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Antarctic ice mass balance estimates from GRACE: Tidal aliasing effects
Author(s) -
Moore Philip,
King Matt A.
Publication year - 2008
Publication title -
journal of geophysical research: earth surface
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2007jf000871
Subject(s) - aliasing , geology , geodesy , groenlandia , ice sheet , climatology , environmental science , oceanography , computer science , artificial intelligence , undersampling
Geophysical interpretation of GRACE gravity fields has provided estimates of Antarctic ice mass change. Such analyses rely on proper consideration of ocean tidal effects through the models CSR4 and FES2004. In general, mis‐modeling of tidal constituents with aliasing period less than 30 day will not have significant impact on ice mass change. However, for constituents, such as K1, K2, and S2, the aliasing period is sufficiently large to potentially compromise long‐term variability studies. Here we quantify tidal aliasing over Antarctica by simulating GRACE signatures due to differences between CSR4 and FES2004, and the best available circum‐Antarctic model, TPXO6.2. The S2 simulations are in close agreement with the observed S2 signal from GRACE. Simulations of ice mass change show that over 2002–2006 long‐term K1 and K2 aliasing is equivalent to a rate error of 4.5 ± 1.3 km 3 /a of ice with CSR4, but only 0.2 ± 0.2 km 3 /a with FES2004. After spatial averaging and destriping, K1 plus K2 mis‐modeling in CSR4 (FES2004) introduce point‐wise errors up to 5 (2) mm/a in equivalent water height over a 3.5 year period. With observed mass change equivalent to less than 30 mm/a of water height over much of Antarctica, the simulations show tidal aliasing uncertainty at the 2–3 mm/a level for August 2002–January 2006, or ∼10% of the signal. With GRACE Release 04, the revised estimate (April 2002–January 2006) of published ice volume decrease is 164 ± 80 km 3 /a of ice, although this value depends very much on the GIA model and GRACE analysis approach.

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