A winter storm left cold temperatures, heavy rains, and even snow on the mountains of Baja California State and other parts of northwestern Mexico, pictured here on February 22nd, 2019. (Photo: Guillermo Arias/AFP/Getty Images)
New research finds that we normalize rising temperatures remarkably quickly.
How about this weird weather we've been having? It's a common query around the Pacific Standard office, and for good reason: Abnormalities such as the recent cold and snow in Southern California capture pretty much everyone's attention.
Climate change is significantly increasing the chances of more unsettling weather in the years to come, including longer and more severe heat waves. But if you're hoping the strange conditions will inspire people to realize that something profoundly dangerous is occurring—and will prod politicians into acting—new research suggests you're likely to be disappointed.
An analysis of more than two million Twitter posts finds that people do indeed take note of abnormal temperatures. But it also reports that our definition of "normal" is based on recent history—roughly, the past two to eight years.
These findings suggest that, in less than a decade, climate change-induced conditions cease to seem all that unusual. That lack of historical perspective may make it hard to grasp the enormity of the changes that are already underway, and which promise to accelerate.
"This data provides empirical evidence of the 'boiling frog' effect with respect to the human experience of climate change," writes a research team led by Fran Moore of the University of California–Davis. As with the imaginary amphibian who fails to jump out of a pot of water as the temperature slowly rises, "the negative effects of a gradually changing environment become normalized, so that corrective measures are never adopted."
The researchers analyzed data on 2.18 billion Tweets originating in the continental United States between March of 2014 and November of 2016. They calculated the emotional sentiment of each using two linguistic software programs, and specifically noted those that included weather-related terms.
These findings were then matched with local weather data for the week they were posted. Average temperatures were compared with similar data from past decades.