climate70: Temperature Summary Data, Geography Limited

Description Usage Format Details Source Examples

Description

A random set of monitoring locations were taken from NOAA data that had both years of interest (1948 and 2018) as well as data for both summary metrics of interest (dx70 and dx90, which are described below).

Usage

1

Format

A data frame with 197 observations on the following 7 variables.

station

Station ID.

latitude

Latitude of the station.

longitude

Longitude of the station.

dx70_1948

Number of days above 70 degrees in 1948.

dx70_2018

Number of days above 70 degrees in 2018.

dx90_1948

Number of days above 90 degrees in 1948.

dx90_2018

Number of days above 90 degrees in 2018.

Details

Please keep in mind that these are two annual snapshots, and a complete analysis would consider much more than two years of data and much additional information for those years.

Source

https://www.ncdc.noaa.gov/cdo-web/datasets, retrieved 2019-04-24.

Examples

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# Data sampled are from the US, Europe, and Australia.
# This geographic limitation may be due to the particular
# years considered, since locations without both 1948 and
# 2018 were discarded for this (simple) data set.
plot(climate70$longitude, climate70$latitude)

plot(climate70$dx70_1948, climate70$dx70_2018)
abline(0, 1, lty = 2)
plot(climate70$dx90_1948, climate70$dx90_2018)
abline(0, 1, lty = 2)
hist(climate70$dx70_2018 - climate70$dx70_1948)
hist(climate70$dx90_2018 - climate70$dx90_1948)

t.test(climate70$dx70_2018 - climate70$dx70_1948)
t.test(climate70$dx90_2018 - climate70$dx90_1948)

openintro documentation built on April 19, 2021, 5:06 p.m.