s2dverification (version 2.4.0)

RatioSDRMS: Computes The Ratio Between the Ensemble Spread and the RMSE of the Ensemble Mean

Description

Matrices var_exp & var_obs should have dimensions between c(nmod/nexp, nmemb/nparam, nsdates, nltime) and c(nmod/nexp, nmemb/nparam, nsdates, nltime, nlevel, nlat, nlon) The ratio between the standard deviation of the members around the ensemble mean in var_exp and the RMSE between var_exp and var_obs is output for each experiment and each observational dataset. The p-value is provided by a one-sided Fischer test.

Usage

RatioSDRMS(var_exp, var_obs)

Value

Matrix with dimensions c(nexp/nmod, nobs, 2, nltime) up to c(nexp/nmod, nobs, 2, nltime, nlevel, nlat, nlon) dimensions. The dimension 2 corresponds to the ratio (SD/RMSE) and the p.value of the one-sided Fisher test with Ho: SD/RMSE = 1.

Examples

# Load sample data as in Load() example:
example(Load)
rsdrms <- RatioSDRMS(sampleData$mod, sampleData$obs)
rsdrms2 <- array(dim = c(dim(rsdrms)[1:2], 4, dim(rsdrms)[4]))
rsdrms2[, , 2, ] <- rsdrms[, , 1, ]
rsdrms2[, , 4, ] <- rsdrms[, , 2, ]
PlotVsLTime(rsdrms2, toptitle = "Ratio ensemble spread / RMSE", ytitle = "", 
            monini = 11, limits = c(-1, 1.3), listexp = c('CMIP5 IC3'), 
            listobs = c('ERSST'), biglab = FALSE, siglev = TRUE, 
            fileout = 'tos_rsdrms.eps')