CRPS | R Documentation |

The Continuous Ranked Probability Score (CRPS; Wilks, 2011) is the continuous version of the Ranked Probability Score (RPS; Wilks, 2011). It is a skill metric to evaluate the full distribution of probabilistic forecasts. It has a negative orientation (i.e., the higher-quality forecast the smaller CRPS) and it rewards the forecast that has probability concentration around the observed value. In case of a deterministic forecast, the CRPS is reduced to the mean absolute error. It has the same units as the data. The function is based on enscrps_cpp from SpecsVerification. If there is more than one dataset, CRPS will be computed for each pair of exp and obs data.

```
CRPS(
exp,
obs,
time_dim = "sdate",
memb_dim = "member",
dat_dim = NULL,
Fair = FALSE,
ncores = NULL
)
```

`exp` |
A named numerical array of the forecast with at least time dimension. |

`obs` |
A named numerical array of the observation with at least time dimension. The dimensions must be the same as 'exp' except 'memb_dim' and 'dat_dim'. |

`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. The default value is 'member'. |

`dat_dim` |
A character string indicating the name of dataset dimension. The length of this dimension can be different between 'exp' and 'obs'. The default value is NULL. |

`Fair` |
A logical indicating whether to compute the FairCRPS (the potential CRPS that the forecast would have with an infinite ensemble size). The default value is FALSE. |

`ncores` |
An integer indicating the number of cores to use for parallel computation. The default value is NULL. |

A numerical array of CRPS with dimensions c(nexp, nobs, the rest dimensions of 'exp' except 'time_dim' and 'memb_dim' dimensions). nexp is the number of experiment (i.e., dat_dim in exp), and nobs is the number of observation (i.e., dat_dim in obs). If dat_dim is NULL, nexp and nobs are omitted.

Wilks, 2011; https://doi.org/10.1016/B978-0-12-385022-5.00008-7

```
exp <- array(rnorm(1000), dim = c(lat = 3, lon = 2, member = 10, sdate = 50))
obs <- array(rnorm(1000), dim = c(lat = 3, lon = 2, sdate = 50))
res <- CRPS(exp = exp, obs = obs)
```

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