Headlines this week proclaimed the worst-case scenarios for climate change were "debunked" and "not credible". As you might expect, things aren't that simple. The stories were sparked by a study by Peter Cox at the University of Exeter, UK, and his colleagues, who attempted to work out how much warming will result from a given increase in carbon dioxide levels. Specifically, if we doubled CO2 levels in the atmosphere and waited for the temperature to stabilise, how much would the world warm? This is known as the equilibrium climate sensitivity, and climate scientists have been trying to work it out for decades.
Of course the heat is not a fluke. This has been coming for some time and it is time for all of us to get real about climate change. It is obvious that the positive steps that were made on a federal level are going to get tied up in ideological manipulation and childish bickering that hampers our progress.
Human-induced climate change has led to an increase in the frequency and intensity of daily temperature extremes and has contributed to a widespread intensification of daily precipitation extremes (1, 2). But has it also made specific extreme weather and climate events--such as floods, droughts, and heat waves--more likely? Although it has been said that individual climate events cannot be attributed to anthropogenic climate change (3), a recent assessment by the National Academies of Science concludes that "this is no longer true as an unqualified blanket statement" (4). Robust event attribution can support decisions such as how to rebuild after a disaster and how to price insurance by quantifying the current risk of such events.
Media frames define distinctive perspectives or ways of communicating about issues and can be manifested through patterns of language use, such as preferences for various key terms and phrases. In this work we develop a novel operationalization of moral evaluation frames and study their use within a corpus of blogs discussing climate change. We compare moral evaluation frames between blogs marked as climate change skeptics and climate change acceptors. We develop a text visualization tool called Lingoscope that allows the user to observe and filter the contextual terms that convey moral framing across large volumes of text, as well as to drill down to specific examples. By focusing on climate-related topics and how they are discussed by climate change skeptics versus climate change acceptors, our approach uncovers and explores how numerous topics are framed in a different moral light in skeptical and acceptor blogs.