(Photo by Nasa, from Unsplash)
This dataset (known as Atlantic HURDAT2) contains historical records on tropical and subtropical cyclones from 1851 to 2015.
Python 2.7 virtual server is used to run the visualization. You must have Python 2.7 installed on your machine.
Clone the repository:
>>git clone https://github.com/dankovacek/hurdat
Navigate to the project directory and run:
python -m SimpleHTTPServer
Open your browser and navigate to
localhost:8000
The dataset has a comma-delimited format, featuring location, maximum wind, central pressure, and size of known tropical and subtropical cyclones. ("Size of cyclone" data is available from 2004 to 2015 only). The cyclone data are provided on a 6-hour interval. The csv data is formatted into two types of lines (or fields): header and data. The header rows contain 4 fields, while the data rows corresponding to the header row follow the header row and the integer at index 3 location of the header row indicates how many data rows correspond to the header row.
For ease of implementation with javascript libraries or other web-based applications, the data have been formatted into a json object. Details about the json object structure follow the description of the csv file format.
From the NHC documentation:
Example:
AL092011, IRENE, 39,
AL – Basin
Atlantic Basin
09 – ATCF cyclone number for that year
2011 – Year
IRENE – Name - (if available, or else “UNNAMED”)
39 – Number of best track entries – rows – to follow
Example:
20110828, 0935, L, TS, 39.4N, 74.4W, 60, 959, 230, 280, 160, 110, 150, 150, 80, 30, 0, 0, 0, 0,
20110828 – Date
Year, Month, Day as (YYYYMMDD)
0935 – Time
Hours and Minutes in UTC (Universal Time Coordinate)
L – Record Identifier
- C – Closest approach to a coast, not followed by a landfall
- G – Genesis
- I – An intensity peak in terms of both pressure and wind
- L – Landfall (center of system crossing a coastline)
- P – Minimum in central pressure
- R – Provides additional detail on the intensity of the cyclone when rapid changes are underway
- S – Change of status of the system
- T – Provides additional detail on the track (position) of the cyclone
- W – Maximum sustained wind speed
TS – Status of system
- TD – Tropical cyclone of tropical depression intensity (< 34 knots)
- TS – Tropical cyclone of tropical storm intensity (34-63 knots)
- HU – Tropical cyclone of hurricane intensity (> 64 knots)
- EX – Extratropical cyclone (of any intensity)
- SD – Subtropical cyclone of subtropical depression intensity (< 34 knots)
- SS – Subtropical cyclone of subtropical storm intensity (> 34 knots)
- LO – A low that is neither a tropical cyclone, a subtropical cyclone, nor an extratropical cyclone (of any intensity)
- WV – Tropical Wave (of any intensity)
- DB – Disturbance (of any intensity)
Location
39.4 N – Latitude and Hemisphere (N or S)
74.4 W – Longitude and Hemisphere (W or E)
Max. Wind Speed and Pressure
60 – Maximum sustained wind (in knots)
959 – Minimum Pressure (in millibars)
The cyclone system is described in wind speed zones:
34 kt (knot) wind radii maximum extents (in nautical miles)
230 – northeastern quadrant
280 – southeastern quadrant
160 – southwestern quadrant
110 – northwestern quadrant
50 kt (knot) wind radii maximum extents (in nautical miles)
150 – northeastern quadrant
150 – southeastern quadrant
80 – southwestern quadrant
30 – northwestern quadrant
64 kt (knot) wind radii maximum extents (in nautical miles)
0 – northeastern quadrant
0 – southeastern quadrant
0 – southwestern quadrant
0 – northwestern quadrant
The hurricane database has been converted into a json object ('result.json'). The object keys correspond to the unique cyclone identifier(ID), while each ID's corresponding value is itself an object containing the following keys:
Value is the cyclone's 'common' name, if one was given.
'track entries' = number of measurement tracks for the cyclone.
As above with CSV. May be blank.
An object with keys 'lat', and 'lon' for geographic coordinates of the datum. Latitude and Longitude have been converted from hemispherical (having directional designations N, W, etc.) to decimal notation (where positive values indicate northern and western hemispheres, negative values indicate southern and eastern.)
Value is maximum speed. As above with CSV format.
Value is minimum pressure. As above with CSV format.
As above with CSV format.
A date object with keys 'year', 'month', 'day' corresponding to the date of the corresponding record.
Value is a 4-digit string representing measurement time, in HHMM format.
An object with keys '30kt', '50kt', '64kt' for wind speeds, each of which is itself a key with values 'SW', 'NE', 'SE', 'NW' describing the extents of the wind at the corresponding speed.
Values are nautical miles or empty string if no data exists.
The data, and the description above were derived from the National Hurricane Center Data Archive, and the Center has also provided more detailed written documentation.
From the Documentation:
"The National Hurricane Center (NHC) conducts a post-storm analysis of each tropical cyclone in its area of responsibility to determine the official assessment of the cyclone's history. This analysis makes use of all available observations, including those that may not have been available in real time. In addition, NHC conducts ongoing reviews of any retrospective tropical cyclone analyses brought to its attention, and on a regular basis updates the historical record to reflect changes introduced via the Best Track Change Committee (Landsea et al. 2004a, 2004b, 2008, 2012, Hagen et al. 2012,)"
-Chris Landsea, James Franklin, and Jack Beven – May 2015
See the NHC disclaimer for more information regarding appropriate use.
Analysis and Visualizations that have used the Hurdat data:
- Interactive Visualization and Analysis of Hurricane Data
- Scientific Visualization Studio
- Generating Hurricanes with a Markov Spatial Process
This dataset represents over a century and a half of work in measuring and tracking cyclones. The D3 javascript library has numerous examples of ways to represent geographc data, and this dataset seems well suited to create a meaningful visualization of historical landfall sites in the coastal US. Perhaps a chloropleth could illustrate the most common landfall locations?
Are there any discernible trends in cyclone intensity, frequency, duration, size, or path over time? How about for specific locations with the highest landfall frequency?
A basic visualization of hurricane track termination points scaled by maximum sustained velocity to qualitatively illustrate relative difference. Based on DataMaps
