] ]. ]
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] ] ]In terms of biodiversity, adaptable species with wide geographic ranges—such as white-tailed deer and feral hogs—are likely to continue to thrive. But those species that depend on particular habitats—polar and alpine species, coral reefs, coldwater fishes—are vulnerable, as are the communities that depend on them culturally and economically. ] According to the Fourth National Climate Assessment, “[S]pecies, including many iconic species, may disappear from regions where they have been prevalent or become extinct, altering some regions so much that their mix of plant and animal life will become almost unrecognizable.” ]
Food and forage production will decline in agricultural regions experiencing increased frequency and duration of drought. Even without drought, higher temperatures will increase evaporation of soil moisture, increasing crop stress and water demand—further stressing U.S. surface and groundwater supplies used for irrigation. And even with irrigation, many commodity crops are likely to experience declines in average yield as temperatures rise beyond their preferred heat tolerance range. Milder winters and shifts in precipitation are likely to increase the incidence of pests and diseases for crops and livestock, while extreme heat—especially nighttime heat—will reduce livestock productivity. Impacts will vary from region to region, depending on the extent of warming and the level of adaptation. ]
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] and the trend is likely to continue as many extreme events become more frequent and severe. The economic impacts of extreme events include not just the direct damages, but also the loss of productivity and interruption of essential services and supply chains that can reach deep into the national economy. ]In many parts of the country, existing infrastructure—septic and stormwater systems, roads, bridges, the energy grid—was not designed to cope with current and future sea level and climate extremes, and current levels of investment aren’t enough to cover necessary repairs and upgrades. ] ]
Beyond extreme events, human-caused climate change is likely to disrupt many sectors of the U.S. economy and the communities that depend on them, including commercial and recreational fisheries, tourism and recreation, and agriculture. ] ] ]
In the short term, farmers in some regions may benefit from the earlier onset of spring and from a longer warm season that is suitable for growing crops. Also, studies show that, up to a certain point, crops and other plants grow better in the presence of higher carbon dioxide levels and seem to be more drought-tolerant. ] But this benefit is a two-edged sword: weeds, many invasive plant species, and insect pests will also thrive in a warmer world. Water availability will be impacted in drier agricultural areas that need irrigation. At some point, the benefits to crops of increased carbon dioxide will likely be overwhelmed by the negative impacts of heat stress and drought.
In the long term, shipping commerce will benefit from the opening of the Northwest Passage for longer periods of the year due to the loss of Arctic sea ice. However, in the long run, if a "business as usual" approach to emitting heat-trapping gases is maintained at the present rate, or faster, then the negative costs and impacts of global warming are very likely to far outweigh the benefits over the course of this century, with increased potential for catastrophic impacts from more extreme events. ] In part, this is because any substantial change, whether warmer or colder, would challenge the societal infrastructure that has developed under the current climate.
If all human emissions of heat-trapping gases were to stop today, Earth’s temperature would continue to rise for a few decades as ocean currents bring excess heat stored in the deep ocean back to the surface. Once this excess heat radiated out to space, Earth’s temperature would stabilize. Experts think the additional warming from this “hidden” heat is unlikely to exceed 0.9° Fahrenheit (0.5°Celsius). ] With no further human influence, natural processes would begin to slowly remove the excess carbon dioxide from the atmosphere, and global temperatures would gradually begin to decline.
It’s true that without dramatic action in the next couple of decades, we are unlikely to keep global warming in this century below 2.7° Fahrenheit (1.5° Celsius) compared to pre-industrial temperatures—a threshold that experts say offers a lower risk of serious negative impacts. ] But the more we overshoot that threshold, the more serious and widespread the negative impacts will be, which means that it is never “too late” to take action.
it is likely many strategies working together will be needed. Generally speaking, here are some examples of mitigation strategies we can use to slow or stop the human-caused global warming ( ): techniques.Note that NOAA doesn’t advocate for or against particular climate policies. Instead, NOAA’s role is to provide data and scientific information about climate, including how it has changed and is likely to change in the future depending on different climate policies or actions society may or may not take. Learn more and .
):Note that NOAA doesn’t advocate for or against particular climate policies. Instead, NOAA’s role is to provide data and scientific information about climate, including how it has changed and is likely to change in the future depending on different climate policies or actions society may or may not take. Learn more and .
NOAA is helping to improve the nation’s resilience to changes in climate and weather. Specifically, NOAA is working to…
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The terms “global warming” and “climate change” are sometimes used interchangeably, but "global warming" is only one aspect of climate change.
“Global warming” refers to the long-term warming of the planet. Global temperature shows a well-documented rise since the early 20th century and most notably since the late 1970s. Worldwide since 1880, the average surface temperature has risen about 1 ° C (about 2 ° F), relative to the mid-20th century baseline (of 1951-1980). This is on top of about an additional 0.15 ° C of warming from between 1750 and 1880.
“Climate change” encompasses global warming, but refers to the broader range of changes that are happening to our planet. These include rising sea levels; shrinking mountain glaciers; accelerating ice melt in Greenland, Antarctica and the Arctic; and shifts in flower/plant blooming times. These are all consequences of warming, which is caused mainly by people burning fossil fuels and putting out heat-trapping gases into the air.
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The signs of global warming are everywhere, and are more complex than just climbing temperatures.
Our planet is getting hotter. Since the Industrial Revolution—an event that spurred the use of fossil fuels in everything from power plants to transportation—Earth has warmed by 1 degree Celsius, about 2 degrees Fahrenheit.
That may sound insignificant, but 2023 was the hottest year on record , and all 10 of the hottest years on record have occurred in the past decade.
Global warming and climate change are often used interchangeably as synonyms, but scientists prefer to use “climate change” when describing the complex shifts now affecting our planet’s weather and climate systems.
Climate change encompasses not only rising average temperatures but also natural disasters, shifting wildlife habitats, rising seas , and a range of other impacts. All of these changes are emerging as humans continue to add heat-trapping greenhouse gases , like carbon dioxide and methane, to the atmosphere.
When fossil fuel emissions are pumped into the atmosphere, they change the chemistry of our atmosphere, allowing sunlight to reach the Earth but preventing heat from being released into space. This keeps Earth warm, like a greenhouse, and this warming is known as the greenhouse effect .
Carbon dioxide is the most commonly found greenhouse gas and about 75 percent of all the climate warming pollution in the atmosphere. This gas is a product of producing and burning oil, gas, and coal. About a quarter of Carbon dioxide also results from land cleared for timber or agriculture.
Methane is another common greenhouse gas. Although it makes up only about 16 percent of emissions, it's roughly 25 times more potent than carbon dioxide and dissipates more quickly. That means methane can cause a large spark in warming, but ending methane pollution can also quickly limit the amount of atmospheric warming. Sources of this gas include agriculture (mostly livestock), leaks from oil and gas production, and waste from landfills.
One of the most concerning impacts of global warming is the effect warmer temperatures will have on Earth's polar regions and mountain glaciers. The Arctic is warming four times faster than the rest of the planet. This warming reduces critical ice habitat and it disrupts the flow of the jet stream, creating more unpredictable weather patterns around the globe.
( Learn more about the jet stream. )
A warmer planet doesn't just raise temperatures. Precipitation is becoming more extreme as the planet heats. For every degree your thermometer rises, the air holds about seven percent more moisture. This increase in moisture in the atmosphere can produce flash floods, more destructive hurricanes, and even paradoxically, stronger snow storms.
The world's leading scientists regularly gather to review the latest research on how the planet is changing. The results of this review is synthesized in regularly published reports known as the Intergovernmental Panel on Climate Change (IPCC) reports.
A recent report outlines how disruptive a global rise in temperature can be:
Limiting the rising in global warming is theoretically achievable, but politically, socially, and economically difficult.
Those same sources of greenhouse gas emissions must be limited to reduce warming. For example, oil and gas used to generate electricity or power industrial manufacturing will need to be replaced by net zero emission technology like wind and solar power. Transportation, another major source of emissions, will need to integrate more electric vehicles, public transportation, and innovative urban design, such as safe bike lanes and walkable cities.
( Learn more about solutions to limit global warming. )
One global warming solution that was once considered far fetched is now being taken more seriously: geoengineering. This type of technology relies on manipulating the Earth's atmosphere to physically block the warming rays of the sun or by sucking carbon dioxide straight out of the sky.
