GPS data reveal that the Brahmaputra Valley has broken from the Indian Plate and rotates clockwise relative to India about a point a few hundred kilometers west of the Shillong Plateau. The GPS velocity vectors define two distinct blocks separated by the Kopili fault upon which 2-3 mm/yr of dextral slip is observed: the Shillong block between longitudes 89 and 93°E rotating clockwise at 1.15°/Myr and the Assam block from 93.5°E to 97°E rotating at ≈1.13°/Myr. These two blocks are more than 120 km wide in a north-south sense, but they extend locally a similar distance beneath the Himalaya and Tibet. A result of these rotations is that convergence across the Himalaya east of Sikkim decreases in velocity eastward from 18 to ≈12 mm/yr and convergence between the Shillong Plateau and Bangladesh across the Dauki fault increases from 3 mm/yr in the west to >8 mm/yr in the east. This fast convergence rate is inconsistent with inferred geological uplift rates on the plateau (if a 45°N dip is assumed for the Dauki fault) unless clockwise rotation of the Shillong block has increased substantially in the past 4-8 Myr. Such acceleration is consistent with the reported recent slowing in the convergence rate across the Bhutan Himalaya. The current slip potential near Bhutan, based on present-day convergence rates and assuming no great earthquake since 1713 A.D., is now~5.4 m, similar to the slip reported from alluvial terraces that offsets across the Main Himalayan Thrust and sufficient to sustain a M w ≥ 8.0 earthquake in this area.

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Total electron content (TEC) data, obtained from satellites, are used in the search for imprints for identifying the probability factor of an impending earthquake. Extraction of earthquake induced signature is done mainly from day-to-day variations in TEC peak (TEC peak. ). The use of a single parameter such as TEC peak is not always enough to formulate such a pointer. The paper therefore focuses on the need to introduce other markers such as the shape of TEC profile and to utilize any modification in the profile shape caused by an impending earthquake to identify precursors. An automatic pattern matching approach for processing global positioning system (GPS) generated TEC records is introduced to achieve this aim and TEC profiles are passed through a template framed from the time series of quiet day data. The Dynamic Time Warping (DTW) algorithm is adopted to look for deviations in the entire TEC profile of days prior to the earthquake with respect to the template. Variation, if any, would be used as an index of earthquake induced signature. A few case studies using this algorithm are presented in the paper. Work is based on TEC data collected from the GPS receiver at Guwahati (268 10 0 N, 918 45 0 E), an equatorial anomaly crest station.

Total Electron Content (TEC) data from GPS are now used as tools for identifying an impending earthquake. The extraction of earthquake induced features from this parameter needs elaborate processing because it involves filtration of data with respect to disturbed day variations, contribution from multi path effects and also normal day-to-day fluctuations even during quiet days. In this paper we introduce, a peak detection algorithm, an automatic pattern matching approach and artificial neural network for processing GPS generated TEC record in where a template is framed from the time series of quiet day data for extraction of pre -seismic parameter. This matching algorithm is adopted to find deviation in TEC time series prior to an impending earthquake from the template and would be used as an index of earthquake induced signature. A few case studies using these techniques are presented in this paper. Work is based on TEC data collected from GPS at Gauhati (26º 10' N, 91º 45' E).

The Varsha, a spectral hydrostatic general circulation model, is run regularly at an eight-processor Flosolver machine at Gauhati University (26 10 0 N, 91 45 0 E), with the aims to predicting track of cyclones generated in the Bay of Bengal and forecasting precipitation occurrence and intensity over the north-eastern part (NE) of India, induced by such events. The initial conditions of the model are prepared from FNL dataset of National Centre for Environmental Prediction (NCEP), available at 1 Â1 resolutions. The predicted tracks of a few cyclonic events as SIDR (Nov, 2007), Aila (May, 2009) and Laila (May, 2010) are presented along with their contribution to precipitation in the NE. Each prediction, when assessed through observations obtained from satellite-based measurements of Tropical Rainfall Measuring Mission (TRMM) and National Oceanic and Atmospheric Administration (NOAA), and also from India Meteorological Department (IMD), shows that the model-generated zonal wind is a good precursor parameter in track determination of a cyclone. The reliability of the model-projected precipitation features over the NE, contributed by such storms, is also highlighted.

Northeast India and its adjoining region constitutes an important geotectonic element of Southeast

The earthquake precursory phenomena detection using ionospheric perturbation characteristics is a new technique used by the scientist now days. This paper focuses a new technique for detecting any modification in the time series profile shape caused by an impending earthquake to identify precursors as well as an image processing technique for epicenter detection. For this purpose IGS Global Navigation Satellite System (GNSS) Total Electron Content Data (TEC) are utilized from different stations across the world. From the experiment it is observed that the method may detect earthquake precursors a few hours or days prior to the main event due to ionospheric perturbations induced by initiation of earthquake process.