This is another round of error minimization. Instead of using the full SOI measure, I decided to compare the Sydney tide gauge data (panel A) to just the Darwin atmospheric pressure anomaly (panel B).

The underlying model forcing between the two is identical, apart from a slight time-scale shift. But the Darwin model has an additional unforced component as shown in panel C of #44.

![SydneyDarwin](http://imageshack.com/a/img674/8568/4w1q98.gif)

I am pulling out all the stops on the analysis with this teleconnection. The correlation coefficient between Darwin and model is almost 61% which makes it higher than the correlation between Darwin and -Tahiti. This you can see below

![DarwinMinusTahiti](http://imagizer.imageshack.us/a/img539/1412/48fe30.gif)

The nature of the characterized behavior is that one will never whether a feature detail is part of the underlying phenomena or some error or disturbance. This will always knock the correlation coefficient down and I am guessing will prevent the correlation coefficient from ever reaching unity.