This Fownes_WCAS2018_Readme.txt file was generated on 2018-03-06 by Jennifer R. Fownes. Updated with publication details by Wendy Kozlowski (eCommons administrator), 2018-11-26. -------------------GENERAL INFORMATION------------------- 1. Dataset Title: Data from: The Influence of Recent Weather on Perceptions of Personal Experience With Climate Change and Extreme Weather in New York State 2. Author Information Principal Investigator Contact Information Name: Jennifer R. Fownes Institution: Center for Conservation Social Science, Department of Natural Resources, Cornell University Address: Fernow Hall, Ithaca, New York, 14850 Email: jf443@cornell.edu Associate or Co-investigator Contact Information Name: Shorna B. Allred Institution:Center for Conservation Social Science, Department of Natural Resources, Cornell University Address: Fernow Hall, Ithaca, New York, 14850 Email: srb237@cornell.edu 3. Date of data collection (single date, range, approximate date) Survey data (columns A - I) were collected from 18 January 2014 - 5 March 2014. Weather data (columns J - U) were collected for that same time period. For future data collection details, see below. 4. Geographic location of data collection (where was data collected?): Data were collected for New York State. Location was identified by county. 5. Information about funding sources that supported the collection of the data: This data was collected through work funded by Federal Capacity (hatch) Funds from the National Institute of Food and Agriculture, U.S. Department of Agriculture, and the Atkinson Center for a Sustainable Future. --------------------------SHARING/ACCESS INFORMATION-------------------------- 1. Licenses/restrictions placed on the data: These data are shared under a Creative Commons Attribution 4.0 International (CC-BY 4.0) license. https://creativecommons.org/licenses/by/4.0/. You are free to share or adapt the material with attribution to the original dataset authors, and acknoledgement of SRI as the survey conductor. See recommended citation below. 2. Links to publications that cite or use the data: Fownes, J.R. and S.B. Allred. Testing the Influence of Recent Weather on Perceptions of Personal Experience With Climate Change and Extreme Weather in New York State. Wea. Climate Soc. https://doi.org/10.1175/WCAS-D-17-0107.1 3. Was data derived from another source? If yes, list source(s): This dataset is derived from 2 sources: I) 2014 Empire State Poll A subset of the data from this source is included in the present dataset (columns A - I). II) National Regional Climate Center (NRCC) weather data Daily weather data were obtained from NRCC as a high-resolution (5 km x 5 km) grid, based on original data from the NOAA regional Climate Center. Data were processed by the authors to create population-weighted county averages. Data measures included and data processing are described below. 4. Links to other publicly accessible locations of the data: A summary of the results for a subset of the survey variables (columns G - I) are available: Allred, S., 2014: What are New Yorkers thinking about Climate Change and Community Resiliency? Cornell Climate Change Briefing for the New York Governor’s Office and Executive Agencies. Albany, NY, https://www.academia.edu/36076219/What_are_New_Yorkers_thinking_about_Climate_Change_and_Community_Resiliency. The entirety of the survey questionnaire is available: 2014 Empire State Poll Questionnaire. Ithaca, NY, https://sri.cornell.edu/sri/files/esp/2014/2014 Questionnaire.pdf. A report of the methodology, data collection and sampling, and sociodemographic characteristics are available: Xian, S., and R. Meyers, 2014: Empire State Poll 2014: Introduction and Methodology. Ithaca, NY, https://www.sri.cornell.edu/sri/files/esp/2014/Report 1 - 2014 - Introduction and Methodology.pdf. 5. Links/relationships to ancillary data sets: NRCC data are available online (http://climod2.nrcc.cornell.edu/). Further data is also available by request (http://www.nrcc.cornell.edu/services/access/access.html). The data for this study were obtained with the assistance of NRCC staff and collaborators. A description of how NRCC gridded data were modeled is available: DeGaetano, A. T., and B. N. Belcher, 2007: Spatial interpolation of daily maximum and minimum air temperature based on meteorological model analyses and independent observations. J. Appl. Meteorol. Climatol., 46, 1981–1992, doi:10.1175/2007JAMC1536.1. 6. Recommended citation for this dataset: Fownes, Jennifer R and Shorna B Allred. 2018. Data from: The Influence of Recent Weather on Perceptions of Personal Experience With Climate Change and Extreme Weather in New York State. Dataset. Cornell University Library's eCommons repository. https://doi.org/10.7298/X4CN722M ---------------------DATA & FILE OVERVIEW--------------------- 1. File List A. Filename: Fownes_WCAS2018.csv Short description: This is a dataset that includes all variables used in descriptive and statistical analyses for the publication listed above. This dataset includes a subset of the 2014 Empire State Poll data and NRCC weather data described above. 2. Additional related data collected that was not included in the current data package: None. 3. Are there multiple versions of the dataset? No --------------------------METHODOLOGICAL INFORMATION-------------------------- 1. Description of methods used for collection/generation of data, and methods for processing the data: I) 2014 Empire State Poll survey data Perceptions of personal experience with climate change were measured as part of the 2014 Empire State Poll (ESP), a telephone survey of adult (18 years and older) residents of NYS, conducted from January 18 through March 5, 2014 (Allred 2014). The sample of completed surveys was 800 respondents, split evenly between downstate (9 counties around New York City) and upstate (52 other counties) to ensure a thorough sampling of upstate residents. Respondents’ location was measured as their self-reported county of residence at the time of the survey. There were respondents from 61 of 62 NYS counties, and the 7 respondents who did not