1. GRACE and geophysical applications
Annette Eicker
Institute of Geodesy and Geoinformation
University of Bonn
Petra:
PT coeff humid? (alpha?)
Das erste Mal Assimilierung in WGHM?
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2. Outline The GRACE mission - observation principle
What are the challenges?
Applications (examples)

3. The GRACE mission

4. Gravity Recovery and Climate Experiment
GRACE:
launch: March 2002
altitude: ~450 km
distance: ~250 km
orbit period: 94 min
polar orbit
JPL

5. GRACE Observations distance: ca. 250 000 000 000 μm
accuracy: 12 digits
Comparison:
average human hair: 0.05 mm => 50 μm
(keep in mind: speed: km/h)
K-band microwave ranging instrument accuracy: < 1 μm
GPS receiver: accuracy: 2-3 cm

6. GRACE results: gravity field
Long-term mean gravity field
(differences of gravity compared to ellipsoid)
gravity anomalies [mGal]

7. GRACE results: gravity field
Long-term mean gravity field
(differences of gravity compared to ellipsoid)
Temporal variations
e.g. monthly models

8. GRACE results: gravity field
First time observation of temporal gravity field variations on the global scale!
New measurement type for hydrology, oceanography, glaciology, geophysics…
download GRACE solutions:
Temporal variations
e.g. monthly models

9. But there are also some challenges….

10. Outline The GRACE mission - observation principle
What are the challenges?
Applications (examples)

11. Challenges Why can GRACE data be a little difficult? 1)
GRACE observes the gravity field from far away
=> Downward continuation 1)

12. Upward/downward continuation
Satellite altitude
[mgal]
Gravitational potential in spherical harmonics
6378 km km
450 km
( km)
(160 km)
(110 km)
Dampening factors
Ground level
[mgal]

13. Upward/downward continuation
Satellite altitude c
observation noise
dampening of small features (high frequencies)
GRACE sees only smoothed version of gravity field
Amplification of (high frequency) noise
[mgal]
noise
Ground level
[mgal]

14. Challenges Why can GRACE data be a little difficult? 1)
GRACE observes the gravity field from far away
=> Downward continuation
The gravity field changes continuously, but it takes
time to collect the data
=> Aliasing 2)

15. Ground tracks

16. GRACE It takes time to collect satellite data,
but the gravity field changes continuously
1 day
15 days
30 days

17. GRACE It takes time to collect satellite data,
but the gravity field changes continuously
tides:
tidal forces (sun, moon, planets)
Earth tides
ocean tides
atmospheric variations and the
reaction of the ocean
pole tides
Short-periodic gravity changes:
atmospheric variations

18. GRACE It takes time to collect satellite data,
but the gravity field changes continuously
tides:
tidal forces (sun, moon, planets)
Earth tides
ocean tides
atmospheric variations and the
reaction of the ocean
pole tides
Short-periodic gravity changes:
ocean tides

19. GRACE It takes time to collect satellite data,
but the gravity field changes continuously
Short-periodic gravity changes:
Models:
JPL DE405
IERS2003
EOT11a
AOD1B
OMCT
tides:
tidal forces (sun, moon, planets)
Earth tides
ocean tides
atmospheric variations and the
reaction of the ocean
pole tides
Short-term gravity variations have to be reduced
BUT: every model has errors

20. Aliasing residual signal (after reduction of models) monthly models
unmodelled variations
Undersampling of the short-term variations
=> „Aliasing“
This results in …

21. Monthly solution 2007 - 04 Why north-south stripes?
very high measurement accuracy along-track
sampling along the orbit => gravity field (unmodelled short-periodic effects) might have changed completely between neighboring arcs

22. Challenges Why can GRACE data be a little difficult? 1)
GRACE observes the gravity field from far away
=> Downward continuation 2)
The gravity field changes continuously, but it takes
time to collect the data
=> Aliasing
We have to do something about the noise
=> Filtering, Leakage 3)

