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The Washington Post's analysis of NOAA climate change data for the contiguous United States
Climate change in the contiguous United States
This repository contains analysis code and data supporting The Washington Post's series, "2ºC: Beyond the Limit." The following stories draw from this analysis:
- "Extreme climate change has arrived in America," published August 13, 2019
- "Fires, floods and free parking: California’s unending fight against climate change," published December 5, 2019
- "In fast-warming Minnesota, scientists are trying to plant the forests of the future," published April 29, 2020
- "This giant climate hot spot is robbing the West of its water," published August 7, 2020
Note that the first two stories, published in 2019, used an earlier version of this analysis that ran through 2018.
About our analysis
To analyze warming temperatures in the United States, The Washington Post used the National Oceanic and Atmospheric Administration’s Climate Divisional Database (nClimDiv) and Gridded 5km GHCN-Daily Temperature and Precipitation Dataset (nClimGrid) data sets, which provide monthly temperature data between 1895 and 2019 for the Lower 48 states. We calculated annual mean temperature trends in each state and county in the Lower 48 using linear regression — analyzing both annual average temperatures and temperatures for the three-month winter season (December, January and February).
How to use the data
We are offering several data files that are the product of our analysis of climate change in the contiguous United States from 1895-2019. When publishing a story, graphic or other work based on this data set, please credit The Washington Post, link to this repository and send us an email so that we can track the ways in which this data is used.
Annual average temperatures the Lower 48 /data/processed/climdiv_national_year.csv, each state /data/processed/climdiv_state_year.csv and county /data/processed/climdiv_county_year.csv. The code to produce this file can be found in /analysis/process_nclimdiv.Rmd. Each row has the following variables:
yearfipsA two digit fips code in the state file and a five digit code in the county file, not present in the national filetempThe average annual temperature in FahrenheittempcThe average annual temperature in Celsius
Temperature change estimates for each of the Lower 48 states /data/processed/model_state.csv. The code to produce this file is found in /analysis/model_temperature_change.Rmd. Each row has the following variables
fipsA two digit fips code for the stateSTATE_NAMEthe state nameAnnualEstimate of annual average temperature change in Celsius for the state, 1895-2019Falltemperature change in September, October and NovemberSpringtemperature change in March, April and MaySummertemperature change in June, July and AugustWintertemperature change in December and the following January and Februarymax_warming_seasonthe season where temperatures are increasing fastest
Temperature change estimates for counties in the contiguous U.S. can be found in /data/processed/model_county.csv. The code to produce this file is found in /analysis/model_temperature_change.Rmd. Each row has the following variables
fipsA five digit fips code for the countyCTYNAMEthe name of the countySTNAMEthe name of the stateAnnualEstimate of annual average temperature change in Celsius for the county, 1895-2019Falltemperature change in September, October and NovemberSpringtemperature change in March, April and MaySummertemperature change in June, July and AugustWintertemperature change in December and the following January and Februarymax_warming_seasonthe season where temperatures are increasing fastest
County temperature change data joined to a shapefile in GeoJSON format /data/processed/model_county.geojson. The code to produce this file is found in /analysis/model_temperature_change.Rmd.
Gridded emperature change data for the contiguous U.S. in GeoTiff format /data/processed/nclimgrid_slopes_1895_2019.tif. The code to produce this file is found in /analysis/analyze_nclimgrid.Rmd.
Reproducing the Post's analysis
We have included code that can be used to reproduce our analysis in the following RMarkdown notebooks:
These files were generated using R version 3.5.1 and the following packages: tidyverse, sf, raster, scales.
Licensing
All code in this repository is available under the MIT License. Files in the data/processed/ directory are available under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.
Contact
Contact [email protected] with any questions about this repository.