Why? Several reasons:
• It’s the biggest source of variability in the Earth’s climate on times scales between a year and a decade. It causes weather disturbances in many regions, especially near the Pacific Ocean. The last really big one happened in 1997-1998, and we’re waiting for the next.
• It’s hard to predict for more than 6 months in advance. It’s not periodic: it’s a quasi-periodic phenomenon that occurs across the tropical Pacific Ocean every 3 to 7 years.
• It matters for global warming. A lot of heat gets stored in the ocean, and a lot comes back into the atmosphere during an El Niño. So, the average surface air temperature of the Earth may reach a new high when the next El Niño comes.
• In February 2014, a paper in Proceedings of the National Academy of Sciences caused a stir by claiming to be able to predict the next El Niño more than 6 months in advance using ideas from network theory. Moreover, it claimed an El Niño would start in late 2014 with a 75% probability.
• The math involved in this paper is interesting, not too complicated, and maybe we can improve on it. At the very least, it raises a lot of questions worth studying. And it’s connected to network theory, one of the Azimuth Project’s specialties!
We are already hard at work on this project. We could use help from computer programmers, mathematicians, and physicists: there is lots to do! But it makes sense to start by explaining the issues and what we’ve done so far. We’ll do that in a series of posts here.
This first post will not get into many details. Instead, I just want to set the stage with some basic information about El Niño.
This animation produced by the Australian Bureau of Meteorology shows how the cycle works:
During La Niña years, trade winds blow across the Pacific Ocean from the Americas to Asia in a strong way. So, warm surface water gets pushed toward Asia. Warmer oceans there create more clouds and rain there. The other side of the Pacific gets cooler, so there is less rain in many parts of the Americas.
During El Niño years, trade winds in the tropical Pacific weaken, and blobs of warm surface water move back toward the Americas. So, the eastern part of the Pacific warms up. We generally get more rain in the Americas… but less in Asia.
The cycle of El Niños and La Niñas is often called the El Niño/Southern Oscillation or ENSO. Why? Because this cycle is linked to the Southern Oscillation: an oscillation in the difference in air pressure between the eastern and western Pacific:
The top graph shows variations in the water temperature of the tropical eastern Pacific ocean: when it’s hot we have an El Niño. The bottom graph shows the air pressure in Tahiti minus the air pressure in Darwin, Australia — up to a normalization constant, this called the Southern Oscillation Index, or SOI. If you stare at the graphs a while, you’ll see they’re quite strongly correlated—or more precisely, anticorrelated, since one tends to go up when the other goes down. So, remember:
There are other ways besides the SOI to tell if an El Niño is happening. We’ll talk later about these quantities, how they’re defined, how you can get the data online, what we’ve done with this data, and what we want to do.
To conclude, I just want you to watch this short movie. NASA’s Jason-2 satellite has detected blobs of hot water moving east toward America! This has made some scientists—not just those using network theory—suspect a big El Niño is on its way, perhaps a repeat of the one that started in 1997.
On the other hand, on June 17th the National Oceanic and Atmospheric Administation (NOAA) said that trends are now running “counter to typical El Niño development”. So we’ll have to wait and see… and meanwhile, try to predict!
If you can’t wait to dive in, start here:
• Experiments in El Niño detection and prediction, Azimuth Forum.
To join this conversation, join the forum by following these instructions:
• Forum help.
This is the paper that got us excited:
• Josef Ludescher, Avi Gozolchiani, Mikhail I. Bogachev, Armin Bunde, Shlomo Havlin, and Hans Joachim Schellnhuber, Very early warning of next El Niño, Proceedings of the National Academy of Sciences, February 2014.
A lot of the methodology is explained here:
• Josef Ludescher, Avi Gozolchiani, Mikhail I. Bogachev, Armin Bunde, Shlomo Havlin, and Hans Joachim Schellnhuber, Improved El Niño forecasting by cooperativity detection, Proceedings of the National Academy of Sciences, 30 May 2013. (For more discussion, go to the Azimuth Forum.)
• El Niño project (part 1): basic introduction to El Niño and our project here.
• El Niño project (part 2): introduction to the physics of El Niño.
• El Niño project (part 3): summary of the work of Ludescher et al.
• El Niño project (part 4): how Graham Jones replicated the work by Ludescher et al, using software written in R.
• El Niño project (part 5): how to download R and use it to get files of climate data.
• El Niño project (part 6): Steve Wenner’s statistical analysis of the work of Ludescher et al.
• El Niño project (part 7): the definition of El Niño.
• El Niño project (part 8): Berezin et al on the stability of climate networks.
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