Correcting GPS measurements for non-tidal loading

Mémin, Anthony; Boy, Jean‐Paul; Santamaría-Gómez, Álvaro

doi:10.1007/s10291-020-0959-3

Cited by 51 publications

(57 citation statements)

References 45 publications

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“…[20][21][22] ). However, the required networks are sparse in many regions of the world, and GNSS time series for individual stations include many non-loading signals and technique-related errors which are difficult to separate [23][24][25] . (4) Data from other sources such as satellite laser ranging (SLR) or from the European Space Agency (ESA) Swarm 3-satellite formation are used to reconstruct low-degree models of the gravity field [26][27][28] .…”

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confidence: 99%

Reconstructing GRACE-type time-variable gravity from the Swarm satellites

Richter

Lück

Kłos

et al. 2021

Sci Rep

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The Gravity Recovery and Climate Experiment (GRACE) mission has enabled mass changes and transports in the hydrosphere, cryosphere and oceans to be quantified with unprecedented resolution. However, while this legacy is currently being continued with the GRACE Follow-On (GRACE-FO) mission there is a gap of 11 months between the end of GRACE and the start of GRACE-FO which must be addressed. Here we bridge the gap by combining time-variable, low-resolution gravity models derived from European Space Agency’s Swarm satellites with the dominating spatial modes of mass variability obtained from GRACE. We show that the noise inherent in unconstrained Swarm gravity solutions is greatly reduced, that basin averages can have root mean square errors reduced to the order of $$\text {cm}$$ cm of equivalent water height, and that useful information can be retrieved for basins as small as $$1000 \times 1000\,\hbox {km}$$ 1000 × 1000 km . It is found that Swarm data contains sufficient information to inform the leading three global mass modes found in GRACE at the least. By comparing monthly reconstructed maps to GRACE data from December 2013 to June 2017, we suggest the uncertainty of these maps to be $$2{-}3\,\text {cm}$$ 2 - 3 cm of equivalent water height.

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confidence: 99%

Reconstructing GRACE-type time-variable gravity from the Swarm satellites

Richter

Lück

Kłos

et al. 2021

Sci Rep

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“…The impact of neglecting the ocean loading component may be intensified in the semi-enclosed bay regions, e.g., the Gulf of Thailand, where the ocean bottom pressure effect is significant [58,63]. Note that this study obtains the atmosphere and ocean signals from the AOD product consistent with GRACE Level-2 processing while using different de-aliasing products or geophysical models, e.g., [64], which may have a different impact on the ∆r estimate. The performance comparison is beyond the scope of this study but can be considered in future analyses.…”

Section: Discussionmentioning

confidence: 96%

The Assessment of Hydrologic- and Flood-Induced Land Deformation in Data-Sparse Regions Using GRACE/GRACE-FO Data Assimilation

Tangdamrongsub

Šprlák

2021

Remote Sensing

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The vertical motion of the Earth’s surface is dominated by the hydrologic cycle on a seasonal scale. Accurate land deformation measurements can provide constructive insight into the regional geophysical process. Although the Global Positioning System (GPS) delivers relatively accurate measurements, GPS networks are not uniformly distributed across the globe, posing a challenge to obtaining accurate deformation information in data-sparse regions, e.g., Central South-East Asia (CSEA). Model simulations and gravity data (from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO)) have been successfully used to improve the spatial coverage. While combining model estimates and GRACE/GRACE-FO data via the GRACE/GRACE-FO data assimilation (DA) framework can potentially improve the accuracy and resolution of deformation estimates, the approach has rarely been considered or investigated thus far. This study assesses the performance of vertical displacement estimates from GRACE/GRACE-FO, the PCRaster Global Water Balance (PCR-GLOBWB) hydrology model, and the GRACE/GRACE-FO DA approach (assimilating GRACE/GRACE-FO into PCR-GLOBWB) in CSEA, where measurements from six GPS sites are available for validation. The results show that GRACE/GRACE-FO, PCR-GLOBWB, and GRACE/GRACE-FO DA accurately capture regional-scale hydrologic- and flood-induced vertical displacements, with the correlation value and RMS reduction relative to GPS measurements up to 0.89 and 53%, respectively. The analyses also confirm the GRACE/GRACE-FO DA’s effectiveness in providing vertical displacement estimates consistent with GRACE/GRACE-FO data while maintaining high-spatial details of the PCR-GLOBWB model, highlighting the benefits of GRACE/GRACE-FO DA in data-sparse regions.

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“…Deformation of the sea floor and surface displacements of the adjacent lands up to several centimeters result from the elastic response of the Earth's crust to ocean tides (tidal loading) [12]. The ocean is also responsible for the so-called non-tidal ocean loading [13][14][15]. These changes of the ocean bottom pressure are due to different processes-namely, the internal mass redistribution of the ocean driven by atmospheric circulation, the global water cycle, and a change in the integrated atmospheric mass over the ocean areas [14].…”

Section: Introductionmentioning

confidence: 99%

“…During the past two decades at least, many studies have been published describing the seasonal variability of the GPS-estimated heights in response to the force exerted by different types of environmental loads. Among others, recent contributions include the following [11,[15][16][17][18]. Long-term signals due to different natural and anthropogenic processes may also characterize the GPS height time series [1,19].…”

Section: Introductionmentioning

confidence: 99%

Interannual Variability of GPS Heights and Environmental Parameters over Europe and the Mediterranean Area

2021

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Vertical deformations of the Earth’s surface result from a host of geophysical and geological processes. Identification and assessment of the induced signals is key to addressing outstanding scientific questions, such as those related to the role played by the changing climate on height variations. This study, focused on the European and Mediterranean area, analyzed the GPS height time series of 114 well-distributed stations with the aim of identifying spatially coherent signals likely related to variations of environmental parameters, such as atmospheric surface pressure (SP) and terrestrial water storage (TWS). Linear trends and seasonality were removed from all the time series before applying the principal component analysis (PCA) to identify the main patterns of the space/time interannual variability. Coherent height variations on timescales of about 5 and 10 years were identified by the first and second mode, respectively. They were explained by invoking loading of the crust. Single-value decomposition (SVD) was used to study the coupled interannual space/time variability between the variable pairs GPS height–SP and GPS height–TWS. A decadal timescale was identified that related height and TWS variations. Features common to the height series and to those of a few climate indices—namely, the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), the East Atlantic (EA), and the multivariate El Niño Southern Oscillation (ENSO) index (MEI)—were also investigated. We found significant correlations only with the MEI. The first height PCA mode of variability, showing a nearly 5-year fluctuation, was anticorrelated (−0.23) with MEI. The second mode, characterized by a decadal fluctuation, was well correlated (+0.58) with MEI; the spatial distribution of the correlation revealed, for Europe and the Mediterranean area, height decrease till 2015, followed by increase, while Scandinavian and Baltic countries showed the opposite behavior.

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Correcting GPS measurements for non-tidal loading

Cited by 51 publications

References 45 publications

Reconstructing GRACE-type time-variable gravity from the Swarm satellites

Reconstructing GRACE-type time-variable gravity from the Swarm satellites

The Assessment of Hydrologic- and Flood-Induced Land Deformation in Data-Sparse Regions Using GRACE/GRACE-FO Data Assimilation

Interannual Variability of GPS Heights and Environmental Parameters over Europe and the Mediterranean Area

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