US temperatures in 1950 and 2022

Description

A representative set of monitoring locations were taken from NOAA data in 1950 and 2022 such that the locations are sampled roughly geographically across the continental US (the observations do not represent a random sample of geographical locations).

Usage

us_temperature

Format

A data frame with 18759 observations on the following 9 variables.

location

Location of the NOAA weather station.

station

Formal ID of the NOAA weather station.

latitude

Latitude of the NOAA weather station.

longitude

Longitude of the NOAA weather station.

elevation

Elevation of the NOAA weather station.

date

Date the measurement was taken (Y-m-d).

tmax

Maximum daily temperature (Farenheit).

tmin

Minimum daily temperature (Farenheit).

year

Year of the measurement.

Details

Please keep in mind that the data represent two annual snapshots, and a complete analysis would consider more than two years of data and a random or more complete sampling of weather stations across the US.

Source

NOAA Climate Data Online. Retrieved 23 September, 2023.

Examples

library(dplyr)
library(ggplot2)
library(maps)

summarized_temp <- us_temperature |>
  group_by(station, year, latitude, longitude) |>
  summarize(tmax_med = median(tmax, na.rm = TRUE)) |>
  mutate(plot_shift = ifelse(year == "1950", 0, 1)) |>
  mutate(year = as.factor(year))

usa <- map_data("state")

ggplot(data = usa, aes(x = long, y = lat)) +
  geom_polygon(aes(group = group), color = "black", fill = "white") +
  geom_point(
    data = summarized_temp,
    aes(
      x = longitude + plot_shift, y = latitude,
      color = tmax_med, shape = year
    )
  ) +
  scale_color_gradient(high = IMSCOL["red", 1], low = IMSCOL["yellow", 1]) +
  ggtitle("Median of the daily high temp, 1950 & 2022") +
  labs(
    x = "longitude",
    color = "median high temp"
  ) +
  guides(shape = guide_legend(override.aes = list(color = "black")))