report their county of residence were removed from analyses. Upstate/downstate population-based sample weights were applied to analyses so that results were representative of NYS residents. The Survey Research Institute of Cornell University conducted the survey as a dual-frame random digit dial (land-line and cellular) telephone survey in both English and Spanish. The sample, acquired from Marketing Systems Group, excluded known business telephone numbers, disconnected numbers, and non-households. Every listed telephone in NYS had an equal chance of being included in the survey. For each telephone number selected, the adult household member who was a resident of NYS and had the most recent birthday was selected to complete the survey, ensuring random selection of members within each household. The cooperation rate (66%) and response rate (21%) are comparable to those obtained by other surveys of NYS residents, including the 2009-2011 American Community Survey by the US Census (Xian and Meyers 2014 [see above for full citation]). Respondents’ perceptions of personal experience were measured as their level of agreement (on a 5-point scale from strongly disagree to strongly agree) with the statement “I have personally experienced the effects of extreme weather or climate change.” This statement did not specify a time period and therefore represents overall perceptions rather than perceptions of specific weather events or trends. This measure combines experiences with both climate change and extreme weather. As a result, respondents may be describing their experience with extreme weather events, climate change, or both. Respondents’ belief in anthropogenic climate change was measured with a combination of two questions. The first assessed belief in the reality and current timing of climate change: “Do you believe climate change is happening?” Response options were “yes,” “no,” or “don’t know.” The second assessed perceived causes of climate change,. Respondents were asked, “assuming climate change is happening, do you think it is:” “caused mostly by human activity,” “caused mostly by natural changes in the environment,” “other,” or “None of the above because climate change isn’t happening.” A composite measure was created to split respondents into three categories. - Belief that climate change is not happening or not sure whether it is happening (coded as 0). These respondents answered the first question as “no” or “don’t know”, and the second as “none of the above because climate change isn’t happening.” - Belief that climate change was happening and caused by natural or other causes (coded as 1). These respondents answered the first question as “yes” and the second as “caused mostly by natural change in the environment” or “other.” - Belief that climate change was happening and caused by humans (coded as 2). These respondents answered the first question as “yes” and the second as “caused mostly by human activity.” Respondents’ sociodemographic characteristics were also measured in the ESP. Respondents reported their political affiliation on a 7-point response scale from Strong Democrat to Strong Republican. Six respondents were excluded from analyses because they did not know their political party (n = 2) or refused to answer (n = 4). Respondents’ gender (male or female) was recorded based on the interviewer’s assessment, with no missing values. Respondents’ age was calculated based on their self-reported year of birth subtracted from the year of the survey (one missing value), and centered for analyses. Respondents’ education level was recorded as the highest level of academic achievement completed on a 7-point scale, with no missing values. To avoid low sample sizes, responses were combined into 3 groups: high school graduate or lower [no schooling or grades 1-8 (n = 11); high school incomplete (n = 43), and high school graduate (n = 157)]; college complete or incomplete or other training [technical, trade, or vocational school (n = 24), some college or 2-year Associate degree (n = 210), or 4-year college degree (n = 187)], and post-graduate training or professional school after college (n = 161). II) NRCC weather data Recent weather was measured as maximum and minimum temperatures and total precipitation in each respondent’s county on the day of the survey and the average of the week preceding the survey (the day of the survey plus the 6 days before that). Daily weather data for the time period of interest were obtained from the Northeast Regional Climate Center (NRCC) as a high-resolution (5 km x 5 km) grid, based on original data from the NOAA Regional Climate Center Applied Climate Information System (DeGaetano and Belcher 2007 [see above for full citation]). Weather was quantified in two different ways: absolute measures (degrees Fahrenheit or inches of precipitation) and relative measures (percentile of the climate normal, a statistical distribution of each weather measure over a historical time period). For relative measures, a 30-year climate normal is generally used, so a 1981-2010 normal was used for temperature. Precipitation data at the 5 km x 5 km resolution were only available from 2002 on, so a 2002-2010 precipitation normal was used. To match weather data to ESP respondents’ locations, weather measures were aggregated at the county level. Some NYS counties are large enough that weather measures at times differed greatly across the county, but respondents’ location within counties was not known. To use measures that represent the average weather experienced by a county resident, county averages were weighted by census tract population. Gridded weather data were linked to the county and 2010 census tract polygons within which they were located using Excel and QGIS, an open-source GIS software. Average weather measures for each census tract were calculated based on the average of the internal grid points or, for census tracts smaller than the grid size, the value of the grid point nearest to the census tract center. Population-weighted census tract weather measures were calculated as the average weather measure for that census tract multiplied by the census tract’s proportion of the county population. Final population-weighted county weather measures were computed as the sum of all population-weighted census tract weather measures within each county. 