Restoring nature may also help limit warming. Trees, oceans, wetlands, and other ecosystems help absorb excess carbon—but when they're lost, so too is their potential to fight climate change.
Ultimately, we'll need to adapt to warming temperatures, building homes to withstand sea level rise for example, or more efficiently cooling homes during heat waves.
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Evidence and causes: update 2020.
Climate change is one of the defining issues of our time. It is now more certain than ever, based on many lines of evidence, that humans are changing Earth's climate. The Royal Society and the US National Academy of Sciences, with their similar missions to promote the use of science to benefit society and to inform critical policy debates, produced the original Climate Change: Evidence and Causes in 2014. It was written and reviewed by a UK-US team of leading climate scientists. This new edition, prepared by the same author team, has been updated with the most recent climate data and scientific analyses, all of which reinforce our understanding of human-caused climate change.
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Open Access
Peer-reviewed
Research Article
Contributed equally to this work with: Maurice Lineman, Yuno Do
Affiliation College of Natural Sciences, Department of Biological Sciences, Pusan National University, Busan, South Korea
* E-mail: [email protected]
The increasing prevalence of social networks provides researchers greater opportunities to evaluate and assess changes in public opinion and public sentiment towards issues of social consequence. Using trend and sentiment analysis is one method whereby researchers can identify changes in public perception that can be used to enhance the development of a social consciousness towards a specific public interest. The following study assessed Relative search volume (RSV) patterns for global warming (GW) and Climate change (CC) to determine public knowledge and awareness of these terms. In conjunction with this, the researchers looked at the sentiment connected to these terms in social media networks. It was found that there was a relationship between the awareness of the information and the amount of publicity generated around the terminology. Furthermore, the primary driver for the increase in awareness was an increase in publicity in either a positive or a negative light. Sentiment analysis further confirmed that the primary emotive connections to the words were derived from the original context in which the word was framed. Thus having awareness or knowledge of a topic is strongly related to its public exposure in the media, and the emotional context of this relationship is dependent on the context in which the relationship was originally established. This has value in fields like conservation, law enforcement, or other fields where the practice can and often does have two very strong emotive responses based on the context of the problems being examined.
Citation: Lineman M, Do Y, Kim JY, Joo G-J (2015) Talking about Climate Change and Global Warming. PLoS ONE 10(9): e0138996. https://doi.org/10.1371/journal.pone.0138996
Editor: Hayley J. Fowler, Newcastle University, UNITED KINGDOM
Received: August 18, 2014; Accepted: September 8, 2015; Published: September 29, 2015
Copyright: © 2015 Lineman et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Data Availability: All relevant data are within the paper.
Funding: This study was financially supported by the 2015 Post-Doc Development Program of Pusan National University.
Competing interests: The authors have declared that no competing interests exist.
Identifying trends in the population, used to be a long and drawn out process utilizing surveys and polls and then collating the data to determine what is currently most popular with the population [ 1 , 2 ]. This is true for everything that was of merit to the political organizations present, regarding any issue of political or public interest.
Recently, the use of the two terms ‘Climate Change’ and ‘Global Warming’ have become very visible to the public and their understanding of what is happening with respect to the climate [ 3 ]. The public response to all of the news and publicity about climate has been a search for understanding and comprehension, leading to support or disbelief. The two terms while having similarity in meaning are used in slightly different semantic contexts. The press in order to expand their news readership/viewer lists has chosen to use this ambiguity to their favor in providing news to the public [ 4 ]. Within the news releases, the expression ‘due to climate change’ has been used to explain phenomological causality.
These two terms “global warming–(GW)” and “climate change–(CC)” both play a role in how the public at large views the natural world and the changes occurring in it. They are used interactively by the news agencies, without a thought towards their actual meaning [ 3 , 4 ]. Therefore, the public in trying to identify changes in the news and their understanding of those changes looks for the meaning of those terms online. The extent of their knowledge can be examined by assessing the use of the terms in online search queries. Information searches using the internet are increasing, and therefore can indicate public or individual interest.
Internet search queries can be tracked using a variety of analytic engines that are independent of, or embedded into, the respective search engines (google trend, naver analytics) and are used to determine the popularity of a topic in terms of internet searches [ 5 ]. The trend engines will look for selected keywords from searches, keywords chosen for their relevance to the field or the query being performed.
The process of using social media to obtain information on public opinion is a practice that has been utilized with increasing frequency in modern research for subjects ranging from politics [ 6 , 7 ] to linguistics [ 8 – 10 ] complex systems [ 11 , 12 ] to environment [ 13 ]. This variety of research belies the flexibility of the approach, the large availability of data availability for mining in order to formulate a response to public opinion regarding the subject being assessed. In modern society understanding how the public responds regarding complex issues of societal importance [ 12 ].
While the two causally connected terms GW and CC are used interchangeably, they describe entirely different physical phenomena [ 14 ]. These two terms therefore can be used to determine how people understand the parallel concepts, especially if they are used as internet search query terms in trend analysis. However, searching the internet falls into two patterns, searches for work or for personal interest, neither of which can be determined from the trend engines. The By following the searches, it is possible to determine the range of public interest in the two terms, based on the respective volumes of the search queries. Previously in order to mine public opinion on a subject, government agencies had to revert to polling and surveys, which while being effective did not cover a very large component of the population [ 15 – 17 ].
Google trend data is one method of measuring popularity of a subject within the population. Individuals searching for a topic use search keywords to obtain the desired information [ 5 , 18 ]. These keywords are topic sensitive, and therefore indicate the level of knowledge regarding the searched topic. The two primary word phrases here “climate change” and “global warming” are unilateral terms that indicate a level of awareness about the issue which is indicative of the individuals interest in that subject [ 5 , 19 , 20 ]. Google trend data relates how often a term is searched, that is the frequency of a search term can be identified from the results of the Google® trend analysis. While frequency is not a direct measure of popularity, it does indicate if a search term is common or uncommon and the value of that term to the public at large. The relationship between frequency and popularity lies in the volume of searches by a large number of individuals over specific time duration. Therefore, by identifying the number of searches during a specific period, it is possible to come to a proximate understanding of how popular or common a term is for the general population [ 21 ]. However, the use of trend data is more appropriately used to identify awareness of an issue rather than its popularity.
This brings us to sentiment analysis. Part of the connection between the search and the populations’ awareness of an issue can be measured using how they refer to the subject in question. This sentiment, is found in different forms of social media, or social networking sites sites i.e. twitter®, Facebook®, linked in® and personal blogs [ 7 , 22 – 24 ]. Thus, the original information, which was found on the internet, becomes influenced by personal attitudes and opinions [ 25 ]and then redistributed throughout the internet, accessible to anyone who has an internet connection and the desire to search. This behavior affects the information that now provides the opportunity to assess public sentiment regarding the prevailing attitudes regarding environmental issues [ 26 , 27 ]. To assess this we used Google® and Twitter® data to understand public concerns related to climate change and global warming. Google trend was used to trace changes in interest between the two phenomena. Tweets (comments made on Twitter®) were analyzed to identify negative or positive emotional responses.
Comparatively, twitter data is more indicative of how people refer to topics of interest [ 28 – 31 ], in a manner that is very linguistically restricted. As well, twitter is used as a platform for verbal expression of emotional responses. Due to the restrictions on tweet size (each tweet can only be 140 characters in length), it is necessary to be more direct in dealing with topics of interest to the tweeter. Therefore, the tweets are linguistically more emotionally charged and can be used to define a level of emotional response by the tweeter.
The choice of target words for the tweets and for the Google trend searches were the specific topic phrases [ 32 , 33 ]. These were chosen because of the descriptive nature of the phrases. Scientific literature is very specific in its use and therefore has very definitive meanings. The appropriation of these words by the population as a method for describing their response to the variation in the environment provides the basis for the choice as target words for the study. The classification of the words as being positive versus negative lies in the direction provided by Frank Lutz. This politicization of a scientific word as a means of directing public awareness, means the prescription of one phrase (climate change) as being more positive than the other (global warming).
