Real‐time GPS sensing of atmospheric water vapor: Precise point positioning with orbit, clock, and phase delay corrections

Li, Xingxing; Dick, Galina; Ge, Maorong; Heise, S.; Wickert, Jens; Bender, Michael A.

doi:10.1002/2013gl058721

Cited by 113 publications

(70 citation statements)

References 21 publications

(37 reference statements)

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“…The observed impact of ambiguity resolution on ZTD is approximately 6 mm, which compares well to, e.g., the 20 % (4-5 mm) impact observed by Geng et al (2009). The recent study by Li et al (2014), which is based on their in-house software and products, also reported on the insignificant differences between the RT-PPP float and fixed solutions after sufficiently long times of convergence. However, they demonstrated the usefulness of ambiguity fixing for the rapid re-initialization of an RT-PPP estimation system (e.g., after an interruption in the data stream).…”

Section: Internal Evaluationsupporting

confidence: 73%

“…Among others, the Centre National d'Etudes Spatiales (CNES) has developed strategies to fix integer ambiguities of un-differenced phase measurements by first fixing the difference between the ambiguities on the two carrier frequencies and then fixing the remaining ambiguity in a global network solution (Loyer et al 2012). To date, only few studies have been performed to study the impact of ambiguity resolution on GNSS-based ZTD estimates in RT-PPP with some of them benefitting from software and products not necessarily available to the community (Shi and Gao 2012;Li et al 2014).…”

Section: Introductionmentioning

confidence: 99%

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Comparative analysis of real-time precise point positioning zenith total delay estimates

et al. 2014

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The continuous evolution of global navigation satellite systems (GNSS) meteorology has led to an increased use of associated observations for operational modern low-latency numerical weather prediction (NWP) models, which assimilate GNSS-derived zenith total delay (ZTD) estimates. The development of NWP models with faster assimilation cycles, e.g., 1-h assimilation cycle in the rapid update cycle NWP model, has increased the interest of the meteorological community toward sub-hour ZTD estimates. The suitability of real-time ZTD estimates obtained from three different precise point positioning software packages has been assessed by comparing them with the state-of-the-art IGS final troposphere product as well as collocated radiosonde (RS) observations. The ZTD estimates obtained by BNC2.7 show a mean bias of 0.21 cm, and those obtained by the G-Nut/Tefnut software library show a mean bias of 1.09 cm to the IGS final troposphere product. In comparison with the RS-based ZTD, the BNC2.7 solutions show mean biases between 1 and 2 cm, whereas the G-Nut/Tefnut solutions show mean biases between 2 and 3 cm with the RS-based ZTD, and the ambiguity float and ambiguity fixed solutions obtained by PPP-Wizard have mean biases between 6 and 7 cm with the references. The large biases in the time series from PPP-Wizard are due to the fact that this software has been developed for kinematic applications and hence does not apply receiver antenna eccentricity and phase center offset (PCO) corrections on the observations. Application of the eccentricity and PCO corrections to the a priori coordinates has resulted in a 66 % reduction of bias in the PPP-Wizard solutions. The biases are found to be stable over the whole period of the comparison, which are criteria (rather than the magnitude of the bias) for the suitability of ZTD estimates for use in NWP nowcasting. A millimeter-level impact on the ZTD estimates has also been observed in relation to ambiguity resolution. As a result of a comparison with the established user requirements for NWP nowcasting, it was found that both the G-Nut/Tefnut solutions and one of the BNC2.7 solutions meet the threshold requirements, whereas one of the BNC2.7 solution and both the PPPWizard solutions currently exceed this threshold.

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Section: Internal Evaluationsupporting

confidence: 73%

Section: Introductionmentioning

confidence: 99%

Comparative analysis of real-time precise point positioning zenith total delay estimates

et al. 2014

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“…Accurate knowledge of water vapor is not only vital for weather forecasting but also an important independent data source for global climate studies. For the last decade, the Global Navigation Satellite System (GNSS) has been used as an emerging and robust tool for remotely sensing integrated water vapor (IWV) for the monitoring of the real-time IWV variations in the atmosphere (Schneider et al, 2010;Rohm et al, 2014;Zhang et al, 2015;Li et al, 2014Li et al, , 2015Guerova et al, 2016) or the studies of climate (Nilsson and Elgered, 2008;Jin and Luo, 2009;Vonder Haar et al, 2012;Ning and Elgered, 2012) due to its 24 h availability, high accuracy, global coverage, high resolution and low cost. The atmospheric parameter directly estimated from GNSS measurements is the GNSS signal's tropospheric zenith total delay (ZTD) which can be effectively divided into the zenith hydrostatic delay (ZHD) and the zenith wet delay (ZWD).…”

Section: Introductionmentioning

confidence: 99%

Determination of zenith hydrostatic delay and its impact on GNSS-derived integrated water vapor

Wang

Zhang

et al. 2017

Atmos. Meas. Tech.

