Difference between revisions of "IC SG7"

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<big>'''JSG 0.7: Computational methods for high-resolution gravity field modelling and nonlinear dif-fusion filtering'''</big>
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<big>'''JSG 0.16: Earth’s inner structure from combined geodetic and geophysical sources'''</big>
  
Chairs: ''R. Čunderlík (Slovakia), K. Mikula (Slovakia)''<br>
+
Chairs: ''Robert Tenzer (China)''<br>
Affiliation: ''Comm. 2, 3 and GGOS''
+
Affiliation: ''Comm. 2 and 3''
  
 
__TOC__
 
__TOC__
 +
 
===Introduction===
 
===Introduction===
Efficient numerical methods and HPC (High Performance Computing) facilities provide new opportunities in many applications in geodesy. The goal of the IC SG is to apply numerical methods like the finite element method (FEM), finite volume method (FVM), boundary element method (BEM) and others mostly for gravity field modelling and non-linear filtering of data on the Earth’s surface. An advantage is that such numerical methods use finite elements as basis functions with local supports. Therefore a refinement of the discretization is very straightforward allowing adaptive refinement procedures as well.
+
 
In case of gravity field modelling, a parallelization of algorithms using the standard MPI (Message Passing Interface) procedures and computations on clusters with distributed memory allows to achieve global or local gravity field models of very high-resolution, where a level of the discretization practically depends on capacity of available HPC facilities. The aforementioned numerical methods allow a detailed discretization of the real Earth’s surface considering its topography. To get precise numerical solution to the geodetic boundary-value problems (BVPs) on such complicated surface it is also necessary handle problems like the oblique derivative.
+
The satellite gravimetry missions, CHAllenging Mini-satellite Payload (CHAMP), the GRavity field and Climate Experiment (GRACE) and the Gravity field and steady-state Ocean Circulation Explorer (GOCE), significantly improved our knowledge on the external gravitational field of the Earth at the long-to-medium wavelengths (approximately up to a spherical harmonic degree of 250). Such improved information in terms of the accuracy and resolution has been utilized in studies of the Earth’s interior for a better understanding of the Earth’s inner structure and processes occurring within the lithosphere and sub-lithospheric mantle. Whereas the long-wavelength spectrum of the Earth’s gravitational field comprises mainly the signature of deep mantle density heterogeneities attributed to mantle convection, the medium wavelengths reflect the density structure of more shallow sources within the lithosphere. This allows studying and interpreting in more detail the gravitational features which are related to the global tectonism (including the oceanic subduction, orogenic formations, earthquakes, global lithospheric plate configuration, etc.), sub-lithospheric stresses, isostatic mechanisms, glacial isostatic adjustment, and other related geodynamic phenomena. Moreover, the Global Gravitational Models (GGMs) have been extensively used in studies of the lithospheric density structure and density interfaces such as for the gravimetric recovery of the Moho depth, lithospheric thickness as well as structure of sedimentary basins.
Data filtering occurs in many applications of geosciences. A quality of filtering is essential for correct interpretations of obtained results. In geodesy we usually use methods based on the Gaussian filtering that corresponds to a linear diffusion. Such filtering has a uniform smoothing effect, which also blurs “edges” representing important structures in the filtered data. In contrary, a nonlinear diffusion allows adaptive smoothing that can preserve main structures in data, while a noise is effectively reduced. In image processing there are known at least two basic nonlinear diffusion models; (i) the regularized Perona-Malik model, where the diffusion coefficient depends on an edge detector, and (ii) the geodesic mean curvature flow model based on a geometrical diffusion of level-sets of the image intensity.
+
 
The aim of the SG is to investigate and develop nonlinear filtering methods that would be useful for a variety of geodetic data, e.g., from satellite missions, satellite altimetry and others. A choice of an appropriate numerical technique is open to members of the SG. An example of the proposed approach is based on a numerical solution of partial differential equations using a surface finite volume method. It leads to a semi-implicit numerical scheme of the nonlinear diffusion equation on a closed surface.
+
Since the gravity observations could not be used alone to interpret the Earth’s inner density structure due to a non-uniqueness of inverse solutions (i.e. infinity many 3-D density structures could be attributed to the Earth’s gravity field), additional information is required to constrain the gravimetric methods for interpreting the Earth’s interior. These constraining data comprise primarily results of seismic surveys as well as additional geophysical, geothermal and geochemical parameters of the Earth. Moreover, numerous recent gravimetric studies of the Earth’s interior focus on the global and regional Moho recovery. The classical isostatic models (according to Airy and Pratt theories) are typically not able to model realistically the actual Moho geometry, due to the fact that the isostatic mass balance depends on loading and effective elastic thickness, rigidity, rheology of the lithosphere and viscosity of the asthenosphere. Moreover, geodynamic processes such as the glacial isostatic adjustment, present-day glacial melting, plate motion and mantle convection contribute to the time-dependent isostatic balance. To overcome these issues, processing strategies of combining gravity and seismic data (and possibly also additional constraining information) have to be applied to determine the actual Moho geometry.  
 +
 
