windRose {openair}

Traditional wind rose plot

Description

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.

Usage

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,
  ...
)

Arguments

mydata

A data frame containing fields ws and wd

ws

Name of the column representing wind speed.

wd

Name of the column representing wind direction.

ws2, wd2

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.

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.

angle

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

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.

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, 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.

cols

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

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").

width

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.

seg

When paddle = TRUE, seg determines with width of the segments. For example, seg = 0.5 will produce segments 0.5 * angle.

auto.text

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.

breaks

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.

offset

The size of the 'hole' in the middle of the plot, expressed as a percentage of the polar axis scale, default 10.

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 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.

max.freq

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.

paddle

Either TRUE or FALSE. If TRUE plots rose using 'paddle' style spokes. If FALSE plots rose using 'wedge' style spokes.

key.header

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.

key.footer

Adds additional text/labels below the scale key. See key.header for further information.

key.position

Location where the scale key is to plotted. Allowed arguments currently include “top”, “right”, “bottom” and “left”.

key

Fine control of the scale key via drawOpenKey().

dig.lab

The number of significant figures at which scientific number formatting is used in break point and key labelling. Default 5.

include.lowest

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().

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.

pollutant

Alternative data series to be sampled instead of wind speed. The windRose() default NULL is equivalent to pollutant = "ws". Use in pollutionRose().

annotate

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").

angle.scale

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

Border colour for shaded areas. Default is no border.

alpha

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.

plot

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.

Details

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.

Value

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.

Note

windRose and pollutionRose both use drawOpenKey() to produce scale keys.

Author(s)

David Carslaw (with some additional contributions by Karl Ropkins)

References

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.

See Also

Other polar directional analysis functions: percentileRose(), polarAnnulus(), polarCluster(), polarDiff(), polarFreq(), polarPlot(), pollutionRose()

Examples

# basic plot
windRose(mydata)

# one windRose for each year
windRose(mydata,type = "year")

# windRose in 10 degree intervals with gridlines and width adjusted
## Not run: 
windRose(mydata, angle = 10, width = 0.2, grid.line = 1)

## End(Not run)