Improved predictions of equatorial TEC for real time applications

It is important to use models developed specifically for the equatorial ionospheric estimation for real-time applications, particularly in Satellite Navigation. This work demonstrates a methodology for improved predictions of VTEC in real time using the model developed for the equatorial ionosphere by the authors. This work has been done using TEC data of the low solar activity period of 2005 obtained using dual frequency GPS receivers installed under the GAGAN project of ISRO. For the purpose, the model is first used in conjunction with Kriging technique. Improvement in accuracy is observed when compared with the estimations from the model alone using the measurements as true reference. Further improvement is obtained by Bayesian combination of these estimates with independent Neural Network based predictions. Statistical performance of improvement is provided. An improvement of ∼1 m in confidence level of estimation of VTEC is obtained.     

Investigation of vertical profile of rain microstructure at Ahmedabad in Indian tropical region

The microstructure of rain has been studied with observations using a vertical looking Micro Rain Radar (MRR) at Ahmedabad (23.06°N, 72.62°E), a tropical location in the Indian region. The rain height, derived from the bright band signature of melting layer of radar reflectivity profile, is found to be variable between the heights 4600 m and 5200 m. The change in the nature of rain, classified on the basis of radar reflectivity, is also observed through the MRR. It has been found that there are three types of rain, namely, convective, mixed and stratiform rain, prevailing with different vertical rain microstructures, such as, Drop Size Distribution (DSD), mean drop size, rain rate, liquid water content and average fall speed of the drops at different heights. It is observed that the vertical DSD profile is more inhomogeneous for mixed and stratiform type rain than for convective type rain. It is also found that the large number of drops of size <0.5 mm is present in convective rain whereas in stratiform rain, drops concentration is appreciable up to 1 mm. A comparison of measurements taken by ground based Disdrometer and that from the 200 m level obtained from MRR shows good agreement for rain rate and DSD at smaller rain rate values. The results may be useful for understanding rain structures over this region.     

Prediction of ionospheric total electron content using adaptive neural network with in-situ learning algorithm

The Ionospheric Total Electron Content is responsible for the group delay of the signals from the Navigation satellites. This delay causes ranging error, which in turn degrades the accuracy of position estimated by the receivers. For critical applications, single frequency receivers resort to Satellite Based Augmentation Systems in order to have improved accuracy and integrity. The performance of these systems in terms of accuracy can be improved if predictions of the delays are available simultaneously with real measurements. This paper attempts to predict the Total Electron Content using adaptive recurrent Neural Network at three different locations of India. These locations are selected at the magnetic equator, at the equatorial anomaly crest and outside the anomaly range, respectively. In-situ Learning Algorithm has been used for tracking the non-stationary nature of the variation. Prediction is done for different prediction intervals. It is observed that, for each case, the mean and root mean square values of prediction errors remain small enough for all practical applications. Analysis of Variance is also done on the results.     

Estimation of equatorial electrojet from total electron content at geomagnetic equator using Kalman filter

The temporal variation of the equatorial electrojet is estimated utilising a suitably designed Kalman filter and using the established empirical relations between the anomaly component of equatorial TEC and the modified electrojet. TEC data obtained from dual frequency GPS receivers are used for the purpose. Estimation requires the a-priori knowledge of the peak electrojet value of the day and hence can be made in post temporal scenario only. Initial results obtained during a low solar activity time in an equinoctial month shows acceptable accuracy of the proposed algorithm. Limited analysis is done by segregating the results into temporal sessions of pre-attainment and post-attainment of the electrojet peak.     

Comparison of global chlorophyll concentrations using MODIS data

Chlorophyll concentrations derived from satellite borne ocean color sensors data provide an idea of the distribution of phytoplanktons across the oceans which help us in understanding the spatial and temporal dynamics of phytoplanktons. The changes in the patterns of distribution and abundance of the planktons have significant impact on the entire ecosystem and play a key role in the global carbon cycle. In this paper, we have analyzed annual and seasonal chlorophyll concentrations retrieved from MODIS data for the periods March 2000–October 2003, which reveal the spatial and seasonal distribution of chlorophyll concentrations across the global oceans. Chlorophyll concentrations anomaly indicate that chlorophyll concentrations in almost all ocean regions responded similarly.     

Energization of charged particle in a time-dependent chaotic magnetic field with an implication of the production of seed particles in solar energetic particle events

We investigate the acceleration of charged particles in a time-dependent chaotic magnetic field in this work. In earlier works, it has been demonstrated that in an asymmetric wire-loop current systems (WLCSs), the magnetic field is of chaotic in nature. Furthermore, observations also showed that there exist time-varying current loops and current filaments in solar corona. It is therefore natural to conceive that the magnetic field on the solar surface is chaotic and time-dependent. Here, we develop a numerical model to study the acceleration process of charged particles in a time-varying chaotic magnetic field that is generated by an ensemble of 8 WLCSs. We found that the motion of energetic particles in the system is of diffusive in nature and a power law spectrum can quickly develop. The mechanism examined here may serve as an efficient pre-acceleration mechanism that generates the so-called seed particles for diffusive shock acceleration at a coronal mass ejection (CME) driven shock in large solar energetic particle (SEP) events.