The traditional wind rose plot that plots wind speed and wind direction by different intervals. The pollution rose applies the same plot structure but substitutes other measurements, most commonly a pollutant time series, for wind speed.
windRose(
mydata,
ws = "ws",
wd = "wd",
ws2 = NA,
wd2 = NA,
ws.int = 2,
angle = 30,
type = "default",
bias.corr = TRUE,
cols = "default",
grid.line = NULL,
width = 1,
seg = NULL,
auto.text = TRUE,
breaks = 4,
offset = 10,
normalise = FALSE,
max.freq = NULL,
paddle = TRUE,
key.header = NULL,
key.footer = "(m/s)",
key.position = "bottom",
key = TRUE,
dig.lab = 5,
include.lowest = FALSE,
statistic = "prop.count",
pollutant = NULL,
annotate = TRUE,
angle.scale = 315,
border = NA,
alpha = 1,
plot = TRUE,
...
)an openair object. Summarised proportions can be
extracted directly using the $data operator, e.g. object$data
for output <- windRose(mydata). This returns a data frame with three
set columns: cond, conditioning based on type; wd, the
wind direction; and calm, the statistic for the proportion of
data unattributed to any specific wind direction because it was collected
under calm conditions; and then several (one for each range binned for the
plot) columns giving proportions of measurements associated with each
ws or pollutant range plotted as a discrete panel.
A data frame containing fields ws and wd
Name of the column representing wind speed.
Name of the column representing wind direction.
The user can supply a second set of wind speed and wind
direction values with which the first can be compared. See
pollutionRose() for more details.
The Wind speed interval. Default is 2 m/s but for low met masts with low mean wind speeds a value of 1 or 0.5 m/s may be better.
Default angle of “spokes” is 30. Other potentially useful
angles are 45 and 10. Note that the width of the wind speed interval may
need adjusting using width.
type determines how the data are split i.e. conditioned,
and then plotted. The default is will produce a single plot using the
entire data. Type can be one of the built-in types as detailed in
cutData e.g. “season”, “year”, “weekday” and so
on. For example, type = "season" will produce four plots --- one for
each season.
It is also possible to choose type as another variable in the data
frame. If that variable is numeric, then the data will be split into four
quantiles (if possible) and labelled accordingly. If type is an existing
character or factor variable, then those categories/levels will be used
directly. This offers great flexibility for understanding the variation of
different variables and how they depend on one another.
Type can be up length two e.g. type = c("season", "weekday") will
produce a 2x2 plot split by season and day of the week. Note, when two
types are provided the first forms the columns and the second the rows.
When angle does not divide exactly into 360 a bias is
introduced in the frequencies when the wind direction is already supplied
rounded to the nearest 10 degrees, as is often the case. For example, if
angle = 22.5, N, E, S, W will include 3 wind sectors and all other
angles will be two. A bias correction can made to correct for this problem.
A simple method according to Applequist (2012) is used to adjust the
frequencies.
Colours to be used for plotting. Options include
“default”, “increment”, “heat”, “jet”,
“hue” and user defined. For user defined the user can supply a list
of colour names recognised by R (type colours() to see the full
list). An example would be cols = c("yellow", "green", "blue",
"black").
Grid line interval to use. If NULL, as in default,
this is assigned based on the available data range. However, it can also be
forced to a specific value, e.g. grid.line = 10. grid.line
can also be a list to control the interval, line type and colour. For
example grid.line = list(value = 10, lty = 5, col = "purple").
For paddle = TRUE, the adjustment factor for width of
wind speed intervals. For example, width = 1.5 will make the paddle
width 1.5 times wider.
When paddle = TRUE, seg determines with width of the
segments. For example, seg = 0.5 will produce segments 0.5 *
angle.
Either TRUE (default) or FALSE. If TRUE
titles and axis labels will automatically try and format pollutant names
and units properly, e.g., by subscripting the ‘2’ in NO2.
Most commonly, the number of break points for wind speed. With
the ws.int default of 2 m/s, the breaks default, 4, generates
the break points 2, 4, 6, 8 m/s. However, breaks can also be used to
set specific break points. For example, the argument breaks = c(0, 1,
10, 100) breaks the data into segments <1, 1-10, 10-100, >100.
The size of the 'hole' in the middle of the plot, expressed as a percentage of the polar axis scale, default 10.
