Atmospheric pressure forced oceans and their effects on Earth’s Rotation: a TOPEX data approach

Monday, 15 December 2014
Nirupam Dey and S R Dickman, Binghamton University, Binghamton, NY, United States
Dey & Dickman [2010] showed (using a theoretical model) that the oceanic response to atmospheric pressure forcing depends on the frequency and spatial pattern of the forcing. We have developed an observational Green’s function approach to determine the frequency- and spatially dependent sea-level response using satellite altimetric data. We applied it to 12 years of TOPEX sea-surface height (SSH) observations smoothed over a 4° × 8° grid at 3 day intervals and corrected for tides, winds, annual signals and secular trends. Wiener filtering, generalized for complex time series, was used to isolate pressure forced SSH within each gridbox. In most of the gridboxes, that SSH, after accounting for the forcing, showed a spatial and spectral dependence – a significant departure from the “inverted barometer” response.

The oceanic currents associated with the response were calculated from a spherical harmonic relation between current velocities and SSH [Dickman 1991]. The rotational effects (polar motion and change in Earth’s spin rate) of the pressure forced SSH & associated currents – with the pressure forcing accounted for, these are essentially Green’s functions – were calculated at specific periods and interpolated to other periods. The rotational effects calculated here are dominated by the pressure-forced SSH and show a strong frequency dependence & significant departures from an inverted barometer excitation. The pressure forced SSH is effective in exciting both prograde & retrograde polar motion at periods of ~ 6 days, and prograde polar motion at periods of 10 – 15 days. Compared to the theoretical approach, our work finds that the prograde component shows higher amplitude and less spatial variability, whereas the other components are ~ similar in amplitude & spatial variability.

When these Green’s functions are combined with any time span of pressure data, they generate the total excitation for that time span. We will discuss the results for various spans of pressure data.