Meteorologists run weather-forecast models to provide good predictions of weather conditions over the next few days. Climate scientists, on the other hand, run global climate models to project the impacts of climate-changing greenhouse gas emissions over the next few decades. In between these two activities is an interesting task that has proven more difficult than either: predicting global temperature over a few years.
A new study by Patrick Brown and Ken Caldeira tries a new approach to this challenge using nothing more than statistical analysis of the previous two years temperatures.
The annual average surface temperature for the globe varies a bit from one year to the next even as a long-term warming trend is apparent. Its those year-to-year wiggles that are hard to predict. They depend on variable regional weather patterns, most notably the El Niño Southern Oscillation. This seesaw pattern of warm surface water along the equatorial Pacific is significant enough to bump the planets average surface temperature up and down. It also affects weather patterns in many places around the world.
And thats true for other ways in which large-scale weather patterns vary. Years in which the planet sets a new temperature record obviously also tend to be warm in most places on a local scale. So the ability to provide some advance warning is useful beyond just the global-temperature bookkeeping.
This is obviously something that climate scientists have played around with for a long time. One way to do it is to input recent temperature data into a climate model and then simulate ahead a year or two. That has some advantages, but the swings of El Niño/La Niña are stubbornly difficult to nail in simulation and these models require supercomputer time.
Another, less resource-intensive option is to attempt a purely statistical prediction based on previous data. This often relies on metrics for variability like the El Niño Southern Oscillation index, which distills sea surface temperature patterns down to a number representing La Niña, neutral, or El Niño states. But while convenient, that might discard data that could drive a better prediction.
A new method
So to try something a little different, the researchers constructed a method that simply takes in temperature data for every cell in a grid covering the globe. For all the data prior to the year 2000, their method analyzes the full temperature pattern over a two-year period and compares that to the average global temperature in following years. The end result is a complex mathematical correlation that can be used to predict future global temperature.
The method was tested several ways. It was repeatedly recalculated based on every year before 2000 except one. Then the method was tested by predicting that missing year—whats known as “leave-one-out” validation. It was also used to predict global temperatures for each year after 2000, which hadnt been used to calculate correlations. In each case, the method actually performed pretty well, beating simple assumptions of a continued trend, as well as climate model simulations.
Taking a closer look at the correlation patterns, the method isnt doing anything too surprising. It picks up on the trend of warming temperatures globally, and it also finds predictive power in the areas of the ocean that vary with things like the El Niño Southern Oscillation. It shows that an El Niño (warm water stretching across to the eastern side of the equatorial Pacific) is associated with a warmer global temperature the next year. The cooler waters of a La Niña, on the other hand, tend to be associated with a warmer global temperature two years afterward—reflecting the back-and-forth nature of this phenomenon.
Alongside the study, the researchers posted up-to-date predictions online, incorporating new data every month to predict the next three years. (You can also see how the method would have predicted each year previous.) It currently predicts that 2020 has a 92 percent chance of being the warmest year on record. The year is halfway through at this point, but thats similar to Berkeley Earths current prediction based on the temperature so far. On the other hand, NOAAs latest prediction—Read More – Source
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