Global warming is defined as the long-term trend of increasing average global temperatures; alternatively, climate change is defined as a change in global or regional climate patterns, in particular a change apparent from the mid to late 20 th century onwards and attributed to the increased levels of atmospheric carbon dioxide arising from the use of fossil fuels. Therefore, the search keywords were chosen based on their scientific value and their public visibility. What is important about the choice of these search terms is that due to their scientific use, they describe a distinctly identifiable state. The more specific these words are, the less risk of the algorithm misinterpreting the keyword and thus having the results misinterpreted [ 34 – 36 ].
The purpose of the following study was to identify trends within search parameters for two specific sets of trend queries. The second purpose of the study was to identify how the public responds emotionally to those same queries. Finally, the purpose of the study was to determine if the two had any connections.
Public awareness of the terms climate change and global warming was identified using Google Trends (google.com/trends) and public databases of Google queries [ 37 ]. To specify the exact searches we used the two terms ‘climate change’ and ‘global warming’ as query phrases. Queries were normalized using relative search volume (RSV) to the period with the highest proportion of searches going to the focal terms (i.e. RSV = 100 is the period with the highest proportion for queries within a category and RSV = 50 when 50% of that is the highest search proportion). Two assumptions were necessary for this study. The first is, of the two terms, climate change and global warming, that which draws more search results is considered more interesting to the general population. The second assumption is that changes in keyword search patterns are indicators of the use of different forms of terminology used by the public. To analyze sentiments related to climate change and global warming, tweets containing acronyms for climate change and global warming were collected from Twitter API for the period from October 12 to December 12, 2013. A total of 21,182 and 26,462 tweets referencing the terms climate change and global warming were collected respectively. When duplicated tweets were identified, they were removed from the analysis. The remaining tweets totaled 8,465 (climate change) and 8,263 (global warming) were compiled for the sentiment analysis.
In Twitter® comments are emotionally loaded, due to their textually shortened nature. Sentiment analysis, which is in effect opinion mining, is how opinions in texts are assessed, along with how they are expressed in terms of positive, neutral or negative content [ 36 ]. Nasukawa and Yi [ 10 ]state that sentiment analysis identifies statements of sentiment and classifies those statements based on their polarity and strength along with their relationship to the topic.
Sentiment analysis was conducted using Semantria® software ( www.semantria.com ), which is available as an MS Excel spreadsheet application plugin. The plugin is broken into parts of speech (POS), the algorithm within the plugin then identifies sentiment-laden phrases and then scores them from -10 to 10 on a logarithmic scale, and finally the scores for each POS are tabulated to identify the final score for each phrase. The tweets are then via statistical inferences tagged with a numerical value from -2 to 2 and given a polarity, which is classified as positive, neutral or negative [ 36 ]. Semantria®, the program utilized for this study, has been used since 2011 to perform sentiment analyses [ 7 , 22 ].
For the analysis, an identity column was added to the dataset to enable analysis of individual tweets with respect to sentiment. A basic sentiment analysis was conducted on the dataset using the Semantria® plugin. The plugin uses a cloud based corpus of words tagged with sentimental connotations to analyze the dataset. Through statistical inference, each tweet is tagged with a sentiment value from -2 to +2 and a polarity of (i) negative, (ii) neutral, or (iii) positive. Positive nature increases with increasing positive sentiment. The nature of the language POS assignation is dependent upon the algorithmic classification parameters defined by the Semantria® program. Determining polarity for each POS is achieved using the relationship between the words as well as the words themselves. By assigning negative values to specific negative phrases, it limits the use of non-specific negation processes in language; however, the program has been trained to assess non-specific linguistic negations in context.
A tweet term frequency dictionary was computed using the N-gram method from the corpus of climate change and global warming [ 38 ]. We used a combination of unigrams and bigrams, which has been reported to be effective [ 39 ]. Before using the N-gram method, typological symbols were removed using the open source code editor (i.e. Notepad) or Microsoft Words’ “Replace” function.
Differences in RSV’s for the terms global warming and climate change for the investigation period were identified using a paired t-test. Pettitt and Mann-Kendall tests were used to identify changes in distribution, averages and the presence of trends within the weekly RSV’s. The Pettitt and MK tests, which assume a stepwise shift in the mean (a break point) and are sensitive to breaks in the middle of a time series, were applied to test for homogeneity in the data [ 40 ]. Temporal trends within the time series were analyzed with Spearman’s non-parametric correlation analysis. A paired t-test and Spearman’s non-parametric correlation analysis were conducted using SPSS software (version 17.0 SPSS In corp. Chicago IL) and Pettitt and MK tests were conducted using XLSTAT (version 7.0).
To determine the accuracy and reliability of the Sentiment analysis, a Pearson’s chi-square analysis was performed. This test identifies the difference ratio for each emotional response group, and then compares them to determine reliance and probability of interactions between the variables, in this case the terms global warming and climate change.
According to Google trend ( Fig 1 ) from 2004–2014, people searched for the term global warming (n = 8,464; mean ± S.D = 25.33 ± 2.05) more frequently than climate change (n = 8,283; mean ± S.D. = 7.97±0.74). Although the Intergovernmental Panel on Climate Change (IPCC) published its Fourth Assessment Report in 2007 and was awarded the Nobel Prize, interest in the term global warming as used in internet searches has decreased significantly since 2010 (K = 51493, t = 2010-May-23, P<0.001). Further the change in RSV also been indicative of the decreased pattern (Kendall’s tau = -0.336, S = -44563, P<0.001). The use of the term “climate change” has risen marginally since 2006 (K = 38681, t = 2006-Oct-08, P<0.001), as indicated by a slight increase (Kendall’s tau = -0.07, S = 9068, P<0.001). These findings show that the difference in usage of the two terms climate change and global warming has recently been reduced.
https://doi.org/10.1371/journal.pone.0138996.g001
The sentiment analysis of tweets ( Fig 2 ) shows that people felt more negative about the term global warming (sentiment index = -0.21±0.34) than climate change (-0.068±0.36). Global warming tweets reflecting negative sentiments via descriptions such as, “bad, fail, crazy, afraid and catastrophe,” represented 52.1% of the total number of tweets. As an example, the tweet, “Supposed to snow here in the a.m.! OMG. So sick of already, but Saturday says 57 WTF!” had the lowest score at -1.8. Another observation was that 40.7% of tweets, including “agree, recommend, rescue, hope, and contribute,” were regarded as neutral. While 7.2% of tweets conveyed positive messages such as, “good, accept, interesting, and truth.” One positive global warming tweet, read, “So if we didn’t have global warming, would all this rain be snow!”. The results from the Pearson’s chi-square analysis showed that the relationship between the variables was significant (Pearson’s chi-square –763.98, d.f. = 2, P<0.001). Negative climate change tweets represented 33.1% of the total while neutral tweets totaled 49.8%, while positive climate change tweets totaled 17.1%.
https://doi.org/10.1371/journal.pone.0138996.g002
Understandably, global warming and climate change are the terms used most frequently to describe each phenomenon, respectively, as revealed by the N-gram analysis ( Table 1 ). When people tweeted about global warming, they repeatedly used associated such as, “ice, snow, Arctic, and sea.” In contrast, tweets referring to climate change commonly used, “report, IPCC, world, science, environment, and scientist.” People seem to think that climate change as a phenomenon is revealed by scientific investigation.
https://doi.org/10.1371/journal.pone.0138996.t001
Internet searches are one way of understanding the popularity of an idea or meme within the public at large. Within that frame of reference, the public looks at these two terms global warming and climate change and their awareness of the roles of the two phenomena [ 41 ]. From 2004 to 2008, the search volumes for the term global warming far exceeded the term climate change. The range for the term global warming in Relative search volumes (RSV) was more than double that of climate change in this period ( Fig 1 ). From 2008 on the RSV’s began to steadily decrease until in 2014 when the RSV’s for the term global warming were nearly identical to those for the term climate change. From 2008 there was an increase in the RSVs for CC until 2010 at which point the RSVs also began to decline for the term climate change. The decline in the term climate change for the most part paralleled that of the term global warming from 2010 on to the present.
