Researchers led by Florian Sévellec, a CNRS researcher at the Laboratory for Ocean Physics and Remote Sensing (LOPS) (CNRS/IFREMER/IRD/University of Brest) and at the University of Southampton, have developed a new method for probabilistic forecasts called PROCAST.
Using the new method, the study, published in the journal Nature Communications on August 14, 2018, shows that at the global level, 2018-2022 may be an even hotter period than expected based on current global warming.
The new research shows that global warming is not linear, and there are variations that can appear in the data, even though global warming still continues on an upward trek when looking at decadal statistics. Here’s what interesting though – CBC Canada is reporting the study also shows that while the past four years were the hottest on record, any kind of global warming “hiatus” we may have been experiencing is about to end.
The global warming hiatus
A lot of publicity has surrounded claims of a global warming hiatus during the period 1998–2013 when there was a period of relatively little change in globally averaged surface temperatures. Climate deniers were quick to point out that this proved climate change was fake.
However, if you open your mind to the science behind climate, you will see many such 15-year periods appear in the surface temperature record, along with robust evidence of the long-term warming trend. And warming caused by greenhouse gas emissions is not linear: it appears to have lapsed in the early 21st century, giving rise to a “hiatus,” according to the new study.
The study used global-mean surface air temperature (GMT) – identified as variations in external climatic forcing, such as volcanic eruptions or aerosol and greenhouse gas emissions. The study also used another parameter, global-mean sea surface temperature (SST), the water temperature close to the ocean’s surface.
The goal of the study was to develop an accurate and reliable inter-annual prediction method because global temperatures are key for determining the regional climate change impacts that scale with global temperature, however, our chaotic climate system limits prediction accuracy on such timescales.
To overcome this, the research team developed a method to predict global-mean surface air temperature and sea surface temperature, based on transfer operators, which allows, by-design, probabilistic forecasts. So as not to lose anyone, in mathematics, the transfer operator encodes information about an iterated map and is frequently used to study the behavior of dynamical systems, statistical mechanics, quantum chaos, and fractals.
The study’s conclusion
Rising CO2 levels have caused the temperature of the planet to rise, says Sévellec. The new method predicts that mean air temperature may be abnormally high in 2018-2022 — higher than figures inferred from anthropogenic global warming alone.
This is mainly due to the low probability of intense cold events. And with respect to sea surface temperatures (SST), adding in the high probability of heat events, along with certain conditions being met, we can expect to see an increase in tropical storm activity.
Phys.org notes that once the algorithm has been ‘learned’ (a process which takes a few minutes), predictions are obtained in a few hundredths of a second on a laptop. But the method only yields an overall average. The research team would like to adapt it to make regional predictions and, in addition to temperatures, estimate precipitation and drought trends.
