Per #1673, update references based on Eric's feedback.

met/docs/Users_Guide/appendixC.rst

@@ -1107,7 +1107,7 @@ A mathematical metric, :math:`m(A,B)\geq 0`, must have the following three prope
 
 The first establishes that a perfect score is zero and that the only way to obtain a perfect score is if the two sets are identical according to the metric. The second requirement ensures that the order by which the two sets are evaluated will not change the result. The third property ensures that if *C* is closer to *A* than *B* is to *A*, then :math:`m(A,C) < m(A,B)`.
 
-It has been argued in :ref:`Gilleland, Part II (2020) <Gilleland_PartII-2020>` that the second property of symmetry is not necessarily an important quality to have for a summary measure for verification purposes because lack of symmetry allows for information about false alarms and misses.
+It has been argued in :ref:`Gilleland (2017) <Gilleland-2017>` that the second property of symmetry is not necessarily an important quality to have for a summary measure for verification purposes because lack of symmetry allows for information about false alarms and misses.
 
 The results of the distance map verification approaches that are included in the Grid-Stat tool are summarized using a variety of measures. These measures include Baddeley's :math:`\Delta` Metric, the Hausdorff Distance, the Mean-error Distance, Pratt's Figure of Merit, and Zhu's Measure. Their equations are listed below.
 

met/docs/Users_Guide/refs.rst

@@ -116,6 +116,15 @@ References
 
 | Gilleland, E., 2010: Confidence intervals for forecast verification.
 |   *NCAR Technical Note* NCAR/TN-479+STR, 71pp.
+|
+
+.. _Gilleland-2017:
+
+| Gilleland, E., 2017. A new characterization in the spatial verification
+|   framework for false alarms, misses, and overall patterns.
+|   Weather Forecast., 32 (1), 187 - 198, doi: 10.1175/WAF-D-16-0134.1.
+|
+
 
 .. _Gilleland_PartI-2020: