EPN-Repro2: A reference GNSS tropospheric data set over Europe

Pacione, R.; Araszkiewicz, Andrzej; Bröckmann, E.; Douša, Jan

doi:10.5194/amt-10-1689-2017

Cited by 62 publications

(45 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Similar biases have been observed for all other European GNSS reprocessing products during the period of 1996-2014 (Pacione et al, 2017). On the other hand, when processing the ERA-Interim using two different software and methodologies within the GNSS4SWEC Benchmark campaign during May and June of 2013 in Central Europe, and by their comparison to two GNSS reference products based on different processing methods, we observed bias differences within ±0.4 mm in ZTD.…”

Section: Zenith Total Delayssupporting

confidence: 52%

“…Comparing the results of the official GOP Repro2 solution (GO4) to those of the legacy solution (GO0) demonstrates an overall improvement of 9 % in terms of accuracy, which corresponds to a similar comparison between the EUREF Repro1 and Repro2 products (Pacione et al, 2017). The improvement is assumed to be even larger (indicated by the coordinate repeatability) since the comparison of tropospheric parameters is limited by a lower quality of reference products derived from NWM data Kačmařík et al, 2017;Bock and Nuret, 2009).…”

Section: Zenith Total Delaysmentioning

confidence: 99%

See 1 more Smart Citation

Tropospheric products of the second GOP European GNSS reprocessing (1996–2014)

2017

Self Cite

View full text Add to dashboard Cite

Abstract. In this paper, we present results of the second reprocessing of all data from 1996 to 2014 from all stations in International Association of Geodesy (IAG) Reference Frame Sub-Commission for Europe (EUREF) Permanent Network (EPN) as performed at the Geodetic Observatory Pecný (GOP). While the original goal of this research was to ultimately contribute to the realization of a new European Terrestrial Reference System (ETRS), we also aim to provide a new set of GNSS (Global Navigation Satellite System) tropospheric parameter time series with possible applications to climate research. To achieve these goals, we improved a strategy to guarantee the continuity of these tropospheric parameters and we prepared several variants of troposphere modelling. We then assessed all solutions in terms of the repeatability of coordinates as an internal evaluation of applied models and strategies and in terms of zenith tropospheric delays (ZTDs) and horizontal gradients with those of the ERA-Interim numerical weather model (NWM) reanalysis. When compared to the GOP Repro1 (first EUREF reprocessing) solution, the results of the GOP Repro2 (second EU-REF reprocessing) yielded improvements of approximately 50 and 25 % in the repeatability of the horizontal and vertical components, respectively, and of approximately 9 % in tropospheric parameters. Vertical repeatability was reduced from 4.14 to 3.73 mm when using the VMF1 mapping function, a priori ZHD (zenith hydrostatic delay), and non-tidal atmospheric loading corrections from actual weather data. Raising the elevation cut-off angle from 3 to 7 • and then to 10 • increased RMS from coordinates' repeatability, which was then confirmed by independently comparing GNSS tropospheric parameters with the NWM reanalysis. The assessment of tropospheric horizontal gradients with respect to the ERA-Interim revealed a strong sensitivity of estimated gradients to the quality of GNSS antenna tracking performance. This impact was demonstrated at the Mallorca station, where gradients systematically grew up to 5 mm during the period between 2003 and 2008, before this behaviour disappeared when the antenna at the station was changed. The impact of processing variants on long-term ZTD trend estimates was assessed at 172 EUREF stations with time series longer than 10 years. The most significant site-specific impact was due to the non-tidal atmospheric loading followed by the impact of changing the elevation cut-off angle from 3 to 10 • . The other processing strategy had a very small or negligible impact on estimated trends.

show abstract

Section: Zenith Total Delayssupporting

confidence: 52%

Section: Zenith Total Delaysmentioning

confidence: 99%

Tropospheric products of the second GOP European GNSS reprocessing (1996–2014)

2017

Self Cite

View full text Add to dashboard Cite

show abstract

“…The GPS data were obtained by the Finnish Geodetic Institute and the National Land Survey of Finland as Receiver INdependent EXchange format (RINEX) files and processed in Precise Point Positioning [38] mode using the Global Navigation Satellite System (GNSS)-Inferred Positioning System and Orbit Analysis Simulation Software package GIPSY-OASIS II [39], with a cut-off angle of 3 • . We fixed Jet Propulsion Laboratory (JPL) fiducial-free satellite orbits, clocks, and earth orientation parameters and state-of-the-art processing options to estimate ZTD with a 5-min sampling [40,41]. The Vienna mapping function [42] was applied to the delay of the signal along each satellite-receiver path in order to map it into the zenith direction.…”

Section: Gps-derived Iwv Datamentioning

confidence: 99%

“…The data are processed using the Bernese 5.0 software with a cut-off angle of 3 • and are provided with a temporal resolution of 30 min. Pacione et al [41] evaluated the agreement between the different GPS software packages-Bernese [46], GAMIT [47], and GIPSY-OASIS II [39]-in terms of the ZTD standard deviation. They found that the overall agreement is better than 3 mm before 26 March 2000 and 2 mm thereafter.…”

Section: Instrumentation At the North Slope Of Alaskamentioning

confidence: 99%

Intercomparison of Integrated Water Vapor Measurements at High Latitudes from Co-Located and Near-Located Instruments

