Time filter

Source Type

Sathishkumar S.,Indian Institute of Geomagnetism | Sridharan S.,National Atmospheric Research Laboratory
Journal of Geophysical Research: Space Physics | Year: 2013

Mesospheric wind observations by the medium frequency radar and geomagnetic field observations at Tirunelveli (8.7°N, 77.8°E, 1.75°N dip angle) are used to study the relative importance of solar and lunar influences in the variabilities of mesospheric tides and equatorial electrojet (EEJ) strength during the unprecedented major stratospheric sudden warming (SSW) of 2009. It is observed that the afternoon reversal in the EEJ, popularly known as counter electrojet, occurs consecutively for several days during the SSW event, when there is an enhancement of solar semidiurnal tide in both zonal wind at 90 km and EEJ strength over Tirunelveli. Although the amplitude of lunar tides also shows enhancement, it is much less than that of solar. The diurnal tidal amplitude in zonal wind and EEJ strength also shows large enhancement just before the onset of SSW. However, solar semidiurnal tide dominates diurnal tide during the SSW. The diurnal tidal phase in zonal wind shifts to a few hours earlier during the SSW. The lunar semidiurnal tidal phase shifts to later hours in both zonal wind and EEJ strength. The main observation of the present study is that the large semidiurnal tide observed during the SSW 2009 is mostly solar driven and only partly lunar driven, although tidal planetary wave interaction also may play a vital role. Although a similar behavior is noticed during the SSW 2006 also, the large lunar semidiurnal tide observed in the EEJ strength without having large lunar semidiurnal tide in the underlying mesospheric winds needs further investigation. © 2012. American Geophysical Union. All Rights Reserved.

Maiti S.,Indian Institute of Geomagnetism | Tiwari R.K.,National Geophysical Research Institute
Geophysics | Year: 2010

The precise classification of changes in rock boundaries/facies from well-log records is a complex problem in geophysical data processing. Observed well-log data are a complex superposition of nonstationary/nonlinear signals of varying wavelengths and frequencies, shaped by the heterogeneous composition and structural variation of rock types in the earth. This impairs our ability to use traditional statistical techniques, which in most cases fail to discriminate and/or, at best, do not precisely extract facies changes from complex well-log signals. We propose a new method, set in a Bayesian neural network (BNN) framework and using a powerful hybrid Monte Carlo simulation scheme to identify facies changes from complex well-log data. We first construct a complex, composite, synthetic time series using the data from three simple models: first-order autoregressive, logistic, and random white noise. Then we attempt to identify individualsignals in the pooled synthetic time series. We use the autocorrelation and the spectral characteristics of the individual signals as input vectors for training, validating, and testing the artificial neural network model. The results show that the Bayesian separation scheme provides consistently good results, with accuracy at more than 74%. When the method was tested using well-log data from the German Continental Deep Drilling Program (KTB), it was able to discriminate boundaries of lithofacies with an accuracy of approximately 92% in validation and 93% in test samples. The efficacy of the BNN in the presence of colored noise suggests that the designed network topology is robust for up to 30% correlated noise; however, adding more noise (say, 50% or more) obscures the desired signals. Our method provides a robust means for decoding finely detailed successions of lithofacies from complex well-log data, better describing the nature of the underlying inhomogeneous crust. © 2010 Society of Exploration Geophysicists.

Maiti S.,Indian Institute of Geomagnetism | Tiwari R.K.,CSIR - Central Electrochemical Research Institute
Journal of Geophysical Research: Solid Earth | Year: 2010

