fix pandas-dev#59772: tz_aware series with NaT raises exception on to_numpy

Author: tomasmacieira

Diff for: pandas/core/arrays/base.py

@@ -592,7 +592,17 @@ def to_numpy(
         -------
         numpy.ndarray
         """
-        result = np.asarray(self, dtype=dtype)
+        if dtype == "datetime64" and self.dtype.kind == "M":
+            # Make sure NaT is not tz_aware
+            result = np.array(
+                [
+                    np.datetime64("NaT", "s") if isna(x) else x.tz_localize(None).asm8
+                    for x in self
+                ],
+                dtype="datetime64[s]",
+            )
+        else:
+            result = np.asarray(self, dtype=dtype)
         if copy or na_value is not lib.no_default:
             result = result.copy()
         if na_value is not lib.no_default:

Diff for: pandas/tests/arrays/test_datetimelike.py

@@ -1356,3 +1356,11 @@ def test_from_pandas_array(dtype):
     result = idx_cls(arr)
     expected = idx_cls(data)
     tm.assert_index_equal(result, expected)
+
+
+def test_to_numpy_with_NaT_tz_aware():
+    # GH#59772
+
+    result = pd.Series(NaT).dt.tz_localize("UTC").to_numpy("datetime64")
+    expected = pd.Series(NaT).to_numpy("datetime64")
+    tm.assert_equal(result, expected)