While we are seeing the increases and decreases in RSVs for both the terms global warming and climate change, the most notable changes occur when the gap between the terms was the greatest, from 2008 through to 2010. During this period, there was a very large gap found between the RSVs for the terms global warming and climate change; however, searches for the term climate change was increasing while searches for the tem global warming were decreasing. The counter movement of the RSV’s for the two terms shows that there is a trend happening with respect to term recognition. At this point, there was an increase in the use of the CC term while there was a corresponding decrease in the use of the GW term. The change in the use of the term could have been due to changes in the publicity of the respective terms, since at this point, the CC term was being used more visibly in the media, and therefore the CC term was showing up in headlines and the press, resulting in a larger number of searches for the CC term. Correspondingly, the decrease in the use of the GW term is likely due to the changes in how the term was perceived by the public. The public press determines how a term is used, since they are the body that consistently utilizes a term throughout its visible life. The two terms, regardless of how they differ in meaning, are used with purpose in a scientific context, yet the public at large lacks this definition and therefore has no knowledge of the variations in the terms themselves [ 42 ]. Therefore, when searching for a term, the public may very well, choose the search term that they are more comfortable with, resulting in a search bias, since they do not know the scientific use of the term.
The increase in the use of the CC term, could be a direct result of the release of the fourth assessment report for the IPCC in 2007 [ 43 ]. The publicity related to the release of this document, which was preceded by the release of the Al Gore produced documentary “An Inconvenient Truth”, both of which were followed by the selection by the Nobel committee of Al Gore and the IPCC scientists for the Nobel Prize in 2007 [ 43 ]. These three acts individually may not have created the increased media presence of the CC term; however, at the time the three events pushed the CC term and increased its exposure to the public which further drove the public to push for positive environmental change at the political level [ 44 , 45 ]. This could very well have resulted in the increases in RSV’s for the CC term. This point is more likely to depict accurately the situation, since in 2010 the use of the two terms decline at almost the same rate, with nearly the same patterns.
Thus with respect to trend analysis, what is interesting is that RSVs are paralleling the press for specific environmental events that have predetermined value according to the press. The press in increasing the visibility of the term may drive the increases in the RSV’s for that term. Prior to 2007, the press was using the GW term indiscriminately whenever issues affecting the global climate arose; however, after the movie, the report and then the Nobel prize the terminology used by the press switched and the CC term became the word du jour. This increased the visibility of the word to the public, thereby it may be that increasing public awareness of the word, but not necessarily its import, is the source for the increases in RSV’s between 2008 and 2010.
The decline in the RSV’s then is a product of the lack of publicity about the issue. As the terms become more familiar, there would be less necessity to drive the term publicly into the spotlight; however, occasionally events/situations arise that refocus the issue creating a resurgence in the terms even though they have reached their peak visibility between 2008 and 2010.
Since these terms have such an impact on the daily lives of the public via local regional national and global weather it is understandable that they have an emotional component to them [ 46 ]. Every country has its jokes about the weather, where they come up with cliché’s about the weather (i.e. if you don’t like the weather wait 10minutes) that often show their discord and disjunction with natural climatological patterns [ 47 ]. Furthermore, some sectors of society (farmers) have a direct relationship with the climate and their means of living; bad weather is equal to bad harvests, which means less money. To understand how society represents this love hate relationship with the weather, the twitter analysis was performed. Twitter, a data restricted social network system, has a limited character count to relay information about any topic the sender chooses to relate. These tweets can be used to assess the sentiment of the sender towards a certain topic. As stated previously, the sentiment is defined by the language of the tweet within the twitter system. Sentiment analysis showed that the two terms differed greatly. Based on the predefined algorithm for the sentiment analysis, certain language components carried a positive sentiment, while others carried a negative sentiment. Tweets about GW and CC were subdivided based on their positive, neutral and negative connotations within the tweet network. These emotions regardless of their character still play a role in how humans interacts with surroundings including other humans [ 48 , 49 ] As seen in Fig 2 the different terms had similar distributions, although with different ranges in the values. Global warming showed a much smaller positive tweet value than did climate change. Correspondent to this the respective percentage of positive sentiments for CC was more than double that of GW. Comparatively, the neutral percentiles were more similar for each term with a small difference. However, the negative sentiments for the two terms again showed a greater disparity, with negative statements about GW nearly double those of climate change.
These differences show that there is a perceptive difference in how the public relates to the two terms Global Warming and Climate Change [ 50 , 51 ]. Climate change is shown in a more positive light than global warming simply based on the tweets produced by the public. The difference in how people perceive climate change and global warming is possibly due to the press, personal understanding of the terms, or level of education. While this in itself is indefinable, since by nature tweets are linguistically restrictive, the thing to take from it is that there is a measurable difference in how individuals respond to climatological changes that they are experiencing daily. These changes have a describable effect on how the population is responding to the publicity surrounding the two terms to the point where it can be used to manipulate governmental policy [ 52 ].
Sentiment analysis is a tool that can be used to determine how the population feels about a topic; however, the nature of the algorithm makes it hard to effectively determine how this is being assessed. For the current study, the sentiment analysis showed that there was a greater negative association with the term global warming than with the term climate change. This difference, which while being an expression of individual like or dislike at the time the tweet was created, denotes that the two terms were either not understood in their true form, or that individuals may have a greater familiarity with one term over the other, which may be due to a longer exposure to the term (GW) or the negative press associated with the term (GW).
Trend analysis identified that the public is aware of the terminology used to describe climatological variation. The terminology showed changes in use over time with global warming starting as the more well-known term, and then its use decreased over time. At the same time, the more definitive term climate change had less exposure early on; however, with the increase of press exposure, the public became increasingly aware of the term and its more accurate definition. This increase appeared to be correspondent with the increasing publicity around three very powerful press exposure events (a documentary, a scientific report release and a Nobel Prize). The more the term was used the more people came to use it, this included searches on the internet.
Comparatively sentiment analysis showed that the two terms had differential expressions in the population. With climate change being seen in a more positive frame than global warming. The use of sentiment analysis as a tool to evaluate how the population is responding to a feature is an important tool. However, it is a tool that measures, it does not define.
Social network systems and internet searches are effective tools in identifying changes in both public awareness and public perception of an issue. However, in and of itself, these are bell ringers they can be used to determine the importance of an issue, but not the rationale behind the why it is important. This is an important fact to remember when using analytical tools that evaluate social network systems and their use by the public.
This study was financially supported by the 2015 Post-Doc. Development Program of Pusan National University
Conceived and designed the experiments: YD GJJ. Performed the experiments: ML YD. Analyzed the data: ML YD. Contributed reagents/materials/analysis tools: JK YD. Wrote the paper: ML YD GJJ.
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The terms “global warming,” “climate crisis,” “climate emergency,” and “climate justice” each draw attention to different aspects of climate change. Psychological theories of attitude formation suggest that people’s attitudes can be influenced by such variations in terminology. In a national experiment, we randomly assigned a national sample of 5,137 U.S. residents to “climate change,” “global warming,” “climate crisis,” “climate emergency,” or “climate justice” and examined their responses. Overall, “climate change” and “global warming” were rated as most familiar and most concerning, and “climate justice” the least, with ratings for “climate crisis” and “climate emergency” falling in between. Moreover, we find no evidence for “climate crisis” or “climate emergency” eliciting more perceived urgency than “climate change” or “global warming.” Rated willingness to support climate-friendly policies and eat less red meat were less affected by presented terms, but they were lowest for “climate justice.” Although effects of terms on rated familiarity, concern, and perceived urgency varied by political leaning, “climate justice” generally received the lowest ratings on these variables among Democrats, Republicans, and Independent/others. Auxiliary analyses found that when terms were unfamiliar, participants were generally less likely to express concern, urgency, policy support, or willingness to eat less red meat. We therefore recommend sticking with familiar terms, conclude that changing terminology is likely not the key solution for promoting climate action, and suggest alternative communication strategies.
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1.1 words matter.
Psychological theories of attitude formation suggest that attitudes about a topic are influenced by topic-related information that comes to mind in the moment (Schwarz 2007 ; Sudman et al. 1996 ). In line with those theories, survey design research has been showing for decades that words that draw attention to different aspects of a topic can sway public opinion about that topic (Cantril 1944 ; Payne 1951 ). Similarly, classic psychological studies have found that seemingly slight variations in how options are framed can affect people’s judgments and decisions (Tversky and Kahneman 1981 ; Levin et al. 1988 ). For example, food without meat and dairy is more likely to be chosen when it is labeled “plant-based” rather than “vegan” -- and becomes even more popular when labels say “healthy” or “sustainable” to emphasize the benefits of eating food without meat and dairy (Sleboda et al. 2024 ). While “healthy” and “sustainable” are not exactly synonyms of the term “vegan,” vegan food does tend to be more healthy and sustainable than non-vegan food (Sleboda et al. 2024 ). Hence, there is reason to suspect that the terms that have been proposed to emphasize different aspects of “climate change” may affect people’s responses, including their concern about the topic, and their willingness to do something about it (e.g. Schuldt et al. 2011 ). The present paper therefore examines public responses to the terms “climate change,” “global warming,” “climate crisis,” “climate emergency,” and “climate justice,” among Democrats, Republicans, and Independents/others (see Sect. 1.6).
