diff --git a/pvlib/clearsky.py b/pvlib/clearsky.py
index d29601038a..d54f57767b 100644
--- a/pvlib/clearsky.py
+++ b/pvlib/clearsky.py
@@ -558,7 +558,7 @@ def _calc_taud(w, aod700, p):
     # set up nan-tolerant masks
     aod700_lt_0p05 = np.full_like(aod700, False, dtype='bool')
     np.less(aod700, 0.05, where=~np.isnan(aod700), out=aod700_lt_0p05)
-    aod700_mask = np.array([aod700_lt_0p05, ~aod700_lt_0p05], dtype=np.int)
+    aod700_mask = np.array([aod700_lt_0p05, ~aod700_lt_0p05], dtype=int)
 
     # create tuples of coefficients for
     # aod700 < 0.05, aod700 >= 0.05
diff --git a/pvlib/tests/iotools/test_ecmwf_macc.py b/pvlib/tests/iotools/test_ecmwf_macc.py
index 4537d22203..b3387817ef 100644
--- a/pvlib/tests/iotools/test_ecmwf_macc.py
+++ b/pvlib/tests/iotools/test_ecmwf_macc.py
@@ -57,7 +57,7 @@ def test_read_ecmwf_macc(expected_test_data):
     expected_times = [
         1351738800, 1351749600, 1351760400, 1351771200, 1351782000, 1351792800,
         1351803600, 1351814400]
-    assert np.allclose(data.index.astype(int) // 1000000000, expected_times)
+    assert np.allclose(data.index.view(np.int64) // 1000000000, expected_times)
     expected_aod = np.array([
         0.39531226, 0.22371339, 0.18373083, 0.15010143, 0.130809, 0.11172834,
         0.09741255, 0.0921606])
diff --git a/pvlib/tests/iotools/test_tmy.py b/pvlib/tests/iotools/test_tmy.py
index d8c1c6efcb..7e4b76c294 100644
--- a/pvlib/tests/iotools/test_tmy.py
+++ b/pvlib/tests/iotools/test_tmy.py
@@ -67,7 +67,7 @@ def test_gh865_read_tmy3_feb_leapyear_hr24():
     assert all(data.index[:-1].year == 1990)
     assert data.index[-1].year == 1991
     # let's do a quick sanity check, are the indices monotonically increasing?
-    assert all(np.diff(data.index.astype(int)) == 3600000000000)
+    assert all(np.diff(data.index.view(np.int64)) == 3600000000000)
     # according to the TMY3 manual, each record corresponds to the previous
     # hour so check that the 1st hour is 1AM and the last hour is midnite
     assert data.index[0].hour == 1
diff --git a/pvlib/tests/test_modelchain.py b/pvlib/tests/test_modelchain.py
index b42acfa54e..17887dc693 100644
--- a/pvlib/tests/test_modelchain.py
+++ b/pvlib/tests/test_modelchain.py
@@ -717,7 +717,7 @@ def test_run_model_with_weather_noct_sam_temp(sapm_dc_snl_ac_system, location,
                                               weather, mocker):
     weather['wind_speed'] = 5
     weather['temp_air'] = 10
-    sapm_dc_snl_ac_system.temperature_model_parameters = {
+    sapm_dc_snl_ac_system.arrays[0].temperature_model_parameters = {
         'noct': 45, 'module_efficiency': 0.2
     }
     mc = ModelChain(sapm_dc_snl_ac_system, location)
diff --git a/pvlib/tests/test_solarposition.py b/pvlib/tests/test_solarposition.py
index 513a7f18d1..7578506561 100644
--- a/pvlib/tests/test_solarposition.py
+++ b/pvlib/tests/test_solarposition.py
@@ -204,21 +204,18 @@ def test_sun_rise_set_transit_ephem(expected_rise_set_ephem, golden):
     expected = pd.DataFrame(index=times,
                             columns=['sunrise', 'sunset'],
                             dtype='datetime64[ns]')
-    expected['sunrise'] = pd.Series(index=times, data=[
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 2), 'sunrise'],
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 3), 'sunrise'],
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 3), 'sunrise'],
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 3), 'sunrise']])
-    expected['sunset'] = pd.Series(index=times, data=[
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 2), 'sunset'],
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 2), 'sunset'],
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 2), 'sunset'],
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 3), 'sunset']])
-    expected['transit'] = pd.Series(index=times, data=[
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 2), 'transit'],
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 2), 'transit'],
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 3), 'transit'],
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 3), 'transit']])
+    idx_sunrise = pd.to_datetime(['2015-01-02', '2015-01-03', '2015-01-03',
+                                  '2015-01-03']).tz_localize('MST')
+    expected['sunrise'] = \
+        expected_rise_set_ephem.loc[idx_sunrise, 'sunrise'].tolist()
+    idx_sunset = pd.to_datetime(['2015-01-02', '2015-01-02', '2015-01-02',
+                                 '2015-01-03']).tz_localize('MST')
+    expected['sunset'] = \
+        expected_rise_set_ephem.loc[idx_sunset, 'sunset'].tolist()
+    idx_transit = pd.to_datetime(['2015-01-02', '2015-01-02', '2015-01-03',
+                                  '2015-01-03']).tz_localize('MST')
+    expected['transit'] = \
+        expected_rise_set_ephem.loc[idx_transit, 'transit'].tolist()
 
