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Estimating high frequency ocean bottom pressure variability
Author(s) -
Quinn Katherine J.,
Ponte Rui M.
Publication year - 2011
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2010gl046537
Subject(s) - aliasing , residual , environmental science , variance (accounting) , satellite , geodesy , statistics , climatology , geology , computer science , mathematics , algorithm , accounting , artificial intelligence , undersampling , engineering , business , aerospace engineering
Knowledge of variability in ocean bottom pressure ( p b ) at periods < 60 days is essential for minimizing aliasing in satellite gravity missions. We assess how well we know such rapid, non‐tidal p b signals by analyzing in‐situ bottom pressure recorder (BPR) data and available global estimates from two very different modeling approaches. Estimated p b variance is generally lower than that measured by the BPRs, implying the presence of correlated model errors. Deriving uncertainties from differencing the model estimates can thus severely underestimate the aliasing errors. Removing estimated series from BPR data tends to reduce the variance by up to ∼5 cm 2 but residual variance is still ∼5–20 cm 2 and not negligible relative to expected variance in climate p b signals. The residual p b variability can be correlated over hundreds of kilometers. Results indicate the need to improve estimates of rapid p b variability in order to minimize aliasing noise in current and future satellite‐based p b observations.