Tracking the 2013 Hurricane Season

With it nearing the end of hurricane season it’s only appropriate to do a brief summary of the activity this year.   It’s been a surprisingly low-key season as far as hurricanes are concerned.  There have been only a few hurricanes and the barometric pressure of any hurricane this season has not even come close to hurricane Sandy (which broke the lowest barometric pressure record).

2013 Hurricane Season

A lot more analysis and visualization could be done with these data.  I will do some further statistical analysis and maybe some time series comparing past recorded hurricanes or maybe some other kriging approaches. Perhaps when I have some more spare time I’ll play with the data even more and look into the sustained wind speed and some of the other hurricane indices (e.g. the Power Dissipation Index).

The following graph shows a histogram of the barometric pressure and how it compares to hurricane Sandy.

2013 Barometric Pressure

In the mean time here is a short piece of code to produce the graphics for the 2013 hurricanes.   It produces a graph of the area around the Atlantic Basin and pulls the data down from Unisys.  It also highlights the East Coast states of the United States.  I have a text file that I put together that lists all the hurricanes by year back through 2007.

Example Code

library(maps)
library(maptools)
library(rgdal)
library(OpenStreetMap) ## for future use to produce aerial image maps
library(raster)

year = 2013
hurricanes = read.table(file=paste(“http://statistical-research.com/wp-content/uploads/2013/10/hurricanes.txt”,sep=””), sep=”,”, fill=TRUE, header=T)
hurricanes = as.vector( subset(hurricanes, hurricanes$YEAR==year, select=c(“NAME”)) )

hurr.dat = list()
max.lon = max.lat = min.lat = min.lon = NULL
b.press = NULL

for(i in 1:nrow(hurricanes)){
raw = read.table(file=paste(“http://weather.unisys.com/hurricane/atlantic/”,year,”/”,hurricanes[i,],”/track.dat”,sep=””), skip=2,fill=TRUE)
colnames(raw) = c(“Latitude”,”Longitude”,”Time”,”WindSpeed”,”Pressure”,”Status”)
raw$Pressure = as.character(raw$Pressure)
raw$Pressure[raw$Pressure==”-“] = NA
raw$Pressure = as.numeric(raw$Pressure)

hurr.dat[[i]] = cbind(raw$Latitude, raw$Longitude, raw$Pressure)
b.press = c(b.press, min(raw$Pressure, na.rm=T))

if(is.null(max.lat)){
max.lat = max(raw$Latitude)
} else if(max.lat < max(raw$Latitude)) { max.lat = max(raw$Latitude) } if(is.null(min.lat)){ min.lat = min(raw$Latitude) } else if (min.lat > min(raw$Latitude)){
min.lat = min(raw$Latitude)
}
if(is.null(max.lon)){
max.lon = max(raw$Longitude)
} else if (max.lon < max(raw$Longitude)){ max.lon = max(raw$Longitude) } if(is.null(min.lon)){ min.lon = min(raw$Longitude) } else if (min.lon > min(raw$Longitude)){
min.lon = min(raw$Longitude)
}

}
xlim <- c(min.lon-5,max.lon+10) ylim <- c(min.lat-5,max.lat+10) state.list <- c('new york','new jersey','virginia','massachusetts','connecticut','delaware','pennsylvania','maryland','north carolina','south carolina','georgia','florida', 'new hampshire','maine','district of columbia','west virginia','vermont') my.map <- map("state", region=state.list, interior = FALSE, xlim=xlim, ylim=ylim) map("state", region=state.list, boundary = TRUE, col="gray", add = TRUE,xlim=xlim) map("world", boundary = TRUE, col="gray", add = TRUE,xlim=xlim) for(j in 1:nrow(hurricanes)){ lines(x=hurr.dat[[j]][,2],y=hurr.dat[[j]][,1],col=j,cex=0.75) points(x=hurr.dat[[j]][,2],y=hurr.dat[[j]][,1],pch=15,cex=0.4, col=j) text(hurr.dat[[j]][1,2], hurr.dat[[j]][1,1],hurricanes[j,]) } title("Path of 2013 Hurricane Season") box() hist(b.press, xlim=c(920,1020), main="Histogram of Barometric Pressure for 2013", xlab="Barometric Pressure (mb)", ylab="Frequency") abline(v=940, col='blue',lwd=3) text(958,.5,"<&lt;2012 Hurricane Sandy") [/sourcecode]

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4 replies on “Tracking the 2013 Hurricane Season

  1. Well, the Atlantic season runs through 30 November, so it’s a little early to declare victory. Although, if memory serves, NOAA et al had predicted a more active than average season.

    From NOAA, yes, memory served (so far):
    “The updated outlook calls for a 70 percent chance of an above-normal season. Across the Atlantic Basin for the entire season – June 1 to November 30 – NOAA’s updated seasonal outlook (which includes the activity to date of tropical storms Andrea, Barry, Chantal, and Dorian) projects a 70 percent chance for each of the following ranges:

    13 to 19 named storms (top winds of 39 mph or higher), including
    6 to 9 hurricanes (top winds of 74 mph or higher), of which
    3 to 5 could be major hurricanes (Category 3, 4 or 5; winds of at least 111 mph)

    These ranges are above the 30-year seasonal averages of 12 named storms, six hurricanes and three major hurricanes.”

  2. Fantastic post! I spent quite a bit of time yesterday on the NOAA website and was looking to do something very similar to what you’ve done here. The NOAA has storm information going back some 150 years.

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