     result = solarposition.sun_rise_set_transit_ephem(times,
                                                       golden.latitude,
@@ -243,21 +240,18 @@ def test_sun_rise_set_transit_ephem(expected_rise_set_ephem, golden):
     expected = pd.DataFrame(index=times,
                             columns=['sunrise', 'sunset'],
                             dtype='datetime64[ns]')
-    expected['sunrise'] = pd.Series(index=times, data=[
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 1), 'sunrise'],
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 2), 'sunrise'],
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 2), 'sunrise'],
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 3), 'sunrise']])
-    expected['sunset'] = pd.Series(index=times, data=[
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 1), 'sunset'],
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 1), 'sunset'],
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 2), 'sunset'],
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 2), 'sunset']])
-    expected['transit'] = pd.Series(index=times, data=[
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 1), 'transit'],
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 1), 'transit'],
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 2), 'transit'],
-        expected_rise_set_ephem.loc[datetime.datetime(2015, 1, 3), 'transit']])
+    idx_sunrise = pd.to_datetime(['2015-01-01', '2015-01-02', '2015-01-02',
+                                  '2015-01-03']).tz_localize('MST')
+    expected['sunrise'] = \
+        expected_rise_set_ephem.loc[idx_sunrise, 'sunrise'].tolist()
+    idx_sunset = pd.to_datetime(['2015-01-01', '2015-01-01', '2015-01-02',
+                                 '2015-01-02']).tz_localize('MST')
+    expected['sunset'] = \
+        expected_rise_set_ephem.loc[idx_sunset, 'sunset'].tolist()
+    idx_transit = pd.to_datetime(['2015-01-01', '2015-01-01', '2015-01-02',
+                                  '2015-01-03']).tz_localize('MST')
+    expected['transit'] = \
+        expected_rise_set_ephem.loc[idx_transit, 'transit'].tolist()
 
     result = solarposition.sun_rise_set_transit_ephem(
         times,
diff --git a/pvlib/tests/test_spa.py b/pvlib/tests/test_spa.py
index ecd28a5123..0730f3403e 100644
--- a/pvlib/tests/test_spa.py
+++ b/pvlib/tests/test_spa.py
@@ -28,7 +28,7 @@
 
 times = (pd.date_range('2003-10-17 12:30:30', periods=1, freq='D')
            .tz_localize('MST'))
-unixtimes = np.array(times.tz_convert('UTC').astype(np.int64)*1.0/10**9)
+unixtimes = np.array(times.tz_convert('UTC').view(np.int64)*1.0/10**9)
 
 lat = 39.742476
 lon = -105.1786
@@ -266,15 +266,15 @@ def test_transit_sunrise_sunset(self):
         times = pd.DatetimeIndex([dt.datetime(1996, 7, 5, 0),
                                   dt.datetime(2004, 12, 4, 0)]
                                  ).tz_localize(
-                                     'UTC').astype(np.int64)*1.0/10**9
+                                     'UTC').view(np.int64)*1.0/10**9
         sunrise = pd.DatetimeIndex([dt.datetime(1996, 7, 5, 7, 8, 15),
                                     dt.datetime(2004, 12, 4, 4, 38, 57)]
                                    ).tz_localize(
-                                       'UTC').astype(np.int64)*1.0/10**9
+                                       'UTC').view(np.int64)*1.0/10**9
         sunset = pd.DatetimeIndex([dt.datetime(1996, 7, 5, 17, 1, 4),
                                    dt.datetime(2004, 12, 4, 19, 2, 2)]
                                   ).tz_localize(
-                                      'UTC').astype(np.int64)*1.0/10**9
+                                      'UTC').view(np.int64)*1.0/10**9
         times = np.array(times)
         sunrise = np.array(sunrise)
         sunset = np.array(sunset)
@@ -284,13 +284,13 @@ def test_transit_sunrise_sunset(self):
 
