diff --git a/rdtools/analysis_chains.py b/rdtools/analysis_chains.py
index 24e8cb7f..159fd057 100644
--- a/rdtools/analysis_chains.py
+++ b/rdtools/analysis_chains.py
@@ -88,19 +88,19 @@ def __init__(self, pv, poa_global=None, temperature_cell=None, temperature_ambie
             pv = normalization.interpolate(pv, interp_freq, max_timedelta)
             if poa_global is not None:
                 poa_global = normalization.interpolate(
-                    poa_global, interp_freq, max_timedelta)
+                    poa_global, pv.index, max_timedelta)
             if temperature_cell is not None:
                 temperature_cell = normalization.interpolate(
-                    temperature_cell, interp_freq, max_timedelta)
+                    temperature_cell, pv.index, max_timedelta)
             if temperature_ambient is not None:
                 temperature_ambient = normalization.interpolate(
-                    temperature_ambient, interp_freq, max_timedelta)
+                    temperature_ambient, pv.index, max_timedelta)
             if power_expected is not None:
                 power_expected = normalization.interpolate(
-                    power_expected, interp_freq, max_timedelta)
+                    power_expected, pv.index, max_timedelta)
             if isinstance(windspeed, pd.Series):
                 windspeed = normalization.interpolate(
-                    windspeed, interp_freq, max_timedelta)
+                    windspeed, pv.index, max_timedelta)
 
         if pv_input == 'power':
             self.pv_power = pv
@@ -169,25 +169,24 @@ def set_clearsky(self, pvlib_location=None, pv_azimuth=None, pv_tilt=None,
             Pandas Time Series or single numeric value.
 
         '''
-        interp_freq = self.interp_freq
         max_timedelta = self.max_timedelta
 
-        if interp_freq is not None:
+        if self.interp_freq is not None:
             if poa_global_clearsky is not None:
                 poa_global_clearsky = normalization.interpolate(
-                    poa_global_clearsky, interp_freq, max_timedelta)
+                    poa_global_clearsky, self.pv_energy.index, max_timedelta)
             if temperature_cell_clearsky is not None:
                 temperature_cell_clearsky = normalization.interpolate(
-                    temperature_cell_clearsky, interp_freq, max_timedelta)
+                    temperature_cell_clearsky, self.pv_energy.index, max_timedelta)
             if temperature_ambient_clearsky is not None:
                 temperature_ambient_clearsky = normalization.interpolate(
-                    temperature_ambient_clearsky, interp_freq, max_timedelta)
+                    temperature_ambient_clearsky, self.pv_energy.index, max_timedelta)
             if isinstance(pv_azimuth, (pd.Series, pd.DataFrame)):
                 pv_azimuth = normalization.interpolate(
-                    pv_azimuth, interp_freq, max_timedelta)
+                    pv_azimuth, self.pv_energy.index, max_timedelta)
             if isinstance(pv_tilt, (pd.Series, pd.DataFrame)):
                 pv_tilt = normalization.interpolate(
-                    pv_tilt, interp_freq, max_timedelta)
+                    pv_tilt, self.pv_energy.index, max_timedelta)
 
         self.pvlib_location = pvlib_location
         self.pv_azimuth = pv_azimuth
diff --git a/rdtools/test/analysis_chains_test.py b/rdtools/test/analysis_chains_test.py
index 511613be..ad81bd38 100644
--- a/rdtools/test/analysis_chains_test.py
+++ b/rdtools/test/analysis_chains_test.py
@@ -78,6 +78,53 @@ def sensor_analysis_exp_power(sensor_parameters):
     return rd_analysis
 
 
+def test_interpolation(basic_parameters, degradation_trend):
+
+    power = degradation_trend
+    shifted_index = power.index + pd.to_timedelta('8 minutes')
+
+    dummy_series = power * 0 + 25
+    dummy_series.index = shifted_index
+
+    basic_parameters['pv'] = power
+    basic_parameters['poa_global'] = dummy_series
+    basic_parameters['temperature_ambient'] = dummy_series
+    basic_parameters['temperature_cell'] = dummy_series
+    basic_parameters['windspeed'] = dummy_series
+    basic_parameters['power_expected'] = dummy_series
+    basic_parameters['interp_freq'] = 'H'
+
+    rd_analysis = TrendAnalysis(**basic_parameters)
+
+    pd.testing.assert_index_equal(rd_analysis.pv_energy.index,
+                                  rd_analysis.poa_global.index[1:])
+    pd.testing.assert_index_equal(rd_analysis.pv_energy.index,
+                                  rd_analysis.temperature_ambient.index[1:])
+    pd.testing.assert_index_equal(rd_analysis.pv_energy.index,
+                                  rd_analysis.temperature_cell.index[1:])
+    pd.testing.assert_index_equal(rd_analysis.pv_energy.index,
+                                  rd_analysis.windspeed.index[1:])
+    pd.testing.assert_index_equal(rd_analysis.pv_energy.index,
+                                  rd_analysis.power_expected.index[1:])
+
+    rd_analysis.set_clearsky(pv_azimuth=dummy_series,
+                             pv_tilt=dummy_series,
+                             poa_global_clearsky=dummy_series,
+                             temperature_cell_clearsky=dummy_series,
+                             temperature_ambient_clearsky=dummy_series)
+
+    pd.testing.assert_index_equal(rd_analysis.pv_energy.index,
+                                  rd_analysis.pv_azimuth.index)
+    pd.testing.assert_index_equal(rd_analysis.pv_energy.index,
+                                  rd_analysis.pv_tilt.index)
+    pd.testing.assert_index_equal(rd_analysis.pv_energy.index,
+                                  rd_analysis.poa_global_clearsky.index)
+    pd.testing.assert_index_equal(rd_analysis.pv_energy.index,
+                                  rd_analysis.temperature_cell_clearsky.index)
+    pd.testing.assert_index_equal(rd_analysis.pv_energy.index,
+                                  rd_analysis.temperature_ambient_clearsky.index)
+
+
 def test_sensor_analysis(sensor_analysis):
     yoy_results = sensor_analysis.results['sensor']['yoy_degradation']
     rd = yoy_results['p50_rd']