1 / 16

The Potential to Estimate Ocean Thermal Expansion by Combining GRACE and Satellite Altimetry

The Potential to Estimate Ocean Thermal Expansion by Combining GRACE and Satellite Altimetry. 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. GOALS.

hang
Télécharger la présentation

The Potential to Estimate Ocean Thermal Expansion by Combining GRACE and Satellite Altimetry

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. The Potential to Estimate Ocean Thermal Expansion by Combining GRACE and Satellite Altimetry 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

  2. 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

  3. 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 2009 3

  4. GRACE Errors long wavelength short 4

  5. GRACE project produces a set of global gravity coefficients (DClm, DSlm) 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

  6. From CSR_RL01 GRACE coefficients • Replacing DC20 with values from SLR analysis and using seasonal model of DC10, DC11, and DS11 terms (Chambers et al., GRL, 2004) 6

  7. 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

  8. 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

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

  10. 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

  11. 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 11

  12. Greenland: 22.0 cm/m2 water mass lost per year (0.75 mm SL) • 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. Oceans: 1.5 mm/year increase in SL Antarctica: 4.1 cm/m2 water mass lost per year (0.75 mm SL) Land: No change 12

  13. Trend removed from Altimeter - TSL • 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

  14. 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 14

  15. Rate Uncertainty for Ocean Mass from GRACE with 3-years of Observations 1 - from range of GIA corrections 2 - doubled simulation estimate to be conservative; systematic! 3 - without interannual uncertainty 4 - all sources of trend uncertainty 15

  16. 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

More Related