Impact of Tropospheric Mismodelling in GNSS Precise Point Positioning: A Simulation Study Utilizing Ray-Traced Tropospheric Delays from a High-Resolution NWM
| dc.contributor.author | Zus, Florian | |
| dc.contributor.author | Balidakis, Kyriakos | |
| dc.contributor.author | Dick, Galina | |
| dc.contributor.author | Wilgan, Karina | |
| dc.contributor.author | Wickert, Jens | |
| dc.date.accessioned | 2021-11-04T09:31:28Z | |
| dc.date.available | 2021-11-04T09:31:28Z | |
| dc.date.issued | 2021-10-02 | |
| dc.date.updated | 2021-11-01T10:57:27Z | |
| dc.description.abstract | In GNSS analysis, the tropospheric delay is parameterized by applying mapping functions (MFs), zenith delays, and tropospheric gradients. Thereby, the wet and hydrostatic MF are derived under the assumption of a spherically layered atmosphere. The coefficients of the closed-form expression are computed utilizing a climatology or numerical weather model (NWM) data. In this study, we analyze the impact of tropospheric mismodelling on estimated parameters in precise point positioning (PPP). To do so, we mimic PPP in an artificial environment, i.e., we make use of a linearized observation equation, where the observed minus modelled term equals ray-traced tropospheric delays from a high-resolution NWM. The estimated parameters (station coordinates, clocks, zenith delays, and tropospheric gradients) are then compared with the known values. The simulation study utilized a cut-off elevation angle of 3° and the standard downweighting of low elevation angle observations. The results are representative of a station located in central Europe and the warm season. In essence, when climatology is utilized in GNSS analysis, the root mean square error (RMSE) of the estimated zenith delay and station up-component equal about 2.9 mm and 5.7 mm, respectively. The error of the GNSS estimates can be reduced significantly if the correct zenith hydrostatic delay and the correct hydrostatic MF are utilized in the GNSS analysis. In this case, the RMSE of the estimated zenith delay and station up-component is reduced to about 2.0 mm and 2.9 mm, respectively. The simulation study revealed that the choice of wet MF, when calculated under the assumption of a spherically layered troposphere, does not matter too much. In essence, when the ‘correct’ wet MF is utilized in the GNSS analysis, the RMSE of the estimated zenith delay and station up-component remain at about 1.8 mm and 2.4 mm, respectively. Finally, as a by-product of the simulation study, we developed a modified wet MF, which is no longer based on the assumption of a spherically layered atmosphere. We show that with this modified wet MF in the GNSS analysis, the RMSE of the estimated zenith delay and station up-component can be reduced to about 0.5 mm and 1.0 mm, respectively. In practice, its success depends on the ability of current (future) NWM to predict the fourth coefficient of the developed closed-form expression. We provide some evidence that current NWMs are able to do so. | en |
| dc.description.sponsorship | DFG, 443676585, Nutzung von GNSS troposphärischen Gradienten für Monitoring und Vorhersage von Extremwetterereignissen | en |
| dc.description.sponsorship | DFG, 418870484, Erweitertes Multi-GNSS Netzwerk zum Monitoring von Extremwetterereignissen | en |
| dc.identifier.eissn | 2072-4292 | |
| dc.identifier.uri | https://depositonce.tu-berlin.de/handle/11303/13803 | |
| dc.identifier.uri | http://dx.doi.org/10.14279/depositonce-12579 | |
| dc.language.iso | en | en |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en |
| dc.subject.ddc | 620 Ingenieurwissenschaften und zugeordnete Tätigkeiten | de |
| dc.subject.other | GNSS precise point positioning | en |
| dc.subject.other | atmospheric remote sensing | en |
| dc.subject.other | numerical weather model | en |
| dc.subject.other | simulation study | en |
| dc.title | Impact of Tropospheric Mismodelling in GNSS Precise Point Positioning: A Simulation Study Utilizing Ray-Traced Tropospheric Delays from a High-Resolution NWM | en |
| dc.type | Article | en |
| dc.type.version | publishedVersion | en |
| dcterms.bibliographicCitation.articlenumber | 3944 | en |
| dcterms.bibliographicCitation.doi | 10.3390/rs13193944 | en |
| dcterms.bibliographicCitation.issue | 19 | en |
| dcterms.bibliographicCitation.journaltitle | Remote Sensing | en |
| dcterms.bibliographicCitation.originalpublishername | MDPI | en |
| dcterms.bibliographicCitation.originalpublisherplace | Basel | en |
| dcterms.bibliographicCitation.volume | 13 | en |
| tub.accessrights.dnb | free | en |
| tub.affiliation | Fak. 6 Planen Bauen Umwelt::Inst. Geodäsie und Geoinformationstechnik::FG GNSS-Fernerkundung, Navigation und Positionierung | de |
| tub.affiliation.faculty | Fak. 6 Planen Bauen Umwelt | de |
| tub.affiliation.group | FG GNSS-Fernerkundung, Navigation und Positionierung | de |
| tub.affiliation.institute | Inst. Geodäsie und Geoinformationstechnik | de |
| tub.publisher.universityorinstitution | Technische Universität Berlin | en |