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The present work evaluates eleven existing empirical models to estimate Precipitable Water Vapor ( P W V ) over a high-altitude (4500 m amsl), cold-desert environment. These models are tested extensively and used globally to estimate P W V for low altitude sites (below 1000 m amsl). The moist parameters used in the model are: water vapor scale height ( H c ), dew point temperature ( T d ) and water vapor pressure ( E s 0 ). These moist parameters are derived from surface air temperature and relative humidity measured at high temporal resolution from automated weather station. The performance of these models are examined statistically with observed high-resolution GPS ( G P S P W V ) data over the region (2005–2012). The correlation coefficient (R) between the observed G P S P W V and Model P W V is 0.98 at daily data and varies diurnally from 0.93 to 0.97. Parameterization of moisture parameters were studied in-depth (i.e., 2 h to monthly time scales) using G P S P W V , T d , and E s 0 . The slope of the linear relationships between G P S P W V and T d varies from 0.073°C −1 to 0.106°C −1 (R: 0.83 to 0.97) while G P S P W V and E s 0 varied from 1.688 to 2.209 (R: 0.95 to 0.99) at daily, monthly and diurnal time scales. In addition, the moist parameters for the cold desert, high-altitude environment are examined in-depth at various time scales during 2005–2012. [ABSTRACT FROM AUTHOR]

Integrated precipitable water vapor (PWV) retrieved from Moderate Resolution Imaging Spectro-radiometer (MODIS) in near-infrared channels is examined with the PWV estimated from the Global Positioning System (GPS) data and measured surface temperature and pressure values over Hanle, located at a high-altitude (∼4500 m) trans-Himalayan region. Since the accuracy of MODIS derived PWV over the large elevated topography of the region is not well studied, the present work focus on the validation of MODIS PWV using the GPS data during 2005–2012. The study reveals that MODIS PWV compares well with the GPS PWV data with bias −0.018 cm, root mean square error (RMSE) 0.137 cm and coefficient of determination ( R 2 ) 0.91. The two types of data products are compared on short (daily) and long temporal (monthly-seasonal) scales in order to evaluate the seasonal dependence of PWV. The peak values of PWV from MODIS and GPS data at the site varied from 1.7 to 2.05 cm and 1.2 to 1.4 cm as the daily and the monthly means, respectively, which occurred during August. However, the seasonal peak of PWV occurred during summer as 0.88 and 0.97 cm for MODIS and GPS data, respectively. The present study noticed that about 85% of the total PWV estimated from MODIS as well as GPS data lies below 1.0 cm over the site. The seasonal study of PWV reveals that MODIS data is found to be underestimating the PWV when compared to GPS data with bias −0.095 cm and RMSE 0.215 cm particularly during summer. This is due to dry and high-altitude terrain of Hanle particularly during summer months. However, there are marginal differences (bias varied from 0.007 to 0.017 cm) during the remaining seasons and seasonally R 2 varies from 0.62 to 0.87. GPS PWV exhibits distinct diurnal cycle with minimum in morning as well as in night and peak in the late afternoon (16–18 h) irrespective of the seasons. However, the diurnal cycle is very prominent during summer than the rest of the seasons. [ABSTRACT FROM AUTHOR]

This study evaluates the impact of multi-GNSS (Global Navigation Satellite System) signals on the estimation of precise position with millimetre accuracy. Compared to standalone satellite systems like the Global Positioning System (GPS), multi-GNSS improves start-up time, performance, satellite visibility, accuracy, spatial geometry and reliability. However, on the flip side it increases the noise, signal interference, hardware complexity of the receiver, intersystem interference and computation complexity which may degrade its performance. Though GNSS is similar at fundamental levels, differences exist in signal structures, reference frames and timing standards. Compatibility and interoperability between the different constellations of the highest order is required to achieve the best results. At present, GPS and Glonass navigation systems are fully functional with global coverage and comparable precision. Glonass satellite constellation, signal structure is slightly different when compared to GPS, whereas major differences exist in the reference frame and epoch time. Combined GPS–Glonass solution significantly improves the accuracy in navigation applications with increased satellite signal observations and spatial distribution of visible satellites. For precise geodetic studies using static post-processing, combined solution may degrade the accuracy, if these differences are not handled carefully. Currently for geodetic studies, only GPS observations are majorly used worldwide. For the first time, daily precise position is estimated for continuous GNSS stations located in India using static postprocessing with standalone GPS, Glonass as well as combined GPS–Glonass to study the impact of multiGNSS signals for geodetic studies. [ABSTRACT FROM AUTHOR]