CSIndicators (version 1.1.2)

CST_PeriodVariance: Period Variance on 's2dv_cube' objects

Description

Period Variance computes the average (var) of a given variable in a period. Two bioclimatic indicators can be obtained by using this function:

• 'BIO4', (Providing temperature data) Temperature Seasonality (Standard Deviation). The amount of temperature variation over a given year (or averaged years) based on the standard deviation (variation) of monthly temperature averages.

• 'BIO15', (Providing precipitation data) Precipitation Seasonality (CV). This is a measure of the variation in monthly precipitation totals over the course of the year. This index is the ratio of the standard deviation of the monthly total precipitation to the mean monthly total precipitation (also known as the coefficient of variation) and is expressed as a percentage.

Usage

CST_PeriodVariance(
  data,
  start = NULL,
  end = NULL,
  time_dim = "time",
  na.rm = FALSE,
  ncores = NULL
)

Value

An 's2dv_cube' object containing the indicator in the element data with dimensions of the input parameter 'data' except the dimension where the var has been computed (specified with 'time_dim'). A new element called 'time_bounds' will be added into the 'attrs' element in the 's2dv_cube' object. It consists of a list containing two elements, the start and end dates of the aggregated period with the same dimensions of 'Dates' element.

Arguments

data

An 's2dv_cube' object as provided function CST_Start or CST_Load in package CSTools.

start

An optional parameter to defined the initial date of the period to select from the data by providing a list of two elements: the initial date of the period and the initial month of the period. By default it is set to NULL and the indicator is computed using all the data provided in data.

end

An optional parameter to defined the final date of the period to select from the data by providing a list of two elements: the final day of the period and the final month of the period. By default it is set to NULL and the indicator is computed using all the data provided in data.

time_dim

A character string indicating the name of the dimension to compute the indicator. By default, it is set to 'time'. More than one dimension name matching the dimensions provided in the object data$data can be specified.

na.rm

A logical value indicating whether to ignore NA values (TRUE) or not (FALSE).

ncores

An integer indicating the number of cores to use in parallel computation.

Examples

exp <- NULL
exp$data <- array(rnorm(45), dim = c(member = 7, sdate = 4, time = 3))
Dates <- c(seq(as.Date("2000-11-01", "%Y-%m-%d", tz = "UTC"), 
              as.Date("2001-01-01", "%Y-%m-%d", tz = "UTC"), by = "month"),
          seq(as.Date("2001-11-01", "%Y-%m-%d", tz = "UTC"), 
              as.Date("2002-01-01", "%Y-%m-%d", tz = "UTC"), by = "month"),
          seq(as.Date("2002-11-01", "%Y-%m-%d", tz = "UTC"), 
              as.Date("2003-01-01", "%Y-%m-%d", tz = "UTC"), by = "month"),
          seq(as.Date("2003-11-01", "%Y-%m-%d", tz = "UTC"), 
              as.Date("2004-01-01", "%Y-%m-%d", tz = "UTC"), by = "month"))
dim(Dates) <- c(sdate = 4, time = 3)
exp$attrs$Dates <- Dates
class(exp) <- 's2dv_cube'

res <- CST_PeriodVariance(exp, start = list(01, 12), end = list(01, 01))