Don P. Chambers College of Marine Science University of South Florida Measuring Mean Ocean Mass Variability with GRACE NASA Sea Level Workshop, Austin TX 2-3 November 2009

2 Sources Long-term redistribution of water mass from grounded ice to ocean »Has been happening since last glaciation »Evidence of acceleration in last several years Exchange of water between continents and ocean as part of global water cycle »Seasonal »Interannual & Decadal? Longer? »How large can these low-frequency fluctuations be?

3 Measuring Mean Ocean Mass Look at mass changes of various components (land, ice sheets, glaciers) infer ocean mass change Remove thermal expansion from global mean sea level Both indirect measurements Weigh the ocean by determining changes in gravity »Gravity Recovery and Climate Experiment (GRACE) »Complements other methods by putting a constraint on them

4 Chambers, Wahr, & Nerem, Preliminary observations of global ocean mass variations with GRACE, Geophys. Res. Ltrs, Seasonal Ocean Mass Change

5 Long-Term Ocean Mass Change from GRACE Although record is still short, several groups have computed trends from GRACE ocean mass GRACE measures ALL gravitational changes over the ocean »Internal mass redistribution has a zero global mean »Large gravitational signal from glacial isostatic adjustment (GIA) of the solid Earth that is not related to present day water mass exchange »The GIA trend is the same order of magnitude as ocean mass trend (but opposite sign) so mostly cancels ocean mass »Still quite a bit of controversy over GIA models and accuracy

6 Glacial Isostatic Adjustment Recently, Peltier [2009] has argued that his ICE- 5G(VM2) model should be used, and gives a correction (add to GRACE measurement of the ocean) of 1.8 mm/year equivalent SL Another GIA model, also based on ICE-5G ice loading and the VM2 mantle viscosity profiles [Paulson et al., 2007] gives a correction of 1.1 mm/year Why the large difference?

7 Ocean Mass Change from GRACE Simply averaging GRACE data over the ocean is trivial Complicated thing is understanding certain subtleties to obtain the most accurate measurement »Geocenter »Replacing C 2,0 coefficient »Mean ocean bottom pressure versus mean ocean mass »Leakage of land hydrology »Glacial Isostatic Adjustment

8 GIA and Mass Conservation Paulson et al impose a mass conservation constraint on geoid response »Makes  C 0,0 term identically zero »GRACE processing does the same thing Peltier enforces mass conservation on the surface load, but not on the geoid response »Non-zero  C 0,0 »Setting value to zero to be consistent with GRACE processing reduces correction from 1.8 mm/year to 1.3 mm/year

9 Rotational Feedback Two different theories used »Peltier – based on Wu and Peltier (1984) theory »Paulson – based on Mitrovica et al. (2005), which argues that the older theory overestimates the true response Paulson Peltier Geoid rates, degree 2 and higher

10 Paulson Peltier GRACE – OMCT – GLDAS (no GIA correction) Would require OBP trends of order 10 cm/year!

11 Long-Term Ocean Mass Change from GRACE Although record is still short, several groups have computed trends from GRACE ocean mass using these two different GIA models More importantly, they have tried to balance the sea level budget Lombard et al. [2007] made first attempt »Compared mean steric sea level with altimetry – GRACE »Large difference caused by errors in thermal data

12 Willis et al. [2008] removed the bad Argo floats from the data set and used newer Jason-1 GDR-B data 4-year trends did not balance, even within the uncertainty

13 Leuliette and Miller [2009] analyzed similar data, but used a different time-span (Jan to December 2007) Found closure much closer than Willis et al. [2008] »Within 1 mm/year

14 GRACE and altimetry time-series similar to those of Willis et al. Argo time-series very different in earlier part »Significantly different reference climatologies for mapping Willis et al. Leuliette and Miller

15 StudyPeriodAltimetryArgoGRACE Willis et al ± ± ± 0.8 Leuliette & Miller ± ± ± 0.5 Cazenave et al (Argo) 2.5 ± ± ± 0.1 Trends Uncertainty estimates for Cazenave et al. are 1-sigma, formal errors only Uncertainty estimates for Leuliette and Miller are 95% confidence interval, assuming random uncorrelated errors Uncertainty estimates for Willis et al. are 95% confidence interval plus potential systematic errors for GRACE

