Difference between revisions of "JSG T.32"

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(Created page with "<big>'''JSG 0.19: High resolution harmonic analysis and synthesis of potential fields'''</big> Chair: ''Sten Claessens (Australia)''<br> Affiliation:''Comm. 2 and GGOS'' __T...")
 
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<big>'''JSG 0.19: High resolution harmonic analysis and synthesis of potential fields'''</big>
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<big>'''JSG 0.19: Time series analysis in geodesy'''</big>
  
Chair: ''Sten Claessens (Australia)''<br>
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Chair: ''Wieslaw Kosek (Poland)''<br>
Affiliation:''Comm. 2 and GGOS''
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Affiliation:''Comm. 3 and GGOS''
  
 
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__TOC__
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===Terms of Reference===
 
===Terms of Reference===
  
The gravitational fields of the Earth and other celestial bodies in the Solar System are customarily represented by a series of spherical harmonic coefficients. The models made up of these harmonic coefficients are used widely in a large range of applications within geodesy. In addition, spherical harmonics are now used in many other areas of science such as geomagnetism, particle physics, planetary geophysics, biochemistry and computer graphics, but one of the first applications of spherical harmonics was related to the gravitational potential, and geodesists are still at the forefront of research into spherical harmonics. This holds true especially when it comes to the extension of spherical harmonic series to ever higher degree and order (d/o).
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Observations of the space geodesy techniques and on the Earth's surface deliver a global picture of the Earth dynamics represented in the form of time series which describe 1) changes of the Earth surface geometry, 2) the fluctuations in the Earth orientation, and 3) the variations of the Earth’s gravitational field. The Earth's surface geometry, rotation and gravity field are the three components of the Global Geodetic Observing System (GGOS) which integrates them into one unique physical and mathematical model. However, temporal variations of these three components represent the total, integral effect of all global mass exchange between all elements of the Earth’s system including the Earth's interior and fluid layers:  atmosphere, ocean and land hydrology.
The maximum d/o of spherical harmonic series of the Earth’s gravitational potential has risen steadily over the past decades. The highest d/o models currently listed by the International Centre for Global Earth Models (ICGEM) have a maximum d/o of 2190. In recent years, spherical harmonic models of the topography and topographic potential to d/o 10,800 have been computed, and with ever-increasing computational prowess, expansions to even higher d/o are feasible. For comparison, the current highest-resolution global gravity model has a resolution of 7.2” in the space domain, which is roughly equivalent to d/o 90,000 in the frequency domain, while the highest-resolution global Digital Elevation Model has a resolution of 5 m, equivalent to d/o ~4,000,000.
 
  
The increasing maximum d/o of harmonic models has posed and continues to pose both theoretical and practical challenges for the geodetic community. For example, the computation of associated Legendre functions of the first kind, which are required for spherical harmonic analysis and synthesis, is traditionally subject to numerical instabilities and underflow/overflow problems. Much progress has been made on this issue by selection of suitable recurrence relations, summation strategies, and use of extended range arithmetic, but further improvements to efficiency may still be achieved.  
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Different time series analysis methods have been applied to analyze all these geodetic time series for better understanding of the relations between all elements of the Earth’s system as well as their geophysical causes. The interactions between different components of the Earth’s system are very complex so the nature of considered signals in the geodetic time series is mostly wideband, irregular and non-stationary. Thus, it is recommended to apply wavelet based spectra-temporal analysis methods to analyze these geodetic time series as well as to explain their relations to geophysical processes in different frequency bands using time-frequency semblance and coherence methods. These spectra-temporal analysis methods and time-frequency semblance and coherence may be further developed to display reliably the features of the temporal or spatial variability of signals existing in various geodetic data, as well as in other source data sources.
  
There are further separate challenges in ultra-high d/o harmonic analysis (the forward harmonic transform) and synthesis (the inverse harmonic transform). Many methods for the forward harmonic transform exist, typically separated into least-squares and quadrature methods, and further comparison between the two at high d/o, including studying the influence of aliasing, is of interest. The inverse harmonic transform, including synthesis of a large variety of quantities, has received much interest in recent years. In moving towards higher d/o series, highly efficient algorithms for synthesis on irregular surfaces and/or in scattered point locations, are of utmost importance.  
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Geodetic time series include for example horizontal and vertical deformations of site positions determined from observations of space geodetic techniques. These site positions change due to e.g. plate tectonics, postglacial rebound, atmospheric, hydrology and ocean loading and earthquakes. However they are used to build the global international terrestrial reference frame (ITRF) which must be stable reference for all other geodetic observations including e.g. satellite orbit parameters and Earth's orientation parameters which consist of precession, nutation, polar motion and UT1-UTC that are necessary for transformation between the terrestrial and celestial reference frames. Geodetic time series include also temporal variations of Earth's gravity field where 1 arc-deg spherical harmonics correspond to the Earth’s centre of mass variations (long term mean of them determines the ITRF origin) and 2 degree spherical harmonics correspond to Earth rotation changes. Time series analysis methods can be also applied to analyze data on the Earth's surface including maps of the gravity field, sea level, ice covers, ionospheric total electron content and tropospheric delay as well as temporal variations of such surface data. The main problems to deal with include the estimation of deterministic (including trend and periodic variations) and stochastic (non-periodic variations and random changes) components of the geodetic time series as well as the application of digital filters for extracting specific components with a chosen frequency bandwidth.
  
