The gravimetric model of the Moho discontinuity is usually derived based on isostatic adjustment theories considering floating crust on the viscous mantle. In computation of such a model some a priori information about the density contrast between the crust and mantle and the mean Moho depth are required. Due to our poor knowledge about them they are assumed unrealistically constant. In this paper, our idea is to improve a computed gravimetric Moho model, by the Vening Meinesz-Moritz theory, using the seismic model in Fennoscandia and estimate the error of each model through a combined adjustment with variance component estimation process. Corrective surfaces of bi-linear, bi-quadratic, bi-cubic and multi-quadric radial based function are used to model the discrepancies between the models and estimating the errors of the models. Numerical studies show that in the case of using the bi-linear surface negative variance components were come out, the bi-quadratic can model the difference better and delivers errors of 2.7 km and 1.5 km for the gravimetric and seismic models, respectively. These errors are 2.1 km and 1.6 km in the case of using the bi-cubic surface and 1 km and 1.5 km when the multi-quadric radial base function is used. The combined gravimetric models will be computed based on the estimated errors and each corrective surface.
Airy G B 1855: Trans. Roy. Soc. (London), ser. B, 145, 1855.
Bassin C, Laske G, Mastersm T G 2000: EOS Trans AGU, 81, F897.
Mastersm T. G., '' (2000) 81EOS Trans AGU: F897-.
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Bjerhammar A 1962: On an explicit solution of the gravimetric boundary value problem for an ellipsoidal surface of reference. Tech. Rep., The Royal Institute of Technology, Division of Geodesy, Stockholm
Bjerhammar A., '', in On an explicit solution of the gravimetric boundary value problem for an ellipsoidal surface of reference, (1962) -.
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