As the SOI model as formulated in this thread is completely guided by physics considerations, it makes sense to revisit certain assumptions. One consideration that I originally started with but eventually left and now am only coming back to is using a lower altitude measure of QBO as a forcing function.

The lower altitude QBO that I originally evaluated was the 70 hPA measure, but I eventually switched over to the 20 hPa data set because it appeared less noisy.

As it turns out that is not a good enough reason as the lower altitude measure is actually more realistic as it is nearer in proximity to interacting with the ocean's surface and thus generating the forcing necessary to push the ocean's volume in a periodically prevailing direction.

The outcome of the switch to the 70 hPa measure is that the long term period remains the same at 2.33 years, but the jitter in the waveform is markedly greater. By modeling the 70 hPA QBO as a frequency modulated time series, the wave-equation fit becomes much better. This is expected as a jitter in the waveform will express itself as a temporarily increasing or decreasing frequency, which can show a significant response in the resonant wave-equation formulation.

![Model fit](

The bottom panel is the modeled QBO, where I tried to achieve at least a CC of 0.7 between the model and the data. The top panel is the data with the fit, where the yellow filled regions show discrepancies between the two sets of data (diffs shown in middle panel).

Don't be alarmed by this as the dipole agreement between -Tahiti and Darwin shows similar deviations, even though they should be dipole replicas of each other. The issue that we are always dealing with is the presence of nuisance noise. So if we map -Tahiti onto Darwin the agreement is there but it also shows significant nuisance noise.


Dealing with dipoles in an electrical engineering lab environment is much easier as the noise can be minimized, but, hey, this is the real world and Nature does not want to give up its secrets easily :)