Pollution rose variation of the traditional wind rose
rose_wind.Rd
Pollution rose variation of the traditional wind rose
Usage
rose_wind(
data,
ws = "ws",
wd = "wd",
ws_int = 2,
angle = 30,
facet = NULL,
bias_corr = TRUE,
breaks = 4,
normalise = FALSE,
statistic = "prop.count",
width = 0.9,
border_colour = NA,
alpha = 1
)
Arguments
- data
A data frame containing fields
ws
andwd
- ws
Name of the column representing wind speed.
- wd
Name of the column representing wind direction.
- ws_int
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. Note, this argument is superseded in
pollutionRose
. Seebreaks
below.- angle
Angle of the spokes. Ideally a number by which 360 is evenly divisible (see
bias_corr
).- facet
One or two faceting columns.
facet
determines how the data are split and then plotted. Whenfacet
is length 1 it is passed toggplot2::facet_wrap()
, and when it is length 2 it is passed toggplot2::facet_grid()
with the first element being used as columns and the second rows. Some other options (e.g., multiplepollutant
columns) can limit the the number of faceting columns to 1.- bias_corr
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, ifangle = 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.- breaks
The number of break points to use when binning the data (used alongside
ws_int
), or a vector of specific break points. For example,breaks = 6
andws_int = 2
generates the break points 2, 4, 6 & 8 m/s, whereasbreaks = c(0, 1, 10, 100)
breaks the data into four segments: <1, 1-10, 10-100, & >100.- normalise
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 proprtion 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.- statistic
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.- width
Width of each bar as a fraction of its maximum width.
width = 1
makes all bars meet at their edges andwidth = 0
makes them disappear entirely. Defaults to0.9
.- border_colour
Border colour for shaded areas. Default is no border.
- alpha
The transparency of the plot. This is mainly useful to overlay it on a map.
See also
Other polar directional analysis functions:
polar_annulus()
,
polar_cluster()
,
polar_diff()
,
polar_freq()
,
polar_plot()
,
rose_metbias()
,
rose_percentile()
,
rose_pollution()