Terms like “climate change” and “global warming” have long been used to describe the climate impacts of increasing anthropogenic greenhouse gases in the atmosphere (Penz 2017 ). Although “climate change” and “global warming” are often used interchangeably in the public discourse (Benjamin 2017 ), they are not synonyms and emphasize different aspects of the phenomenon. Specifically, “climate change” refers to diverse changes in the climate that may or may not be due to human activity while “global warming” refers to increasing global surface temperatures and implies that humans are actively warming the planet (Penz 2017 ). Indeed, the term “climate change” was initially popularized by an advisor to the Bush administration to de-emphasize the role of human activity (Penz 2017 ). Google Trends between 2004 and 2014 found that, as an internet search term, “climate change” was initially less popular than “global warming” (Lineman et al. 2015 ). Consistent with this trend, a 2003 public perception study in South England found that “climate change” was less familiar than “global warming,” while also raising less concern or calls for action (Whitmarsh 2009 ). However, “climate change” and “global warming” were similarly likely to be searched in 2014, and “climate change” had overtaken “global warming” in 2016 (Penz 2017 ).
In addition to “climate change” and “global warming,” other terms have been introduced to focus the public discourse on other aspects of the phenomenon. Like “global warming,” none of these terms are synonyms of “climate change,” but they emphasize aspects of climate change to try to increase public responsiveness. In 2019, The Guardian newspaper switched to using “climate crisis” and “climate emergency” in an effort to raise concern and convey urgency (Schäfer et al. 2023 ). Additionally, the term “climate justice” has been introduced by left-leaning grassroot organizations to draw attention to climate change as a human rights challenge (Dutta 2019 ). That is, disadvantaged communities will suffer the most from the effects of climate change despite being the least responsible for causing it (Dutta 2019 ; Schlosberg and Collins 2014 ; Saraswat and Kumar 2016 ). It has been suggested that linking climate policy to justice may increase public support (Bergquist et al. 2020 ).
Americans who lean Republican are traditionally more skeptical about climate change than Americans who lean Democrat (Pew Research Center 2023a ), in agreement with political parties’ stance on the issue. In part, this reflects Americans’ tendency to support the views of their political party and devalue the views of the other political party (van Boven et al. 2018 ).
Since the early 2000s, national experiments have been examining whether the words used for “climate change” affect this partisan divide (e.g., Akerlof and Maibach 2011 ; Schuldt et al. 2011 ; Villar and Krosnick 2011 ). In the early 2000’s, Republicans in the United States (U.S.) reported being more skeptical when they were asked about “global warming” than when they were asked about “climate change,” perhaps because Republicans tended to question “global warming” during unseasonably cold weather (Schuldt et al. 2011 , 2015 ; Morin-Chassé et al. 2020 ). A Republican senator even brought a snowball into U.S. Congress in 2015 to highlight how cold it was and to question “global warming” (Fisher et al. 2015 ).
In line with this finding, Republicans used to consider “climate change” as more serious than “global warming” (Villar and Krosnick 2011 ). In contrast, Democrats considered “global warming” more serious than “climate change” (Villar and Krosnick 2011 ), perhaps because the former suggests the contribution of human activity (Penz 2017 ). When asked to choose between “climate change” and “global warming,” most Americans had no preference, though Democrats slightly preferred “global warming” (Akerlof and Maibach 2011 ). However, Democrats and Independents/others showed relatively less skepticism than Republicans, independent of the presented terms (Schuldt et al. 2011 ).
Over time, partisan differences in responses to the terms “climate change” and “global warming” have faded (Schuldt et al. 2020 ). In 2018, about 75% of Republicans and 95% of Democrats indicated that they thought “climate change” and “global warming” were real, thus no longer showing an effect of terminology on reported concerns (Schuldt et al. 2020 ). However, the influence of saying “climate change” or “global warming” may be stronger on concerns than on willingness to act, and on Independents/others who do not have strong opinions about the phenomenon (Benjamin et al. 2017 ).
Few studies have examined public responses to “climate crisis” and “climate emergency,” which were introduced to raise public concern and emphasize urgency (Schäfer et al. 2023 ). One study with a U.S. national sample found no differences in willingness to support specific policies after reading news stories mentioning “climate crisis,” “climate emergency” or “climate change,” and there were no partisan differences in responses to those terms (Feldman and Hart 2021 ). However, perceived credibility and newsworthiness were generally worse for “climate emergency” than for “climate change” (Feldman and Hart 2021 ). Two other studies also examined public responses to the “climate crisis,” but not whether they varied by political leaning (Jaskuslky and Besel 2013 ; Hung and Bayrak 2020 ). The first study found that American undergraduate students expressed the least concern about rising temperatures after reading a news story about the “climate crisis,” as compared to “climate change,” or “global warming” (Jaskulsky and Besel 2013 ). The second study was conducted with Taiwanese adults, and found no differences in their reported concerns or willingness to act when they were asked about the “climate crisis” or “climate change” (Hung and Bayrak 2020 ). However, people with individualistic or hierarchical world views reported relatively less willingness to act on the “climate crisis” than on “climate change” (Hung and Bayrak 2020 ). While these findings suggest that saying “climate crisis” or “climate emergency” could potentially be counterproductive (Jaskulsky and Besel 2013 ; Hung and Bayrak 2020 ; Feldman and Hart 2021 ), public responses to terms change over time (Schuldt et al. 2020 ; Benjamin et al. 2017 ).
We found no national experiments that examined the relative benefits of using the term “climate justice” as compared to other terms. As noted, the term “climate justice” was introduced by left-leaning grassroots organizations to emphasize the unfairness of unequal vulnerabilities to climate change (Dutta 2019 ; Schlosberg and Collins 2014 ), and linking climate policy to justice may improve public support (Bergquist et al. 2020 ). However, one study that examined U.S. residents’ familiarity with the concept found that only 37–44% was aware that climate change affects “some groups more than others” (Schuldt and Pearson 2023 ). Moreover, a study in the United Kingdom found that narratives that focus on “climate justice” are politically polarizing because they resonate with left-leaning audiences and are off-putting to right-leaning audiences (Whitmarsh and Corner 2017 ). It remains an open question how the term “climate justice” will be received by U.S. residents with different political leanings.
Here, we aimed to examine public responses to terms that emphasize different aspects of climate change, and whether these responses differed by respondents’ political leaning. Specifically, we conducted a national terminology experiment in which we randomly assigned a nationally representative sample of 5,137 U.S. adults to survey questions about the terms “climate change,” “global warming,” “climate crisis,” “climate emergency,” and “climate justice.” Our first research aim was to examine the effect of terminology on participants’ ratings of familiarity, concern, perceived urgency, willingness to support policies, and willingness to eat less red meat. Thus, we incorporated measures of beliefs and intentions to act, in recognition of previous findings suggesting that the use of different terms is more likely to affect beliefs than intentions to act (Benjamin et al. 2017 ). Willingness to eat less red meat was included because the IPCC ( 2019 ; 2022 ) has recommended this dietary shift as a major opportunity for reducing greenhouse gas emissions, which would, in turn, curb climate change and its disproportionate impact on vulnerable communities. Our second research aim was to examine whether the effects of the randomly assigned terms on ratings of familiarity, concern, urgency, willingness to support climate-friendly policies, and willingness to eat less red meat were moderated by Democratic, Republican, or Independent/other political leaning.
Our sample includes 5,137 participants of the Understanding America Study, a national survey panel directed by the University of Southern California’s Understanding America Study (UAS), including 1,852 Democrats, 1,697 Republicans, and 1,588 Independent/others. Panel members were recruited from randomly selected U.S. addresses, sampling probabilities were adjusted for underrepresented populations, and internet-connected tablets were provided to interested individuals if needed. They are regularly invited to complete surveys and receive $20 for each 30 minutes of participation.
