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A new El Nino blog posting from NOAA
In this post, I’ll discuss why the analog approach to forecasting often delivers disappointing results. Basically, it doesn’t work well because there are usually very few, if any, past cases on record that mimic the current situation sufficiently closely. The scarcity of analogs is important because dissimilarities between the past and the present, even if seemingly minor, amplify quickly so that the two cases end up going their separate ways.
What they are going by:
Van den Dool (1994)’s "Searching for analogs, how long must we wait?" calculates that we would have to wait about 10^30 years to find 2 observed atmospheric flow patterns that match to within observational error over the Northern Hemisphere. While the ocean is not as changeable as the atmospheric flow, it is clear that finding close matching analogs would also require a very long historical dataset.
This is counter to what I am finding. It is well known that periodic forcing when applied to a near-chaotic system can re-align the behavior to a more deterministic regime.
Osipov, Grigory V, Jürgen Kurths, and Changsong Zhou. Synchronization in Oscillatory Networks. Springer, 2007.
I think that the rationale for not finding the underlying ENSO pattern yet is that they may not have not looked hard enough. The 10^30 years is a red herring.
They do say that there is some hope, using alternative methods:
Although this uncertainty in outcomes is somewhat smaller than that what we would have if we selected years completely randomly from the history, it is larger than that from our most advanced dynamical and statistical models. This is one reason analog forecasting systems have been largely abandoned over the last two decades as more modern prediction systems have proven to provide better accuracy.