diff --git a/numtraits.py b/numtraits.py
index 45d059f..b6d416d 100644
--- a/numtraits.py
+++ b/numtraits.py
@@ -25,7 +25,9 @@
 
 from __future__ import print_function
 
-from traitlets import TraitType, TraitError
+import warnings
+
+from traitlets import TraitType, TraitError, Undefined
 
 import numpy as np
 
@@ -38,16 +40,18 @@
 class NumericalTrait(TraitType):
     info_text = 'a numerical trait, either a scalar or a vector'
     def __init__(self, ndim=None, shape=None, domain=None,
-                 default=None, convertible_to=None):
-        super(NumericalTrait, self).__init__()
+                 default_value=Undefined, convertible_to=None, default=Undefined):
+        if default is not Undefined:
+            if default_value is not Undefined:
+                raise TypeError('Cannot set default and default_value simultaneously')
+            warnings.warn(DeprecationWarning('`default` has been renamed to `default_value`'))
+            default_value = default
+        super(NumericalTrait, self).__init__(default_value=default_value)
 
         # Just store all the construction arguments.
         self.ndim = ndim
         self.shape = shape
         self.domain = domain
-        # TODO: traitlets supports a `default` argument in __init__(), we should
-        # probably link them together once we start using this.
-        self.default = default
         self.target_unit = convertible_to
 
         if self.target_unit is not None:
@@ -97,7 +101,7 @@ def validate(self, obj, value):
         if self.ndim is not None:
 
             if self.ndim == 0:
-                if not is_scalar:
+                if not is_scalar and num_value.ndim:
                     raise TraitError("{0} should be a scalar value".format(self.name))
 
             if self.ndim > 0:
diff --git a/test_numtraits.py b/test_numtraits.py
index 5cd9ff7..c4af70f 100644
--- a/test_numtraits.py
+++ b/test_numtraits.py
@@ -13,6 +13,7 @@ class ScalarProperties(HasTraits):
     d = NumericalTrait(ndim=0, domain='negative')
     e = NumericalTrait(ndim=0, domain='strictly-negative')
     f = NumericalTrait(ndim=0, domain=(3, 4))
+    g = NumericalTrait(ndim=0, default_value=2)
 
 class TestScalar(object):
 
@@ -79,6 +80,14 @@ def test_range(self):
             self.sp.f = 7
         assert exc.value.args[0] == "f should be in the range [3:4]"
 
+    def test_scalar_quantities(self):
+        """ Tests for issue #14.
+        """
+        quantities = pytest.importorskip("quantities")
+        self.sp.a = 1*quantities.m
+
+    def test_default_value(self):
+        assert self.sp.g == 2
 
 class ArrayProperties(HasTraits):
 
@@ -90,6 +99,7 @@ class ArrayProperties(HasTraits):
     f = NumericalTrait(domain=(3, 4), ndim=1)
     g = NumericalTrait(shape=(3, 4))
 
+
 class TestArray(object):
 
     def setup_method(self, method):