Okay, it sounds like David is interested:

> I like the sound of the El Niño project, especially if programming could really help out!

> Let’s read up on the materials that John has pointed us to, and discuss.

You should mainly ask questions, and make me answer them... though some reading would do us all good.

To copy and then _improve on_ this paper on El Niño prediction:

* Josef Ludescher, Avi Gozolchiani, Mikhail I. Bogachev, Armin Bunde, Shlomo Havlin, and Hans Joachim Schellnhuber, [Improved El Niño forecasting by cooperativity detection](http://www.pnas.org/content/early/2013/06/26/1309353110.full.pdf+html),
_Proceedings of the National Academy of Sciences_, 30 May 2013.

we would first need to get ahold of daily temperature data for "14 grid points in the El Niño basin and 193 grid points outside this domain" from 1981 to 2014. That's 207 locations and 34 years. This data is supposedly available from the National Centers for Environmental Prediction and the National Center for Atmospheric Research Reanalysis I Project.

The paper starts by taking these temperatures, computing the average temperature at each day of the year at each location, and subtracting this from the actual temperatures to obtain "temperature anomalies". In other words, we want a big array of numbers like this: the temperature on March 21st 1990 at some location, minus the average temperature on all March 21sts from 1981 to 2014 at that location.

Then they process this array of numbers in various ways, which I can explain...

They consider all _pairs_ of locations, so at some point they are working with 207 × 207 × 365 × 34 numbers. Is that a lot of numbers these days?