Sensitivity of GNSS tropospheric gradients to processing options

Kačmařík, Michal; Douša, Jan; Zus, Florian; Václavovic, Pavel; Balidakis, Kyriakos; Dick, Galina; Wickert, Jens

doi:10.5194/angeo-37-429-2019

Cited by 33 publications

(36 citation statements)

References 39 publications

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“…Kačmařík et al (2019) report gradient amplitudes of up to 3-4 mm during the passage of an occlusion front over Germany. Nahmani et al (2019) studied gradients during the passage of mesoscale convective systems in West Africa and Koulali et al (2012) showed correlations between gradients and precipitation and moisture fluxes in Morocco. Other specific weather phenomena that can cause horizontal variability in the partial pressure of water vapour, and hence also the wet refractivity, are sea breeze (Craig et al, 1945;Miller et al, 2003), cloud rolls (Brown, 1970), and convection processes in general.…”

Section: Cause Of Horizontal Gradients and Modelsmentioning

confidence: 99%

“…Of specific interest in our study was to investigate if there is any systematic seasonal behaviour in the estimated gradients in Sweden and if they can be explained by the influence of regional-scale weather systems. The question about the seasonal changes of gradients was previously studied by Koulali et al (2012). Another issue is that comparisons of estimated GPS gradients with a high temporal resolution are rather sparse and have, to our knowledge, so far not covered periods of many years.…”

Section: Introductionmentioning

confidence: 99%

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On the information content in linear horizontal delay gradients estimated from space geodesy observations

et al. 2019

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Abstract. We have studied linear horizontal gradients in the atmospheric propagation delay above ground-based stations receiving signals from the Global Positioning System (GPS). Gradients were estimated from 11 years of observations from five sites in Sweden. Comparing these gradients with the corresponding ones from the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses shows that GPS gradients detect effects over different timescales caused by the hydrostatic and the wet components. The two stations equipped with microwave-absorbing material below the antenna, in general, show higher correlation coefficients with the ECMWF gradients compared to the other three stations. We also estimated gradients using 4 years of GPS data from two co-located antenna installations at the Onsala Space Observatory. Correlation coefficients for the east and the north wet gradients, estimated with a temporal resolution of 15 min from GPS data, can reach up to 0.8 for specific months when compared to simultaneously estimated wet gradients from microwave radiometry. The best agreement is obtained when an elevation cut-off angle of 3∘ is applied in the GPS data processing, in spite of the fact that the radiometer does not observe below 20∘. We also note a strong seasonal dependence in the correlation coefficients, from 0.3 during months with smaller gradients to 0.8 during months with larger gradients, typically during the warmer and more humid part of the year. Finally, a case study using a 15 d long continuous very-long-baseline interferometry (VLBI) campaign was carried out. The comparison of the gradients estimated from VLBI and GPS data indicates that a homogeneous and frequent sampling of the sky is a critical parameter.

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Section: Cause Of Horizontal Gradients and Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On the information content in linear horizontal delay gradients estimated from space geodesy observations

et al. 2019

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“…During GNSS data processing, other parameters were also estimated and this might introduce some errors in the results. Gradients are also sensitive to the processing settings, such as the elevation cutoff angle, gradient mapping function, and GNSS constellation, as shown by Kačmařík et al (2019).…”

Section: Comparison With Gradients From Gradmentioning

confidence: 99%

“…Several mapping functions have already been published, for instance the Global Mapping Functions, GMF (Böhm et al, 2006a), and the Vienna Mapping Functions 1, VMF1 (Böhm et al, 2006b). Recently, a refined version of VMF1, VMF3 (Landskron and Böhm, 2017), was released.…”

Section: Introductionmentioning

confidence: 99%

Assessing the performance of Vienna Mapping Functions 3 for GNSS stations in Indonesia using Precise Point Positioning

2020

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Abstract. Tropospheric delay is one of the major error sources for space geodetic techniques, such as the Global Navigation Satellite Systems (GNSS). Mapping functions are used to scale the delay from zenith direction to the elevation angle of the signal. Several mapping functions have already been published, including the Global Mapping Functions (GMF) and Vienna Mapping Functions 1 (VMF1). Recently, a refined version of VMF1, VMF3, was released. The tropospheric gradients GRAD were also determined using the same data set as VMF3. This study aims to test the performance of VMF3 on GNSS observations in Indonesia, using observations from 21 stations of the permanent GNSS network in Indonesia, InaCORS. Data processing was carried out using Precise Point Positioning in Bernese GNSS Software, version 5.2 for the year 2014. Station coordinates were estimated daily, while the zenith wet delays were estimated every 30 min and tropospheric gradients were estimated hourly. A similar processing scheme was carried out using GMF and VMF1. Generally, the results from VMF3 agree very well with the results from GMF and VMF1, although small biases can be found, especially for the height component. Based on the repeatability, while there is no significant difference for the latitude and longitude, there are slight improvements for the height, particularly compared to GMF. The estimated gradients tend to fluctuate more compared to gradients from GRAD. The correlation coefficients between the estimated gradients and those from GRAD are small, with the largest being 0.65 at site CUKE.

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“…The discrepancies found between the different sources can be explained by the fact that the external source applies flat weighting on the observations, while TOMION makes use of negative exponential of the elevation angle of the transmitter. Another cause of scale differences can be the different mapping functions used for the gradient term: Chen and Herring () in TOMION and Bar‐Sever et al () in GIPSY, and as it is stated in Kačmařík et al (), systematic errors effects of up to 0.3 mm were observed in estimated tropospheric gradients when using different gradient mapping functions which depend on the applied observation elevation‐dependent weighting as well. Furthermore, in TOMION, we use VMF1, whereas UNR adopts GMF (Global Mapping Function; Böhm et al, ) for mapping the symmetric term ( m d and m w in equation ).…”

Section: Gps Processing and Validationmentioning

confidence: 99%

Interpretation of the Tropospheric Gradients Estimated With GPS During Hurricane Harvey

Graffigna

Hernández‐Pajares

Gende

et al. 2019

Earth and Space Science

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During the last decade Global Positioning System (GPS) Continuous Operating Reference Stations networks have become a new important data source for meteorology. This has dramatically improved the ability to remotely sense the atmosphere under the influence of severe mesoscale and synoptic systems. The zenith tropospheric delay (ZTD) is one of the atmospheric variables continuously observed, and its horizontal variations, the horizontal tropospheric gradients, are routinely computed nowadays within the dual‐frequency GPS processing, but their interpretation and relationship with the weather is still an open question. The purpose of this paper is to contribute in this direction by studying the effect that Hurricane Harvey had on the spatial and temporal behavior of the ZTDs and gradients, when it reached Texas coast, during 18–31 August 2017. The results show that ZTD time series present a clear and rapid increase larger than 10 cm in a few hours when the hurricane reached the area. Gradients behaviors show that the hurricane also produced significant changes on them, since the magnitude and predominant directions before and after the hurricane arrived are completely different. Noticeably, the gradient vectors before the landing are consistently related to the horizontal winds and pressure fields. In this manuscript we demonstrate that the ZTD gradients can show a consistent signature under severe weather events, strongly suggesting their potential application for short‐term weather forecasting.

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Sensitivity of GNSS tropospheric gradients to processing options

Cited by 33 publications

References 39 publications

On the information content in linear horizontal delay gradients estimated from space geodesy observations

On the information content in linear horizontal delay gradients estimated from space geodesy observations

Assessing the performance of Vienna Mapping Functions 3 for GNSS stations in Indonesia using Precise Point Positioning

Interpretation of the Tropospheric Gradients Estimated With GPS During Hurricane Harvey

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