• Keine Ergebnisse gefunden

Glacier clustersGlacier clusters

4.2.2 Observation Equations of the Fingerprint Inversion


Changes in the Stokes coefficients from GRACE are linked to the mass related components of the fingerprints. The unknown time varying magnitude can be linearly linked to the Stokes coefficients of GRACE:


... δCnmaxnmax


xice xglac xhydro


+e. (4.28)

Since mass is conserved globally, and the GRACE data has its reference frame origin in the center of mass of the Earth system, only coefficients with degrees larger than 1 are consid-ered. This automatically transforms all of the fingerprints to the CM frame. The unknown time varying magnitudes, are grouped in different mass contributions. xice represents the factors associated with the ice sheets in Greenland and Antarctica,xglac contain the mag-nitudes of the remaining (clusters of) land glaciers, and xhydro is linked to the terrestrial

6see also Eq.4.13for the spectral representation of a basin average

hydrological variations. The variations due to glacial isostatic adjustment effects are con-tained in the vectorxgia.

The columns of the design matrix A are composed of the corresponding fingerprints expressed in terms of normalized Stokes coefficients:

A(t) =

δC20Greenland1 δC20Greenland2 · · · δC20giaN(t−t0)

... ... ...

δCnGreenland1maxnmax δCnGreenland2maxnmax · · · δCngiamaxNnmax(t−t0)

. (4.29)

For convenience, the fingerprints of the ice sheets and the land glaciers are normalized such that its mass contribution represents 1 Gton. In this way, the unknown factorsxcan be directly interpreted as eustatic sea level contributions in the units Gtons. It should be noted that no such normalization is applied in the case of the GIA contribution. Since the present day GIA component of relative sea level rise is zero, a division by zero would be the result. Furthermore, a normalization is also not recommended when using EOFs as base functions (which is the case for the hydrological and steric parameters). Often, there are EOFs which have a (almost) zero contribution to sea level. A normalization would then induce large scale differences between the columns ofA.

The GIA induced signal has a secular nature, the corresponding GIA potential rates are therefore scaled by the time difference with respect to the reference timet0. For the release 05 GRACE data, the 1st of January 2005 is used, which is the reference time of the static background model Eigen-6c. Currently, the GIA component is the only time dependent factor in the design matrix. It is therefore smarter to store only the time independent part, without (t−t0), of the matrix and introduce this time dependency at the level of the nor-mal equations as described in App. C.5.

Monthly normal equations of GRACE release 05 are available up to degree and order 180. In addition to the standard de-aliasing models, the time variable component of the Eigen-6C is removed a priori (in the standard GRACE solutions, this signal is restored). To make the signal consistent with the altimetry data, the time varying component is restored on the normal equation level in accordance with App. C.3. On top of that, I also apply an a priori correction which ensures that the background de-aliasing model has a zero mean over the ocean. This makes the signal content consistent with that of the altimeters, and it prevents the background models to introduce artificial changes in the ocean mean. The latter potentially cause (systematic) errors in the estimated parameters.

This large truncation degree of the normal equation systems does not allow a direct so-lution of all the Stokes coefficients. However using the transformation method of App.

C.5, the normal equation systems may be transformed in terms of fingerprint magnitudes, without the need for solving but with retaining the full information up to degree and or-der 150. Coefficients with degrees larger than 150 are eliminated from the normal equation systems.


bGRC =ATb, (4.30)

[lTPl] =lTPl. (4.31)

The transformation operation drastically reduces the amount of unknowns, and thus the storage requirements, of the normal equation system from approximately 23000 to only about 125 (the number of mass related fingerprints).


As explained in Sec.3.2.1, an altimeter is sensitive to changes in the geoid height. In addi-tion, the range measurement is also affected by changes in the volume of the ocean basin and ocean-wide shifts due to the changing ocean mass. The altimetric observable for each surface loading fingerprint therefore consists of the (elastic) term ˜S+U. The GIA compo-nent has the same form.

Similar to GRACE, a linear observation equation can be constructed for the corrected altimetry data (see Eq.3.7):





xice xglac xhydro



 tx ty tz


+e. (4.32)

The columns of matrix B contain the geocentric sea level changes associated with the unknown patterns:

B(t) =

00Greenland1Greenland200 · · · S˜gia00N(t−t0) aδC10Greenland1 aδC10Greenland2 · · · aδC10giaN(t−t0)

... ... ...

aδCnGreenland1maxnmax aδCGreenland2nmaxnmax · · · aδCngiamaxNnmax(t−t0)

. (4.33)

here, the Stokes coefficients scaled by the Earth radiusarepresent the induced geoid changes.

To be as close to the altimeter reference system as possible, the geoid changes are provided in the CF system, by choosing the appropriate degree 1 coefficients. The matrixYmaps the patterns, expressed in spherical harmonics, to the locations of the altimeter measurements:


00(θ1,λ1) · · · Y¯nmaxnmax(θ1,λ1)

... ... ...

00(θM,λM) · · · Y¯nmaxnmax(θM,λM)

. (4.34)

The amount of rows ofYcan reach several hundred thousand. From a storage perspective it is therefore advised not to compute the matrixYexplicitly.

The steric EOFs, provided on a geographic grid, are stacked in the matrixC. These are then interpolated to the altimeter points by means of the (sparse) bi-linear interpolation


Finally, a set of correction parameters is introduced, which may absorb remaining differ-ences between the origin of the altimeter measurements (a CN frame) and the CF frame.

The estimated offset is expected to be small as the origin of the reference system of the al-timeters is expected to be close to the center of surface figure (CF). This issue is further elab-orated upon in Sec4.2.4. For each observation, the translation vector,

tx ty tzT

CNCF, is projected onto the local radial direction by matrixP



... eTM,h


sinθ1cosλ1 sinθ1sinλ1 cosθ1

... ... ...

sinθMcosλM sinθMsinλM cosθM

. (4.35)

When all the unknowns are stacked in one vector the resulting observation equation is described by:






xglac xhydro

xgia xster




xglac xhydro

xgia xster


+e. (4.36)

For each altimeter, the normal equations can now be build by using the range error as a diagonal error-covariance,Calt=diag

σ∆h21· · ·σ∆h2M. Similar to the GRACE processing, the introduction of the secular time dependency is postponed until after the assembly of the normal equations. It now also becomes clear what the advantage of the OpenADB altimeter data is. In the so-called ’BINS’ format, the altimeter data is sampled in bins which do not change position in time. This means that for each mission (here Jason 1, Jason 1 extended mission, and Jason 2), a design matrixDcan be precomputed (each one is approximately 700 Mb) and stored on disk. The normal equation systems are transformed according to

Nalt=DTCalt1D, (4.37)

balt=DTCalt1∆h, (4.38)

[l0TPl0]alt=∆hTCalt1∆h. (4.39) A screening of the data has been performed, before the assembly of the normal equation systems to reduce the effect of outliers and seasonal sea-ice at the higher latitudes. For this means, data with excessive large sea level anomalies and range errors (magnitudes larger than 1 m), have been excluded. In addition, a sea-ice mask, derived from the maximum sea-ice extent (Cavalieri et al.,1996) has been applied to the data. This step removes valid measurements in the summer months, and reduces the maximum latitude reached. At the same time however, a potential seasonal aliasing of high latitude signal is also avoided (data at the higher latitudes is constrained only during the summer months).