23. Filtering
Gaussian filter
water height [cm]

24. Filtering
Gaussian filter
Filter: 200 km
water height [cm]

25. Filtering
Gaussian filter
Filter: 250 km
water height [cm]

26. Filtering
Gaussian filter
Filter: 300 km
water height [cm]

27. Filtering
Gaussian filter
Filter: 400 km
water height [cm]

28. Filtering Gaussian filter Filter: 500 km 2007 - 04
water height [cm]
stronger filtering => less noise
But:
filtering implies spatial averaging also of the signal
=> „Leakage effect“

29. (unfiltered, without noise)
Leakage
modelled signal
(unfiltered, without noise)
signal
(500 km Gauss filter)
stronger filtering => less noise
But:
filtering implies spatial averaging also of the signal
=> „Leakage effect“

30. (unfiltered, without noise)
Leakage
river basin
average:
7.4 cm/year
4.0 cm/year
modelled signal
(unfiltered, without noise)
signal
(500 km Gauss filter)
stronger filtering => less noise
But:
filtering implies spatial averaging also of the signal
=> „Leakage effect“

31. Leakage Leakage Leakage-Out Leakage-In
Filter
Signal original
Region of
interest
Leakage-Out
Leakage-In
stronger filtering => less noise
But:
filtering implies spatial averaging also of the signal
=> „Leakage effect“

32. Leakage Leakage Leakage-Out Leakage-In
Filter
Signal original
Region of
interest
Leakage-Out
Leakage-In
Generally damping of signal in region of interest
=> underestimation of amplitude
=> Estimation of re-scaling factor to obtain full signal.
(Can be difficult!)

33. Challenges Why can GRACE data be a little difficult? 1)
GRACE observes the gravity field from far away
=> Downward continuation 2)
The gravity field changes continuously, but it takes
time to collect the data
=> Aliasing 3)
We have to do something about the noise
=> Filtering, Leakage
GRACE observes the integral mass signal
=> Loading, Signal separation 4)

34. Loading
GRACE measures gravitational potential => conversion to mass
Mantle
Crust
Mass
But: GRACE has no depth perception

35. Loading
mass gain
mass loss
GRACE measures gravitational potential => conversion to mass
Mass
But: GRACE has no depth perception
Crust
Signal separation of variations at surface and in mantle using loading theory
Mantle
gravity field coefficients
equivalent
water height
elastic response of the Earth
(load love numbers)

36. Signal Separation Hydrology Ice Atmosphere Ocean
Separation of integral mass signal:
Reduction of unwanted signals
using models
=> Model errors included in mass
estimate
statistical / mathematical
approaches (e.g. PCA, ICA)
GIA
Mantle and Crust

37. Outline The GRACE mission - observation principle
What are the challenges?
Applications (examples)

38. GRACE results
(ITG-Grace03)
Already reduced: tides (ocean, Earth, …), atmosphere & ocean variations

39. water height [cm/year]
Trend and amplitude
Annual amplitude
Trend
water height [cm/year]
water height [cm]

40. Annual amplitude
water height [cm]

41. Hydrology
1gt = 1km³ water!
Amazon
[giga tons]

42. Hydrology
1gt = 1km³ water!
Amazon
[giga tons]
equator
Orinoco

43. Hydrology GRACE time series provide valuable information to
hydrologists
WHY?
Improvement of global
hydrological models
canopy
snow
soil
groundwater
local lakes
local wetlands
river
global wetlands
WaterGAP: models water storages
and flows on 0.5° x 0.5 ° grid
global lakes
(Döll et al 2003)
Problems: model physics, insufficient data coverage
(e.g. percipitation)

44. Hydrology
1gt = 1km³ water!
Amazon
GRACE
[giga tons]

45. Hydrology 1gt = 1km³ water! Amazon
GRACE
[giga tons]
Underestimation of amplitude in the model
WaterGAP
Possible solution: model calibration

46. Hydrology Underestimation of amplitude in the model!
GRACE
WaterGAP
WaterGAP calibrated
(Werth et al. 2009)
Underestimation of amplitude in the model!
Possible solution: model calibration

47. Trend 47

48. India

49. India GRACE Groundwater withdrawal seems to be detectable by GRACE
Rodell et al. (2009), Nature

50. India Why is this so important?
Groundwater withdrawal seems to be detectable by GRACE
e.g. altimetry
e.g. SMOS
canopy
surface waters
soil
snow
groundwater
For the first time it is possible to observe groundwater changes from space

