diff --git a/R/CST_Calibration.R b/R/CST_Calibration.R
index b58dd08ede34093076d0e493006453ea3025fbca..2884712ac89a94ba3203b5102c92e3c61afa1e05 100644
--- a/R/CST_Calibration.R
+++ b/R/CST_Calibration.R
@@ -300,8 +300,8 @@ Calibration <- function(exp, obs, cal.method = "mse_min",
 	    #correct evaluation subset
       var.cor.fc[ , eval.dexes] <- .correct.crps.min.fc(fc.ev , mbm.par, na.rm = na.rm)
     } else if (cal.method == 'rpc-based') {
-      ens_mean.ev <- s2dv::MeanDims(data = fc.ev, dims = names(amt.mbr), na.rm = na.rm)
-      ens_mean.tr <- s2dv::MeanDims(data = fc.tr, dims = names(amt.mbr), na.rm = na.rm) ## Ensemble mean
+      ens_mean.ev <- multiApply::Apply(data = fc.ev, target_dims = names(amt.mbr), fun = mean, na.rm = na.rm)$output1 ## Ensemble mean
+      ens_mean.tr <- multiApply::Apply(data = fc.tr, target_dims = names(amt.mbr), fun = mean, na.rm = na.rm)$output1 ## Ensemble mean
       ens_spread.tr <- multiApply::Apply(data = list(fc.tr, ens_mean.tr), target_dims = names(amt.sdate), fun = "-")$output1 ## Ensemble spread
       exp_mean.tr <- mean(fc.tr, na.rm = na.rm) ## Mean (climatology)
       var_signal.tr <- var(ens_mean.tr, na.rm = na.rm) ## Ensemble mean variance