GetProbs: Compute probabilistic forecasts or the corresponding...

In s2dv: A Set of Common Tools for Seasonal to Decadal Verification

Compute probabilistic forecasts or the corresponding observations

Description

Compute probabilistic forecasts from an ensemble based on the relative thresholds, or the probabilistic observations (i.e., which probabilistic category was observed). A reference period can be specified to calculate the absolute thresholds between each probabilistic category. The absolute thresholds can be computed in cross-validation mode. If data is an ensemble, the probabilities are calculated as the percentage of members that fall into each category. For observations (or forecast without member dimension), 1 means that the event happened, while 0 indicates that the event did not happen. Weighted probabilities can be computed if the weights are provided for each ensemble member and time step. The absolute thresholds can also be provided directly for probabilities calculation.

Usage

GetProbs(
  data,
  time_dim = "sdate",
  memb_dim = "member",
  indices_for_quantiles = NULL,
  prob_thresholds = c(1/3, 2/3),
  abs_thresholds = NULL,
  bin_dim_abs = "bin",
  weights = NULL,
  cross.val = FALSE,
  ncores = NULL
)

Arguments

data	A named numerical array of the forecasts or observations with, at least, time dimension.
time_dim	A character string indicating the name of the time dimension. The default value is 'sdate'.
memb_dim	A character string indicating the name of the member dimension to compute the probabilities of the forecast, or NULL if there is no member dimension (e.g., for observations, or for forecast with only one ensemble member). The default value is 'member'.
indices_for_quantiles	A vector of the indices to be taken along 'time_dim' for computing the absolute thresholds between the probabilistic categories. If NULL (default), the whole period is used. It is only used when 'prob_thresholds' is provided.
prob_thresholds	A numeric vector of the relative thresholds (from 0 to 1) between the categories. The default value is c(1/3, 2/3), which corresponds to tercile equiprobable categories.
abs_thresholds	A numeric array or vector of the absolute thresholds in the same units as data. If an array is provided, it should have at least 'bin_dim_abs' dimension. If it has more dimensions (e.g. different thresholds for different locations, i.e. lon and lat dimensions), they should match the dimensions of data, except the member dimension which should not be included. The default value is NULL and, in this case, 'prob_thresholds' is used for calculating the probabilities.
bin_dim_abs	A character string of the dimension name of 'abs_thresholds' array in which category limits are stored. It will also be the probabilistic category dimension name in the output. The default value is 'bin'.
weights	A named numerical array of the weights for 'data' with dimensions 'time_dim' and 'memb_dim' (if 'data' has them). The default value is NULL. The ensemble should have at least 70 members or span at least 10 time steps and have more than 45 members if consistency between the weighted and unweighted methodologies is desired.
cross.val	A logical indicating whether to compute the thresholds between probabilistic categories in cross-validation mode. The default value is FALSE.
ncores	An integer indicating the number of cores to use for parallel computation. The default value is NULL.

Value

A numerical array of probabilities with dimensions c(bin_dim_abs, the rest dimensions of 'data' except 'memb_dim'). 'bin' dimension has the length of probabilistic categories, i.e., length(prob_thresholds) + 1.

Examples

data <- array(rnorm(2000), dim = c(ensemble = 25, sdate = 20, time = 4))
res <- GetProbs(data = data, time_dim = 'sdate', memb_dim = 'ensemble', 
               indices_for_quantiles = 4:17)

# abs_thresholds is provided
abs_thr1 <- c(-0.2, 0.3)
abs_thr2 <- array(c(-0.2, 0.3) + rnorm(40) * 0.1, dim = c(cat = 2, sdate = 20))
res1 <- GetProbs(data = data, time_dim = 'sdate', memb_dim = 'ensemble',
                prob_thresholds = NULL, abs_thresholds = abs_thr1)
res2 <- GetProbs(data = data, time_dim = 'sdate', memb_dim = 'ensemble',
                prob_thresholds = NULL, abs_thresholds = abs_thr2, bin_dim_abs = 'cat')

s2dv documentation built on Oct. 13, 2024, 9:07 a.m.