed by the Global Navigation Satellite System (GNSS) stations in northern Australia. The onset time of the anomaly, determined by the Akaike’s information criterion, is 41.5 min before the earthquake in Australia, which is very close to the time observed in Japan. The positive TEC anomalies in Australia emerged on the same longitude as the land area of NE Japan. This supports the model that electric fields within the ionosphere redistributed the electrons immediately before large earthquakes. However, the observed anomaly is shifted equatorward by ∼500 km reflecting the difference in physical mechanisms between the two hemispheres. We also found that the geomagnetic declination near the conjugate point simultaneously started to change ∼40 min before the earthquake, but its physical implication is yet to be explored.