Another question that has occupied geodesists for many decades is whether there is a substantial benefit to the use of oblate ellipsoidal (or spheroidal) harmonics instead of spherical harmonics. The limitations of the spherical harmonic series for use on or near the Earth’s surface are becoming more and more apparent as the maximum d/o of the harmonic series increase. There are still open questions about the divergence effect and the amplification of the omission error in spherical and spheroidal harmonic series inside the Brillouin surface.  
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The multiple methods of time series analysis may be encouraged to be applied to the preprocessing of raw data from various geodetic measurements in order to promote the quality level of enhancement of signals existing in these data. The topic on the improvement of the edge effects in time series analysis may also be considered, since they may affect the reliability of long-range tendency (trends) estimated from data series as well as the real-time data processing and prediction.
  
The Hotine-Jekeli transformation between spherical and spheroidal harmonic coefficients has proven very useful, in particular for spherical harmonic analysis of data on a reference ellipsoid. It has recently been improved upon and extended, while alternatives using surface spherical harmonics have also been proposed, but the performance of the transformations at very high d/o may be improved further. Direct use of spheroidal harmonic series requires (ratios of) associated Legendre functions of the second kind, and their stable and efficient computation is also of ongoing interest.
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For coping with small geodetic samples one can apply simulation-based methods and if the data are sparse, Monte-Carlo simulation or bootstrap technique may be useful. Understanding the nature of geodetic time series is very important from the point of view of appropriate spectral analysis as well as application of filtering and prediction methods.
  
 
===Objectives===
 
===Objectives===
  
The objectives of this study group are to:
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* Study of the nature of geodetic time series to choose optimum time series analysis methods for filtering, spectral analysis, time frequency analysis and prediction.
* Create and compare stable and efficient methods for computation of ultra-high degree and order associated Legendre functions of the first and second kind (or ratios thereof), plus its derivatives and integrals.
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* Study of Earth's geometry, rotation and gravity field variations and their geophysical causes in different frequency bands.
* Study the divergence effect of ultra-high degree spherical and spheroidal harmonic series inside the Brillouin sphere/spheroid.
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* Evaluation of appropriate covariance matrices for the time series by applying the law of error propagation to the original measurements, including weighting schemes, regularization, etc.
* Verify the numerical performance of transformations between spherical and spheroidal harmonic coefficients to ultra-high degree and order.
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* Determination of the statistical significance levels of the results obtained by different time series analysis methods and algorithms applied to geodetic time series.
* Compare least-squares and quadrature approaches to very high-degree and order spherical and spheroidal harmonic analysis.
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* Development and comparison of different time series analysis methods in order to point out their advantages and disadvantages.
* Study efficient methods for ultra-high degree and order harmonic analysis (the forward harmonic transform) for a variety of data types and boundary surfaces.
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* Recommendations of different time series analysis methods for solving problems concerning specific geodetic time series.
* Study efficient methods for ultra-high degree and order harmonic synthesis (the inverse harmonic transform) of point values and area means of all potential quantities of interest on regular and irregular surfaces.
 
  
 
===Program of activities===
 
===Program of activities===
  
* Providing a platform for increased cooperation between group members, facilitating and encouraging exchange of ideas and research results.
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* Launching of a website about time series analysis in geodesy providing list of papers from different disciplines as well as unification of terminology applied in time series analysis.
* Creating and updating a bibliographic list of relevant publications from both the geodetic community as well as other disciplines for the perusal of group members.
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* Working meetings at the international symposia and presentation of research results at the appropriate sessions.
* Organizing working meetings at international symposia and presenting research results in the appropriate sessions.
 
  
 
===Membership===
 
===Membership===
  
'' '''Sten Claessens (Australia), chair''' <br /> Hussein Abd-Elmotaal (Egypt) <br /> Oleh Abrykosov (Germany) <br /> Blažej Bucha (Slovakia) <br /> Toshio Fukushima (Japan) <br /> Thomas Grombein (Germany) <br /> Christian Gruber (Germany) <br /> Eliška Hamáčková (Czech Republic) <br /> Christian Hirt (Germany) <br /> Christopher Jekeli (USA) <br /> Otakar Nesvadba (Czech Republic) <br /> Moritz Rexer (Germany) <br /> Josef Sebera (Czech Republic) <br /> Kurt Seitz (Germany) <br />''
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'' '''Wieslaw Kosek (Poland), chair''' <br /> Michael Schmidt (Germany) <br /> Jan Vondrák (Czech Republic) <br /> Waldemar Popinski (Poland) <br /> Tomasz Niedzielski (Poland) <br /> Johannes Boehm (Austria) <br /> Dawei Zheng (China) <br /> Yonghong Zhou (China) <br /> Mahmut O. Karslioglu (Turkey) <br /> Orhan Akyilmaz (Turkey) <br /> Laura Fernandez (Argentina) <br /> Richard Gross (USA) <br /> Olivier de Viron (France) <br /> Sergei Petrov (Russia) <br /> Michel Van Camp (Belgium) <br /> Hans Neuner (Germany) <br /> Xavier Collilieux (France) <br />''

