diff --git a/dartwrf/obsseq.py b/dartwrf/obsseq.py
index 5a06a7ceea4505d5bbc1ee670e787a0251535e40..adb1ca69567ba96089b8bf0d69197818c905f434 100755
--- a/dartwrf/obsseq.py
+++ b/dartwrf/obsseq.py
@@ -226,20 +226,29 @@ class ObsSeq(object):
         list_of_obsdict = obs_list_to_dict(obs_list)
         return list_of_obsdict
 
-    def get_prior_Hx_matrix(self):
-        """Return prior Hx array (n_obs, n_ens)"""
+    def _get_model_Hx(self, what):
+        if what not in  ['prior', 'posterior']:
+            raise ValueError
 
         # which columns do we need?
         keys = self.df.columns
-        keys_bool = np.array(['prior ensemble member' in a for a in keys])
+        keys_bool = np.array([what+' ensemble member' in a for a in keys])
 
         # select columns in DataFrame
-        prior_Hx = self.df.iloc[:, keys_bool]
+        Hx = self.df.iloc[:, keys_bool]
 
         # consistency check: compute mean over ens - compare with value from file
-        assert np.allclose(prior_Hx.mean(axis=1), self.df['prior ensemble mean'])
+        assert np.allclose(Hx.mean(axis=1), self.df[what+' ensemble mean'])
+
+        return Hx.values
 
-        return prior_Hx.values
+    def get_prior_Hx(self):
+        """Return prior Hx array (n_obs, n_ens)"""
+        return self._get_model_Hx('prior')
+
+    def get_posterior_Hx(self):
+        """Return posterior Hx array (n_obs, n_ens)"""
+        return self._get_model_Hx('posterior')
 
     def get_truth_Hx(self):
         return self.df['truth'].values
@@ -416,6 +425,7 @@ class ObsSeq(object):
 
         def write_obs(i, obs, next_i_obs=None, prev_i_obs=None):
             """Write the observation section of a obs_seq.out file
+
             Args:
                 i   (int):      index of observation
                 obs (dict):     observation data