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GOCE ITALY

GOCE ITALY. scientific tasks and first results. Fernando Sansò and the GOCE Italy group. General Purpose. A research project supported by ASI to study scientific applications of GOCE solutions

richard-gibbs
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GOCE ITALY

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  1. GOCE ITALY scientifictasks and first results Fernando Sansò and the GOCE Italy group

  2. General Purpose A research project supported by ASI to study scientific applications of GOCE solutions to Earth sciences and engineering, in particular intermediary products of the space-wise solution.

  3. In the “corners” of the space-wise solution (grids of gradients at satellite altitude) there is more information, in particular locally, than what can be expressed in terms of a global truncated spherical harmonics expansion. A Scientificconjecture

  4. Local applications with GOCE data Geoid ondulation errors of Piemonte (Italy) using ground Δg (on the right) plus GOCE Trr (on the left)

  5. Local applications with GOCE data Mean dynamic sea surface topography (MDSST) using ground Δg, N from altimetry plus GOCE Trr and T

  6. Solid Earth signal in Gravity Data An example of time variable gravity Post Glacial Rebound (PGR) fingerprint mGal/yr The static gravity together with the dynamic component allows us to better constrain the Earth model for PGR simulation.

  7. Solid Earth signal in Gravity Data Some examples of static gravity PGR fingerprint By changing Earth parameters, in particular mantle viscosity, we get different patterns for the PGR fingerprint in the static gravity.

  8. GOCE marine geoid and geostrophic currents Best tidal model for correction of GOCE data Targets and Structureof GOCE Italy 1 PoliMi 2 UniMi 3 UniPd 4 OGS 5 ALTEC 6 UniTs Global gravity field Solid earth dynamics: analysis of directsignals The GOCE POD recomputed Verylocal geoids for engineering and civilprotection (test area Piemonte) Archive of geological signals in GOCE observable Local gravity field GOCE and Post glacial rebound Flows of salt and temperature throughstraits (test area Mediterranean) A GOCE toolbox Interpretation for case studies South America Galileian Plus:Project management and engineeringsupport

  9. GOCE Italy website http://www.goceitaly.asi.it

  10. Here we concentrate only on one of the problems we want to tackle within the GOCE-Italy project: Combination of the GOCE model with an existing Global Gravity Model (e.g. EGM 08) First results already presented

  11. At satellite level, apply the Wiener Orbital Filter to damp measurement noise and shorten the timewise correlation length. Philosophy of the space-wise approach Trr Orbit At satellite level (or little below) predict grids of Trrand T by collocation on a sphere.

  12. The final result is estimate of the coefficients estimate of the (full) covariance function Philosophy of the space-wise approach Harmonic analysis of the grid at satellite level Monte Carlo tricks, empirical adjustments and iterations!

  13. The combination procedure • The target is: • Combine with • assuming to be block diagonal (by orders). • The problems are: • is too large to be inverted exactly (also a problem of conditioning of Monte Carlo approximation); but fortunately it is almost block diagonal; • we do not have a “normal matrix” for GOCE data, while has a known “normal matrix”

  14. The solution is in principal trivial: apply least squares to where is the projector on the coefficients up to the maximum degree of GOCE, and with the solution in the updating form: The combination procedure

  15. Remember: dimension of full but with prevailing blocks The problem is computability ≠0 ≠0

  16. Remember: dimension of block diagonal. The problem is computability 0 0 By orders

  17. Reordering of the unknowns 1 2 3 1 2 3 Always by order… but first 1, than 2, than 3 Reordered covariance matrix of the model TM

  18. Reordering of the unknowns AG is a block diagonal matrix Note that: So the numerical problem becomes: find such that block diagonal and compute

  19. Note that: in this way all coefficients with |m|≤ n ≤ NG and 0 ≤|m|≤ Ns are corrected, in particular also those of area 2. Expected results If we disregard the non-diagonal part of CG (i.e. RG) then only 1 will be corrected! -NG NG

  20. In a low degree simulation with a “realistic” CG we can see the effects of changes in error variances for coefficients in area 2 due to the non diagonal part of CG Expected results

  21. And then… …all the rest of the never ending story.

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