 +
The gravimetric methods applied in studies of the Earth’s inner density structure comprise - in principle - two categories. The methods for the gravimetric forward modeling are applied to model (and remove) the gravitational signature of known density structures in order to enhance the gravitational contribution of unknown (and sought) density structures and interfaces. The gravimetric inverse methods are then used to interpret these unknown density structures from the refined gravity data. It is obvious that the combination of gravity and seismic data (and other constraining information) is essential especially in solving the gravimetric inverse problems.  
 +
 
 +
This gives us the platform and opportunities towards improving the theoretical and numerical methods applied in studies of Earth’s interior from multiple data sources, primarily focusing but not restricting only to combining gravimetric and seismic data. It is expected that the gravity data could improve our knowledge of the Earth’s interior over significant proportion of the world where seismic data are sparse or completely absent (such large parts of oceanic areas, Antarctica, Greenland and Africa). The gravity data could also provide additional information on the lithospheric structure and mechanisms, such as global tectonic configuration, geometry of subducted slabs, crustal thickening of orogenic formations and other phenomena.
  
 
===Objectives===
 
===Objectives===
  
* to develop numerical models for solving the geodetic BVPs using numerical methods like FEM, FVM, BEM and others,
+
* Development of the theoretical and numerical algorithms for combined processing of gravity, seismic and other types of geophysical data for a recovery of the Earth’s density structures and interfaces.
* to investigate the problem of oblique derivative,
+
* Development of fast numerical algorithms for combined data inversions.
* to implement parallelization of numerical algorithms using the standard MPI procedures,
+
* Development of stochastic models for combined inversion including optimal weighting, regularization and spectral filtering. 
* to perform large-scale parallel computations on clusters with distributed memory,
+
* Better understanding of uncertainties of interpreted results based on the error analysis of input data and applied numerical models. Geophysical and geodynamic clarification of results and their uncertainties.
* to investigate methods for nonlinear filtering of data on closed surfaces using the regularized Perona-Malik model or mean curvature flow model,
+
* Recommendations for optimal data combinations, better understanding of possibilities and limiting factors associated with individual data types used for geophysical and geodynamic interpretations.
* to derive fully-implicit and semi-implicit numerical schemes for the linear and nonlinear diffusion equation on closed surfaces using the surface FVM,
 
* to develop algorithms for the nonlinear filtering of data on the Earth’s surface,
 
* to summarize the developed methods and achieved numerical results in journal papers.
 
  
 
===Program of activities===
 
===Program of activities===
active participation in major geodetic conferences,
+
 
working meetings at international symposia,
+
* Launching of a web page with emphasis on exchange of ideas and recent progress, providing and updating bibliographic list of references of research results and relevant publications from different disciplines.
organization of a conference session.
+
* Work progress meetings at the international symposia and presentation of research results at the appropriate sessions.
 +
* Possible collaboration between various geoscience study groups dealing with the modeling of the Earth’s interior and related scientific topics.  
  
 
===Members===
 
===Members===
  
'' '''Róbert Čunderlík (Slovakia), chair<br />
+
'' '''Robert Tenzer (China), chair''' <br /> Lars Sjöberg (Sweden) <br /> Mohammad Bagherbandi (Sweden) <br /> Carla Braitenberg (Italy) <br /> Mehdi Eshagh (Sweden) <br /> Mirko Reguzzoni (Italy) <br /> Xiaodong Song (USA) <br />''
Karol Mikula (Slovakia), chair'''<br />
 
Ahmed Abdalla, New Zealand<br />
 
Michal Beneš (Czech Republic)<br />
 
Zuzana Fašková (Slovakia)<br />
 
Marek Macák (Slovakia)<br />
 
Otakar Nesvadba (Czech Republic)<br />
 
Róbert Špir (Slovakia)<br />
 
Róbert Tenzer (New Zealand)<br />''
 

