In ZellW/LearnPlotting:

From https://rpubs.com/gaston/hurricanes

Description

Inspired by Aaron Koblin's flight patterns and by Mapped British Shipping, I decided to play with a different data about storms (i.e. hurricanes) and try to map their trajectories.

The Data

The data is freely available from the International Best Track Archive for Climate Stewardship (IBTrACS)[http://www.ncdc.noaa.gov/ibtracs/index.php?name=wmo-data] at the National Climatic Data Center website and can be downloaded in different formats. In my case I decided to use the csv files although you can find a lot of different formats (pick the one that best fits your needs or preferences).

# load packages

library(maps)
library(ggplot2)
#library(R.utils)
#gunzip("./data/Allstorms.ibtracs_wmo.v03r07.csv.gz")

# NOAA url
noaa = "ftp://eclipse.ncdc.noaa.gov/pub/ibtracs/v03r03/wmo/csv/basin/"

# basins
basin = c("NA", "EP")

# read files from IBTrACS
NA.basin = read.csv(paste(noaa, "Basin.", basin[1], ".ibtracs_wmo.v03r03.csv", 
    sep = ""), skip = 1, stringsAsFactors = FALSE)
EP.basin = read.csv(paste(noaa, "Basin.", basin[2], ".ibtracs_wmo.v03r03.csv", 
    sep = ""), skip = 1, 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$Latitude = as.numeric(gsub("^ ", "", NA.basin$Latitude))
NA.basin$Longitude = as.numeric(gsub("^ ", "", NA.basin$Longitude))
NA.basin$Wind.WMO. = as.numeric(gsub("^ ", "", NA.basin$Wind.WMO.))

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

# 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])

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

Prepare the plot ingredients

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 1999 and 2010
substorms = subset(storms, Season %in% 1999:2010)
nop = which(substorms$Name == "NOT NAMED")
substorms = substorms[-nop, ]

# 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

# map with ggplot
#with new ggplot2, opts has been deprecated. You can simply replace it with theme() in your code.
#•theme_blank(), theme_text(), theme_rect(), theme_line(), and theme_segment() are deprecated. You can replace them with element_blank(), #element_text(), element_rect(), and element_line().
#•Previously, the way to set the title of a plot was opts(title="Title text"). In the new version, use ggtitle("Title text") or labs(title="Title #text").

# 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", colour = "gray10", size = 0.2) + geom_path(data = substorms, 
#     aes(group = ID, colour = Wind.WMO.), alpha = 0.5, size = 0.8) + xlim(-138, 
#     -20) + ylim(3, 55) + labs(x = "", y = "", colour = "Wind \n(knots)") + theme(panel.background = element_rect(fill = "gray10", 
#     #colour = "gray30"), title = "Hurricane Trajectories 1999 - 2010", axis.text.x = element_blank(), 
#     colour = "gray30"), ggtitle("Hurricane Trajectories 1999 - 2010"), axis.text.x = element_blank(), 
#     axis.text.y = element_blank(), axis.ticks = element_blank(), panel.grid.major = element_blank(), 
#     panel.grid.minor = element_blank())
# 
# # show me the map
# map1

Cliff mods below to get the one above working

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", colour = "gray10", size = 0.2) + geom_path(data = substorms, 
    aes(group = ID, colour = Wind.WMO.), alpha = 0.5, size = 0.8) + xlim(-138, 
    -20) + ylim(3, 55) + labs(x = "", y = "", colour = "Wind \n(knots)")+ 
     theme(panel.background = element_rect(fill = "gray10", colour = "gray30")

           , title = "Hurricane Trajectories 1999 - 2010"

           , axis.text.x = element_blank(), 
    colour = "gray30"), ggtitle("Hurricane Trajectories 1999 - 2010"))

#, axis.text.x = element_blank(), 
    #axis.text.y = element_blank(), axis.ticks = element_blank(), panel.grid.major = element_blank(), 
    #panel.grid.minor = element_blank())

# 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", colour = "gray10", size = 0.2) + geom_path(data = substorms, 
    aes(group = ID, colour = Wind.WMO.), size = 0.5) + xlim(-138, -20) + ylim(3, 
    55) + labs(x = "", y = "", colour = "Wind \n(knots)") + facet_wrap(~Month) + 
    opts(title = "Hurricane Trajectories by Month (1999 - 2010)", panel.background = element_rect(fill = "gray10", 
        colour = "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())

map2