Geocenter motion estimates from the IGS Analysis Center solutions P. Rebischung, X. Collilieux, Z....
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Transcript of Geocenter motion estimates from the IGS Analysis Center solutions P. Rebischung, X. Collilieux, Z....
Geocenter motion estimatesfrom the IGS Analysis Center
solutions
P. Rebischung, X. Collilieux, Z. AltamimiIGN/LAREG & GRGS
1EGU General Assembly, Vienna, 26 April 2012
Background
• Global GNSS solutions are sensitive to geocenter motion in two different ways:
2
Through orbit dynamics Through loading deformations
Background
• Main limitation of « orbit dynamics »:
• The non-gravitational forces acting on GNSS satellites are not modeled accurately enough.
→ ACs have to estimate empirical accelerations which correlate with the CM location (origin).
3
Example of accelerations that would be felt by a satellite if CM was shifted by 1 mm in the Z direction. Accelerations are shown in the « DYB » frame:
― D: Satellite-Sun axis
― Y: Rotation axis of solar panels
― B: Third axis
Correlations with some parameters of the CODE model are obvious (constant along D; once-per-rev along B).
Methodology
• Data:• Weekly solutions from 7 ACs (COD, EMR, ESA, GFZ, JPL, MIT, NGS)• 1998.0 – 2008.0 : reprocessed solutions• 2008.0 – 2011.3 : operational solutions
• Stacking:• For each AC, stack weekly solutions into a long-term piecewise linear
frame.
• Geocenter motion estimation:• Pseudo-Observations = weekly minus regularized position differences• Three possible models
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Methodology
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Network shift approach
CF approachaka degree-1 deformation approach
(Blewitt et al., 2001)
CM approach(Lavallée et al., 2006)
nmnnn1
nmCFii
max
σARXTδX
ii RXTδX
with degree-1 Love numbers in CF frame with degree-1 Love numbers in CM frame
Estim
ates
of r
CM-C
F
from
orb
it dy
nam
ics
from
load
ing
defo
rmati
ons
1,0
11,
1,1
σ2σ2σ
loadCFT
TshiftCFTTshiftT
In the CM approach,both information contribute to the same estimate
(because degree-1 deformations have a translational part in the CM frame).
nmnnn1
nmCMii
max
σARXδX
1,0
11,
1,1
σ2σ2σ
CMT
In the following, use:
• well-d
istributed sub-network
• identity weight m
atrix
In the following, use n max=5
In the following, use n max=5
• Sub-annual frequencies corrupted by (odd) draconitic harmonics
Z: network shift approach
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All ACs a
ffected
Z: network shift approach• Low frequencies well explained by
annual + 1st draconitic:
→ Progressive phase shift wrt SLR• Similar patterns for ACs using the CODE model• Different pattern for JPL (and EMR?)
• Underlying annual signal unreliable:
7
Z: CF approach
8
• Draconitics smaller than in the network shift approach:
Z: CF approach
9
• Annual signal in phase with SLR for all ACs, over the whole time period
• But amplitude over-estimated:
• Also found with simulations (see Collilieux et al., JoG 2012)
• Aliasing of >5-degree deformations?
Note on the CM approach
• CM approach ≈ weighted mean of orbit dynamics and loading deformations
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≈ 0.65 for X≈ 0.60 for Y≈ 0.45 for Z
≈ 0.35 for X≈ 0.40 for Y≈ 0.55 for Z
with nmax=5
Z: CM approach
11
)0.550.45( loadCFshiftCM ZZZ
• Some draconitics averaged; other cancelled (depending on their relative phases in Zshift and ZCF)
• ZCM alternately:• In good agreement with SLR;• ≈ 0;• Out-of-phase (recently, except JPL).
→ Is it really reasonable to make this weighted mean?
Z: CM approach
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)0.550.45( loadCFshiftCM ZZZ
X
• Network shift approach:• Draconitics up to 2 mm• Annual signal partly detected
• CF approach:• Draconitics as large as in net. shift• Annual signal in phase with SLR• Amplitude over-estimated
• CM approach:• Sometimes in good agreement
with SLR• But not always
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Y
• Network shift approach:• Draconitics up to 2 mm• Rather good annual signal
• CF approach:• Draconitics as large as in net. shift• Rather good annual signal• But slight phase shift for some ACs
• CM approach:• Strikingly good agreement with SLR• Net. shift & CF errors cancel out.
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Conclusions (1/2)
• Network shift (orbit dynamics):• All ACs affected by draconitics as large as « true » annual signal
• Effect of draconitics different for JPL (and EMR?) than for other ACs in Z(JPL’s first draconitic not in phase with other ACs)
• Underlying annual signals:• Unreliable in Z• Partly detected in X• Agrees well with SLR in Y
• CF approach (loading deformations):• Also corrupted by draconitics
• As large as in network shift in X & Y• But ~twice smaller in Z
• Annual signals in phase with SLR• But amplitudes over-estimated in X & Z
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Conclusions (2/2)
• CM approach (≈ weighted average):
• In X & Z, network shift and CF errors cancel sometimes out,but not always.
→ Isn’t the unification of orbit dynamics and loading deformations questionable?
• Strikingly good results in Y: network shift and CF errors cancel out.→ Why?
16
Additional slides
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Note on the network shift approach
• Using raw cov. matrices gives unrealistic results:
• Shift estimates are perturbedby correlations with degree-1deformations.
•
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≈ 0.5 for X & Y≈ 0.8 for Z
X
19
Y
20
Z
21
X: draconitic harmonicsRadius = 2 mm
22
Network shift
CF
CM
1st 2nd 3rd 4th 5th 6th 7th
23
Network shift
CF
CM
Y: draconitic harmonicsRadius = 2 mm
1st 2nd 3rd 4th 5th 6th 7th
24
Network shift
CF
CM
Z: draconitic harmonicsRadius = 5 mm
Radius = 10 mm1st 2nd 3rd 4th 5th 6th 7th