Be the first to hear about new surveys and studies.

Map · Sep 24, 2020

Americans’ Interest in Climate News 2020


These maps show how Americans’ interest in news stories about climate change vary at the state, congressional district, and county levels.

About Downscaling Climate Opinions

This version of the Yale Climate Opinion Maps is based on data from autumn 2020. Americans are interested in climate news and require information about the global warming’s impacts and solutions in order to inform their decision making about policies to reduce global warming or prepare for the impacts. Such opinions vary, however, depending on where people live. So why would we rely on just one national number to understand public interest in climate change news at the state and local levels? Public opinion polling is generally done at the national level, because local level polling is very costly and time intensive. Our team of scientists, however, has developed a geographic and statistical model to downscale national opinion results to the state, congressional district, and county levels. We can now estimate public opinion across the country, revealing a rich picture of the diversity of Americans’ interest in learning more about climate change.

Explore the maps by clicking on your state, congressional district, or county and compare the results across questions and with other geographic areas. Beneath each map are bar charts displaying the results for every question at whichever geographic scale is currently selected.

See the methods page for more information about uncertainty estimates. In some cases, numbers that should sum to 100% or differences from the national average that should sum to zero are off by one percentage point; these effects are due to rounding errors.

This research and website are funded by Covering Climate Now, the Skoll Global Threats Fund, the Energy Foundation, the 11th Hour Project, the Grantham Foundation for the Protection of the Environment, the MacArthur Foundation, the Overlook Foundation and the Endeavor Foundation. We are very grateful to Martial Jefferson, Lisa Fernandez, Eric Fine, and Seth Rosenthal for their assistance with and support of the project. For further questions about these maps or what they mean, please see our Frequently Asked Questions tab (above).

Methodology

This site provides estimates of U.S. interest in news stories at the state and local levels – a new source of high-resolution data on public opinion that can inform national, state and local decision-making, policy, and education initiatives. The estimates are derived from a statistical model using multilevel regression with post-stratification (MRP) on a large national survey dataset (n>5,700), along with demographic and geographic population characteristics.

For the model estimates, uncertainty ranges are based on 95% confidence intervals using 999 bootstrap simulations. These confidence intervals indicate that the 2020 model is accurate to approximately ±7 percentage points at the state level, and ±8 percentage points at the county and congressional district levels. Such error ranges include the error inherent in the original national surveys themselves, which is typically ±3 percentage points.

For more details on the model or methods, please see the peer-reviewed paper: Howe, P., Mildenberger, M., Marlon, J.R., and Leiserowitz, A., “Geographic variation in opinions on climate change at state and local scales in the USA,” Nature Climate Change. DOI: 10.1038/nclimate2583.

Survey Question Wording

Model estimates in the maps were derived from public responses to the following survey questions. The response categories for many questions were collapsed into a single variable for mapping. “Extremely interested”, “Very interested”, “Moderately interested”, and “A little interested” were combined into a single measure of “interested.” “Not at all interested” is modeled as it is. The responses below are color coded to indicate how they were grouped into the variables shown on the maps. Individuals who did not answer the question were not modeled separately and appear as gray segments within the bar charts.

Interest in news stories

Whether global warming is or is not happening

How interested are you in news stories about the following topics?

  • Extremely interested
  • Very interested
  • Moderately interested
  • A little interested
  • Not at all interested
  • Refused

The causes of global warming

How interested are you in news stories about the following topics?

  • Extremely interested
  • Very interested
  • Moderately interested
  • A little interested
  • Not at all interested
  • Refused

The impacts of global warming on your local community

How interested are you in news stories about the following topics?

  • Extremely interested
  • Very interested
  • Moderately interested
  • A little interested
  • Not at all interested
  • Refused

The impacts of global warming elsewhere in the United States

How interested are you in news stories about the following topics?

  • Extremely interested
  • Very interested
  • Moderately interested
  • A little interested
  • Not at all interested
  • Refused

The impacts of global warming around the world

How interested are you in news stories about the following topics?

  • Extremely interested
  • Very interested
  • Moderately interested
  • A little interested
  • Not at all interested
  • Refused

Actions that are being taken in your local community in response to global warming

How interested are you in news stories about the following topics?

  • Extremely interested
  • Very interested
  • Moderately interested
  • A little interested
  • Not at all interested
  • Refused

Actions that are being taken by the U.S. government in response to global warming

How interested are you in news stories about the following topics?

  • Extremely interested
  • Very interested
  • Moderately interested
  • A little interested
  • Not at all interested
  • Refused

Actions that are being taken by foreign governments in response to global warming

How interested are you in news stories about the following topics?

  • Extremely interested
  • Very interested
  • Moderately interested
  • A little interested
  • Not at all interested
  • Refused

Actions that are being taken by businesses in response to global warming

How interested are you in news stories about the following topics?

  • Extremely interested
  • Very interested
  • Moderately interested
  • A little interested
  • Not at all interested
  • Refused

Actions that the presidential candidates plan to take in response to global warming

How interested are you in news stories about the following topics?