Revision as of 09:10, 29 April 2016

JSG 0.19: Time series analysis in geodesy

Chair: Wieslaw Kosek (Poland)
Affiliation:Comm. 3 and GGOS

Terms of Reference

Observations of the space geodesy techniques and on the Earth's surface deliver a global picture of the Earth dynamics represented in the form of time series which describe 1) changes of the Earth surface geometry, 2) the fluctuations in the Earth orientation, and 3) the variations of the Earth’s gravitational field. The Earth's surface geometry, rotation and gravity field are the three components of the Global Geodetic Observing System (GGOS) which integrates them into one unique physical and mathematical model. However, temporal variations of these three components represent the total, integral effect of all global mass exchange between all elements of the Earth’s system including the Earth's interior and fluid layers: atmosphere, ocean and land hydrology.

Different time series analysis methods have been applied to analyze all these geodetic time series for better understanding of the relations between all elements of the Earth’s system as well as their geophysical causes. The interactions between different components of the Earth’s system are very complex so the nature of considered signals in the geodetic time series is mostly wideband, irregular and non-stationary. Thus, it is recommended to apply wavelet based spectra-temporal analysis methods to analyze these geodetic time series as well as to explain their relations to geophysical processes in different frequency bands using time-frequency semblance and coherence methods. These spectra-temporal analysis methods and time-frequency semblance and coherence may be further developed to display reliably the features of the temporal or spatial variability of signals existing in various geodetic data, as well as in other source data sources.

Geodetic time series include for example horizontal and vertical deformations of site positions determined from observations of space geodetic techniques. These site positions change due to e.g. plate tectonics, postglacial rebound, atmospheric, hydrology and ocean loading and earthquakes. However they are used to build the global international terrestrial reference frame (ITRF) which must be stable reference for all other geodetic observations including e.g. satellite orbit parameters and Earth's orientation parameters which consist of precession, nutation, polar motion and UT1-UTC that are necessary for transformation between the terrestrial and celestial reference frames. Geodetic time series include also temporal variations of Earth's gravity field where 1 arc-deg spherical harmonics correspond to the Earth’s centre of mass variations (long term mean of them determines the ITRF origin) and 2 degree spherical harmonics correspond to Earth rotation changes. Time series analysis methods can be also applied to analyze data on the Earth's surface including maps of the gravity field, sea level, ice covers, ionospheric total electron content and tropospheric delay as well as temporal variations of such surface data. The main problems to deal with include the estimation of deterministic (including trend and periodic variations) and stochastic (non-periodic variations and random changes) components of the geodetic time series as well as the application of digital filters for extracting specific components with a chosen frequency bandwidth.

The multiple methods of time series analysis may be encouraged to be applied to the preprocessing of raw data from various geodetic measurements in order to promote the quality level of enhancement of signals existing in these data. The topic on the improvement of the edge effects in time series analysis may also be considered, since they may affect the reliability of long-range tendency (trends) estimated from data series as well as the real-time data processing and prediction.

For coping with small geodetic samples one can apply simulation-based methods and if the data are sparse, Monte-Carlo simulation or bootstrap technique may be useful. Understanding the nature of geodetic time series is very important from the point of view of appropriate spectral analysis as well as application of filtering and prediction methods.

Objectives

  • Study of the nature of geodetic time series to choose optimum time series analysis methods for filtering, spectral analysis, time frequency analysis and prediction.
  • Study of Earth's geometry, rotation and gravity field variations and their geophysical causes in different frequency bands.
  • Evaluation of appropriate covariance matrices for the time series by applying the law of error propagation to the original measurements, including weighting schemes, regularization, etc.
  • Determination of the statistical significance levels of the results obtained by different time series analysis methods and algorithms applied to geodetic time series.
  • Development and comparison of different time series analysis methods in order to point out their advantages and disadvantages.
  • Recommendations of different time series analysis methods for solving problems concerning specific geodetic time series.

Program of activities

  • Launching of a website about time series analysis in geodesy providing list of papers from different disciplines as well as unification of terminology applied in time series analysis.
  • Working meetings at the international symposia and presentation of research results at the appropriate sessions.

Membership

Wieslaw Kosek (Poland), chair
Michael Schmidt (Germany)
Jan Vondrák (Czech Republic)
Waldemar Popinski (Poland)
Tomasz Niedzielski (Poland)
Johannes Boehm (Austria)
Dawei Zheng (China)
Yonghong Zhou (China)
Mahmut O. Karslioglu (Turkey)
Orhan Akyilmaz (Turkey)
Laura Fernandez (Argentina)
Richard Gross (USA)
Olivier de Viron (France)
Sergei Petrov (Russia)
Michel Van Camp (Belgium)
Hans Neuner (Germany)
Xavier Collilieux (France)