Position estimation of the target is essential in all fields- agriculture, forestry, defense, aviation, remote sensing, communication, maritime and shipping, navigation, railways, road transport and safety, urban planning and development, land survey, and climate study, etc. While the accurate position is the most important aspect of remote sensing, the attainment of it is a challenge. In navigation systems, the error in position estimation occurs due to various factors, viz. the presence of electrons in the ionosphere, the satellite and receiver clock offset, multipath effect, the non-uniform refractive index of the troposphere, the error due to PRN code noise and noise within the receiver, and errors in the ephemeris data, to name a few. In this paper, the authors have attempted to give an account of precision of position estimation by the Indian Regional Navigation Satellite System (IRNSS), by estimating the total slant delay caused to the satellite signal. The total slant delay (TSD) in the troposphere is caused due to the change in refractive index in the troposphere. The non-uniform refractive index is caused due to variation in temperature, pressure, and water vapor present in the troposphere. The non-uniform refractive index causes the refraction of the signal causing bending and slowing. The paper presents the diurnal, daily, and monthly variations of total slant delay (TSD) over a few tropical locations in India, namely Bhubaneswar (20.14°N, 85.67°E), Gandaki (13.45°N, 79.16°E), Goa (15.45°N, 73.81°E), Kanakapura (12.54°N, 77.429°E), and Kolkata (22.53°N, 88.33°E). In an attempt to find out the factors that govern the TSD, in this paper, the authors have analyzed a few meteorological elements, viz. the surface pressure (SP), surface temperature (ST), relative humidity (RH), and integrated precipitable water (IPWV). They have also studied the dependence of TSD on the total solar irradiance (TSI). The study reveals that the TSD follows the solar cycle. Besides, the study further shows the relationship between the TSD and the meteorological elements mentioned above. The investigation shows that the total slant delay (TSD) retrieved from the different satellites in the IRNSS constellation is different. Thus, for accurate position estimation of the target, it is necessary to take an average of TSD estimated by all the satellites. The diurnal variation of TSD shows that in a month, every day its crests occur at regular intervals. The troughs of TSD also recur after a fixed interval. The periodicity of the crests and troughs is uniform throughout a particular month, i.e. the crests occur exactly at the same time every day at regular intervals; so also the troughs. This observation led the authors to investigate the solar cycle. The study reveals that both TSD and total solar irradiance replicates each other. The study also indicates that total slant delay decreases as the elevation of the satellite w.r.t. the Earth’s station increases.
Rainfall dynamics has been being one of the least understood topics and has been affecting human civilization since time immemorial. Because of its all-pervading effect on all aspects of the society, starting from the day-to-day living of mankind to agriculture, industry, aviation, weather monitoring, and weather forecast, etc., probably it stands out to be the most significant factor that needs attention. Moreover, change in rainfall pattern all over the world necessitates an investigation of this parameter in-depth. The tropics play an essential role in regulating the atmospheric heat engine. So, the cloud characteristics in this region demand careful attention and understanding. In this paper the authors have investigated rainfall and upper air meteorological elements, viz. the cloud liquid water (CLW), the precipitation water (PW) and the latent heat (LH) derived from the data product 2A12 of the Tropical Microwave Imager (TMI) onboard the Tropical Rainfall Measuring Mission (TRMM) satellite over four tropical locations in India, namely Bangalore (12.97N, 77.59E), Bhubaneswar (20.29N, 85.82E), Calcutta (22.57N, 88.36E), and Gadanki (13.45N, 9.16E). The study shows that the rainfall can be predicted with excellent accuracy based on the cloud liquid water (CLW), the precipitation water (PW), and the latent heat (LH). It is further found out from the investigation that though all these parameters can predict rainfall independently, all the elements put together can predict rainfall with greater accuracy. The paper presents functional relationships between rainfall and these parameters. These relationships can be used for quantitative estimation of rainfall in the data-sparse region. The article also highlights the vertical profile of these parameters starting from the Earth's surface up to 18 km above. The article describes the characterization technique for convective/stratiform dominance on surface rainfall.