Yale Climate Opinion Maps for Strategists

Frequently Asked Questions

What do these maps depict?
The maps depict estimates of the percentage of American adults (age 25 and over) who hold particular beliefs, attitudes, and policy preferences about global warming. The estimates were generated from a statistical model that incorporates actual survey responses from a large dataset of >22,000 individuals since 2008. The actual survey responses were combined with demographic data from the Census to estimate opinions based on information such as gender, race and ethnicity, and educational attainment; they also take into account changes in public opinion over time.

Where do the survey data underlying the estimates come from?
The data underlying the maps come from a large national survey dataset ( >22,000 respondents) collected between 2008 through 2018 as part of the Climate Change in the American Mind project led by the Yale Program on Climate Change Communication and the George Mason University Center for Climate Change Communication. Reports from the individual surveys are available here: CCAM Reports.

How accurate are the estimates?
No model is perfect and there are uncertainties in the model estimates. To validate the model, we conducted independent surveys in four states (CA, TX, OH, CO) and two metropolitan areas (Columbus, OH and San Francisco, CA) and compared the survey results to our model estimates. On average, the model estimates differed from the survey results by 2.9 percentage points among the four states and 3.6 percentage points among the two metropolitan areas, within the survey margins of error. A series of technical simulations estimate that the model has an average margin of error of ±7 percentage points at the state and congressional district levels, ±8 percentage points at the metro and county levels. Such error ranges include the error inherent in the original national surveys themselves, which is typically ±3 percentage points. The model uncertainties are smaller at broad geographic scales (e.g., the state level), and are larger at finer geographic scales (e.g., at the county and city levels). The model estimates also tend to be conservative, so geographic areas with extremely high or low measures are not estimated as well as areas with values closer to the national average for each survey question.

What does the gray color mean on some of the bars beneath the maps?
The gray area reflects people who refused to answer the question or said “don’t know”. We do not provide specific values for the gray areas because we did not model this group specifically.

Do the maps account for differences in population density across the country?
No, the maps depict the estimated proportion of people within each geographic area who would answer each question as indicated. We have not adjusted the maps based on population density differences. It is important to keep in mind that some geographic areas may be large, but have few residents (e.g., Wyoming), while other geographic areas may be small, but have many residents (e.g., New Jersey). For reference, Wikipedia has a population density map here. The type of map used in this tool is called a choropleth map, which means the colors on the maps reflect the percentage of the population in a given geographic unit. These kinds of maps are used to represent everything from election results (e.g.,the red state / blue state maps common during presidential elections) to census and economic data (e.g., per capita income or unemployment rates).

Do these maps reflect changes in opinions due to recent extreme weather events like Superstorm Sandy?
Perhaps. The maps may reflect the impacts that specific extreme weather events had on public opinion in a given geographic unit. If public opinion in a particular area has been influenced by local events it is possible that the model would detect such an influence. However, data from specific events or types of events are not explicitly built into the model as predictor variables.

Can I use the data?
Yes. We encourage you to explore the maps and use the results in your own work. The data are available on our Data Download tab at the top of this page so that you can do your own analyses and create your own visualizations. If you publish an academic paper using these data please acknowledge the source by using the following citation:
Howe, P., Mildenberger, M., Marlon, J., & Leiserowitz, A. (2015) “Geographic variation in opinions on climate change at state and local scales in the USA,” Nature Climate Change. DOI: 10.1038/nclimate2583.
If you publish a news article, visualization or blog post using these data, please include a link back to the Yale Climate Opinion Maps website.

How do these new YCOM v3 (2018) maps compare with the original YCOM v1 (2014) and YCOM v2 (2016) maps?
Public concern about global warming has generally increased since 2014. However, improvements to our 2016 and 2018 model, including new data that increase our ability to resolve differences between jurisdictions, may have contributed to shifts in our 2016 and 2018 model estimates as compared with those of 2014. As a result, we recommend caution interpreting any changes over time because we can’t easily disaggregate what is a true shift between 2014 and either 2016 or 2018 and what reflects the model’s improved ability to map climate beliefs at the local scale. 2016 and 2018, on the other hand, come from the same model but have different input data from the census and election behavior. So while those years are comparable to some extent, note it is difficult to disentangle the change in demographics and the change in opinions.
We’re working on a new model that directly models time and will capture the change quantitatively, which is more reliable than simply subtracting two years. Join our mailing list to be alerted about new results showing changes in opinions over time for each state.