seas.sum {seas}R Documentation

Seasonal sum data object

Description

Create a seasonal sum object used for analysis of precipitation data (among other things, such as recharge rates).

Usage

# minimum usage
seas.sum(x)

# all options
seas.sum(x, start, end, width = 11, var, prime, a.cut = 0.3, 
     na.cut = 0.2, unit = "mm", id, name)

Arguments

x time-varying data.frame with variables which are summed, such as precipitation
start start year; if omitted minimum year will be used
end end year; if omitted will use same as start, and if start is omitted, will use maximum year
width a number specifying the width of the bin (factor) in days, or "mon" for Months (see mkfact for others)
var a character array of the names from x that are to be summed, such as c("rain","snow","precip"), if available
prime a single variable from var which is the prime variable of interest, such as "precip"; this is the variable used for comparison with a.cut and na.cut in the resulting active and na dimensions
a.cut cut-off value for the day to be considered an active or ‘wet day’ (based on the prime variable); a trace amount of 0.3 mm is suggested; if a.cut is NA or zero, the active variable and analysis will be ignored
na.cut cut-off fraction of missing values; can be single value or a vector for c(annual,seasonal); details given below
unit unit for seas.sum object; useful for future plotting
id unique station identifier used to extract a subset of data from dat
name provide a name for the seasonal sum object; otherwise generated from id (if available)

Details

This function is used to discretize and sum time-varying data in a data.frame for analysis in seasonal and annual parts. This is particularly useful for calculating normals of rates, such as precipitation and recharge. This function simply sums up each variable in each bin for each year, and provides the results in several arrays.

Sums are not normalized, and represent a sum for the number of days in the bin (seasonal data) or year (for annual data). Seasonal data can be normalized by the number of days (for a rate per day) or by the number of active days where prime > a.cut.

For annual sums, years with many missing values are ignored (receiving a value of NA) since it has insufficient data for a complete sum. The amount of allowable NA values is controlled by na.cut, which is a fraction of NA values for the whole year (default is 0.2).

The seasonal sums are calculated independently from the annual sums. Individual bins from each year with many missing values are ignored, where the amount of allowable NA values is controlled by na.cut (fraction of NAs in each bin of each individual year; default is 0.2).

Value

Returns a seas.sum object, which is a list with the following elements:

ann data.frame of annual data; the columns are:
year
year
active
the number of ‘active’ days in the year where the prime variable is above a.cut (if used)
days
number of days in the year
na
number of missing days in the year
1 or more variables
annual sum of each variable; if the original units were mm/day, they are now mm/year
seas array of seasonal data; the dimensions are:
[[1]]
years
[[2]]
bins, or seasonal factors generated by mkfact
[[3]]
sums of variables for each bin of each year; if the original unit was mm/day, it is now mm per number of days, which is held in the days item
active the number of ‘active’ days in the bin where the prime variable is above a.cut (if used)
days number of days in the bin; this array is useful for normalizing the numbers in seas to comparable units of mm/day
na number of missing days in each bin
call function call
years years (same as ann[[1]] and seas[[1]])
var variables which the sums represent (part of ann[[2]] and seas[[3]])
prime prime variable
unit unit of variable
width width argument passed to mkfact
bins
names of bins returned by mkfact (same as seas[[2]])
precip.only value used in argument (modified if insufficient data found in dat)
na.cut value used in argument
a.cut value used in argument; if it is zero or NA, this will be FALSE
id value used in argument; or found in dat$id if present and not given as argument
name either given by name argument or generated from id or from dat object name

Author(s)

M.W. Toews

See Also

image.seas.sum to view the result result, seas.norm to view a “normal”

Examples

loc <- Sys.getlocale()
on.exit(Sys.setlocale(locale=loc))
Sys.setlocale(loc="C")
data(mscstn)
data(mscdata)

dat.ss <- seas.sum(mscdata,id=1108447,width="mon")

# Annual data
dat.ss$ann

# Demonstrate how to slice through a cubic array
dat.ss$seas["1990",,]
dat.ss$seas[,"Feb",] # month names are locale specific
dat.ss$seas[,,"precip"]

# Simple calculation on an array
(monthly.mean <- apply(dat.ss$seas[,,"precip"],2,mean,na.rm=TRUE))
barplot(monthly.mean,ylab="Mean monthly total (mm/month)",
        main="Un-normalized mean precipitation in Vancouver, BC")
text(6.5,150,paste("Un-normalized rates given 'per month' should be",
        "avoided since ~3-9% error is introduced",
        "to the analysis between months",sep="\n"))

# Normalized precip
norm.monthly <- dat.ss$seas[,,"precip"]/dat.ss$days
norm.monthly.mean <- apply(norm.monthly,2,mean,na.rm=TRUE)
print(round(norm.monthly,2))
print(round(norm.monthly.mean,2))
barplot(norm.monthly.mean,ylab="Normalized mean monthly total (mm/day)",
        main="Normalized mean precipitation in Vancouver, BC")

# Better graphics of data
dat.ss <- seas.sum(mscdata,id=1108447)
image(dat.ss)

[Package seas version 0.2-1 Index]