R: Ensemble Mean Error Skill scores

EnsErrorss {easyVerification} | R Documentation

## Ensemble Mean Error Skill scores

### Description

Computes various ensemble mean error skill scores. `EnsMaess` computes the mean absolute error, `EnsMsess` the mean squared error, and `EnsRmsess` the square root of the mean squared error.

### Usage

    EnsErrorss(ens, ens.ref, obs, type)

    EnsMaess(ens, ens.ref, obs)

    EnsMsess(ens, ens.ref, obs)

    EnsRmsess(ens, ens.ref, obs)

### Arguments

`ens` | n x k matrix of n forecasts from k ensemble members
`ens.ref` | n x l matrix of m reference forecasts from l ensemble members
`obs` | n verifying observations
`type` | specifying what error metric to compute, one of [me, mae, mse, rmse]

### See Also

`veriApply`, `EnsError`

### Examples

    tm <- toymodel()

    ## compute RMSE skill score against reference forecast with a bias of +2
    EnsErrorss(ens=tm$fcst, ens.ref=tm$fcst + 2, obs=tm$obs, type='rmse')

    ## compute skill score using veriApply
    veriApply("EnsRmsess", fcst=tm$fcst, obs=tm$obs, fcst.ref=tm$fcst + 2)

[Package easyVerification version 0.4.4 Index]