Initially, 7,607 participants were invited to complete a survey that asked about their political leaning. Only those 5,763 (75%) who reported their political leaning were eligible for our survey. Of those, 5,137 (89%) completed our survey, thus retaining 68% of original invitees. Figure S1 shows the flowchart of participants’ pathway through the surveys. Table 1 compares sample demographics to 2022 population statistics from the U.S. Census, before and after applying post-stratification weights. These post-stratification weights, generated through a raking algorithm, were used in all analyses to align the sample to the U.S. adult population, in terms of age, gender, race/ethnicity, education, and geographic location (see www.uasdata.usc.edu/page/Weights ).
Participants were randomly assigned to receive questions about “climate change” (unweighted N = 1,071), “global warming” (unweighted N = 1,009), “climate crisis” (unweighted N = 1,037), “climate emergency” (unweighted N = 1,014), and “climate justice” (unweighted N = 1,006). Table S1 shows demographic characteristics of participants who completed our questions about each randomized term. Participants received five questions about their assigned term (Table 2 ). The questions about willingness to support policies and willingness to eat less red meat were preceded by a sentence that mentioned the assigned term (Table 2 ). Survey design research suggests that people take into account such preceding sentences when interpreting survey questions (Schwarz 1999 ). As is common practice on the UAS, we also offered a Spanish version of our survey (Table S3 ), even though few UAS participants tend to select it. Indeed, most American residents of Hispanic origin are proficient in English (Pew Research Center 2023b ).
Our survey was conducted in June-August 2023 (survey #556 of the Understanding America Study; https://uasdata.usc.edu/index.php ). In December 2022-February 2023, participants had been asked “regardless of how you are registered to vote, are you more closely aligned with…” (survey #500 of the Understanding America Study; https://uasdata.usc.edu/index.php ). They could indicate Democrat, Republican, Independent (no party), Libertarian, Green Party, some other party, or not aligned with any party. Participants indicating the latter five responses were classified as Independents/others. Table S2 shows that self-reported political leaning was significantly associated with each demographic characteristic, with Republicans being the least likely to indicate wanting the Spanish survey version, or being 65 or younger, female, college-educated, or from a racial/ethnic minority group.
For ease of interpretation, we present the percent of participants who gave a positive response by using the top half of the 4-point rating scale for each of our dependent variables (Table 3 ). Terms’ mean ratings of familiarity, concern, perceived urgency, willingness to support policies, and willingness to eat less red meat appear in Figs. 1 and 2 . Our main analyses treated each rating as a continuous variable. For each rating, we conducted a separate Analysis of Covariance in which we examined the effect of terminology (“climate change,” “global warming,” “climate crisis,” “climate emergency,” or “climate justice”) and political leaning (Democrat, Republican, or Independent/other) as well as their interaction (Table 4 ). Because demographic characteristics were associated with political leaning (Table S2 ), covariates included selecting the Spanish (vs. English) survey version, being aged 65 or older (vs. not), being female (vs. not), having a college degree (vs. not), and identifying with the three largest race/ethnicity groups, including Hispanic (vs. not), Non-Hispanic White (vs. not) or Non-Hispanic Black (vs. not). Overall conclusions were unaffected by including or excluding these covariates. We computed partial η 2 to assess the effect size for each main effect and the interaction. For partial η 2 , 0.01 reflects a small effect size, 0.06 a medium effect size, and 0.14 a large effect size (Cohen 1969 ). We treated significant effects with a partial η 2 < 0.01 as showing no meaningful difference.
Mean reported ( A ) familiarity, ( B ) concern, ( C ) urgency, ( D ) willingness to support policies, and ( E ) willingness to eat less red meat by term
Note: Survey questions and response scales are described in Table 2 . Poststratification weights were used in these analyses. Error bars reflect standard errors. Significance tests of pairwise comparisons between terms are reported in Table S4
Mean reported ( A ) familiarity, ( B ) concern, ( C ) urgency, ( D ) willingness to support policies, and ( E ) willingness to eat less red meat, by term and political leaning
Note: Survey questions and response scales are described in Table 2 . Poststratification weights were used in these analyses. Error bars reflect standard errors. Significance tests of pairwise comparisons between terms are reported in Table S5 - S7
To address our first research aim, we examined the main effect of the randomly assigned term on participants’ ratings of familiarity, concern, perceived urgency, willingness to support policies, and willingness to eat less red meat elicited by the terms (Table 4 ). We also conducted pairwise comparisons of terms with Bonferroni-corrected p -values to adjust for the number of tests (Table S4 ).
To address our second research aim, we examined the interaction effect of the randomly assigned term and participants’ political leaning, on ratings of familiarity, concern, urgency, willingness to support climate-friendly policies, and willingness to eat less red meat (Table 4 ). To better understand these interactions, we conducted a separate Analyses of Covariance on each rating to examine the effect of terms among Democrats, Republicans, and Independents/others, using the same covariates (Table 5 ). For these analyses, we also report effect sizes (Table 5 ) and pairwise comparisons with Bonferroni-corrected p -values (Table S5 - S7 ).
In auxiliary analyses, we examined the role familiarity played in reported urgency, willingness to support climate-friendly policies, and willingness to eat less red meat. This involved an Analyses of Covariance in which we added familiarity and its interactions with the randomly assigned term, political leaning, or both, using the same covariates as mentioned above (Table 6 ). We also conducted separate Analyses of Covariance to examine the effect of familiarity by term and political leaning (Table S8 - S9 ). Familiarity was dichotomized for these auxiliary analyses to facilitate interpretations of these auxiliary analyses, treating “somewhat familiar” and “very familiar” as familiar and treating “not familiar at all” and “not that familiar” as unfamiliar. As noted, post-stratification weights were used in all analyses (see www.uasdata.usc.edu/page/Weights ).
A majority of participants indicated being very familiar or somewhat familiar with “climate change,” “global warming,” “climate crisis,” or “climate emergency,” but not “climate justice” (Table 3 ). However, ratings of familiarity varied across terms (Fig. 1 A), seen in a significant main effect with a large effect size (Table 4 ). “Climate change” and “global warming” received the highest ratings of familiarity (Fig. 1 A), with pairwise comparisons suggesting that both terms were rated as similarly familiar and significantly more familiar than each of the other terms (Table S4 ). “Climate justice” was rated as the least familiar (Fig. 1 A), and significantly less familiar than each of the other terms (Table S4 ). The other two terms fell in between (Fig. 1 A), with “climate crisis” rated as significantly more familiar than “climate emergency” (Table S4 ).
A breakdown by political leaning showed that a large majority of Democrats, Republicans, and Independents/others were familiar with the terms “climate change,” and “global warming” (Table 3 ). A somewhat smaller majority in each group reported being familiar with the terms “climate crisis,” and “climate emergency” (Table 3 ). In each political group, “climate justice” was the least familiar, with the majority rating it as unfamiliar rather than familiar (Table 3 ). Ratings of familiarity also showed this relative pattern across terms (Fig. 2 A). Democrats and Independents/others were generally somewhat more familiar with the terms than Republicans (Fig. 2 A), seen in a significant main effect of political leaning on familiarity ratings with a small effect size (Table 4 ). More importantly, we found a significant interaction between terms and political leaning with a small effect size (Table 4 ): The effect of terms on familiarity ratings was somewhat more pronounced for, in order, Republicans, Independents/others, and Democrats (Table 5 ). “Climate crisis,” “climate emergency” and “climate justice” were each significantly less familiar than “climate change” and “global warming” for each political leaning (Table S5 - S7 ), but “climate justice” was especially unfamiliar to Republicans (Fig. 2 A).
A majority of participants expressed being very concerned or somewhat concerned with “climate change,” “climate change,” “climate crisis,” or “climate emergency,” but not “climate justice” (Table 3 ). Ratings of concern varied across terms (Fig. 1 B), resulting in a significant main effect with a medium effect size (Table 6 ). “Climate change” and “global warming” were rated as eliciting the most concern (Fig. 1 B), with pairwise comparisons suggesting that both terms elicited similar concern and at least somewhat more concern than each of the other terms (Table S4 ). “Climate justice” was rated as the least concerning (Fig. 1 B) and received significantly lower ratings of concern than each of the other terms (Table S4 ). The other two terms fell in between (Fig. 1 B), with “climate crisis” raising similar concern as “climate emergency” (Table S4 ).
