CPA {SeaVal}

Coefficients of Predictive Ability

Description

Function for calculating coefficients of predictive ability (CPAs) of ensemble mean forecasts stored in long data tables:#' Can also handle point forecasts. Warning: This metric always needs several years of data since the ranks on which it is based are calculated across multi-year samples.

Usage

CPA(
  dt,
  f,
  o = "obs",
  by = by_cols_ens_fc_score(dt),
  pool = "year",
  mem = "member",
  dim.check = TRUE
)

Arguments

dt

Data table containing the predictions.

f

column name of the prediction.

o

column name of the observations.

by

column names of grouping variables, all of which need to be columns in dt. A separate CPA is computed for each value of the grouping variables. Default is to group by all instances of month, season, lon, lat, system and lead_time that are columns in dt.

pool

column name(s) for the variable(s) along which is averaged. Needs to contain 'year' per warning above.

mem

Number of column containing the number of the ensemble member.

dim.check

Logical. If True, a simple test whether the dimensions match up is conducted: The data table should only have one row for each level of c(by,pool,mem)

Value

A data table with the scores

Examples

dt = data.table(fc = 1:4,obs = c(4,4,7,7),member = c(1,2,1,2),year = c(1999,1999,2000,2000))
CPA(dt,f = 'fc')