51. Trend
Greenland
Antarctica
Alaska 51

52. Trend 52

53. Greenland Mass loss in Greenland as observed by GRACE
Mass loss: ~ 240 Gt/year
(GFZ-RL05 time series)
water height [m]
Jakobshavn glacier
Acceleration?!
water height trend [m/year]
Leakage is very important (and difficult)
in Greenland!!
(ITG-Grace regional solution)

54. How is the melted ice distributed in the oceans?
Sea level change

55. Sea level What happens when ice is melting in Greenland?
Simulated sea level change
after 40 years
FESOM (Brunnabend et al 2012)
Water is being attracted
Ice
Greenland
Ocean
Step: Ice generates gravity

56. Sea level What happens when ice is melting in Greenland? Greenland
At same time:
- continents rise (reduced loading)
sea floor deforms (increased loading)
this again changes gravity …
Sea level is sinking at the Greenland coast
Greenland
Ocean
Simulated sea level change
after 40 years
FESOM (Brunnabend et al 2012)
Step: Ice generates gravity

57. Sea level What happens when ice is melting in Greenland?
At same time:
- continents rise (reduced loading)
sea floor deforms (increased loading)
this again changes gravity …
„Fingerprint“ of Greenland ice melting
Sea level is sinking at the Greenland coast
Greenland
Ocean
Simulated sea level change
after 40 years
FESOM (Brunnabend et al 2012)
Step: Ice generates gravity

58. Contributions to sea level change
Ice
Sea level trend as observed
by GRACE
(Riva et al. 2010) 58
Hydrology
(Jensen et al. 2013)

59. Sea level What happens when ice is melting in Greenland?
At same time:
- continents rise (reduced loading)
sea floor deforms (increased loading)
this again changes gravity …
„Fingerprint“ of Greenland ice melting
Sea level is sinking at the Greenland coast
Greenland
Ocean
Simulated sea level change
after 40 years
Cannot be observed
by GRACE
FESOM (Brunnabend et al 2012)
Step: Ice generates gravity
Increase in global temperature heats the ocean (=> volume change)
Step: Ice generates gravity

60. Altimetry 60
Determination of geometric sea level variations

61. Sea level (NASA) Altimetry observes both mass variations
and volume change (steric sea level change)
Separation only possible when combining GRACE and altimetry 61
(NASA)

62. Altimetry
Sea level 62
Böning et al. (2012)

63. Sea level Altimetry Sea level drops 6 mm in 2010 ! What happened here?63
Sea level drops 6 mm
in 2010 !
What happened
here?
Böning et al. (2012)

64. Altimetry
Sea level 64
Böning et al. (2012)

65. Sea level Altimetry Water redistribution observed by GRACE65
Water redistribution observed by GRACE
Böning et al. (2012)

66. Trend per year 66

67. Glacial isostatic adjustment (GIA)1
Mantle
Crust
Ice 3
Mantle
Crust
Ice 2
Mantle
Crust
Ice 4
Mantle
Crust
Viscoelastic response of the Earth

68. Glacial isostatic adjustment (GIA)
GRACE
Model (adjusted to GRACE)
(Sasgen 2011)

69. Trend 69

70. Earthquakes Sumatra-Andaman earthquake (December 2004)
Han et al. 2006, Science

71. Earthquakes Model Sumatra-Andaman earthquake (December 2004)
Tohoku earthquake (Fukushima, April 2004)
Model
GRACE
Han et al. 2006, Science
Matsuo and Heki, 2011

72. Summary and outlook The GRACE mission - observation principle
GRACE offers many interesting applications,
e.g. in hydrology, oceanography, glaciology,
geophysics, …
but there are still enough challenges left,
=> we are far from completly undertstanding the data
The GRACE mission
- observation principle
Applications (examples)
Outlook:
end of GRACE mission lifetime to be expected in the next 1-3 years
(batteries are a problem!)
GRACE follow-on mission will be launched August 2017
=> longer time series, important for climate research
GRACE-FO: laser interferometer as technoloy demonstrator
=> distance between satellites 5-50x more accurate
but that does not mean that the gravity field will be equally more accurate