A new probabilistic approach based on the concept of Bayesian neural network (BNN) learning theory is proposed for decoding litho-facies boundaries from well-log data. We show that how a multi-layer-perceptron neural network model can be employed in Bayesian framework to classify changes in litho-log successions. The method is then applied to the German Continental Deep Drilling Program (KTB) well-log data for classification and uncertainty estimation in the litho-facies boundaries. In this framework, a posteriori distribution of network parameter is estimated via the principle of Bayesian probabilistic theory, and an objective function is minimized following the scaled conjugate gradient optimization scheme. For the model development, we inflict a suitable criterion, which provides probabilistic information by emulating different combinations of synthetic data. Uncertainty in the relationship between the data and the model space is appropriately taken care by assuming a Gaussian a priori distribution of networks parameters (e.g., synaptic weights and biases). Prior to applying the new method to the real KTB data, we tested the proposed method on synthetic examples to examine the sensitivity of neural network hyperparameters in prediction. Within this framework, we examine stability and efficiency of this new probabilistic approach using different kinds of synthetic data assorted with different level of correlated noise. Our data analysis suggests that the designed network topology based on the Bayesian paradigm is steady up to nearly 40% correlated noise; however, adding more noise (∼50% or more) degrades the results. We perform uncertainty analyses on training, validation, and test data sets with and devoid of intrinsic noise by making the Gaussian approximation of the a posteriori distribution about the peak model. We present a standard deviation error-map at the network output corresponding to the three types of the litho-facies present over the entire litho-section of the KTB. The comparisons of maximum a posteriori geological sections constructed here, based on the maximum a posteriori probability distribution, with the available geological information and the existing geophysical findings suggest that the BNN results reveal some additional finer details in the KTB borehole data at certain depths, which appears to be of some geological significance. We also demonstrate that the proposed BNN approach is superior to the conventional artificial neural network in terms of both avoiding "over-fitting" and aiding uncertainty estimation, which are vital for meaningful interpretation of geophysical records. Our analyses demonstrate that the BNN-based approach renders a robust means for the classification of complex changes in the litho-facies successions and thus could provide a useful guide for understanding the crustal inhomogeneity and the structural discontinuity in many other tectonically complex regions. Copyright 2010 by the American Geophysical Union.

Reddy C.D.,Indian Institute of Geomagnetism
Geodesy and Geodynamics | Year: 2016

The lithosphere and the atmosphere/ionosphere, continuously exchange energy through various coupling mechanisms. Earthquake creates waves of energy, e.g. direct shock acoustic waves (SAWs) and Rayleigh wave induced acoustic waves (RAWs). In the event of an earthquake occurring beneath the sea, atmospheric gravity waves (AGWs) are also generated. If the earthquake is large enough (Mw > 6), SAWs, RAWs and AGWs induce detectable ionospheric plasma perturbations. Inferring the seismological information from these seismo-ionospheric manifestations is the subject that pertains to ionospheric seismology. Both ground and satellite based advanced radio techniques are being used in monitoring ionospheric plasma perturbations. In this study, seismo-ionospheric anomalies and implications from recent GNSS observations in India and South-East Asia are discussed, mainly pertaining to the following. (1) From the ionospheric plasma response to 2015 Nepal earthquake, the estimated group velocity for Andaman and Indian shield regions are 2100 ms-1 and 3900 ms-1 respectively and validated from ground measurements. (2) Atmospheric acoustic resonance at 4.0 mHz and a train of wave packet of TEC variation resulting from the beat phenomenon observed at the site 'umlh' and (3) GNSS-based tsunami warning which is going to be promising tool in augmenting the existing tsunami warning systems. © 2016 Institute of Seismology, China Earthquake Administration.

Sripathi S.,Indian Institute of Geomagnetism
Indian Journal of Radio and Space Physics | Year: 2012

In the present paper, for the first time, an attempt has been made to study the seasonal, altitudinal, diurnal and latitudinal variation of low latitude electron density obtained using COSMIC radiooccultation (RO) measurements over Indian longitudes during the deep solar minimum year 2008. The seasonal variation shows enhanced electron densities at vernal and autumn equinoxes compared to winter and summer seasons. The observations also suggest a shift in the time and altitude at which the peak of the electron density occurs in different seasons. An important finding is that there exists an equinoctial asymmetry in the electron density with respect to altitude and latitude, where the electron density is higher at vernal equinox compared to autumn equinox. The latitudinal and seasonal variationof peak electron density (NmF2) during 10:00-14:00 hrs LT indicate enhanced equatorial ionization anomaly (EIA) on either side of the magnetic equator at both vernal and autumn equinoxes compared to theother seasons. Seasonal variation of equatorial electrojet (EEJ) strength obtained from geomagnetic H-field variations also shows strong EEJ at vernal and autumn equinoxes indicating that EEJ strength indeed partly controls the EIA development. Further, the results indicate that NmF2 over the northern EIA crest region is correlated well with solar flux.

