Plot a time series of vertical profiles (vpts)

Plot a time series of vertical profiles of class vpts.

# S3 method for class 'vpts'
plot(
  x,
  xlab = "time",
  ylab = "height [m]",
  quantity = "dens",
  log = NA,
  barbs = TRUE,
  barbs_height = 10,
  barbs_time = 20,
  barbs_dens_min = 5,
  zlim,
  legend_ticks,
  legend.ticks,
  main,
  barbs.h = 10,
  barbs.t = 20,
  barbs.dens = 5,
  na_color = "#C8C8C8",
  nan_color = "white",
  n_color = 1000,
  palette = NA,
  ...
)

Arguments

x: A vp class object inheriting from class vpts.
xlab: A title for the x-axis.
ylab: A title for the y-axis.
quantity: Character string with the quantity to plot, one of 'dens','eta','dbz','DBZH' for density, reflectivity, reflectivity factor and total reflectivity factor, respectively.
log: Logical, whether to display quantity data on a logarithmic scale.
barbs: Logical, whether to overlay speed barbs.
barbs_height: Integer, number of barbs to plot in altitudinal dimension.
barbs_time: Integer, number of barbs to plot in temporal dimension.
barbs_dens_min: Numeric, lower threshold in aerial density of individuals for plotting speed barbs in individuals/km^3.
zlim: Optional numerical atomic vector of length 2, specifying the range of quantity values to plot.
legend_ticks: Numeric atomic vector specifying the ticks on the color bar.
legend.ticks: Deprecated argument, use legend_ticks instead.
main: A title for the plot.
barbs.h: Deprecated argument, use barbs_height instead.
barbs.t: Deprecated argument, use barbs_time instead.
barbs.dens: Deprecated argument, use barbs_dens_min instead.
na_color: Color to use for NA values, see class vpts() conventions.
nan_color: Color to use for NaN values, see class vpts() conventions.
n_color: The number of colors (>=1) to be in the palette.
palette: (Optional) character vector of hexadecimal color values defining the plot color scale, e.g. output from viridis
...: Additional arguments to be passed to the low level image plotting function.

Value

No return value, side effect is a plot.

Details

Aerial abundances can be visualized in four related quantities, as specified by argument quantity:

dens: the aerial density of individuals. This quantity is dependent on the assumed radar cross section (RCS) in the x$attributes$how$rcs_bird attribute
eta: reflectivity. This quantity is independent of the value of the rcs_bird attribute
dbz: reflectivity factor. This quantity is independent of the value of the rcs_bird attribute, and corresponds to the dBZ scale commonly used in weather radar meteorology. Bioscatter by birds tends to occur at much higher reflectivity factors at S-band than at C-band
DBZH: total reflectivity factor. This quantity equals the reflectivity factor of all scatterers (biological and meteorological scattering combined)

Aerial velocities can be visualized in three related quantities, as specified by argument quantity:

ff: ground speed. The aerial velocity relative to the ground surface in m/s.
u: eastward ground speed component in m/s.
v: northward ground speed component in m/s.

barbs

In the speed barbs, each half flag represents 2.5 m/s, each full flag 5 m/s, each pennant (triangle) 25 m/s

legend_ticks / zlim

Default legend ticks and plotting range are specified based on quantity, radar wavelength (S- vs C-band), and value of log

log

Quantities u and v cannot be plotted on a logarithmic scale, because these quantities assume negative values. For quantities DBZH and dbz log=TRUE is ignored, because these quantities are already logarithmic.

Examples

# locate example file:
ts <- example_vpts
# plot density of individuals for the first 500 time steps, in the altitude
# layer 0-3000 m.
plot(ts[1:500], ylim = c(0, 3000))
#> Warning: Irregular time-series: missing profiles will not be visible. Use 'regularize_vpts' to make time series regular.

# plot total reflectivity factor (rain, birds, insects together):
plot(ts[1:500], ylim = c(0, 3000), quantity = "DBZH")
#> Warning: Irregular time-series: missing profiles will not be visible. Use 'regularize_vpts' to make time series regular.

# regularize the time grid, which includes empty (NA) profiles at
# time steps without data:
ts_regular <- regularize_vpts(ts)
#> projecting on 300 seconds interval grid...
plot(ts_regular)

# change the color of missing NA data to red
plot(ts_regular, na_color="red")

# change the color palette:
plot(ts_regular[1:1000], ylim = c(0, 3000), palette=viridis::viridis(1000))

# change and inverse the color palette:
plot(ts_regular[1:1000], ylim = c(0, 3000), palette=rev(viridis::viridis(1000, option="A")))

# plot the speed profile:
plot(ts_regular[1:1000], quantity="ff")

# plot the northward speed component:
plot(ts_regular[1:1000], quantity="v")

# plot speed profile with more legend ticks,
plot(ts_regular[1:1000], quantity="ff", legend_ticks=seq(0,20,2), zlim=c(0,20))