Latest revision as of 15:24, 24 April 2016

JSG 0.16: Earth’s inner structure from combined geodetic and geophysical sources

Chairs: Robert Tenzer (China)
Affiliation: Comm. 2 and 3

Introduction

The satellite gravimetry missions, CHAllenging Mini-satellite Payload (CHAMP), the GRavity field and Climate Experiment (GRACE) and the Gravity field and steady-state Ocean Circulation Explorer (GOCE), significantly improved our knowledge on the external gravitational field of the Earth at the long-to-medium wavelengths (approximately up to a spherical harmonic degree of 250). Such improved information in terms of the accuracy and resolution has been utilized in studies of the Earth’s interior for a better understanding of the Earth’s inner structure and processes occurring within the lithosphere and sub-lithospheric mantle. Whereas the long-wavelength spectrum of the Earth’s gravitational field comprises mainly the signature of deep mantle density heterogeneities attributed to mantle convection, the medium wavelengths reflect the density structure of more shallow sources within the lithosphere. This allows studying and interpreting in more detail the gravitational features which are related to the global tectonism (including the oceanic subduction, orogenic formations, earthquakes, global lithospheric plate configuration, etc.), sub-lithospheric stresses, isostatic mechanisms, glacial isostatic adjustment, and other related geodynamic phenomena. Moreover, the Global Gravitational Models (GGMs) have been extensively used in studies of the lithospheric density structure and density interfaces such as for the gravimetric recovery of the Moho depth, lithospheric thickness as well as structure of sedimentary basins.

Since the gravity observations could not be used alone to interpret the Earth’s inner density structure due to a non-uniqueness of inverse solutions (i.e. infinity many 3-D density structures could be attributed to the Earth’s gravity field), additional information is required to constrain the gravimetric methods for interpreting the Earth’s interior. These constraining data comprise primarily results of seismic surveys as well as additional geophysical, geothermal and geochemical parameters of the Earth. Moreover, numerous recent gravimetric studies of the Earth’s interior focus on the global and regional Moho recovery. The classical isostatic models (according to Airy and Pratt theories) are typically not able to model realistically the actual Moho geometry, due to the fact that the isostatic mass balance depends on loading and effective elastic thickness, rigidity, rheology of the lithosphere and viscosity of the asthenosphere. Moreover, geodynamic processes such as the glacial isostatic adjustment, present-day glacial melting, plate motion and mantle convection contribute to the time-dependent isostatic balance. To overcome these issues, processing strategies of combining gravity and seismic data (and possibly also additional constraining information) have to be applied to determine the actual Moho geometry.

The gravimetric methods applied in studies of the Earth’s inner density structure comprise - in principle - two categories. The methods for the gravimetric forward modeling are applied to model (and remove) the gravitational signature of known density structures in order to enhance the gravitational contribution of unknown (and sought) density structures and interfaces. The gravimetric inverse methods are then used to interpret these unknown density structures from the refined gravity data. It is obvious that the combination of gravity and seismic data (and other constraining information) is essential especially in solving the gravimetric inverse problems.

This gives us the platform and opportunities towards improving the theoretical and numerical methods applied in studies of Earth’s interior from multiple data sources, primarily focusing but not restricting only to combining gravimetric and seismic data. It is expected that the gravity data could improve our knowledge of the Earth’s interior over significant proportion of the world where seismic data are sparse or completely absent (such large parts of oceanic areas, Antarctica, Greenland and Africa). The gravity data could also provide additional information on the lithospheric structure and mechanisms, such as global tectonic configuration, geometry of subducted slabs, crustal thickening of orogenic formations and other phenomena.

Objectives

  • Development of the theoretical and numerical algorithms for combined processing of gravity, seismic and other types of geophysical data for a recovery of the Earth’s density structures and interfaces.
  • Development of fast numerical algorithms for combined data inversions.
  • Development of stochastic models for combined inversion including optimal weighting, regularization and spectral filtering.
  • Better understanding of uncertainties of interpreted results based on the error analysis of input data and applied numerical models. Geophysical and geodynamic clarification of results and their uncertainties.
  • Recommendations for optimal data combinations, better understanding of possibilities and limiting factors associated with individual data types used for geophysical and geodynamic interpretations.

Program of activities

  • Launching of a web page with emphasis on exchange of ideas and recent progress, providing and updating bibliographic list of references of research results and relevant publications from different disciplines.
  • Work progress meetings at the international symposia and presentation of research results at the appropriate sessions.
  • Possible collaboration between various geoscience study groups dealing with the modeling of the Earth’s interior and related scientific topics.

Members

Robert Tenzer (China), chair
Lars Sjöberg (Sweden)
Mohammad Bagherbandi (Sweden)
Carla Braitenberg (Italy)
Mehdi Eshagh (Sweden)
Mirko Reguzzoni (Italy)
Xiaodong Song (USA)