diff --git a/inst/doc/usecase/ex1_12_rotated_coordinates.R b/inst/doc/usecase/ex1_12_rotated_coordinates.R
index f657a70418aead4f1bc7770e430f4a887f37b03a..5c24c502523a3908b152a54d9266f0feec2ba50a 100644
--- a/inst/doc/usecase/ex1_12_rotated_coordinates.R
+++ b/inst/doc/usecase/ex1_12_rotated_coordinates.R
@@ -11,31 +11,29 @@ date <- c('20131229', '20131230')
 # two temporal dimensions: one for days and another four hours
 data_split <- Start(dataset = path,
               var = 'od550du',
-              lev = 'all',
               date = date,
               time = 'all',
               rlat = 'all',
               rlon = 'all',
-              return_vars = list(lev = NULL, time = NULL,
+              return_vars = list(time = NULL,
                                  rlat = NULL, rlon = NULL,
                                  lat = NULL, lon = NULL),
               retrieve = TRUE, num_procs = 1)
 # one temporal dimension
 data <- Start(dataset = path,
               var = 'od550du',
-              lev = 'all',
               date = date,
               time = 'all',
               rlat = 'all',
               rlon = 'all',
               time_across = 'date',
               merge_across_dims = TRUE,
-              return_vars = list(lev = NULL, time = 'date',
+              return_vars = list(time = 'date',
                                  rlat = NULL, rlon = NULL,
                                  lat = NULL, lon = NULL),
               retrieve = TRUE, num_procs = 1)
 # check both are consistent:
-all(data[1,1,1,1:8,,]==data_split[1,1,1,1,,,])
+all(data[1,1,1:8,,]==data_split[1,1,1,,,])
 
 # Save important information from attributes
 lat <- attributes(data)$Variables$common$lat
@@ -43,12 +41,11 @@ lon <- attributes(data)$Variables$common$lon
 rlat <- attributes(data)$Variables$common$rlat
 rlon <- attributes(data)$Variables$common$rlon
 # Or check information:
-attributes(data)$Variables$common$lev
 attributes(data)$Variables$common$time
 
 
 # PLOT:
-map <- data[1,1,1,1,,] # Time-step 1
+map <- data[1,1,1,,] # Time-step 1
 library(sf)
 library(ggplot2)
 map <- data.frame(rlat = rep(rlat, length(rlon)),