CSIndicators (version 1.1.2)

CST_AbsToProbs: Transform ensemble forecast into probabilities

Description

The Cumulative Distribution Function of a forecast is used to obtain the probabilities of each value in the ensemble. If multiple initializations (start dates) are provided, the function will create the Cumulative Distribution Function excluding the corresponding initialization.

Usage

CST_AbsToProbs(
  data,
  start = NULL,
  end = NULL,
  time_dim = "time",
  memb_dim = "member",
  sdate_dim = "sdate",
  ncores = NULL
)

Value

An 's2dv_cube' object containing the probabilites in the element data.

Arguments

data

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

start

An optional parameter to define 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 define 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 temporal dimension. By default, it is set to 'time'. More than one dimension name matching the dimensions provided in the object data$data can be specified. This dimension is required to subset the data in a requested period.

memb_dim

A character string indicating the name of the dimension in which the ensemble members are stored.

sdate_dim

A character string indicating the name of the dimension in which the initialization dates are stored.

ncores

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

Examples

exp <- NULL
exp$data <- array(rnorm(216), dim = c(dataset = 1, member = 2, sdate = 3, 
                 time = 9, lat = 2, lon = 2))
class(exp) <- 's2dv_cube'
exp_probs <- CST_AbsToProbs(exp)
exp$data <- array(rnorm(5 * 3 * 214 * 2),
                 c(member = 5, sdate = 3, time = 214, lon = 2)) 
exp$attrs$Dates <- c(seq(as.Date("01-05-2000", format = "%d-%m-%Y"), 
                        as.Date("30-11-2000", format = "%d-%m-%Y"), by = 'day'),
                    seq(as.Date("01-05-2001", format = "%d-%m-%Y"), 
                        as.Date("30-11-2001", format = "%d-%m-%Y"), by = 'day'),
                    seq(as.Date("01-05-2002", format = "%d-%m-%Y"), 
                        as.Date("30-11-2002", format = "%d-%m-%Y"), by = 'day'))
dim(exp$attrs$Dates) <- c(time = 214, sdate = 3)
exp_probs <- CST_AbsToProbs(data = exp, start = list(21, 4), end = list(21, 6))