windchill.R

library(tidyverse)
#Wind speeds from the percentile bands in 
#https://weatherspark.com/y/23912/Average-Weather-in-New-York-City-New-York-United-States-Year-Round
#https://weatherspark.com/y/14091/Average-Weather-in-Chicago-Illinois-United-States-Year-Round
#weather.gov wind chill chart at https://www.weather.gov/safety/cold-wind-chill-chart

get_wind_chill = function(temp,wind){
  35.74 + .6251*temp - 35.75 * wind^.16 + .4275 * temp * wind^.16
}

toC = function(F) {(F - 32) * 5 / 9}

speeds = c(10,15,25)

mini_df = data.frame(temp=c(35,35,27.5,27.5),
                     wind=c(10,16,14,22),
                     lab=c("NYC Avg","NYC Windy","Chicago Avg","Chicago Windy")
                     ) %>%
  mutate(
    wind_speed = factor(wind, levels = speeds),
    wind_chill = round(get_wind_chill(temp,wind),0)) 
  
df = expand.grid(temp = seq(5, 40, by = 2), wind = speeds) %>%
  mutate(
    wind_speed = factor(wind, levels = speeds),
    wind_chill = round(get_wind_chill(temp,wind),2)) 

p=ggplot(df,aes(x=temp,y=wind_chill-temp, group=wind_speed, color=wind_speed))
p = p + geom_line(size = 1) +
    ylim(c(-25,0)) +
    theme_bw() +
    labs(x = "Temperature", y = "Adjustment to temperature\nto get wind chill (F)") +
 geom_text(show.legend=FALSE,data=mini_df,
   aes(x=temp,y=wind_chill-temp+1.25,label=lab,group=NULL,color=NULL)) +
 geom_point(show.legend=FALSE,data=mini_df,size=2,
   aes(x=temp,y=wind_chill-temp,group=NULL,color=NULL)) +
 theme(legend.position = "bottom") 
p
ggsave(plot=p,file="windchill_chicago_nyc.png",width=6,height=4)