By Cai McCann
Undoubtedly, climate change means significant changes in climate patterns.
What’s the first idea that comes to mind with this phrase, climate change? Ice caps melting? Skyrocketing carbon emissions? That particularly hot month you suffered through in the summer?
What about fractals?
Climate change remains one of the greatest challenges of our century, as a global-scale symptom of anthropogenic stressors, such as fossil fuel use and carbon emissions. One of the most prominent rate-limiting factors for addressing climate change is denial. Enter fractals.
What is a fractal?
As some quick trivia, fractals are iterative, infinitely-detailed, and intricate patterns generated from specific collections of complex numbers. Fractals are an age-old phenomenon; they exist everywhere in the physical world. From the minute details of nature, such as ice crystals, plant growth, and paths of river beds, to the profoundly vast cosmos, fractals are fundamental to life as we know it (Taylor, 2008).
These resulting patterns can help us understand climate change.
Climate also repeats as fractals. Crucial to addressing climate change denialism is whether these human-induced changes are real and distinctly different from climate per usual.
Meet the researchers, Peter Ditlevsen and Zhi-Gang Shao. In a 2015 collaboration, they investigated temperature records of ocean sediment and ice core data ranging from the last hundred to millions of years in Greenland and Antarctica, essentially a proxy for the Northern Atlantic climate during the interglacial period.
You might wonder, how did they obtain data from five million years ago?
They inferred relationships in the temperature record at certain time periods to indirectly estimate weather back in time, and most importantly, they did it through fractal modeling. When viewed as a fractal, climate behaves with similar variations over a specific window of time.
What did they find?
First, the natural and human-induced climate states don’t behave the same way. They discovered that climate modeling for the earliest time periods, ice age climates, were multi-fractal, i.e. were chaotic, unpredictable, and accompanied by drastically fluctuating, extreme winter/summer seasons. Moving forward in time to the current warm interglacial climate, the fractal behavior becomes monofractal. This fractal behavior is more stable, which entails less extreme ratios of climate over different time periods with respect to time scales.
Second, not only do these two periods behave differently, the current human-induced changes don’t behave in a monofractal way. Thus, this monofractal model enables us to better differentiate natural and human-related climate change.
Boom. We have a breakthrough.
Understanding natural climate variability as a fractal demonstrates the utility of fractal analysis for assessing climate change. For example, with enough accumulated stress caused by humans, the climate state could shift to a new system (Shao & Ditlevsen, 2016).
Weather is deeply seeded in fractal and chaos theory, and while the math is beyond the scope of this article, research into these wonderful, self-iterative, infinitesimally dynamic patterns delimits the bounds between normal climate and concerning, human-caused change.
OVER TO YOU
Sometimes the material is difficult, and you will find that there is a ton still to learn. That’s all right. The thing is, even though the words “multi-fractal” and “time scale ratios” may get thrown around a lot, they become tools to understand other relevant and profound dialogues. It’s not usually about trying to have a more STEM-mindset, but it does have a lot to do with trying to be aware of and gain a better understanding about climate change issues that deal with the world around us.
References:
JarektBot. "File:Mandel Zoom 11 to 12.png." Wikimedia Commons. Wikimedia Commons, 2015. Web. 20 Feb. 2016. <https://commons.m.wikimedia.org/wiki/File:Mandel_zoom_11_to_12.png#mw-jump-to-license>.
Shao, Z.-G., & Ditlevsen, P. D. (2016). Contrasting scaling properties of interglacial and glacial climates. Nature Communications, 7, 109-51. https://doi.org/10.1038/ncomms10951
Taylor, R. P. (n.d.). Biophilic Fractals and the Visual Journey of Organic Screen-savers. Society for Chaos Theory in Psychology & Life Sciences. Nonlinear Dynamics, Psychology, and Life Sciences, 12(1), 117-29.