A breakdown by political leaning shows that most Democrats and Independents/others were concerned about each term, except for “climate justice,” which only raised concern among a majority of Democrats (Table 3 ). No term raised enough concern to reach a majority among Republicans (Table 3 ). Indeed, we found a significant main effect of political leaning on ratings of concern with a large effect size (Table 4 ): Concern was generally highest among Democrats and lowest among Republicans, with Independents/others falling in between (Fig. 2 B). There was no significant interaction between terms and political leaning (Table 4 ): For every political leaning, “climate justice” consistently elicited the least concern (Fig. 2 B), and received significantly lower ratings of concern than every other term (Table S5 - S7 ).
Most participants felt that it was somewhat urgent or very urgent to do something about “climate change,” “global warming,” “climate crisis,” “climate emergency,” and “climate justice” (Table 3 ). Ratings of urgency varied across terms (Fig. 1 C), as seen in a significant main effect with a relatively small effect size (Table 4 ). “Climate change,” “global warming,” climate crisis,” and “climate emergency” were all rated as similarly urgent, except that “global warming” was rated as slightly more urgent than “climate crisis” (Table S4 ). “Climate justice” was rated as significantly less urgent than all other terms (Table S4 ).
A majority of Democrats and Independents/others perceived urgency to do something about each term– but not Republicans (Table 3 ). Indeed, there was a significant main effect of political leaning on urgency ratings with a large effect size (Table 4 ): Perceived urgency was highest among Democrats and lowest among Republicans (Fig. 2 C). More importantly, the effect of terms on ratings of urgency varied by political leaning (Fig. 2 C), as seen in a significant interaction between terms and political leaning with a large effect size, F (2, 4441) = 2.97, partial η 2 = 0.26, p < 0.01. The effect of terms on urgency ratings showed a medium effect size among Democrats, and a small effect size among Republicans, with Independent/others falling in between (Table 5 ). Both Democrats and Independent/others rated each term as significantly more urgent than “climate justice,” while Democrats also rated “global warming” as significantly more urgent than “climate emergency” (Table S5 - S7 ). Republicans’ ratings of urgency showed few significant differences between terms, except that they rated “global warming” and “climate emergency” as somewhat more urgent than “climate justice” (Table S6 ).
A majority of participants reported being somewhat willing or very willing to support policies to do something about “climate change,” “global warming,” “climate crisis,” “climate emergency,” and “climate justice” (Table 3 ). Ratings of policy support did not vary meaningfully across terms (Fig. 1 D), as seen in a significant main effect with a very small effect size (Table 4 ). Pairwise comparisons suggested that ratings of policy support were mostly similar across terms, except that “global warming” received significantly higher ratings of policy support than “climate justice” despite the difference being small (Table S4 ).
A majority of Democrats and Independents/others supported policies to do something about each term (Table 3 ). Even among Republicans, a slight majority indicated willingness to support policies to do something about each term, with the lowest support still being at 50% for “climate change” (Table 3 ). Yet, there was a significant main effect of political leaning on ratings of willingness to support policies with a large effect size (Table 4 ): Democrats showed the highest and Republicans the lowest willingness to support policies. There was no significant interaction between terms and political leaning (Table 4 ). Pairwise comparisons of terms within each political group found no significant differences, except that Independent/others responded slightly more positively to “global warming” than to “climate crisis” (Table S5 - S7 ).
A majority of participants reported being somewhat willing or very willing to eat less red meat to do something about “climate change,” “climate change,” “climate crisis,” “climate emergency,” and “climate justice” (Table 3 ). Ratings of willingness to eat less red meat did not vary meaningfully across terms (Fig. 1 E), as seen in a significant main effect with a very small effect size (Table 4 ). Indeed, pairwise comparisons found only two small significant differences, suggesting that “global warming” and “climate emergency” received somewhat higher ratings for willingness to eat less red meat, compared to “climate justice” (Table S4 ).
A majority of Democrats and Independents/others, but not Republicans, indicated being willing to eat less red meat independent of the term that was used (Table 3 ). Rated willingness to eat less red meat was indeed highest among Democrats and lowest among Republicans (Fig. 2 E), as confirmed in a significant main effect of political leaning with a large effect size (Table 4 ). There was no significant interaction between terms and political leaning (Table 4 ). Indeed, pairwise comparisons of terms within each political group found no significant differences, except that Democrats responded slightly more positively to “global warming” than to “climate justice” (Table S5 - S7 ).
Among participants who found a term unfamiliar (vs. familiar), ratings of concern, urgency, willingness to support climate-friendly policies, and willingness to eat less red meat were generally lower (Fig. 3 ). Familiarity had a significant effect on each of these dependent variables, with a medium effect size for concern, and a smaller effect size for perceived urgency, willingness to support policies, and willingness to eat less red meat (Table 6 ). The effect of familiarity did not significantly vary with the randomized term, with two exceptions: There was a significant interaction with a small effect size for willingness to support climate-friendly policies and for willingness to eat less red meat (Table 6 ), which suggested that the effect of familiarity was the least pronounced for “climate justice” (Fig. 3 ; Table S8 ).
Mean reported ( A ) concern, ( B ) urgency, ( C ) willingness to support policies, and ( D ) willingness to eat less red meat by term and familiarity
Note: Familiarity was dichotomized, treating “somewhat familiar” and “very familiar” as familiar and treating “not familiar at all” and “not that familiar” as unfamiliar. Survey questions and response scales are described in Table 2 . Poststratification weights were used in these analyses. Error bars reflect standard errors. Significance tests are reported in Table S8
The effect of familiarity did significantly vary by political leaning, seen in a significant interaction with a small effect size for each dependent variable (Table 6 ). Specifically, while familiarity tended to make no difference for Republicans, Democrats and Independents/others generally responded more strongly if a term was familiar (Figure S2 - S4 ), with effect sizes typically being largest among Democrats (Table S9 ). Three-way interactions between familiarity, randomized term and political leaning had a very small effect size for each dependent variable (Table 6 ), suggesting no meaningful variation.
Psychological theories of attitude formation suggest that attitudes about a topic are influenced by topic-related information that comes to mind in the moment (Schwarz 2007 ; Sudman et al. 1996 ). Therefore, it has been posited that changing terms to emphasize different aspects of “climate change” may influence public concern and willingness to act (e.g. Schuldt et al. 2011 ). In a national terminology experiment, we therefore compared public responses to the term “climate change” as well as alternative terms that emphasize different aspects of the phenomenon: “global warming,” “climate crisis,” “climate emergency,” and “climate justice.” Although the terms “climate change” and “global warming” are often used interchangeably in public discourse, “climate change” refers to diverse changes in the climate while seemingly de-emphasizing human activity, and “global warming” refers to increasing global surface temperatures and implies that this is due to humans actively warming the planet (Penz 2017 ). The terms “climate crisis,” “climate emergency,” and “climate justice” have more recently been introduced to emphasize urgency (Schäfer et al. 2023 ). The term “climate justice” has been used by left-leaning grassroots organizations to emphasize the unfairness of unequal vulnerabilities (Dutta 2019 ; Schlosberg and Collins 2014 ).
Across a national U.S. sample, we found that the more traditional terms “climate change” and “global warming” were rated as more familiar than the relatively newer terms “climate crisis” and “climate emergency.” Perhaps due to being less familiar, the terms “climate crisis” and “climate justice,” which were introduced to emphasize urgency (Schäfer et al. 2023 ), actually elicited somewhat less concern. Moreover, "climate crisis" or "climate emergency" did not elicit greater perceptions of urgency than “climate change” and “global warming.” The term “climate justice” was least familiar and generally performed most poorly on all dependent measures. This may, in part, reflect low familiarity with the idea that climate change disproportionally affects vulnerable communities (Schuldt and Pearson 2023 ). Additionally, the term “climate justice” may resonate less with people than the other terms.
Respondents’ willingness to support policies and willingness to eat less red meat were generally less affected by the presented terms than their ratings of concern and urgency. This finding is in line with previous suggestions that terminology effects are stronger for beliefs than for willingness to act, with the latter having a higher threshold (Benjamin et al. 2017 ). However, our study suggested that both willingness to support policies and willingness to eat less red meat were lowest in response to “climate justice.” If people are unaware of the disproportionate effect of climate change on vulnerable communities (Schuldt and Pearson 2023 ), they may find it harder to see the need to act on it even if they have heard of the term “climate justice.”