Tsurutani B.T.,Jet Propulsion Laboratory | Lakhina G.S.,Indian Institute of Geomagnetism
Geophysical Research Letters | Year: 2014

A "perfect" interplanetary coronal mass ejection could create a magnetic storm with intensity up to the saturation limit (Dst ∼ -2500 nT), a value greater than the Carrington storm. Many of the other space weather effects will not be limited by saturation effects, however. The interplanetary shock would arrive at Earth within ∼12 h with a magnetosonic Mach number ∼45. The shock impingement onto the magnetosphere will create a sudden impulse of ∼234 nT, the magnetic pulse duration in the magnetosphere will be ∼22 s with a dB/dt of ∼30 nT s-1, and the magnetospheric electric field associated with the dB/dt ∼1.9 V m-1, creating a new relativistic electron radiation belt. The magnetopause location of 4 R E from the Earth's surface will allow expose of orbiting satellites to extreme levels of flare and ICME shock-accelerated particle radiation. The results of our calculations are compared with current observational records. Comments are made concerning further data analysis and numerical modeling needed for the field of space weather. ©2014. American Geophysical Union. All Rights Reserved.

Sripathi S.,Indian Institute of Geomagnetism | Bhattacharyya A.,Indian Institute of Geomagnetism
Journal of Geophysical Research: Space Physics | Year: 2012

This paper describes the quiet time variabilities of the ionospheric total electron content (TEC) derived from the signals from Global Positioning Satellite System (GPS) recorded at several stations in India along with simultaneous observations of equatorial electrojet (EEJ) strength obtained from geomagnetic field variations during January-March 2006 when sudden stratospheric warming (SSW) events occurred. Analysis of the observations presented here confirms that strong correlation exists among the variabilities in EEJ strength and GPS TEC observations. Investigations suggest that there exist large-scale wave like structures with periodicity of quasi 16-day wave in the TEC observations near the equatorial ionization anomaly (EIA) crest quite similar to that of EEJ strength. Our observations also indicate the existence of morning enhancement and evening reduction of TEC and EEJ strength and vice versa during SSW events similar to that reported elsewhere. Using these observations, it is suggested that the quiet time variabilities seen in the GPS TEC over EIA could be caused due to the nonlinear interaction of upward propagating planetary waves (PWs) with atmospheric tides. Presence of similar periods in the EEJ strength and TEC observations near the EIA crest region, supports the view that the large-scale wave like structures seen in TEC near the EIA crest are associated with PWs that are modifying the primary eastward electric field in the equatorial E region and hence the EEJ strength through non linear interactions with atmospheric tides. Copyright 2012 by the American Geophysical Union.

Tsurutani B.T.,Jet Propulsion Laboratory | Lakhina G.S.,Indian Institute of Geomagnetism | Verkhoglyadova O.P.,Jet Propulsion Laboratory
Journal of Geophysical Research: Space Physics | Year: 2013

The fundamental features of ∼0.1-0.2 s duration ∼0.5 s spaced ionospheric electron precipitation "microbursts," ∼5 to 15 s microburst "trains," and 5-15 s electron precipitation pulsations are reviewed in light of similar temporal structures of electromagnetic whistler mode "chorus" waves detected in the outer magnetosphere. Past observations of microbursts point to extremely rapid (ms timescale) wave-particle interactions, probably between lower band chorus subelements (durations of ∼10 to 100 ms) and energetic ∼10 to 100 keV electrons. A recent theory explaining such rapid interaction rates observed in microbursts is briefly reviewed. Arguments are given why ∼5-15 s X-ray (and optical) pulsations are also associated with chorus scattering of energetic electrons. Comments about relativistic (E > 1 MeV) microbursts are also provided. There are, however, many other unsolved problems of outer zone energetic electron precipitation. The authors will attempt to indicate several of these for the interested reader. Finally, an appendix is provided for a brief review of two-frequency chorus and some current problems with that topic. ©2013. American Geophysical Union. All Rights Reserved.

