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Throwing the Dice with Climate Data

By Deborah Resnick

Russian-heat-wave-300x232In the summer of 2010, Russia suffered a heat wave that killed 700 people. This heat wave exceeded anything on record for Russia. As with any catastrophic weather event, climate change was immediately blamed for the heat wave. Scientists have used a Monte Carlo simulation to determine if global warming was a factor.

The Monte Carlo simulation uses a combination of defined and random influences and then runs a program thousands of times as a way of generating enough data to prove or disprove an hypothesis. In this instance, Stefan Rahmstorg and Dim Coumou based the simulation on the July temperatures for the previous 100 years.

They found that there was an 80% probability that the extreme weather of July 2010 was caused by global climate change, which conflicted with an earlier study that ruled out any impact from such a cause. To be clear, the Monte Carlo simulation did not give the causes of climate change, only the effects of climate change on a particular scenario.

Global climate change cannot be fully explained by simulations without as much data as can be procured. To fully comprehend the global environmental challenges we face, we need to collect and analyze as much raw data as possible. By inputting real data into a system, such as a Monte Carlo simulation, we improve the accuracy of the model, and are then able to extrapolate results more precisely. Ultimately, the model is only as good as the available data. If a flood pattern for an area is every 6 years, then 60 years of data are necessary for the pattern to emerge. Industrial countries have been collecting weather data and storing it in databases for the past 50 years. Climate data before the 20th century is incomplete and inconsistent. Climate models rely on flexible statistics to compensate for the lack of substantial data but the solution is to have more data.

In a world with increased severe weather events, collection of raw data and making that data available to scientists around the world is critical for us to understand and address the current and future challenges of climate change.

References

Keim, Brandon. Wired Science, “Russian Heat Wave Statistically Linked to Climate Change,” 24 October, 2011: http://www.wired.com/wiredscience/2011/10/russian-heat-climate-change/.

Woller, Joy. University of Nebrasca-Lincoln. “The Basics of Monte Carlo Simulations.” Spring 1996: http://www.chem.unl.edu/zeng/joy/mclab/mcintro.html.

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