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 I wrote my own post on obtaining and visualizing this data (now out of date), which is the basis for this package.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).
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:
::install_github("cortinah/hockeystick") remotes
Retrieve NOAA/ESRL Mauna Loa CO2 Observatory concentration data and plot:
library(hockeystick)
<- get_carbon()
ml_co2 plot_carbon(ml_co2)
Retrieve GCP global CO2 emissions and plot:
<- get_emissions()
emissions plot_emissions(emissions)
Retrieve NASA/GISS global surface temperature anomaly data and plot:
<- get_temp()
anomaly plot_temp(anomaly)
Visualize warming using Ed Hawkins styled “warming stripes”:
warming_stripes()
warming_stripes(stripe_only = TRUE, col_strip = viridisLite::viridis(11))
Retrieve tide gauge and satellite sea level data and plot:
<- get_sealevel()
gmsl plot_sealevel(gmsl)
Retrieve July annual Arctic Sea Ice Index and plot:
<- get_seaice()
seaice plot_seaice(seaice)
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:
<- get_icecurves()
arcticice plot_icecurves(arcticice)
Retrieve Common Era temperature reconstruction and plot it with instrumental record:
<- get_temp2k()
anomaly2k plot_temp2k(anomaly2k)
Retrieve NOAA HURDAT2 hurricane data and plot:
<- get_hurricanes()
hurricanes plot_hurricanes(hurricanes)
plot_hurricane_nrg(hurricanes)
Retrieve Vostok paleo ice core data and plot:
<- get_paleo()
vostok plot_paleo(vostok)
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.
climate_grid()
warming_stripes()
is
based on. https://dominicroye.github.io/en/2018/how-to-create-warming-stripes-in-r/hockeystick
is driven by my interest in tracking climate
data and making it easily available to the community.