Geom for Hurricanes

The purpose of this exercise is to build a new geom using grid and ggplot2 packages to facilitate in visualizing hurricane winds on a map.

Hurricanes

Hurricanes can have asymmetrical wind fields, with much higher winds on one side of a storm compared to the other. Hurricane wind radii report how far winds of a certain intensity (e.g., 34, 50, or 64 knots) extended from a hurricane’s center, with separate values given for the northeast, northwest, southeast, and southwest quadrants of the storm. The 34 knot radius in the northeast quadrant, for example, reports the furthest distance from the center of the storm of any location that experienced 34-knot winds in that quadrant.

This wind radii data provide a clearer picture of the storm structure than the simpler measurements of a storm’s position and maximum winds. For example, if a storm was moving very quickly, the forward motion of the storm might have contributed significantly to wind speeds to the right of the storm’s direction of forward motion, and wind radii might be much larger for the northeast quadrant of the storm than the northwest quadrant.

Data

The aforementioned wind radii are available for Atlantic basin tropical storms since 1988 through the Extended Best Tract dataset maintained by Colorodo State University.

Load Data

One of the functions in this package allow us to import raw Extended Best Track (EBTRK) data. The example data has 29 variables and 11,824 rows. The first few rows of the raw data are displayed below.

storm_id	storm_name	month	day	hour	year	latitude	longitude	max_wind	min_pressure	rad_max_wind	eye_diameter	pressure_1	pressure_2	radius_34_ne	radius_34_se	radius_34_sw	radius_34_nw	radius_50_ne	radius_50_se	radius_50_sw	radius_50_nw	radius_64_ne	radius_64_se	radius_64_sw	radius_64_nw	storm_type	distance_to_land	final
AL0188	ALBERTO	08	05	18	1988	32.0	77.5	20	1015	NA	NA	NA	NA	0	0	0	0	0	0	0	0	0	0	0	0		218	.
AL0188	ALBERTO	08	06	00	1988	32.8	76.2	20	1014	NA	NA	NA	NA	0	0	0	0	0	0	0	0	0	0	0	0		213	.
AL0188	ALBERTO	08	06	06	1988	34.0	75.2	20	1013	NA	NA	NA	NA	0	0	0	0	0	0	0	0	0	0	0	0		149	.
AL0188	ALBERTO	08	06	12	1988	35.2	74.6	25	1012	NA	NA	NA	NA	0	0	0	0	0	0	0	0	0	0	0	0		126	.
AL0188	ALBERTO	08	06	18	1988	37.0	73.5	25	1011	NA	NA	NA	NA	0	0	0	0	0	0	0	0	0	0	0	0		197	.
AL0188	ALBERTO	08	07	00	1988	38.7	72.4	25	1009	NA	NA	NA	NA	0	0	0	0	0	0	0	0	0	0	0	0		193	.

Tidy Data

We also need to “tidy” the data and format it to be used with geom_hurricane. As such, the data_tidy function allows the user to do so. The first few rows of the tidy data are presented below.

storm_id	date	latitude	longitude	wind_speed	ne	se	sw	nw
Alberto-1988	1988-08-05 18:00:00	32.0	-77.5	34	0	0	0	0
Alberto-1988	1988-08-05 18:00:00	32.0	-77.5	50	0	0	0	0
Alberto-1988	1988-08-05 18:00:00	32.0	-77.5	64	0	0	0	0
Alberto-1988	1988-08-06 00:00:00	32.8	-76.2	34	0	0	0	0
Alberto-1988	1988-08-06 00:00:00	32.8	-76.2	50	0	0	0	0
Alberto-1988	1988-08-06 00:00:00	32.8	-76.2	64	0	0	0	0

Select Hurricane

Finally, the data_filter_hurricane function allows the user to select the hurricane that needs to be plotted.

Hurricane names are recycled. Therefore, the user needs to specify the year of the hurricane.

The example below shows the filtered and formatted tidy data for the

storm_id	date	latitude	longitude	wind_speed	ne	se	sw	nw
Katrina-2005	2005-08-25 12:00:00	26.2	-79.0	34	60	60	30	50
Katrina-2005	2005-08-25 18:00:00	26.2	-79.6	34	70	70	50	60
Katrina-2005	2005-08-25 18:00:00	26.2	-79.6	50	25	25	20	20
Katrina-2005	2005-08-26 00:00:00	25.9	-80.3	34	70	70	50	40
Katrina-2005	2005-08-26 00:00:00	25.9	-80.3	50	20	20	20	20
Katrina-2005	2005-08-26 00:00:00	25.9	-80.3	64	10	10	10	10

Examples

Landfall

Hurricane Katrina appeared to make landfall on October 29, 2005 around 6 AM CDT. We will filter the data highlited above and plot the hurricane geom to visualize the wind speeds as it made landfall in Louisiana.

library(ggmap)
get_map("Louisiana", zoom = 6, maptype = "toner-background") %>%
  ggmap(extent = "device") +
  geom_hurricane(data = katrina_lf,
                 aes(x = longitude, y = latitude, 
                     r_ne = ne, r_se = se, r_nw = nw, r_sw = sw,
                     fill = wind_speed, color = wind_speed),
                 alpha = 0.5) + 
  scale_color_manual(name = "Wind speed (kts)", 
                     values = c("red", "orange", "yellow")) + 
  scale_fill_manual(name = "Wind speed (kts)", 
                    values = c("red", "orange", "yellow"))

Hurricane Path

The path of the hurricane can be seen in the animation below.

library(gganimate)
library(gifski)
library(magick)

hurricane_path <- 
    get_map("Jacksonville", zoom = 5, maptype = "hybrid") %>%
    ggmap(extent = "device") +
    geom_hurricane(data = katrina,
                   aes(x = longitude, y = latitude, 
                     r_ne = ne, r_se = se, r_nw = nw, r_sw = sw,
                     fill = wind_speed, color = wind_speed),
                 alpha = 0.5) + 
  scale_color_manual(name = "Wind speed (kts)", 
                     values = c("red", "orange", "yellow")) + 
  scale_fill_manual(name = "Wind speed (kts)", 
                    values = c("red", "orange", "yellow")) +
  transition_time(date) +
  ease_aes('linear')

animate(hurricane_path, renderer = magick_renderer())