Don P. Chambers Center for Space Research The University of Texas at Austin Understanding Sea-Level Rise and Variability 6-9 June, 2006 Paris, France The.

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Presentation transcript:

Don P. Chambers Center for Space Research The University of Texas at Austin Understanding Sea-Level Rise and Variability 6-9 June, 2006 Paris, France The Potential to Estimate Ocean Thermal Expansion by Combining GRACE and Satellite Altimetry

GOALS 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 2

Gravity Recovery & Climate Experiment (GRACE) Science Goals Measure time variable gravity field to detect changes in the water storage and movement from reservoir to another (e.g., from ice sheets to ocean) Mission Joint 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) Orbit Launched: March 17, 2002 Regular Science Data: August, 2002 Original Lifetime: 5 years Recently NASA/DLR extended mission through

GRACE Errors long wavelength short 4

GRACE project produces a set of global gravity coefficients (  C lm,  S lm ) every month Can convert these to a time-series of monthly average water level (sea level) over a basin by Ocean kernel Ocean kernel designed to minimize error from GRACE noise AND aliasing of hydrology signals [Swenson and Wahr, JGR, 2002] 5

From CSR_RL01 GRACE coefficients »Replacing  C 20 with values from SLR analysis and using seasonal model of  C 10,  C 11, and  S 11 terms (Chambers et al., GRL, 2004) 6

Glacial 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? 7

GIA 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 8

Adding maximum GIA correction to GRACE changes interpretation of trend significantly 9

Degree 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 10

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 coefficientsGRACE w/ degree 1 coefficients 11

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/m 2 water mass lost per year (0.75 mm SL) Antarctica: 4.1 cm/m 2 water mass lost per year (0.75 mm SL) Oceans: 1.5 mm/year increase in SL Land: No change 12

We have limited knowledge of interannual variations in ocean mass Some evidence of ± 4-5 mm variations at ENSO periods With 1-year smoothing 13 Trend removed from Altimeter - TSL

Simulate interannual ocean mass by scaling SOI to estimate from J. Willis in »55 yr. trend set to zero Estimate 95% confidence interval based on standard deviation of trends over 3-15 yr intervals 14

Rate Uncertainty for Ocean Mass from GRACE with 3-years of Observations 15 SourceUncertainty (mm/year) Formal0.3 Knowledge of GIA correction0.7 1 Knowledge of degree 1 rates year period & ENSO-like variability2.8 RSS (3-year rate) RSS (long-term) from range of GIA corrections 2 - doubled simulation estimate to be conservative; systematic! 3 - without interannual uncertainty 4 - 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 16