plot.seas.norm {seas}

Plot seasonal normal of a variable, including precipitation normals

Description

Plots a “normal” of a seasonal variable, including a precipitation normal (which shows rain and snow fractions, where available). Significant missing data values are also indicated.

Usage

## S3 method for class 'seas.norm'
plot(x, start = 1, rep = 0, ylim,
     varwidth = FALSE, normwidth = FALSE,
     leg, add.alt = FALSE, main, ylab, ...)

Arguments

x

a seas.norm object created by either seas.norm or precip.norm

start

starting bin

rep

repeat bins

ylim

range of y-axis; either as a single value, c(0, max), or as two values c(min, max)

varwidth

logical; varies the width of each bar directly proportional to the frequency of active days (defined by a threshold); the value is normalized according to the next argument

normwidth

normalizes the width of the bars to a fixed numeric value (in days), or the maximum value if given TRUE; the default FALSE value normalizes each bar to the number of potentially active days

leg

if TRUE shows a legend summary of the statistics in the upper left hand corner; it can also be a c(x, y) pair or “locator” to manually place the legend on the active graphics device

add.alt

logical; adds imperial units on the right-hand y-axis

main

title for plot; if it is missing, then it will automatically be generated

ylab

y-axis label; if it is missing, then it will automatically be generated

...

ignored

Details

The varwidth variable is useful for separating different precipitation patterns throughout the season. It changes the width of the bar proportional to the frequency of precipitation events within the bin. Ideally, the bars will be tall and narrow with intense storms that occur infrequently, such as convective storms. Conversely the bars will be broader with less-intense rainfall events occurring more frequently.

Author(s)

Mike Toews

See Also

seas.norm, precip.norm, seas.sum

Examples

data(mscdata)
dat <- mksub(mscdata, id=1108447)
d.ss <- seas.sum(dat)
plot(seas.norm(d.ss))
plot(precip.norm(d.ss, fun=median))
plot(precip.norm(d.ss, fun=mean))
plot(precip.norm(d.ss, fun=mean, norm="active"))
plot(precip.norm(d.ss, fun=median, norm="active"))
plot(precip.norm(d.ss), start=15, rep=12)
mar <- par("mar")
plot(precip.norm(d.ss), add.alt=TRUE)

par(mar=mar)
d2.ss <- seas.sum(dat, start.day=as.Date("2000-08-01"))
plot(precip.norm(d2.ss, fun="mean"))