Towards the Combination of Data Sets from Various Observation Techniques

Schmidt, Michaël; Göttl, Franziska; Heinkelmann, Robert

doi:10.1007/978-3-319-10828-5_6

Cited by 8 publications

(4 citation statements)

References 12 publications

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“…In this research, we additionally demonstrate that: (1) different observation types can be introduced into the evaluation model at the spectral level of their highest sensitivities, which makes it possible to benefit from the individual strengths of each data set optimally; (2) since all computations within the pyramid algorithm are based on linear equation systems (Schmidt et al 2015), all covariance information can easily be calculated following the law of error propagation from the higher levels and serve as input for the lower levels; (3) as the number of required SRBFs decreases from the highest level to the lower levels, the design matrices of the lowerresolution data sets are now calculated with a smaller number of grid points, which reduces the computational effort significantly. We test the MRR based on the pyramid algorithm by using simulated data and then apply it to real data in different study areas.…”

Section: Introductionmentioning

confidence: 82%

Combination of different observation types through a multi-resolution representation of the regional gravity field using the pyramid algorithm and parameter estimation

Liu¹,

Schmidt²,

Sánchez³

2022

J Geod

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The optimal combination of different types of gravity observations is the key to obtaining a high-resolution and high-precision regional gravity model. Current studies based on spherical radial basis functions (SRBFs) majorly consider a single-level approach for data combination. Despite the promising results reported in numerous publications, it has been suspected that the single-level model might be biased towards high-resolution measurements. Instead, a multi-resolution representation (MRR) can be applied to further take into consideration the varying spectral sensitivities of different observation techniques. In this study, we develop a new MRR scheme based on the pyramid algorithm and sequential parameter estimation. We propose strategies to solve the challenges in the practical application of the pyramid algorithm, and this study represents its first successful realization in regional gravity field modeling. The modeling results based on both simulated and real gravity data show that either the single-level approach or the MRR without pyramid algorithm is able to capture gravity information from lower resolution measurements as sufficient as our newly developed MRR algorithm. In the simulated case, the RMS error w.r.t. the validation data obtained by the MRR based on the pyramid algorithm decreases by 50% and 35%, in comparison to that of the single-level model and the MRR without pyramid algorithm, respectively. In the real case, the improvement achieved by the MRR based on the pyramid algorithm is 35% and 23% in the onshore area, and it reaches 63% and 57% in the offshore area, compared to the single-level approach and the MRR without pyramid algorithm, respectively.

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Section: Introductionmentioning

confidence: 82%

Combination of different observation types through a multi-resolution representation of the regional gravity field using the pyramid algorithm and parameter estimation

Liu¹,

Schmidt²,

Sánchez³

2022

J Geod

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“…In contrast to the rigorous combination at one level J presented here, a spectral combination at different levels might optimize the results. We plan further investigations by applying a MRR (mentioned in section 3.1.5) and implementing a pyramid algorithm for a step‐by‐step combination of those observations [see Schmidt et al , ], which contribute most at corresponding resolution levels.…”

Section: Discussionmentioning

confidence: 99%

Combination of various observation techniques for regional modeling of the gravity field

Lieb¹,

Schmidt²,

Dettmering³

et al. 2016

JGR Solid Earth

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Modeling a very broad spectrum of the Earth's gravity field needs observations from various measurement techniques with different spectral sensitivities. Typically, high‐resolution regional gravity data are combined with low‐resolution global observations. To exploit the gravitational information as optimally as possible, we set up a regional modeling approach using radial spherical basis functions, emphasizing the strengths of various data sets by the flexible combination of high‐ and middle‐resolution terrestrial, airborne, shipborne, and altimetry measurements. The basis functions are defined and located in the region of interest in such a manner, which the highest measure of information of the input data is captured. Any functional of the Earth's gravity field can be derived, as, e.g., quasi‐geoid heights or gravity anomalies. Here we present results of a study area in Northern Germany. A comprehensive cross validation to external observation data delivers standard deviations less than 5 cm. Differences to an existing regional quasi‐geoid model count on average ±6 cm and proof the plausibility of our solution. The comparison with existing global models reaches higher standard deviations for the more sensitive gravity anomalies as for quasi‐geoid heights, showing the additional value of our solution in the high frequency domain. Covering a broad frequency spectrum, our regional models can be used as basis for various applications, such as refinement of global models, national geoid determination, and detection of mass anomalies in the Earth's interior.

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“…A proper combination of the excitation functions from GRACE and altimetry requires accounting for the different accuracy levels of the observation methods in the stochastic model. Traditionally, this is done by using variance component estimation (VCE) as outlined, e.g., by Koch [1999] or Schmidt et al [2012]. In our case, it seems not reasonable to apply VCE because we do not know the complete stochastic model of the gravimetric and altimetric input data.…”

Section: Combination and Validationmentioning

confidence: 98%

Combination of gravimetric and altimetric space observations for estimating oceanic polar motion excitations

Göttl¹,

Schmidt²,

Heinkelmann³

et al. 2012

J. Geophys. Res.

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[1] Global dynamic processes cause variations in the Earth's rotation, which are monitored by various geometric observation techniques such as Global Navigation Satellite Systems (GNSS), Satellite Laser Ranging (SLR), and Very Long Baseline Interferometry (VLBI) with millimeter accuracy. The integral effect on Earth rotation of mass displacements and motion is therefore precisely known, but the separation of contributions from particular geodynamic processes remains a challenge. Here we show that the oceanic mass effect on Earth rotation can be derived from both time variable gravity field solutions from the Gravity Recovery And Climate Experiment (GRACE) and sea level anomalies (SLA) observed from satellite altimeter missions. The GRACE solutions require filtering and the application of an ocean mask, whereas the SLA need to be corrected for the steric effect as polar motion is only affected by mass redistributions. We assess the accuracy of our oceanic polar motion excitations by using GRACE and SLA solutions from different processing centers. In addition, we compare polar motion excitations from GRACE, satellite altimeter data and their combinations with excitations estimated from ocean models. We show that the combination of gravimetric and altimetric solutions reduces systematic errors of the individual solutions. The combined solutions are about 2 times more accurate than ocean model results and about 3 times more accurate than the so-called reduced geodetic excitation functions. We anticipate our analysis to be valuable input for improved modeling of oceanic mass redistributions.

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Towards the Combination of Data Sets from Various Observation Techniques

Cited by 8 publications

References 12 publications

Combination of different observation types through a multi-resolution representation of the regional gravity field using the pyramid algorithm and parameter estimation

Combination of different observation types through a multi-resolution representation of the regional gravity field using the pyramid algorithm and parameter estimation

Combination of various observation techniques for regional modeling of the gravity field

Combination of gravimetric and altimetric space observations for estimating oceanic polar motion excitations

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