The tropospheric delay is a serious error source for positioning using Global Navigation Satellite Systems (GNSS). Since the scientific applications of GNSS positioning such as crustal deformation studies and earthquakes prediction require high accuracy in positioning, analysis of tropospheric delay calculation is necessary to improve GNSS positioning accuracy.In this study data from ground based GNSS receivers are used to evaluate effect of the tropospheric delay in position determination accuracy. These data are also used to study the tropospheric delay characteristics. The collected GNSS data are for the year 2013, taken from 8 stations from Egypt Permanent GNSS Network (EPGN) and 13 IGS stations. The GNSS data were processed using advanced GNSS software called Bernese V 5.0.The results show that the RMS of the coordinates is better in case of making estimation for the troposphere ZWD and bad in case of ignoring the troposphere. Also there is a correlation between the troposphere and the height component. The troposphere ZWD values have daily, temporal and spatial variation, depending on time in the day, day in the year, geographic location of the station and how near it to water. The ZWD values also go upward from the start to the end of the year, and also it shows high correlation with the water vapor content in the troposphere.
Abstract. In the last decades, Global navigation satellite systems (GNSS) have provided an exceptional opportunity to retrieve atmospheric parameters globally through GNSS radio occultation (GNSS-RO). In this paper, data of 12 GNSS-RO missions from June 2001 to November 2020 with high resolution were used to investigate the possible widening of the tropical belt along with the probable drivers and impacts in both hemispheres. Applying both lapse rate tropopause (LRT) and cold point tropopause (CPT) definitions, the global tropopause height shows increase of approximately 36 m/decade and 60 m/decade, respectively. Moreover, the tropical edge latitude (TEL) estimated based on two tropopause height metrics, in the northern hemisphere (NH) and southern hemisphere (SH), are different from each other. For the first metric, subjective method, the tropical width from GNSS has expansion behavior in NH with ~ 0.41°/decade and a minor expansion in SH with ~ 0.08°/decade. In case of ECMWF Reanalysis v5 (ERA5) there is no significant contraction in both NH and SH. For Atmospheric Infrared Sounder (AIRS), there are expansion behavior in NH with ~ 0.34°/decade and strong contraction in SH with ~ −0.48°/decade. Using the second metric, objective method, the tropical width from GNSS has expansion in NH with ~ 0.13°/decade, and no significant expansion in SH. In case of ERA5, there is no significant signal in NH while SH has a minor contraction. AIRS has an expansion with ~ 0.13°/decade in NH, and strong contraction in SH with ~ −0.37°/decade. The variability of tropopause parameters (temperature and height) is maximum around the TEL locations at both hemispheres. The total column ozone (TCO) shows increasing rates globally, and the rate of increase at the SH is higher than that of the NH. There is a good agreement between the spatial and temporal patterns of TCO variability and the TEL location estimated from GNSS LRT height. Carbon dioxide (CO2), and Methane (CH4), the most important greenhouse gases (GHGs) and the main drivers of global warming, have a global increasing rate and the increasing rate of the NH is similar to that of the SH. The spatial pattern in the NH is located more pole ward than its equivalent at the SH. Both surface temperature and precipitation increase in time and have strong correlation with GNSS LRT height. Both show higher increasing rates at the NH, while the precipitation at the SH has slight decrease and the surface temperature increases. The surface temperature shows a spatial pattern with strong variability, which broadly agrees with the TEL locations. The spatial pattern of precipitation shows northward occurrence. In addition, Standardized Precipitation Evapotranspiration Index (SPEI) has no direct connection with the TEL behavior.
Abstract. In the last decades, several studies reported the tropics' expansion, but the rates of expansion are widely different. In this paper, data of 12 global navigation satellite systems radio occultation (GNSS-RO) missions from June 2001 to November 2020 with high resolution were used to investigate the possible widening of the tropical belt along with the probable drivers and impacts in both hemispheres. Applying both lapse rate tropopause (LRT) and cold point tropopause (CPT) definitions, the global tropopause height shows an increase of approximately 36 and 60 m per decade, respectively. The tropical edge latitudes (TELs) are estimated based on two tropopause height metrics, subjective and objective methods. Applying both metrics, the determined TELs using GNSS have expansive behavior in the Northern Hemisphere (NH), while in the Southern Hemisphere (SH) there are no significant trends. In the case of ECMWF Reanalysis v5 (ERA5) there are no considerable trends in both hemispheres. For the Atmospheric Infrared Sounder (AIRS), there is expansion in the NH and observed contraction in the SH. The variability of tropopause parameters (temperature and height) is maximum around the TEL locations in both hemispheres. Moreover, the spatial and temporal patterns of total column ozone (TCO) have good agreement with the TEL positions estimated using GNSS LRT height. Carbon dioxide (CO2) and methane (CH4), the most important greenhouse gases (GHGs) and the main drivers of global warming, have spatial modes in the NH that are located more poleward than that in the SH. Both surface temperature and precipitation have strong correlation with GNSS LRT height. The surface temperature spatial pattern broadly agrees with the GNSS TEL positions. In contrast, the standardized precipitation evapotranspiration index (SPEI) has no direct connection with the TEL behavior. The results illustrate that the tropics' widening rates are different from one dataset to another and from one metric to another. In addition, TEL behavior in the NH is different from that in the SH. Furthermore, the variability of meteorological parameters agrees with GNSS TEL results more than with that of other datasets.
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