3. Describe any quality-assurance procedures performed on the data: Data were spot-checked at each stage of processing to ensure quality. Weather data were visualized in QGIS (an open-source Geographic Information Systems program), and each county examined to make sure that results reflected the original data.7. People involved with sample collection, processing, analysis and/or submission: The 2014 Empire State Poll survey data were collected by the Cornell University Survey Research Institute. The NRCC weather data were obtained with the assistance of NRCC staff. The first author for this dataset (Jennifer R. Fownes) completed data processing, analysis, and submission. The second author (Shorna B. Allred) was consulted. ----------------------DATA-SPECIFIC INFORMATION FOR: Fownes_WCAS2018.csv------------------------ 1. Number of variables: 252. Number of cases/rows: 8003. Variable List I) Variables from the 2014 Empire State Poll A. Name: CASEID Description: A unique identifier assigned to each survey respondent without any sensitive information. B. Name: DATE Description: The data now which the survey was administered to each respondent (yyyy-mm-dd) C. Name: WEIGHT Description: Sampling weight applied to survey respondent based on reported location (upstate vs downstate) D. Name: nysregion Description: Survey respondent’s region of residence. This was assigned based on self-reported county of residence (see Variable E) 1 = downstate, 2 = upstate E. Name: county Description: Survey respondent’s self-reported county of residence FIPS code F. Name: countname Description: Survey respondent’s self-reported county of residence Name of county G. Name: SBq1 Description: Survey respondent’s answer to the following question: Do you believe that climate change is happening? 1 = No, 2 = Yes, 3 = Don’t know H. Name: SBq2 Description: Survey respondent’s answer to the following question: “Assuming climate change is happening, do you think it is…” 1 = Caused mostly by human activity, 2 = Caused mostly by natural changes in the environment, 3 = Other, 4 = None of the above because climate change isn’t happening, -2 = Do not know I. Name: SBq3 Description: Survey respondents' answer to the following question: How much do you agree or disagree with the following statement: "I have personally experienced the effects of extreme weather or climate change." 1 = Strongly disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly agree J: Name: politicalparty Description: Survey respondents' answer to the following question: "Generally speaking, when it comes to political parties in the United States, how would you best describe yourself?" 1 = Strong Democrat, 2 = Not very strong Democrat, 3 = Independent (close to Democrat), 4 = Independent (close to neither), 5 = Independent (close to Republican), 6 = Not very strong Republican, 7 = Strong Republican, 8 = Other party affiliation, -2 = Do not know, -1 = Refused to answer K: age Description: Calculated as 2014 (the year of survey administration) minus survey respondents' self-reported year of birth L: gender Description: Recorded by interviewer without a question M: education Description: Survey respondents' answer to the following question: "What is the last grade or class that you completed in school?" 1 = None or grades 1-8; 2 = High school incomplete (grades 9-11); 3 = High school graduate (grade 12 or GED certificate); 4 = Technical, trade, or vocational school after high school; 5 = Some college, no 4-year degree (including 2-year Associate degree); 6 = College graduate (BS, BA, or other 4-year degree); 7 = Post-graduate training or professional schooling after college II) Variables calculated from NRCC weather data N. Name: MaxT_D0 Description: Absolute maximum temperature in the respondent's county on the day the survey was administered to the respondent (degrees Fahrenheit) O. Name: MaxT_wk Description: Absolute maximum temperature in the respondent's county averaged over the week before the survey was administered to the respondent (degrees Fahrenheit) P. Name: MaxTp_D0 Description: Relative maximum temperature in the respondent's county on the day the survey was administered to the respondent (percentile of normal) Q. Name: MaxTp_wk Description: Relative maximum temperature in the respondent's county averaged over the week before the survey was administered to the respondent (percentile of normal) R. Name: MinT_D0 Description: Absolute minimum temperature in the respondent's county on the day the survey was administered to the respondent (degrees Fahrenheit) S. Name: MinT_wk Description: Absolute minimum temperature in the respondent's county averaged over the week before the survey was administered to the respondent (degrees Fahrenheit) T. Name: MinTp_D0 Description: Relative minimum temperature in the respondent's county on the day the survey was administered to the respondent (percentile of normal) U. Name: MinTp_wk Description: Relative minimum temperature in the respondent's county averaged over the week before the survey was administered to the respondent (percentile of normal) V. Name: Precip_D0 Description: Absolute precipitation in the respondent's county on the day the survey was administered to the respondent (inches liquid) W. Name: Precip_wk Description: Absolute precipitation in the respondent's county averaged over the week before the survey was administered to the respondent (inches liquid) X. Name: Precipp_D0 Description: Relative precipitation in the respondent's county on the day the survey was administered to the respondent (percentile of normal) Y. Name: Precipp_wk Description: Relative precipitation in the respondent's county averaged over the week before the survey was administered to the respondent (percentile of normal) 4. Missing data codes: Variable: county (if this variable was missing, then columns F and N - Y were also missing) -1 NA -2 NA