Estimating atmospheric pressure loading regression coefficients from GPS observations

Kaniuth, K; Vetter, Sandra

doi:10.1007/s10291-005-0019-z

Cited by 7 publications

(8 citation statements)

References 18 publications

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“…The pressure anomaly range is large at the high latitude under consideration, with an overall peak to peak maximum of over 70 hPa during the study and a maximum daily range of 40 hPa. These values are very similar to those experienced at high northern latitudes (Kaniuth and Vetter, 2006).…”

Section: Analysis Of Vertical Motions In Gps Time-seriessupporting

confidence: 84%

“…As pressure changes the tropospheric delay estimates vary. This could show up in the GPS time-series as height changes, which could be wrongly interpreted as the response to local load changes (Kaniuth and Vetter, 2006). We use relative antenna phase center variation tables from NGS and the Niell Mapping Function (Niell, 1996) when processing Cape Roberts.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of continuous GPS measurements from southern Victoria Land, Antarctica

Willis

2007

Open-File Report

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Several years of continuous data have been collected at remote bedrock Global Positioning System (GPS) sites in southern Victoria Land, Antarctica. Annual to sub-annual variations are observed in the position time-series. An atmospheric pressure loading (APL) effect is calculated from pressure field anomalies supplied by the European Centre for Medium-Range Weather Forecasts (ECMWF) model loading an elastic Earth model. The predicted APL signal has a moderate correlation with the vertical position time-series at McMurdo, Ross Island (International Global Navigation Satellite System Service (IGS) station MCM4), produced using a global solution. In contrast, a local solution in which MCM4 is the fiducial site generates a vertical time series for a remote site in Victoria Land (Cape Roberts, ROB4) which exhibits a low, inverse correlation with the predicted atmospheric pressure loading signal. If, in the future, known and well modeled geophysical loads can be separated from the time-series, then local hydrological loading, of interest for glaciological and climate applications, can potentially be extracted from the GPS time-series.

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Section: Analysis Of Vertical Motions In Gps Time-seriessupporting

confidence: 84%

Section: Introductionmentioning

confidence: 99%

Analysis of continuous GPS measurements from southern Victoria Land, Antarctica

Willis

2007

Open-File Report

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“…Similar results were obtained for GPS . Linear ATML regression coefficients between vertical site displacements and local pressure variations have been derived as estimable quantities from VLBI (MacMillan and Gipson, 1994) and GPS observations (Kaniuth and Vetter, 2005). Their results reveal an improved baseline length repeatability but also demonstrate the limitations of fitting local pressure variations to deformation caused by regional pressure anomalies.…”

Section: Geodetic Conceptmentioning

confidence: 97%

Global-scale validation of model-based load deformation of the Earth's crust from continental watermass and atmospheric pressure variations using GPS

Fritsche

Döll

Dietrich

2012

Journal of Geodynamics

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“…Geodetic time series recorded by the Global Positioning System (GPS) have revealed that surface load variations can induce measurable surface strain. Variations of surface loading can result from various sources: tidal loading [ Agnew , , ], continental water storage [ Blewitt et al , ; Bevis et al , ; Van Dam et al , ; Davis et al , ; Bettinelli et al , ; Steckler et al , ; Elósegui et al , ; Fu and Freymueller , ; Fu et al , ; Wahr et al , ], ice and snow [ Grapenthin et al , ; Matsuo and Heki , ; Jiang et al , ], and atmospheric pressure [ Kaniuth and Vetter , ]. The analysis of these signals has attracted much attention.…”

Section: Introductionmentioning

confidence: 99%

Modeling deformation induced by seasonal variations of continental water in the Himalaya region: Sensitivity to Earth elastic structure

et al. 2014

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Strong seasonal variations of horizontal and vertical positions are observed on GPS time series from stations located in Nepal, India, and Tibet (China). We show that this geodetic deformation can be explained by seasonal variations of continental water storage driven by the monsoon. For this purpose, we use satellite data from the Gravity Recovery and Climate Experiment to determine the time evolution of surface loading. We compute the expected geodetic deformation assuming a perfectly elastic Earth model. We consider Green's functions, describing the surface deformation response to a point load, for an elastic homogeneous half‐space model and for a layered nonrotating spherical Earth model based on the Preliminary Reference Earth Model and a local seismic velocity model. The amplitude and phase of the seasonal variation of the vertical and horizontal geodetic positions can be jointly adjusted only with the layered Earth model, while an elastic half‐space model fails, emphasizing the importance of using a realistic Earth elastic structure to model surface displacements induced by surface loading. We demonstrate, based on a formal inversion, that the fit to the geodetic data can be improved by adjusting the layered Earth model. Therefore, the study also shows that the modeling of geodetic seasonal variations provides a way to probe the elastic structure of the Earth, even in the absence of direct measurements of surface load variations.

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Estimating atmospheric pressure loading regression coefficients from GPS observations

Abstract: ERRATUMThe online version of the article can be found at http://www.dx

Cited by 7 publications

References 18 publications

Analysis of continuous GPS measurements from southern Victoria Land, Antarctica

Analysis of continuous GPS measurements from southern Victoria Land, Antarctica

Global-scale validation of model-based load deformation of the Earth's crust from continental watermass and atmospheric pressure variations using GPS

Modeling deformation induced by seasonal variations of continental water in the Himalaya region: Sensitivity to Earth elastic structure

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