Reddy C.D.,Indian Institute of Geomagnetism | Seemala G.K.,Indian Institute of Geomagnetism
Journal of Geophysical Research A: Space Physics | Year: 2015

The coseismic-induced ionospheric total electron content (TEC) perturbations were analyzed following the Mw 7.8 Nepal earthquake (28.147°N, 84.708°E; depth ∼15 km) that occurred on 25 April 2015 at 06:11:26 UTC. The ionospheric response is due to both the modes, i.e.; shock acoustic waves (slow mode) and Rayleigh wave induced (fast mode). The continuous Global Positioning System (GPS) data at about 60 sites from various GPS networks have been used in the present study. All the sites within epicentral distance of ∼2400 km and 70°-170° azimuth recorded the Rayleigh wave-induced TEC response, while the sites within ∼400-2200 km in the same azimuth recorded the response from both the modes. The maximum coseismic-induced peak-to-peak TEC amplitude is ∼1.2 total electron content unit, 1 TECU = 1016 el m-2. From Hodochron plot, the apparent Rayleigh wave velocity has been determined as ∼2400 m/s on the average and the acoustic wave velocity as 1180 m/s, both these waves being discernible beyond ∼1200 km of epicentral distance as also evident from Hodochron plot and wavelet spectrographs. We reckoned the Rayleigh wave group velocities using ionospheric response at selected radial pairs of stations and validated. The ionospheric response distribution seen mainly depending on the epicentral distance, satellite geometry, directivity of radiation pattern, and the upper crustal heterogeneity. This study highlights the characteristics of ionospheric response consequent to the 2015 Nepal earthquake. Key Points Lithosphere-atmosphere-ionosphere coupling Characteristics of ionospheric response of Nepal earthquake Imaging the Rayleigh wave propagation from ionospheric response induced by Nepal earthquake ©2015. American Geophysical Union. All Rights Reserved.

Kakad B.,Indian Institute of Geomagnetism
Solar Physics | Year: 2011

The purpose of the present study is to develop an empirical model based on precursors in the preceding solar cycle that can be used to forecast the peak sunspot number and ascent time of the next solar cycle. Statistical parameters are derived for each solar cycle using "Monthly" and "Monthly smoothed" (SSN) data of international sunspot number (Ri). Primarily the variability in monthly sunspot number during different phases of the solar cycle is considered along with other statistical parameters that are computed using solar cycle characteristics, like ascent time, peak sunspot number and the length of the solar cycle. Using these statistical parameters, two mathematical formulae are developed to compute the quantities [QC]n and [L]n for each nth solar cycle. It is found that the peak sunspot number and ascent time of the n+1th solar cycle correlates well with the parameters [QC]n and [L]n/[SMax]n+1 and gives a correlation coefficient of 0. 97 and 0. 92, respectively. Empirical relations are obtained using least square fitting, which relates [SMax]n+1 with [QC]n and [Ta]n+1 with [L]n/[SMax]n+1. These relations predict a peak of 74±10 in monthly smoothed sunspot number and an ascent time of 4. 9±0. 4 years for Solar Cycle 24, when November 2008 is considered as the start time for this cycle. Three different methods, which are commonly used to define solar cycle characteristics are used and mathematical relations developed for forecasting peak sunspot number and ascent time of the upcoming solar cycle, are examined separately. © 2011 Springer Science+Business Media B.V.

Loading Indian Institute of Geomagnetism collaborators
Loading Indian Institute of Geomagnetism collaborators