So you want to start preparing your region or city for climate change. You might look at one of the many reports predicting the problems that a warming planet will bring. But as you try to delve into regional or local details, the uncertainty of what might happen increases. A new technique from MIT researchers aims to quantify regional outcomes from climate change–and the uncertainty involved.
The tool combines climate analysis data used by the Intergovernmental Panel on Climate Change with the MIT Integrated Global System Modeling framework (a computer model that examines economic data and natural systems). “We need to consider range of causes of uncertainty [in climate change]. The technique is a way to combine not only factors contributing to uncertainty on the science side, but also uncertainty in economics,” explains MIT researcher Adam Schlosser. “By combining these two effects, we can build hybrid frequency distribution–a way of representing the chances of all possible outcomes.”
The idea, says Schlosser, is to look at the data “not along the lines of ’20 years from now it’s going to rain on Tuesday.’ It’s more ’20 years from now we see that there’s a greater likelihood of a certain amount of rain occurring over a given season or a given year.'”
In a recent report, MIT researchers used the technique to examine potential temperature and precipitation changes across the world, in places like Western Europe, the Amazon Region, and the South African Region). These two factors were chosen because they are two major players in climate change prediction, but any number of other factors–including sea level rise–could be used with the technique.
The tool can’t hone in on city-level data quite yet (it has been applied to country and basin-wide issues), but there are real-world applications for city planners right now, especially in developing countries where cities are just now emerging. A new city can use predicted shifts in temperature and precipitation to plan its infrastructure. As Schlosser explains: “For a city to actually grow in a certain area, that has consequences on the resources of surrounding area, and if the climate were to shift in some appreciable way in that region, that’s a stress, a factor one must consider.”
But for a place like New York City, where climate preparation isn’t about deciding where to expand but how to protect existing infrastructure, the MIT technique’s data isn’t yet granular enough. That’s something the team is working on.
There are other climate change prediction tools out there, but Schlosser says the MIT technique is unique in taking into account economic data.