diff --git a/metsim/disaggregate.py b/metsim/disaggregate.py
index 78c891f..b1ea2f9 100644
--- a/metsim/disaggregate.py
+++ b/metsim/disaggregate.py
@@ -109,7 +109,7 @@ def disaggregate(df_daily: pd.DataFrame, params: dict,
     if 'wind' in df_daily:
         df_disagg['wind'] = wind(df_daily['wind'].values, ts, params)
 
-    return df_disagg.fillna(method='ffill')
+    return df_disagg.fillna(method='ffill').fillna(method='bfill')
 
 
 def set_min_max_hour(tiny_rad_fract: np.array, yday: np.array, n_days: int,
@@ -514,7 +514,7 @@ def vapor_pressure(vp_daily: np.array, temp: np.array, t_t_min: np.array,
     """
     # Linearly interpolate the values
     interp = scipy.interpolate.interp1d(t_t_min, vp_daily / cnst.MBAR_PER_BAR,
-                                        fill_value='extrapolate')
+                                        bounds_error=False)
     vp_disagg = interp(ts * np.arange(0, n_out))
 
     # Account for situations where vapor pressure is higher than
diff --git a/metsim/metsim.py b/metsim/metsim.py
index cbaed46..81ea718 100644
--- a/metsim/metsim.py
+++ b/metsim/metsim.py
@@ -582,7 +582,7 @@ def _validate_setup(self):
             errs.append("Output variable list must not be empty")
 
         # Check output variables are valid
-        daily_out_vars = ['t_min', 't_max', 'prec', 'vapor_pressure',
+        daily_out_vars = ['t_min', 't_max', 't_day', 'prec', 'vapor_pressure',
                           'shortwave', 'tskc', 'pet', 'wind']
         out_var_check = ['temp', 'prec', 'shortwave', 'vapor_pressure',
                          'air_pressure', 'rel_humid', 'spec_humid',
diff --git a/metsim/tests/test_metsim.py b/metsim/tests/test_metsim.py
index 68064e4..70dc80e 100755
--- a/metsim/tests/test_metsim.py
+++ b/metsim/tests/test_metsim.py
@@ -235,7 +235,7 @@ def test_disaggregation_values():
     # The location we will test against
     loc = (1, 4)
 
-    def check_data(out, good, tol=0.02):
+    def check_data(out, good, tol=0.03):
         assert isinstance(out, pd.DataFrame)
         for var in ms.params['out_vars']:
             # Check to make sure each variable has normalized
@@ -276,7 +276,7 @@ def check_data(out, good, tol=0.02):
     ds.close()
 
 
-@pytest.mark.parametrize('kind', ['ascii', 'bin', 'nc', 
+@pytest.mark.parametrize('kind', ['ascii', 'bin', 'nc',
                                   'constant_vars_ascii',
                                   'constant_vars_bin',
                                   'constant_vars_nc'])