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(3) The global average root mean square of the north gradient and east gradient estimated by GPT3 is 0.77 mm and 0.73 mm, respectively, which are strongly correlated with each other, with values increasing from the equator to lower latitudes and decreasing from lower to higher la...

Assessment of Empirical Troposphere Model GPT3 Based on NGL's Global Troposphere Products.

SENSORS, no. 13 (2020): 3631

Cited by: 0|Views132
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Abstract

Tropospheric delay is one of the major error sources in GNSS (Global Navigation Satellite Systems) positioning. Over the years, many approaches have been devised which aim at accurately modeling tropospheric delays, so-called troposphere models. Using the troposphere data of over 16,000 global stations in the last 10 years, as calculated ...More

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Introduction
  • The Global Navigation Satellite Systems (GNSS) signals are delayed and bent as they pass through the atmosphere, and the positioning error due to this is defined as atmospheric delay.
  • The tropospheric delay can be divided into hydrostatic delay (HD) and wet delay (WD) [1,2].
  • The hydrostatic delay accounts for 90% of the total tropospheric delay and can be accurately estimated by the model with a calculation accuracy of up to millimeters [3].
  • The wet delay is the main limiting factor of the tropospheric delay modeling accuracy, which is often involved in calculations as unknown parameters in precision positioning
Highlights
  • The Global Navigation Satellite Systems (GNSS) signals are delayed and bent as they pass through the atmosphere, and the positioning error due to this is defined as atmospheric delay
  • (3) The global average root mean square (RMS) of the north gradient and east gradient estimated by GPT3 is 0.77 mm and 0.73 mm, respectively, which are strongly correlated with each other, with values increasing from the equator to lower latitudes and decreasing from lower to higher latitudes
  • The information expressed in Figure 4 can be synthesized into the following: (1) the RMS values of zenith total delay (ZTD) calculated using GPT3 is not significantly correlated with the longitude of the station site; the overall positive and negative BIAS values are independent of longitude, but there are small positive BIAS aggregations in the 0 to 30 degrees west longitude region
  • We describe the development of Global Pressure and Temperature (GPT) series models and the Nevada Geodetic Laboratory (NGL) troposphere products with more than 10,000 stations worldwide over a 20-year span and, the NGL troposphere products are evaluated using IGS troposphere products as true values, and the results show that NGL products have the same accuracy as IGS
  • The accuracy of the three parameters calculated using the GPT3 model was evaluated and analyzed in a total of four dimensions in time and space, and the following conclusions have been drawn: (1) The global average BIAS of ZTD, Grad.N, and Grad.E calculated by GPT3 is −0.99 cm, −0.029 mm, −0.016 mm, respectively, and the global average RMS is 4.41 cm, 0.77 mm, 0.73 mm, respectively
  • (3) The RMS of ZTD, Grad.N, and Grad.E are negatively correlated with the ellipsoidal height and latitude while not significantly correlated with longitude
Methods
  • This study focuses on the assessment of the GPT3 model using America Nevada Geodetic Laboratory (NGL) troposphere products, to begin with, the authors provide a brief background on the materials and assessment methods used.
  • The empirical model GPT, which is based on spherical harmonics up to degree and order nine, uses the monthly average grid data ERA40 of 40 years of global temperature and pressure with a spatial resolution of 15◦ × 15◦ provided by ECMWF, provides pressure and temperature at any site in the vicinity of the Earth’s surface [11].
  • The north gradient and east gradient were added to the output parameters of GPT3 [14,19]
Results
  • The information expressed in Figure 4 can be synthesized into the following: (1) the RMS values of ZTD calculated using GPT3 is not significantly correlated with the longitude of the station site; the overall positive and negative BIAS values are independent of longitude, but there are small positive BIAS aggregations in the 0 to 30 degrees west longitude region.
  • (3) The RMS of ZTD, Grad.N, and Grad.E are negatively correlated with the ellipsoidal height and latitude while not significantly correlated with longitude
Conclusion
  • The authors describe the development of GPT series models and the NGL troposphere products with more than 10,000 stations worldwide over a 20-year span and, the NGL troposphere products are evaluated using IGS troposphere products as true values, and the results show that NGL products have the same accuracy as IGS.
  • (2) The BIAS of ZTD, Grad.N, and Grad.E and the RMS of ZTD all show obvious seasonal variations, with the BIAS of ZTD in the opposite phase of the northern and southern hemispheres.
  • There is a strong correlation between the RMS of Grad.N and Grad.E
Summary
  • Introduction:

    The Global Navigation Satellite Systems (GNSS) signals are delayed and bent as they pass through the atmosphere, and the positioning error due to this is defined as atmospheric delay.
  • The tropospheric delay can be divided into hydrostatic delay (HD) and wet delay (WD) [1,2].
  • The hydrostatic delay accounts for 90% of the total tropospheric delay and can be accurately estimated by the model with a calculation accuracy of up to millimeters [3].
  • The wet delay is the main limiting factor of the tropospheric delay modeling accuracy, which is often involved in calculations as unknown parameters in precision positioning
  • Methods:

    This study focuses on the assessment of the GPT3 model using America Nevada Geodetic Laboratory (NGL) troposphere products, to begin with, the authors provide a brief background on the materials and assessment methods used.
  • The empirical model GPT, which is based on spherical harmonics up to degree and order nine, uses the monthly average grid data ERA40 of 40 years of global temperature and pressure with a spatial resolution of 15◦ × 15◦ provided by ECMWF, provides pressure and temperature at any site in the vicinity of the Earth’s surface [11].
  • The north gradient and east gradient were added to the output parameters of GPT3 [14,19]
  • Results:

    The information expressed in Figure 4 can be synthesized into the following: (1) the RMS values of ZTD calculated using GPT3 is not significantly correlated with the longitude of the station site; the overall positive and negative BIAS values are independent of longitude, but there are small positive BIAS aggregations in the 0 to 30 degrees west longitude region.
  • (3) The RMS of ZTD, Grad.N, and Grad.E are negatively correlated with the ellipsoidal height and latitude while not significantly correlated with longitude
  • Conclusion:

    The authors describe the development of GPT series models and the NGL troposphere products with more than 10,000 stations worldwide over a 20-year span and, the NGL troposphere products are evaluated using IGS troposphere products as true values, and the results show that NGL products have the same accuracy as IGS.
  • (2) The BIAS of ZTD, Grad.N, and Grad.E and the RMS of ZTD all show obvious seasonal variations, with the BIAS of ZTD in the opposite phase of the northern and southern hemispheres.
  • There is a strong correlation between the RMS of Grad.N and Grad.E
Tables
  • Table1: Correlation coefficient
Download tables as Excel
Funding
  • This research is supported by the National Natural Science Foundation of China (No.11673050); the Key Program of Special Development funds of Zhangjiang National Innovation Demonstration Zone (Grant No ZJ2018-ZD-009); National Key R&D Program of China (No 2018YFB0504300); and the Key R&D Program of Guangdong province (No 2018B030325001).
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Author
Junsheng Ding
Junsheng Ding
Junping Chen
Junping Chen
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