Estimating high frequency ocean bottom pressure variability

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 similar to 5 cm(2) but residual variance is still similar to 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. Citation: Quinn, K. J., and R. M. Ponte (2011), Estimating high frequency ocean bottom pressure variability, Geophys. Res. Lett., 38, L08611, doi:10.1029/2010GL046537.