A new mathematical model developed at the Rochester Institute of Technology (RIT) is shedding light on the fate of one of the world’s oldest societies, the Indus Valley Civilization. The researchers found that climate change altered monsoon patterns just before the Bronze Age society collapsed.
The Indus River Valley Civilization was thriving in modern-day Pakistan in 2600 BC at the same time as ancient Egypt, yet suddenly declined before vanishing around 1300 BC. Some experts have theorized that the Indus Valley Civilization was destroyed in a war by northern invaders, while other theories have pointed to earthquakes or climate change.
In a new paper, RIT Professor Nishant Malik outlines his new mathematical technique. He designed the method to study paleoclimate time series, which are datasets that provide information about past climates based on indirect observations.
By measuring a specific isotope in stalagmites collected from a cave in South Asia, scientists were able to reconstruct a record of monsoon rainfall in the region for the past 5,700 years. However, studying paleoclimate time series poses several problems that make it challenging to analyze them with the mathematical tools that are typically used to understand climate, said Professor Malik.
“Usually the data we get when analyzing paleoclimate is a short time series with noise and uncertainty in it. As far as mathematics and climate is concerned, the tool we use very often in understanding climate and weather is dynamical systems. But dynamical systems theory is harder to apply to paleoclimate data.”
“This new method can find transitions in the most challenging time series, including paleoclimate, which are short, have some amount of uncertainty and have noise in them.”
The mathematical technique draws on methods from the fields of machine learning and information theory. Based on this approach, the analysis showed that there was a major shift in monsoon patterns just before the end of the Indus civilization, and the pattern reversed course right before it declined. This trend is consistent with abrupt climate change.
Professor Malik said he hopes the method will allow scientists to develop more automated techniques to identify transitions in additional paleoclimate data.
The study is published in Chaos: An Interdisciplinary Journal of Nonlinear Science.