16 StudyPeriodMisbalance Willis et al ± 1.4 mm/yr 1 Leuliette & Miller ± 1.4 mm/yr 1 Cazenave et al (Argo) 0.2 ± 0.4 mm/yr 2 Misbalance of SL Budget 1 Paulson et al. [2007] GIA model 2 Peltier [2004] GIA model

17 Jason-1 data have undergone a substantial preprocessing since studies published Several bias changes in the JMR have been corrected

18 StudyPeriodJason-1 GDRB Jason-1 GDRC New Residual Misbalance Willis et al mm/yr1.8 mm/yr1.5 mm/yr 1 Leuliette & Miller mm/yr1.4 mm/yr-0.2 mm/yr 1 Cazenave et al (Argo) 2.5 mm/yr1.4 mm/yr-0.9 mm/yr 2 Updated Trends with GDR-C 1 Paulson et al. [2007] GIA model 2 Peltier [2004] GIA model

19 Jason-1,2 GDR-C data Argo data only after 2005 (when previous analyses agree), more floats with a pressure bias removed GFZ_RL04 data, Paulson GIA correction

20 Jason-1,2 – Argo trend: +1.0 ± 0.8 mm/year GRACE: +0.9 ± 0.8 mm/year »95% confidence interval

21 A Note on Uncertainty Difference between processing centers: ± 0.3 mm/yr »Higher than formal error of fit GIA uncertainty: ± 0.3 mm/yr »After constraining  C 00 to zero »Still allowing large differences in rotational feedback model Leakage from hydrology: < ± 0.1 mm/yr »Simulated data, kernel method, no ocean with 300 km of land Geocenter correction: ± 0.1 mm/year »Based on difference of using geocenter estimate [Swenson et al., 2008] and no geocenter estimate Sum (not RSS): ± 0.8 mm/yr Seasonal removed, 3-month running mean

22 Seasonal removed GRACE trend (2003 – ): +1.3 ± 0.8 mm/year »Using GFZ coefficients, middle of trends from 3 centers »Significant (5 mm or more) interannual variability

23 Conclusions Better understand why previous sea level budget studies gave mixed results »Jason-1 data had several biases that were corrected in reprocessing »Mapping methods for Argo data before 2005 changes time-series dramatically, suggesting one needs to be cautious when using these data Comparisons of two GIA models (Peltier, Paulson) indicate Paulson model more consistent with GRACE observations »Peltier model would imply ocean bottom pressure changes that are far too large to be real

24 Conclusions (cont) Using Argo data after 2005 and new Jason-1 data, sea level budget closes to 0.1 mm/year »Only when using Paulson GIA model GRACE trend for 2003 to is 1.3 ± 0.8 mm/year »Important to account for more than formal uncertainty of fit »Still need to understand why solutions from different centers have trends that differ at the 30% level »Still need to get consensus GIA model with uncertainty »Still significant interannual variations »Not sure how representative this is of the longer-term trend

25 Extras

26 Geocenter Swenson et al. [JGR, 2008] derived a method to estimate geocenter corrections for GRACE data based on an ocean model, mean ocean mass variations, and GRACE observations for degree 2 and higher »Monthly estimates have seasonal and interannual variability Estimated trends are significantly smaller than those from a simulation based solely on ice melting [Chambers et al., GRL, 2007] »That study ignored land hydrology changes that can also affect low-frequency geocenter change

27 From Swenson et al. [JGR, 2008]

28 Leakage Simulated hydrology, ice sheet, and glacier melting trends [Chambers, GJI, 2008] Simulation truncated at degree 60 After additional 300km smoothing Found that minimal leakage occurred with no smoothing and area within 300km of coastlines ignored Not doing this could lead to ocean mass trends 30% smaller

29 Reconciling with Other Estimates This analysis indicates the trend in sea level from ocean mass gain is +1.3 ± 0.8 mm/year »Over the last 7 years only How to reconcile this with other estimates based on summing Greenland, Antarctica, and glacier contributions »Cazenave et al [2009] obtains 2.2 ± 0.3 mm/year over One could argue they agree at upper level of uncertainty »Would argue GRACE uncertainty estimate more realistic

30 A Closer look at Other Summations of Contributors Cazenave et al. contributors [ ] »Greenland + Antarctica = 1.0 mm/year »Glaciers + Ice Caps = 1.1 mm/year »Terrestrial Waters = 0.17 mm/year Glaciers and Ice Caps »How much do ice caps in Arctic near Greenland leak into Greenland estimates? »Double counting?

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