Author:
Wu Yihao,Luo Zhicai,Zhong Bo,Xu Chuang
Abstract
Abstract. A multilayer approach is set up for local gravity field recovery
within the framework of multi-resolution representation, where the gravity
field is parameterized as the superposition of multiple layers of Poisson
wavelets located at different depths beneath the Earth's surface. The layers
are designed to recover gravity signals at different scales, where the
shallow and deep layers mainly capture the short- and long-wavelength
signals, respectively. The depths of these layers are linked to the locations
of different anomaly sources beneath the Earth's surface, which are estimated
by wavelet decomposition and power spectrum analysis. For testing the
performance of this approach, a gravimetric quasi-geoid model over the North
Sea, QGNSea V1.0, is modeled and validated against independent control data.
The results show that the multilayer approach fits the gravity data better
than the traditional single-layer approach, particularly in regions with
topographical variation. An Akaike information criterion (AIC) test shows
that the multilayer model obtains a smaller AIC value and achieves a better
balance between the goodness of fit of data and the simplicity of the model.
Further, an evaluation using independent GPS/leveling data tests the ability
of regional models computed from different approaches towards realistic
extrapolation, which shows that the accuracies of the QGNSea V1.0 derived
from the multilayer approach are better by 0.4, 0.9, and 1.1 cm in the
Netherlands, Belgium, and parts of Germany, respectively, than that using the
single-layer approach. Further validation with existing models shows that
QGNSea V1.0 is superior with respect to performance and may be beneficial for
studying ocean circulation between the North Sea and its neighboring waters.
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