If TRUE each wind direction segment is normalised to
equal one. This is useful for showing how the concentrations (or other
parameters) contribute to each wind sector when the proportion of time the
wind is from that direction is low. A line showing the probability that the
wind directions is from a particular wind sector is also shown.
Controls the scaling used by setting the maximum value for the radial limits. This is useful to ensure several plots use the same radial limits.
Either TRUE or FALSE. If TRUE plots rose
using 'paddle' style spokes. If FALSE plots rose using 'wedge' style
spokes.
Adds additional text/labels above the scale key. For
example, passing windRose(mydata, key.header = "ws") adds the
addition text as a scale header. Note: This argument is passed to
drawOpenKey() via quickText(), applying the auto.text argument, to
handle formatting.
Adds additional text/labels below the scale key. See
key.header for further information.
Location where the scale key is to plotted. Allowed arguments currently include “top”, “right”, “bottom” and “left”.
Fine control of the scale key via drawOpenKey().
The number of significant figures at which scientific number formatting is used in break point and key labelling. Default 5.
Logical. If FALSE (the default), the first
interval will be left exclusive and right inclusive. If TRUE, the
first interval will be left and right inclusive. Passed to the
include.lowest argument of cut().
The statistic to be applied to each data bin in the
plot. Options currently include “prop.count”, “prop.mean” and
“abs.count”. The default “prop.count” sizes bins according to
the proportion of the frequency of measurements. Similarly,
“prop.mean” sizes bins according to their relative contribution to
the mean. “abs.count” provides the absolute count of measurements in
each bin.
Alternative data series to be sampled instead of wind speed.
The windRose() default NULL is equivalent to pollutant = "ws". Use
in pollutionRose().
If TRUE then the percentage calm and mean values are
printed in each panel together with a description of the statistic below
the plot. If " " then only the statistic is below the plot. Custom
annotations may be added by setting value to c("annotation 1",
"annotation 2").
The scale is by default shown at a 315 degree angle.
Sometimes the placement of the scale may interfere with an interesting
feature. The user can therefore set angle.scale to another value
(between 0 and 360 degrees) to mitigate such problems. For example
angle.scale = 45 will draw the scale heading in a NE direction.
Border colour for shaded areas. Default is no border.
The alpha transparency to use for the plotting surface (a value
between 0 and 1 with zero being fully transparent and 1 fully opaque).
Setting a value below 1 can be useful when plotting surfaces on a map using
the package openairmaps.
Should a plot be produced? FALSE can be useful when
analysing data to extract plot components and plotting them in other ways.
Other parameters that are passed on to drawOpenKey,
lattice:xyplot and cutData. Axis and title labelling options
(xlab, ylab, main) are passed to xyplot via
quickText to handle routine formatting.
David Carslaw (with some additional contributions by Karl Ropkins)
For windRose data are summarised by direction, typically by 45 or 30
(or 10) degrees and by different wind speed categories. Typically, wind
speeds are represented by different width "paddles". The plots show the
proportion (here represented as a percentage) of time that the wind is from a
certain angle and wind speed range.
By default windRose will plot a windRose in using "paddle" style
segments and placing the scale key below the plot.
The argument pollutant uses the same plotting structure but
substitutes another data series, defined by pollutant, for wind speed.
It is recommended to use pollutionRose() for plotting pollutant
concentrations.
The option statistic = "prop.mean" provides a measure of the relative
contribution of each bin to the panel mean, and is intended for use with
pollutionRose.
Applequist, S, 2012: Wind Rose Bias Correction. J. Appl. Meteor. Climatol., 51, 1305-1309.
Droppo, J.G. and B.A. Napier (2008) Wind Direction Bias in Generating Wind Roses and Conducting Sector-Based Air Dispersion Modeling, Journal of the Air & Waste Management Association, 58:7, 913-918.
Other polar directional analysis functions:
percentileRose(),
polarAnnulus(),
polarCluster(),
polarDiff(),
polarFreq(),
polarPlot(),
pollutionRose()
# basic plot
windRose(mydata)
# one windRose for each year
windRose(mydata,type = "year")
# windRose in 10 degree intervals with gridlines and width adjusted
if (FALSE) {
windRose(mydata, angle = 10, width = 0.2, grid.line = 1)
}
Run the code above in your browser using DataLab