Assessing water vapor tomography in Hong Kong with improved vertical and horizontal constraints

Xia, Pengfei; Ye, Shirong; Jiang, Peng; Pan, Lin; Guo, Min

doi:10.5194/angeo-36-969-2018

Cited by 14 publications

(15 citation statements)

References 36 publications

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“…In the vertical domain, the optimal top boundary of the two tomographic experiments is first determined according to the water vapor distribution derived from local radiosonde data in Hong Kong and Xuzhou, respectively (Zhang et al 2020b). Fifteen uneven vertical divisions are implemented for both areas (Xia et al 2018), with the interval of 0.4 km for each layer from the first to the tenth layer, and the interval of 1.0, 1.0, 1.5, 1.5, 2.0 km from the eleventh to 15th layer. Additionally, in the experiments, the average 3-day radiosonde data before the tomography time windows are used to initialize the tomography models (Zhao et al 2018).…”

Section: Experiments Setupmentioning

confidence: 99%

A new hybrid observation GNSS tomography method combining the real and virtual inverted signals

Zhang

Zhang²,

Chang³

et al. 2021

J Geod

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Accurate three-dimensional (3D) atmospheric water vapor distribution, which plays a crucial role in understanding the meteorological phenomena and hazards, has been successfully retrieved using Global Navigation Satellite System (GNSS) tomography technique. Presently, the problem of the ill-posed tomography system, that results from poor GNSS acquisition geometry, remains a vital issue to be solved. In this paper, we develop a new hybrid observation GNSS tomography (HOGT) method, which constructs and introduces the virtual signals, inverted to the real rays, to address the acquisition geometry defect. Within the HOGT, the slant wet delay (SWD) of the virtual inverted signal (VIS) is estimated by means of the tropospheric parameters derived from the hourly ERA5 data using the ray-tracing algorithm. Two designed experiments, based on the dense and sparse GNSS networks (corresponding to Hong Kong and Xuzhou), respectively, are implemented to assess the performance of HOGT for the different networks. The results reveal that HOGT provides a more robust observation geometry and more accurate water vapor distribution than the traditional tomography model, with the mean number of the crossed voxels enhanced by 26.45% and 27.11% for the two networks, and the average root-mean-square error (RMSE) of the tomography solutions improved by 18.18% and 38.28% in the two areas, respectively. Furthermore, HOGT shows a significant improvement close to the Erath's surface from 0 to 2 km, implying its superior capability to optimize the accuracy of tomography results. An additional experiment to investigate the performance of the proposed method under different time resolutions demonstrates that HOGT can be promised to retrieve more accurate water vapor distribution over short time intervals, especially for rainy days with an interval of 10 min or even shorter, which highlights the interest in tomography solutions for improving the understanding of severe weather. KeywordsGlobal Navigation Satellite System (GNSS) • Hybrid observation GNSS tomography (HOGT) • Virtual inverted signals (VIS) • Dense and sparse networks • ERA5 • Radiosonde B Shubi Zhang

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Section: Experiments Setupmentioning

confidence: 99%

A new hybrid observation GNSS tomography method combining the real and virtual inverted signals

Zhang

Zhang²,

Chang³

et al. 2021

J Geod

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“…The ω values obtained in different seasons (spring, summer, autumn, and winter) are shown in Figure 2. In addition, the distribution of ω across China was derived from these values based on the Gauss distance-weighting function [27,28], as shown in the four subgraphs in Figure 3. Figures 2 and 3 illustrate that the ω coefficients varied by more than ±2 in some areas, depending on the season.…”

Section: The Determination Of the Mixing Ratio Of The Atmosphere (ω)mentioning

confidence: 99%

A New Method for Estimating Tropospheric Zenith Wet-Component Delay of GNSS Signals from Surface Meteorology Data

Xia

Jing-chao

et al. 2020

Remote Sensing

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A new concept is proposed for estimating the zenith wet delay (ZWD) and atmospheric weighted average temperature by inputting the temperature, total pressure, and specific humidity from surface weather data. In addition, a new ZWD integral method is described for highly accurate calculation of the ZWD from radiosonde observation. To evaluate the advantages of the new discrete integral formula, we utilized the 8-year radiosonde profiles of 85 stations in China from 2010 to 2017 to validate the accuracy of the radiosonde-derived ZWD. The results showed that the mean accuracy of the ZWD derived from radiosonde data was 4.28 mm. Next, the new ZWD model was assessed using two sets of reference values derived from radiosonde data and GNSS precise point positioning in China. The results confirm that the new development improved the accuracy of the estimation of the tropospheric wet delay from the surface meteorological data. The performance of this new model can be seen as an important step toward accurately correcting the tropospheric delay in Global Navigation Satellite System (GNSS) real-time navigation and positioning. It can also be used in GNSS meteorology for weather forecasting and climate research.

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“…Introducing moderateresolution imaging spectroradiometer (MODIS) [10], interferometric synthetic aperture radar (InSAR) [11], and ground-based meteorological observation [12] data into the tomographic model, also helps to solve the above problem. Introducing wet refractivity profiles that are derived from radio occultation data can also considerably improve tomographic solutions [13][14][15]. In addition to the effective methods mentioned above, increasing the number of observations is also effective.…”

Section: Introductionmentioning

confidence: 99%

LEO Constellation-Augmented Multi-GNSS for 3D Water Vapor Tomography

Xiong

Ren

et al. 2021

Remote Sensing

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Global navigation satellite systems (GNSS) water vapor tomography is an important technique to obtain the three-dimensional distribution of atmospheric water vapor. The rapid development of low Earth orbit (LEO) constellations has led to a richer set of observations, which brings new expectations for water vapor tomography. This paper analyzes the influence of LEO constellation-augmented multi-GNSS(LCAMG)on the tomography, in terms of ray distribution, tomography accuracy, and horizontal resolution, by simulating LEO constellation data. The results show that after adding 288 LEO satellites to GNSS, the 30-min ray distribution effect of GNSS can be achieved in 10 min, which can effectively shorten the observation time by 66.7%. In the 10-min observation time, the non-repetitive effective observation value of LCAMG is 2.38 times that of GNSS, and the accuracy is 1.27% higher than that of GNSS. Compared with GNSS and the global positioning system (GPS), at a horizontal resolution of 13 × 14, the proportion of empty voxels in LCAMG reduces by 5.22% and 22.53%, respectively.

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Assessing water vapor tomography in Hong Kong with improved vertical and horizontal constraints

Cited by 14 publications

References 36 publications

A new hybrid observation GNSS tomography method combining the real and virtual inverted signals

A new hybrid observation GNSS tomography method combining the real and virtual inverted signals

A New Method for Estimating Tropospheric Zenith Wet-Component Delay of GNSS Signals from Surface Meteorology Data

LEO Constellation-Augmented Multi-GNSS for 3D Water Vapor Tomography

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