’Visualizing Hurricane Paths

Visuals

2022

Published

June 1, 2022

The Data

The data is freely available from the International Best Track Archive for Climate Stewardship (IBTrACS)[https://www.ncei.noaa.gov/products/international-best-track-archive] at the National Climatic Data Center website and can be downloaded in different formats.

Basins include: - NA - North Atlantic - EP - Eastern North Pacific - WP - Western North Pacific - NI - North Indian - SI - South Indian - SP - Southern Pacific - SA - South Atlantic

This project includes only North Atlantic and Eastern North Pacific.

# load packages
library(tidyverse)
library(maps)
library(ggplot2)

NA.basin = read.csv("ibtracs.NA.list.v04r00.csv", stringsAsFactors = FALSE)
EP.basin = read.csv("ibtracs.EP.list.v04r00.csv", stringsAsFactors = FALSE)

# remove variable information
NA.basin = NA.basin[-1, ]
EP.basin = EP.basin[-1, ]

# formatting some columns
NA.basin$Season = as.numeric(NA.basin$SEASON)
NA.basin$Latitude = as.numeric(gsub("^ ", "", NA.basin$LAT))
NA.basin$Longitude = as.numeric(gsub("^ ", "", NA.basin$LON))
NA.basin$Wind.WMO. = as.numeric(gsub("^ ", "", NA.basin$WMO_WIND))

EP.basin$Season = as.numeric(EP.basin$SEASON)
EP.basin$Latitude = as.numeric(gsub("^ ", "", EP.basin$LAT))
EP.basin$Longitude = as.numeric(gsub("^ ", "", EP.basin$LON))
EP.basin$Wind.WMO. = as.numeric(gsub("^ ", "", EP.basin$WMO_WIND))

# extract month for dataset NA.basin
time.date = strsplit(NA.basin$ISO_TIME, " ")
iso.date = unlist(lapply(time.date, function(x) x[1]))
iso.month = substr(iso.date, 6, 7)
NA.basin$Month = factor(iso.month, labels = c(month.name))

# extract month for dataset EP.basin
time.date = strsplit(EP.basin$ISO_TIME, " ")
iso.date = unlist(lapply(time.date, function(x) x[1]))
iso.month = substr(iso.date, 6, 7)
#EP.basin$Month = factor(iso.month, labels = c(month.name)[-4])
EP.basin$Month = factor(iso.month, labels = c(month.name))

# join data frames
storms = rbind(NA.basin, EP.basin)

Prepare the plot

Once we’ve cleaned and processed the data, the next step is to prepare the ingredients for plotting a map. For this example, I’m selecting hurricanes from 1999 to 2010, and removing unnamed storms:

# world map
wm = map_data("world")

# select storms between 2000 and 2021

substorms <- storms %>% filter(Season %in% c(2000:2021) & NAME != "NOT_NAMED")

# add and ID with name and season
substorms$ID = as.factor(paste(substorms$NAME, substorms$SEASON, sep = "."))

# storm name as factor
substorms$NAME = as.factor(substorms$NAME)

Overall Hurricanes

Let’s plot the data with all the selected storms

map1 = ggplot(substorms, aes(x = Longitude, y = Latitude, group = ID)) + 
  geom_polygon(data = map_data("world"), aes(x = long, y = lat, group = group), 
               fill = "gray25", color = "gray10", size = 0.2) + 
  geom_path(data = substorms, aes(group = ID, color = Wind.WMO.), alpha = 0.5, size = 0.8) + 
  xlim(-138, -20) + ylim(3, 55) + 
  labs(x = "", y = "", color = "Wind \n(knots)") + 
  theme(panel.background = element_rect(fill = "gray10", color = "gray30"), axis.text = element_blank()) +
  ggtitle("Hurricane Trajectories 2000 - 2021")

# show me the map
map1

Hurricanes by month

Let’s get a more interesting visualization by months

# with facet-wrap by Month
map2 = ggplot(substorms, aes(x = Longitude, y = Latitude, group = ID)) + 
  geom_polygon(data = map_data("world"), aes(x = long, y = lat, group = group), fill = "gray25", color = "gray10", size = 0.2) + 
  geom_path(data = substorms, aes(group = ID, color = Wind.WMO.), size = 0.5) + 
  xlim(-138, -20) + ylim(3, 55) + 
  labs(x = "", y = "", color = "Wind \n(knots)") + 
  facet_wrap(~Month) + 
  # opts(title = "Hurricane Trajectories by Month (1999 - 2010)", 
  #      panel.background = element_rect(fill = "gray10", color = "gray30"), 
  #      axis.text.x = element_blank(), axis.text.y = element_blank(), 
  #      axis.ticks = element_blank(), panel.grid.major = element_blank(), panel.grid.minor = element_blank())

  theme(panel.background = element_rect(fill = "gray10", color = "gray30"), axis.text = element_blank(),
        axis.text.y = element_blank(), axis.ticks = element_blank(), panel.grid.major = element_blank(), 
        panel.grid.minor = element_blank()) + 
  ggtitle("Hurricane Trajectories by Month (2000 - 2021)")

map2