  • Extremely interested
  • Very interested
  • Moderately interested
  • A little interested
  • Not at all interested
  • Refused

The YPCCC is pleased to offer our downscaled climate change opinion estimates to the public. These data are distributed under the following terms of use. This is a legal agreement between you, the end-user (“User”) and Yale University on behalf of the Yale Program on Climate Change Communication (the “YPCCC”).  By downloading the survey data made available on this web site (“Data”) you are agreeing to be bound by the terms and conditions of this agreement.  If you do not agree to be bound by these terms, do not download or use the Data. The YPCCC hereby grants to the User a non-exclusive, revocable, limited, non-transferable license to use the Data solely for (1) research, scholarly or academic purposes, (2) the internal use of your business, or (3) your own personal non-commercial use.  You may not reproduce, sell, rent, lease, loan, distribute or sublicense or otherwise transfer any Data, in whole or in part, to any other party, or use the Data to create any derived product for resale, lease or license.  Notwithstanding the foregoing, you may incorporate limited portions of the Data in scholarly, research or academic publications or for the purposes of news reporting, provided you acknowledge the source of the Data (with express references to the YPCCC, as well as the complete title of the report) and include the following legend: The YPCCC bears no responsibility for the analyses or interpretations of the data presented here.

THE DATA IS PROVIDED “AS IS” WITHOUT ANY WARRANTY OF ANY KIND, EITHER EXPRESS OR IMPLIED, ARISING BY LAW OR OTHERWISE, INCLUDING BUT NOT LIMITED TO WARRANTIES OF COMPLETENESS,  NON-INFRINGEMENT, ACCURACY, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.  THE USER ASSUMES ALL RISK ASSOCIATED WITH USE OF THE DATA AND AGREES THAT IN NO EVENT SHALL YALE BE LIABLE TO YOU OR ANY THIRD PARTY FOR ANY INDIRECT, SPECIAL, INCIDENTAL, PUNITIVE OR CONSEQUENTIAL DAMAGES INCLUDING, BUT NOT LIMITED TO, DAMAGES FOR THE INABILITY TO USE EQUIPMENT OR ACCESS DATA, LOSS OF BUSINESS, LOSS OF REVENUE OR PROFITS, BUSINESS INTERRUPTIONS, LOSS OF INFORMATION OR DATA, OR OTHER FINANCIAL LOSS, ARISING OUT OF THE USE OF, OR INABILITY TO USE, THE DATA BASED ON ANY THEORY OF LIABILITY INCLUDING, BUT NOT LIMITED TO, BREACH OF CONTRACT, BREACH OF WARRANTY, TORT (INCLUDING NEGLIGENCE), OR OTHERWISE, EVEN IF USER HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.

The YPCCC has taken measures to ensure that the Data is devoid of information that could be used to identify individuals (e.g., names, telephone numbers, email addresses, social security numbers) who participated in or who were the subject of any research surveys or studies used to collect the Data (“Personally Identifying Information”).  However, in the event that you discover any such Personally Identifying Information in the Data, you shall immediately notify the YPCCC and refrain from using any such Personally Identifying Information. This license will terminate (1) automatically without notice from the YPCCC if you fail to comply with the provisions of this agreement, or (2) upon written notice (by e-mail, U.S. or otherwise) from the YPCCC.  Upon termination of this agreement, you agree to destroy all copies of any Data, in whole or in part and in any and all media, in your custody and control. This agreement shall be governed by, construed and interpreted in accordance with the laws of the State of Connecticut. You further agree to submit to the jurisdiction and venue of the courts of the State of Connecticut for any dispute relating to this Agreement. Please use the following citation in any work that makes use of the data and documentation as follows: Howe, Peter D., Matto Mildenberger, Jennifer R. Marlon, and Anthony Leiserowitz (2015). “Geographic variation in opinions on climate change at state and local scales in the USA.” Nature Climate Change, doi:10.1038/nclimate2583. Direct any questions to the YPCCC at climatechange@yale.edu.

To access the data, fill out your information and then click "Email me the data"

* indicates required
Affiliation *
Would you like to be notified about data updates? *
I agree to the terms *

Frequently Asked Questions

What do these maps depict?
The maps depict estimates of the percentage of American adults (age 18 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, but combines these responses with demographic data from the U.S. Census to estimate opinions for different groups of people based on information such as their 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 ( >5,700 respondents) collected in the summer 2020 by the Yale Program on Climate Change Communication, George Mason University Center for Climate Change Communication and Covering Climate Now.
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 develop estimates for these particular responses.
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, blog post, or other publication using these data or maps, please include the link to the Yale Climate Opinion Maps website and attribution to the Yale Program on Climate Change Communication.

How do the YCOM maps compare from year to year?
We originally created YCOM in 2014 and then updated it in 2016, 2018, 2019, and 2020.  Public concern about global warming has generally increased since 2014. However, improvements to our model, including new data that increase our ability to resolve differences between jurisdictions, and data for adults 18+ (prior estimates only included data for adults 25+) may have contributed to shifts in our current 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 any particular year and what reflects the model’s improved ability to map climate beliefs at the local scale. We are currently working on a new tool which will show changes in opinions over time for each state. Join our mailing list via the “Subscribe” button below on the right to be alerted when we release this new tool.