Index: /issm/trunk-jpl/src/m/io/loadvars.py
===================================================================
--- /issm/trunk-jpl/src/m/io/loadvars.py	(revision 26128)
+++ /issm/trunk-jpl/src/m/io/loadvars.py	(revision 26129)
@@ -30,5 +30,5 @@
     filename = ''
     nvdict = {}
-    debug = False  #print messages if true
+    debug = True  #print messages if true
 
     if len(args) >= 1 and isinstance(args[0], str):
@@ -174,9 +174,9 @@
             for groupindex, listclass in enumerate(groupclass):
                 for var in listclass.variables:
-                    if debug:
-                        print("    ==> treating var {}".format(var))
                     if var not in ['errlog', 'outlog']:
                         varval = listclass.variables[str(var)]
                         vardim = varval.ndim
+                        if debug:
+                            print("    ==> treating var {} of dimension {}".format(var, vardim))
                         #There is a special treatment for results to account for its specific structure
                         #that is the new export version where time is a named dimension
@@ -263,4 +263,13 @@
                                         strings2 = [str(arg[1]) for arg in varval]
                                         Tree.__dict__[str(var)] = OrderedDict(list(zip(strings1, strings2)))
+                                else:
+                                    if type(Tree) == list:
+                                        t = indexlist[i]
+                                        if listtype == 'dict':
+                                            Tree[t][str(var)] = varval[:, :].data
+                                        else:
+                                            Tree[t].__dict__[str(var)] = varval[:, :].data
+                                    else:
+                                        Tree.__dict__[str(var)] = varval[:, :].data
                             elif vardim == 3:
                                 Tree.__dict__[str(var)] = varval[:, :, :].data