hockeystick
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Download and Visualize Essential Global Heating Data in R
hockeystick 
The goal of hockeystick
is to make essential Climate Change datasets
easily available to non-climate experts. hockeystick
users can
download the latest raw data from authoritative sources as well as view
it via pre-defined ggplot2 charts. Datasets include atmospheric
CO2, instrumental, reconstructed, and paleo ice-core
temperature records, sea levels, and Arctic/Antarctic sea-ice.
The choice of data was originally based on Professor Stefan Rahmstorf’s presentation on The 5 Most Important Data Sets of Climate Science. I came across this on a post on the Open Mind blog. I wrote my own post on obtaining and visualizing this data (now out of date), which is the basis for this package. Additional datasets and visualizations have been added over The name of the package stems from the well known hockeystick temperature chart.
hockeystick
was highlighted on the RStudio
RViews
blog by Joseph Rickert as one of the “Top 40” new packages on CRAN in
February 2021.
NEW in version 0.5.0: North Atlantic hurricane data from NOAA.
NEW in version 0.6.0: Global CO2 emissions by region and country from GCP (see below).
Installation
To install the latest hockeystick
release from CRAN type:
install.packages("hockeystick")
You may alternatively install the development version from https://github.com/cortinah/hockeystick with:
remotes::install_github("cortinah/hockeystick")
Downloading and viewing climate change data
Retrieve NOAA/ESRL Mauna Loa CO2 Observatory concentration data and plot:
library(hockeystick)
ml_co2 <- get_carbon()
plot_carbon(ml_co2)
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Retrieve GCP global CO2 emissions and plot:
emissions <- get_emissions()
plot_emissions(emissions)
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Retrieve NASA/GISS global surface temperature anomaly data and plot:
anomaly <- get_temp()
plot_temp(anomaly)
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Visualize warming using Ed Hawkins styled “warming stripes”:
warming_stripes()
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warming_stripes(stripe_only = TRUE, col_strip = viridisLite::viridis(11))
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Retrieve tide gauge and satellite sea level data and plot:
gmsl <- get_sealevel()
plot_sealevel(gmsl)
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Retrieve July annual Arctic Sea Ice Index and plot:
seaice <- get_seaice()
plot_seaice(seaice)
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get_seaice()
arguments can be modified to download Antarctic sea ice,
and allow any month.
You can also visualize sea ice by month and year:
arcticice <- get_icecurves()
plot_icecurves(arcticice)
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Retrieve Common Era temperature reconstruction and plot it with instrumental record:
anomaly2k <- get_temp2k()
plot_temp2k(anomaly2k)
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Retrieve NOAA HURDAT2 hurricane data and plot:
hurricanes <- get_hurricanes()
plot_hurricanes(hurricanes)
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plot_hurricane_nrg(hurricanes)
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Retrieve Vostok paleo ice core data and plot:
vostok <- get_paleo()
plot_paleo(vostok)
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Managing the cache
By default, no climate data is cached, and all data is downloaded every
time any of the get_
functions is called. To cache data for future
use, use the write_cache = TRUE
option, available in all of the get_
functions. To download and cache all data use
hockeystick_update_all()
. To view the files, date, and size of cached
data use hockeystick_cache_details()
. To re-download data from the
source use the use_cache = FALSE
argument in any of the get_
functions, for example:
get_carbon(use_cache = FALSE, write_cache = TRUE)
. To delete all
cached data use hockeystick_cache_delete_all()
.
Users may also cache data by default by adding
options(hs_write_cache = TRUE)
to their script or .Rprofile
file.
All together now: climate data grid
climate_grid()
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Acknowledgments
- Carbon Dioxide concentrations: Dr. Pieter Tans, NOAA/GML (https://gml.noaa.gov/ccgg/trends/) and Dr. Ralph Keeling, Scripps Institution of Oceanography.
- Global temperature anomaly: GISS Surface Temperature Analysis (GISTEMP), version 4. GISTEMP Team, 2020: NASA Goddard Institute for Space Studies. https://data.giss.nasa.gov/gistemp/
- Warming Stripes design from Ed Hawkins’ Climate Lab.
https://www.climate-lab-book.ac.uk/2018/warming-stripes/. In
addition grateful to Dr. Dominic Royé for posting his approach to
plotting them using ggplot2, which
warming_stripes()
is based on. https://dominicroye.github.io/en/2018/how-to-create-warming-stripes-in-r/ - Sea level data: NOAA Laboratory for Satellite Altimetry (sat) and Commonwealth Scientific and Industrial Research Organisation (tide gauges)
- Sea Ice Index: National Snow & Ice Data Center. Data Archive: https://nsidc.org/data/explore-data
- Vostok carbon dioxide and temperature data: https://cdiac.ess-dive.lbl.gov/trends/co2/vostok.html
- Common Era reconstructed temperature data: PAGES2k Consortium and NOAA).
- Hurricanes: National Oceanic and Atmospheric Administration HURDAT Atlantic Hurricane Database Re-analysis Project, particularly Dr. Chris Landsea.
- Carbon Dioxide emissions: Global Carbon Project and Our World In Data
- Thank you to Dirk Eddelbuettel for providing the .isConnected function from his tint package to test for internet connectivity.
Notes and resources
- All data is compiled to the best of my ability from reliable and
peer-reviewed sources. Please open an issue if you are aware of
enhanced or additional data that may be added to the package.
Building
hockeystick
is driven by my interest in tracking climate data and making it easily available to the community. - Here are some online resources I have found very helpful to learn mo re about climate science:
- MIT edX Global Warming Science. https://www.edx.org/course/global-warming-science
- SDG Academy: Climate Change: The Science and Global Impact. https://sdgacademy.org/course/climate-change-the-science-and-global-impact/