Modeling of local ionospheric time varying characteristics based on singular value decomposition over low-latitude GPS stations

Singular Value Decomposition (SVD) model is implemented to recognize the Total Electron Content (TEC) time series of daily, temporal as well as seasonal characteristics throughout the 24th solar cycle period of the year 2015 in the study. The Vertical (vTEC) analysis has been carried out with Global Positioning System (GPS) data sets collected from five stations from India namely GNT, Guntur (16.44^° N, 80.62^° E), and IISC, Bangalore (12.97^° N, 77.59^° E), LCK2, Lucknow (26.76^° N, 80.88^° E), one station from Thailand namely AITB, Bangkok (14.07^° N, 100.61^° E), and one station from South Andaman Island namely PBR, Port Blair (11.43^° N, 92.43^° E), located in low latitude region. The first five singular value modes constitute about 98% of the total variance, which are linearly transformed from the observed TEC data sets. So it is viable to decrease the number of modeling parameters. The Fourier Series Analysis (FSA) is carried out to characterize the solar-cycle, annual and semi-annual dependences through modulating the first three singular values by the solar (F10.7) and geomagnetic (Ap) indices. The positive correlation coefficient (0.75) of daily averaged GPS–TEC with daily averaged F10.7 strongly supports the temporal variations of the ionospheric features depends on the solar activity. Further, the significance and reliability of the SVD model is evaluated by comparing it with GPS–TEC data and the standard global model (Standard Plasma-Spherical Ionospheric Model, SPIM and International Reference Ionosphere, IRI 2016).     

Vegetation damage assessment due to Hudhud cyclone based on NDVI using Landsat-8 satellite imagery

Developing nations are abandoned against tropical cyclones because of climatic changeability; the atmosphere is probably going to expand the recurrence and extent of some outrageous climate and calamity occasions. Urban areas and towns arranged along the coastline front belt in Visakhapatnam region experienced serious harm because of Hudhud cyclone, which happened on October 12, 2014. The fundamental motivation behind this exploration was to distinguish the vegetation damage in Visakhapatnam and neighbouring towns. In this analysis, Landsat-8 satellite datasets procured prior and then afterward the cyclone have been utilized; image processing techniques have been completed to evaluate the progressions of pre- and post-disaster condition. Vegetation index strategy was utilized to assess the damage to vegetation. Arrangement results and land utilize land cover change investigation demonstrate that 13.25% of agriculture Kharif and 31.1% of vegetation was damaged. Normalized difference vegetation index (NDVI) maps were produced for the previously, then after the cyclone circumstance, and vegetation biomass damage was evaluated in Visakhapatnam and Bhimunipatanam. General loss of vegetation in both the spots was 30.67 and 43.37 km². The result of this review can be utilized by decision makers for the post-disaster support for rebuilding of influenced regions.     

Observed intra-seasonal to interannual variability of the upper ocean thermal structure in the southeastern Arabian Sea during 2002–2008

The southeastern Arabian Sea (SEAS), located in the Indian Ocean warm pool, is a key-region of the regional climate system. It is suspected to play an important role in the dynamics of the Asian summer monsoon system. The present study reports the salient features derived from a newly harvested observational dataset consisting of repeated fortnightly XBT transects in the SEAS over the period 2002–2008. The fortnightly resolution of such a multi-year record duration is unprecedented in this part of the world ocean and provides a unique opportunity to examine the observed variability of the near-surface thermal structure over a wide spectrum, from intra-seasonal to interannual timescales. We find that most of the variability is trapped in the thermocline, taking the form of upwelling and downwelling motions of the thermal stratification. The seasonal variations are consistent with past studies and confirm the role of the monsoonal wind forcing through linear baroclinic waves (coastally-trapped Kelvin and planetary Rossby waves). Sub-seasonal variability takes the form of anomalous events lasting a few weeks to a few months and occurs at two preferred timescales: in the 30–110 day band, within the frequency domain of the Madden–Julian oscillation and in the 120–180 day band. While this sub-seasonal variability appears fairly barotropic in the offshore region, the sign of the anomaly in the upper thermocline is opposite to that in its lower part on many occasions along the coast. Our dataset also reveals relatively large interannual temperature variations of about 1 °C from 50 to 200 m depth that reflect a considerable year-to-year variability of the magnitude of both upwelling and downwelling events. This study clearly demonstrates the necessity for sustained long-term temperature measurements in the SEAS.