Abstract

Global navigation satellite systems (GNSSs) have become an important tool for remotely sensing water vapor in the atmosphere. In GNSS data processing, mapping functions and gradient models are needed to map the zenith tropospheric delay (ZTD) to the slant total tropospheric delay (STD) along a signal path. Therefore, it is essential to investigate the spatial–temporal performance of various mapping functions and gradient models in the determination of STD. In this study, the STDs at nine elevations were first calculated by applying the ray-tracing method to the atmospheric European Reanalysis-Interim (ERA—Interim) dataset. These STDs were then used as the reference to study the accuracy of the STDs that determined the ZTD together with mapping functions and gradient models. The performance of three mapping functions (i.e., Niell mapping function (NMF), global mapping function (GMF), and Vienna mapping function (VMF1)) and three gradient models (i.e., Chen, MacMillan, and Meindl) in six regions (the temperate zone, Qinghai–Tibet Plateau, Equator, Sahara Desert, Amazon Rainforest, and North Pole) in determining slant tropospheric delay was investigated in this study. The results indicate that the three mapping functions have relatively similar performance above a 15° elevation, but below a 15° elevation, VMF1 clearly performed better than the GMF and NMF. The results also show that, if no gradient model is included, the root-mean-square (RMS) of the STD is smaller than 2 mm above the 30° elevation and smaller than 9 mm above the 15° elevation but shows a significant increase below the 15° elevation. For example, in the temperate zone, the RMS increases from approximately 35 mm at the 10° elevation to approximately 160 mm at the 3° elevation. The inclusion of gradient models can significantly improve the accuracy of STDs by 50%. All three gradient models performed similarly at all elevations and in all regions. The bending effect was also investigated, and the results indicate that the tropospheric delay caused by the bending effect is normally below 13 mm above a 15° elevation, but this delay increases dramatically from approximately 40 mm at a 10° elevation to approximately 200 mm at a 5° elevation, and even reaches 500–700 mm at a 3° elevation in most studied regions.

Highlights

  • Global navigation satellite systems (GNSSs) have become an important tool for remotely sensing water vapor in the atmosphere

  • Previous studies have shown that the GNSS-derived zenith tropospheric delay (ZTD), zenith wet delay (ZWD), and precipitable water vapor (PWV) [5,6] have a very high accuracy [7,8,9,10,11], as well as and the ability to capture the evolution of severe weather [12,13,14] and climate change [4,12,15,16,17,18], or can be used in operational weather forecasting by assimilating these variables into a numerical weather prediction (NWP) model [19,20]

  • The accuracy of GNSS-derived slant total tropospheric delay (STD) is closely related to the adopted mapping functions and gradient models

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Summary

Introduction

Global navigation satellite systems (GNSSs) have become an important tool for remotely sensing water vapor in the atmosphere. Previous studies have shown that the GNSS-derived ZTD (the propagation delay of GNSS signal owing to the total effect of water vapor and dry air at the zenith), ZWD, and PWV [5,6] have a very high accuracy [7,8,9,10,11], as well as and the ability to capture the evolution of severe weather [12,13,14] and climate change [4,12,15,16,17,18], or can be used in operational weather forecasting by assimilating these variables into a numerical weather prediction (NWP) model [19,20]. ZWD and PWV are integrated values over a GNSS station and do not provide any information on the vertical distribution of water vapor, which means that severe weather evolution is not always captured by only monitoring ZWD or PWV [21]

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