Because of demonstrated partisan differences in responses to terminology, we also examined how responses to terms varied between individuals who leaned Democrat, Republican, or Independent/other (e.g., Akerlof and Maibach 2011 ; Schuldt et al. 2011 ; Villar and Krosnick 2011 ). Effects of terms varied by participants’ political leaning, but only for ratings of familiarity, concern, and perceived urgency– with willingness to act only showing main effects of terms and of political leaning. All political groups were familiar with the more traditional terms “climate change” and “global warming,” relatively less familiar with “climate crisis” and “climate emergency,” and least familiar with “climate justice.” Those terminology effects on familiarity were most pronounced among Republicans, who were especially unfamiliar with “climate justice.” For ratings of concern and perceived urgency, terminology effects showed large effect sizes. Terminology effects on ratings of concern and perceived urgency were most pronounced for Democrats, with a relatively larger benefit of using the traditional terms “climate change” or “global warming” instead of “climate justice.” Thus, unlike in the United Kingdom (Whitmarsh and Corner 2017 ), “climate justice” did not appear to polarize American audiences much along political lines– perhaps because the issue is currently not yet that familiar in the U.S. (Schuldt and Pearson 2023 ).
Nevertheless, a consistent finding across all political groups was that “climate change” and “global warming” performed similarly well, and about as well or better than alternative terms on all outcome variables. Even though the terms “climate change” and “global warming” were differentially favored by Democrats and Republicans in the past, there is a growing trend to treat these two terms as interchangeable (Benjamin et al. 2017 ). Even among Independents/others we now find that these two terms elicit similar responses, while in 2012 they were the last group to respond differentially (and more positively) to “climate change” vs. “global warming” (Benjamin 2017 ).
In line with psychological theories of attitude formation (Schwarz 2007 ; Sudman et al. 1996 ), these findings suggest that it matters somewhat which terms we use for climate change. Specifically, “climate change” and “global warming” are likely the most effective terms to use, followed by “climate crisis” and “climate emergency,” with “climate justice” being the least effective. However, our findings also suggest a need to temper the conclusion that climate terms matter, for two reasons. First, the effect of terms was less strong for willingness to support policies and willingness to eat less red meat, than for expressed concern, and perceived urgency. This finding is in line with previous reports that terminology effects tend to be smaller for willingness to act than for expressed beliefs (Benjamin et al. 2017 ). Second, the effect of political ideology was stronger than the effect of terminology for expressed concern, perceived urgency, willingness to support policies, and willingness to eat less red meat, in line with previous suggestions that Americans follow the views of their political party (van Boven et al., 2018 ). That is, Republicans generally responded most negatively to presented terms. The relative advantage of using the terms “climate change” or “global warming” was also the lowest among Republicans. Hence, changing the terms we use is likely not the key solution for promoting climate action.
Like any study, ours has limitations. First, our study presents only one snapshot in time, and the popularity and effectiveness of terms may change over time (Penz 2017 ; Schuldt et al. 2020 ; Benjamin et al. 2017 ). The term “climate justice” may increase willingness to act, as it becomes more familiar. Yet, it is possible that “climate justice” will become politically polarizing as it becomes more familiar, following findings from the United Kingdom, where the “justice” framing resonates with left-leaning audiences while right-leaning audiences find it off-putting (Whitmarsh and Corner 2017 ). Second, we did not assess how participants interpreted each term, or the reasoning behind their responses. It is possible that those who said that they were familiar with a term did not know what it meant, or that those who said that they were unfamiliar with a term were nevertheless able to make an educated guess that affected their responses. Moreover, people may have perceived “climate change” as the main concern, and “climate justice” as a secondary outcome. Third, we presented terms without further explanation, to test the effect of their mere usage on public responses. Providing definitions of less familiar terms like “climate justice” is likely needed to raise public awareness that climate change affects some more than others (Schuldt and Pearson 2023 ). Many people are also unaware that eating less red meat can reduce greenhouse gas emissions (Kause et al. 2019 ), and may therefore benefit from information about how eating less red meat could curb climate change and its impacts on vulnerable communities. Fourth, questions about willingness to support policies and willingness to eat less red meat were preceded by a sentence that mentioned the randomly assigned term (Table 2 ). However, survey design research suggests that people do take into account such preceding sentences when interpreting survey questions (Schwarz 1999 ). Fifth, we only examined willingness to eat less red meat as a personal action, and not willingness to engage in other actions to reduce carbon emissions. Sixth, our study was conducted during an exceptionally hot summer that brought unprecedented heat waves, droughts, and wildfires across the U.S. Because the term “global warming” tends to elicit thoughts of these hot weather events, participants may have expressed relatively more concern about “global warming” than they might have otherwise (Whitmarsh 2009 ). Seventh, in line with most previous studies, we focused on how terminology effects varied with participants’ political leaning (e.g., Schuldt et al. 2011 ; Vilnar et al. 2011). However, participants’ climate change beliefs may be more complex (Benjamin et al. 2017 ), and that complexity may affect how they respond to presented terms. Eighth, our study only focused on the U.S., and different terms may be more effective for communicating about climate change in other countries. For example, people in Africa may be more likely to indicate that they are perceiving long-term severe weather changes than that they are perceiving climate change (Bruine de Bruin and Dugan 2022 ).
The terms we use to talk about climate change matter, but only somewhat. The traditional terms “climate change” and “global warming” are generally familiar, among Democrats, Republicans, and Independents/others. The newer terms “climate crisis,” “climate emergency,” and “climate justice” are generally less familiar, and may not raise as much concern as the traditional terms “climate change” and “global warming.” Sticking with familiar terms is advisable because public responsiveness may be lower when terms are unfamiliar. Although we did not test the term “climate upheaval,” which has recently been introduced to emphasize the sudden worrisome change associated with climate change (Chen 2024 ), we suspect that it will be more effective to stick with the familiar terms “climate change” and “global warming.” Indeed, interviews with climate-concerned and climate-ambivalent Americans found that they wanted climate change communications to use familiar terms (Bruine de Bruin et al. 2021 ). This finding was replicated in Germany (Wege et al. 2024 ).
However, terms’ effects on willingness to act were small at best, and Republicans were often unresponsive. Climate change communications may therefore need to go beyond terminology to promote willingness to act. For example, effective communication strategies include using compelling everyday language, presenting clear graphs, emphasizing social norms, and making climate-friendly actions the default (Bruine de Bruin et al. 2021 ; Bruine de Bruin et al. 2024; Constantino et al. 2022 ; Nisa et al. 2019 ; Sleboda et al. 2024 ; Wege et al. 2024 ). Moreover, efforts to reach Republicans may require messages from Conservative spokespeople, and involving the private sector in climate change mitigation (Goldberg et al. 2021 ; Gillis et al. 2021 ).
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We thank the team of the Understanding America Study at the University of Southern California’s Center for Economic and Social Research for data collection, especially Jill Darling and Bart Orriens.
We gratefully acknowledge funding from the University of Southern California’s Wrigley Institute for Environmental Studies. Bruine de Bruin was additionally supported by a gift from the Golden Belt Community Foundation.
Open access funding provided by SCELC, Statewide California Electronic Library Consortium
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Schaeffer Institute for Public Policy and Government Service, Sol Price School of Public Policy, University of Southern California, Los Angeles CA, USA
Wändi Bruine de Bruin
Department of Psychology, University of Southern California, Los Angeles CA, United States
Wändi Bruine de Bruin, Gale M. Sinatra & Norbert Schwarz
Rossier School of Education, University of Southern California, Los Angeles CA, United States
Laurel Kruke & Gale M. Sinatra
Mind and Society Center, University of Southern Californai, Los Angeles CA, United States
Norbert Schwarz
Marshall School of Business, University of Southern California, Los Angeles CA, United States
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Bruine de Bruin, W., Kruke, L., Sinatra, G.M. et al. Should we change the term we use for “climate change”? Evidence from a national U.S. terminology experiment. Climatic Change 177 , 129 (2024). https://doi.org/10.1007/s10584-024-03786-3
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