The partition of regional sea level variability

摘要

The existing altimetric record offers an unprecedented view of sea level (zeta) variability on a global scale for more than 2 decades. Optimal inference from the data involves appropriate partition of signal and noise, in terms of relevant scales, physical processes and forcing mechanisms. Such partition is achieved here through fitting a general circulation model to altimeter and other datasets to produce a "best" estimate of zeta variability directly forced by the atmosphere-the signal of primary interest here. In this context noise comes primarily from instrument errors and meso-scale eddies, as expected, but spatial smoothing effectively reduces this noise. A separate constraint is thus formulated to measure the fit to monthly, large-scale altimetric variability that unlike the daily, pointwise constraint shows a high signal-to-noise ratio.