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Abstract. Surface pressure is a necessary meteorological variable for the accurate determination of integrated water vapor (IWV) using Global Navigation Satellite System (GNSS). The lack of pressure observations is a big issue for the conversion of historical GNSS observations, which is a relatively new area of GNSS applications in climatology. Hence the use of the surface pressure derived from either a blind model (e.g., Global Pressure and Temperature 2 wet, GPT2w) or a global atmospheric reanalysis (e.g., ERAInterim) becomes an important alternative solution. In this study, pressure derived from these two methods is compared against the pressure observed at 108 global GNSS stations at four epochs (00:00, 06:00, 12:00 and 18:00 UTC) each day for the period 2000-2013. Results show that a good accuracy is achieved from the GPT2w-derived pressure in the latitude band between −30 and 30 • and the average value of 6 h root-mean-square errors (RMSEs) across all the stations in this region is 2.5 hPa. Correspondingly, an error of 5.8 mm and 0.9 kg m −2 in its resultant zenith hydrostatic delay (ZHD) and IWV is expected. However, for the stations located in the mid-latitude bands between −30 and −60 • and between 30 and 60 • , the mean value of the RMSEs is 7.3 hPa, and for the stations located in the high-latitude bands from −60 to −90 • and from 60 to 90 • , the mean value of the RMSEs is 9.9 hPa. The mean of the RMSEs of the ERAInterim-derived pressure across at the selected 100 stations is 0.9 hPa, which will lead to an equivalent error of 2.1 mm and 0.3 kg m −2 in the ZHD and IWV, respectively, determined from this ERA-Interim-derived pressure. Results also show that the monthly IWV determined using pressure from ERAInterim has a good accuracy − with a relative error of better than 3 % on a global scale; thus, the monthly IWV resulting from ERA-Interim-derived pressure has the potential to be used for climate studies, whilst the monthly IWV resulting from GPT2w-derived pressure has a relative error of 6.7 % in the mid-latitude regions and even reaches 20.8 % in the highlatitude regions. The comparison between GPT2w and seasonal models of pressure-ZHD derived from ERA-Interim and pressure observations indicates that GPT2w captures the seasonal variations in pressure-ZHD very well.

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“…Since then, extensive research has been conducted [3][4][5]. In recent years, Li et al have conducted a lot of studies about using multi-GNSS data to retrieve atmospheric parameters in real time [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

An Improved Tomography Approach Based on Adaptive Smoothing and Ground Meteorological Observations

et al. 2017

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Using the Global Navigation Satellite System (GNSS) to sense three-dimensional water vapor (WV) has been intensively investigated. However, this technique still heavily relies on the a priori information. In this study, we propose an improved tomography approach based on adaptive Laplacian smoothing (ALS) and ground meteorological observations. By using the proposed approach, the troposphere tomography is less dependent on a priori information and the ALS constraints match better with the actual situation than the constant constraints. Tomography experiments in Hong Kong during a heavy rainy period and a rainless period show that the ALS method gets superior results compared with the constant Laplacian smoothing (CLS) method. By validation with radiosonde and European Centre for Medium-Range Weather Forecasts (ECMWF) data, we found that the introduction of ground meteorological observations into tomography can solve the perennial problem of resolving the wet refractivity in the lower troposphere and thus significantly improve the tomography results. However, bad data quality and incompatibility of the ground meteorological observations may introduce errors into tomography results.

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Real‐time GPS sensing of atmospheric water vapor: Precise point positioning with orbit, clock, and phase delay corrections

Cited by 113 publications

References 21 publications

Comparative analysis of real-time precise point positioning zenith total delay estimates

Comparative analysis of real-time precise point positioning zenith total delay estimates

Determination of zenith hydrostatic delay and its impact on GNSS-derived integrated water vapor

An Improved Tomography Approach Based on Adaptive Smoothing and Ground Meteorological Observations

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