Fionda

Cadeddu

Mattioli³

et al. 2019

Remote Sensing

Self Cite

View full text Add to dashboard Cite

Data from global positioning system (GPS) ground-based receivers, ground-based microwave radiometers (MWRs), and radiosondes (RS) at two high-latitude sites were compared. At one site, the North Slope of Alaska (NSA), Barrow, Alaska (USA), the instruments were co-located, while at the other site, the second ARM Mobile Facility (AMF2), Hyytiälä, Finland, the GPS receiver was located about 20 km away from the MWRs and RS. Differences between the GPS-derived integrated water vapor (IWV) and the other three instruments were analyzed in terms of mean differences and standard deviation. A comparison of co-located and near-located independently calibrated instruments allowed us to isolate issues that may be specific to a single system and, to some extent, to isolate the effects of the distance between the GPS receiver and the remaining instruments. The results showed that at these two high-latitude sites, when the IWV was less than 15 kg/m 2 , the GPS agreed with other instruments within 0.5-0.7 kg/m 2 . When the variability of water vapor was higher, mostly in the summer months, the GPS agreed with other instruments within 0.8-1 kg/m 2 . The total random uncertainty between the GPS and the other systems was of the order of 0.6-1 kg/m 2 and was the dominant effect when the IWV was higher than 15 kg/m 2 . a very-long-baseline interferometry (VLBI) radio telescope [5], and numerical weather prediction models [6][7][8]. From a statistical point of view, intercomparison analyses have highlighted discrepancies in terms of systematic errors (bias) and random errors (standard deviation, SD). These discrepancies can be attributed to climatic conditions, the length of observations, and characteristics of the instruments such as instrumental errors, the volume sampled, sensitivity, and the sampling time as well as to water vapor retrieval algorithms.The need to monitor and improve the quantification of water vapor is also essential considering incoming next-generation 5G wireless networks. In communications systems based on 5G technology, high data capacity and low latency are achieved by moving operational frequencies toward spectral regions such as the millimeter-wave band (30-300 GHz). From a communications point of view, for planning outdoor millimeter/submillimeter communication networks, water vapor is a source of signal degradations. To improve propagation models and experimental capability in the estimation of water vapor [9,10], accurate investigations of water vapor uncertainties in different climatic scenarios are desirable. However, even more importantly, since the critical 23.8-GHz water vapor frequency is so close to the 5G 24-GHz band, there is a high risk of interference, which impacts the ability to detect water vapor in the atmosphere accurately [11].In this work, we specifically focus on IWV high-latitude observations, as their retrieval remains an important challenge in this climatic regime: for example, satellite retrievals suffer from high surface reflectivity and low solar zenith angle [12]. IWV from GPSes ...

show abstract

“…The GPS station is operated by the Finnish Geodetic Institute and the National Land Survey of Finland. GPS data were obtained as RINEX files and 5 processed in Precise Point Positioning mode using GIPSY-OASIS II and state-of-the-art processing options to derive ZTD with a 5-minute sampling (Pacione et al, 2014;Pacione et al, 2017). The ZTD known as the "tropospheric total delay" by the neutral atmosphere can be expressed as the sum of two components: zenith hydrostatic delay (ZHD) due to hydrostatic gases (mainly oxygen) and ZWD due to water vapour (Elgered, 1993).…”

Section: Gps Datamentioning

confidence: 99%

Experimental total uncertainty of the derived GNSS-integrated water vapour using four co-located techniques in Finland

Fionda

Cadeddu

Mattioli³

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

Abstract. In this work, we examine data from a Global Positioning System (GPS) ground-based receiver, two co-located ground-based microwave radiometers (MWRs), and radiosondes (RAOBs) to characterize the uncertainties associated with integrated water vapour (IWV) values estimated from the GPS in a sub-Arctic climate region. The experiment was carried out 15 during the Biogenic Aerosols-Effects on Clouds and Climate research campaign conducted using the Atmospheric Radiation Measurement Program's second Mobile Facility (AMF2) in collaboration with the University of Helsinki. The GPS receiver was located about 20 km away from the AMF2 instruments (radiometers and RAOB). The GPS data were processed in Precise Point Positioning mode using the state-of-the-art scientific software GIPSY-OASIS II. Differences between the GPS-derived IWV and that derived from the other three instruments are analysed in terms of bias, standard deviation, and root-mean-square 20 error (RMSE). The availability of three co-located, independently calibrated systems (two MWRs and one RAOB) allows us to isolate issues that may be specific to a single system and to isolate the effects of the distance between the GPS receiver and the remaining instruments. The representativeness error due to the 20-km distance between the GPS and the other systems is of the order of 0.6-1.5 kg/m 2 and in this study is the dominant effect when the IWV is higher than 20 kg/m 2 . The RMSE between the instruments shows that in the sub-Arctic region, when the IWV variability is less than 20 kg/m 2 , the GPS agrees 25 with other instruments to within 0.5 kg/m 2 . When the variability of water vapour in the 20-km region is higher than 20 kg/m 2 , mostly in the summer months, the GPS agrees with other instruments within 1-2 kg/m 2 .

show abstract

EPN-Repro2: A reference GNSS tropospheric data set over Europe

Cited by 62 publications

References 50 publications

Tropospheric products of the second GOP European GNSS reprocessing (1996–2014)

Tropospheric products of the second GOP European GNSS reprocessing (1996–2014)

Intercomparison of Integrated Water Vapor Measurements at High Latitudes from Co-Located and Near-Located Instruments

Experimental total uncertainty of the derived GNSS-integrated water vapour using four co-located techniques in Finland

Contact Info

Product

Resources

About