Don P. ChambersDon P. ChambersCenter for Space ResearchCenter for Space Research
The University of Texas at AustinThe University of Texas at Austin
Understanding Sea-Level Rise and VariabilityUnderstanding Sea-Level Rise and Variability
6-9 June, 20066-9 June, 2006
Paris, FranceParis, France
The Potential to Estimate The Potential to Estimate Ocean Thermal Expansion by Ocean Thermal Expansion by
Combining GRACE and Satellite Combining GRACE and Satellite AltimetryAltimetry
GOALSGOALS
• Computing mean ocean mass component of sea level from GRACE
• Potential for combining with altimetry to determine long-term trend in steric sea level
» Steric SL = Altimeter SL - GRACE SL
• Sources of uncertainty in rate estimate for GRACE
» Glacial Isostatic Adjustment (GIA) correction
» Degree 1 gravity coefficients (geocenter)
» Interannual variations in ocean mass and a short record
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Gravity Recovery & Climate Experiment Gravity Recovery & Climate Experiment (GRACE)(GRACE)
Science GoalsMeasure time variable gravity field to detect changes in the water storage and movement from reservoir to another (e.g., from ice sheets to ocean)
MissionJoint NASA/German mission implemented by NASA and DLR (Deutschen Zentrum für Luft-und Raumfahrt) under the NASA Earth System Science Pathfinder Program.Science data processing by University of Texas Center for Space Research (UTCSR) and GeoForschungsZentrum (GFZ)
OrbitLaunched: March 17, 2002Regular Science Data: August, 2002Original Lifetime: 5 yearsRecently NASA/DLR extended mission through 2009
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GRACE ErrorsGRACE Errors
long wavelength short
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•GRACE project produces a set of global gravity coefficients (Clm, Slm) every month
•Can convert these to a time-series of monthly average water level (sea level) over a basin by
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ηba sin =QlΩba sinl,m
∑ W lmCΔClm +W lm
SΔSlm( )
Ql =aρE3ρW
2l +1( )1+ kl( )
Ocean kernel
•Ocean kernel designed to minimize error from GRACE noise AND aliasing of hydrology signals [Swenson and Wahr, JGR, 2002]
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• From CSR_RL01 GRACE coefficients
» Replacing C20 with values from SLR analysis and using seasonal model of C10, C11, and S11 terms (Chambers et al., GRL, 2004)
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Glacial Isostatic AdjustmentGlacial Isostatic Adjustment
• GRACE will measure:
» The long-term gravitational change due to glacial isostatic adjustment (GIA)
» Gravitational changes due to water mass transfer from melting of ice sheets
» Shorter period exchanges of water mass with continents
• Can we model GIA adequately over the ocean to remove this signal?
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GIA in GRACE ObservationGIA in GRACE Observation
• GRACE will observe a fall in SL related to GIA
• Part of drop in sea level measured by GRACE since 2002 is this GIA signal
• M. Tamisiea has calculated that the GIA signal in the GRACE observations ranges from -0.6 to -2 mm/year
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• Adding maximum GIA correction to GRACE changes interpretation of trend significantly
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Degree 1 Gravity VariationsDegree 1 Gravity Variations
• GRACE satellites orbit instantaneous mass center of Earth
• Degree 1 gravity coefficients are zero in a reference frame that is centered on the instantaneous mass center
• Terrestrial reference frame has a fixed center not at instantaneous mass center
• Water mass flux in a terrestrial reference frame will have variations in degree 1 terms
• To use GRACE to measure mass flux in an Earth-fixed frame, we have to model/measure these degree 1 variations
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• Previously demonstrated importance of modeling degree 1 variations for seasonal ocean mass studies [Chambers et al., GRL, 2004; Chambers, JGR, 2006].
• Seasonal models of degree 1 variations have some level of consistency
• Trends are completely unknown
GRACE w/o degree 1 coefficients GRACE w/ degree 1 coefficients
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• Convert simulated water level changes into gravity field coefficients (to degree/order 180)
• Compute ocean mass with and without degree 1 terms
• Result: trend is 0.1 mm/year lower if degree 1 not used.
Greenland: 22.0 cm/m2 water mass lost per year (0.75 mm SL)
Antarctica: 4.1 cm/m2 water mass lost per year (0.75 mm SL)
Oceans: 1.5 mm/year increase in SL
Land: No change
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• We have limited knowledge of interannual variations in ocean mass
• Some evidence of ± 4-5 mm variations at ENSO periods
With 1-year smoothing
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Trend removed from Altimeter - TSL
• Simulate interannual ocean mass by scaling SOI to estimate from J. Willis in 1997-1998
» 55 yr. trend set to zero
• Estimate 95% confidence interval based on standard deviation of trends over 3-15 yr intervals
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Rate Uncertainty for Ocean Mass from Rate Uncertainty for Ocean Mass from GRACE with 3-years of ObservationsGRACE with 3-years of Observations
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Source Uncertainty (mm/year)
Formal 0.3
Knowledge of GIA correction 0.71
Knowledge of degree 1 rates 0.22
3-year period & ENSO-like variability 2.8
RSS (3-year rate)3 0.8
RSS (long-term)4 2.9
1 - from range of GIA corrections2 - doubled simulation estimate to be conservative; systematic!3 - without interannual uncertainty4 - all sources of trend uncertainty
• Why the big difference between in situ TSL and space-based estimates?
» Unknown error in one or more of the systems?
» Changes in deep ocean heat storage not measured by Argo floats?
Yearly averages, maximum GIA correction added to GRACE
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