         times = pd.DatetimeIndex([dt.datetime(1994, 1, 2), ]
                                  ).tz_localize(
-                                     'UTC').astype(np.int64)*1.0/10**9
+                                     'UTC').view(np.int64)*1.0/10**9
         sunset = pd.DatetimeIndex([dt.datetime(1994, 1, 2, 16, 59, 55), ]
                                   ).tz_localize(
-                                      'UTC').astype(np.int64)*1.0/10**9
+                                      'UTC').view(np.int64)*1.0/10**9
         sunrise = pd.DatetimeIndex([dt.datetime(1994, 1, 2, 7, 8, 12), ]
                                    ).tz_localize(
-                                       'UTC').astype(np.int64)*1.0/10**9
+                                       'UTC').view(np.int64)*1.0/10**9
         times = np.array(times)
         sunrise = np.array(sunrise)
         sunset = np.array(sunset)
@@ -305,19 +305,19 @@ def test_transit_sunrise_sunset(self):
                                   dt.datetime(2015, 8, 2),
                                   dt.datetime(2015, 12, 2)],
                                  ).tz_localize(
-                                     'UTC').astype(np.int64)*1.0/10**9
+                                     'UTC').view(np.int64)*1.0/10**9
         sunrise = pd.DatetimeIndex([dt.datetime(2015, 1, 2, 7, 19),
                                     dt.datetime(2015, 4, 2, 5, 43),
                                     dt.datetime(2015, 8, 2, 5, 1),
                                     dt.datetime(2015, 12, 2, 7, 1)],
                                    ).tz_localize(
-                                       'MST').astype(np.int64)*1.0/10**9
+                                       'MST').view(np.int64)*1.0/10**9
         sunset = pd.DatetimeIndex([dt.datetime(2015, 1, 2, 16, 49),
                                    dt.datetime(2015, 4, 2, 18, 24),
                                    dt.datetime(2015, 8, 2, 19, 10),
                                    dt.datetime(2015, 12, 2, 16, 38)],
                                   ).tz_localize(
-                                      'MST').astype(np.int64)*1.0/10**9
+                                      'MST').view(np.int64)*1.0/10**9
         times = np.array(times)
         sunrise = np.array(sunrise)
         sunset = np.array(sunset)
@@ -331,18 +331,18 @@ def test_transit_sunrise_sunset(self):
                                   dt.datetime(2015, 8, 2),
                                   dt.datetime(2015, 12, 2)],
                                  ).tz_localize(
-                                     'UTC').astype(np.int64)*1.0/10**9
+                                     'UTC').view(np.int64)*1.0/10**9
         sunrise = pd.DatetimeIndex([dt.datetime(2015, 1, 2, 7, 36),
                                     dt.datetime(2015, 4, 2, 5, 58),
                                     dt.datetime(2015, 8, 2, 5, 13),
                                     dt.datetime(2015, 12, 2, 7, 17)],
-                                   ).tz_localize('Asia/Shanghai').astype(
+                                   ).tz_localize('Asia/Shanghai').view(
                                        np.int64)*1.0/10**9
         sunset = pd.DatetimeIndex([dt.datetime(2015, 1, 2, 17, 0),
                                    dt.datetime(2015, 4, 2, 18, 39),
                                    dt.datetime(2015, 8, 2, 19, 28),
                                    dt.datetime(2015, 12, 2, 16, 50)],
-                                  ).tz_localize('Asia/Shanghai').astype(
+                                  ).tz_localize('Asia/Shanghai').view(
                                       np.int64)*1.0/10**9
         times = np.array(times)
         sunrise = np.array(sunrise)
@@ -355,7 +355,7 @@ def test_transit_sunrise_sunset(self):
     def test_earthsun_distance(self):
         times = (pd.date_range('2003-10-17 12:30:30', periods=1, freq='D')
                    .tz_localize('MST'))
-        unixtimes = times.tz_convert('UTC').astype(np.int64)*1.0/10**9
+        unixtimes = times.tz_convert('UTC').view(np.int64)*1.0/10**9
         unixtimes = np.array(unixtimes)
         result = self.spa.earthsun_distance(unixtimes, 64.0, 1)
         assert_almost_equal(R, result, 6)
diff --git a/pvlib/tests/test_tracking.py b/pvlib/tests/test_tracking.py
index 7e51adc956..c88c92b248 100644
--- a/pvlib/tests/test_tracking.py
+++ b/pvlib/tests/test_tracking.py
@@ -7,7 +7,7 @@
 
 import pvlib
 from pvlib import tracking
-from .conftest import DATA_DIR, assert_frame_equal
+from .conftest import DATA_DIR, assert_frame_equal, assert_series_equal
 from pvlib._deprecation import pvlibDeprecationWarning
 
 SINGLEAXIS_COL_ORDER = ['tracker_theta', 'aoi',
@@ -462,21 +462,21 @@ def test_slope_aware_backtracking():
     """
     Test validation data set from https://www.nrel.gov/docs/fy20osti/76626.pdf
     """
-    expected_data = np.array(
-        [('2019-01-01T08:00-0500',  2.404287, 122.79177, -84.440, -10.899),
-         ('2019-01-01T09:00-0500', 11.263058, 133.288729, -72.604, -25.747),
-         ('2019-01-01T10:00-0500', 18.733558, 145.285552, -59.861, -59.861),
-         ('2019-01-01T11:00-0500', 24.109076, 158.939435, -45.578, -45.578),
-         ('2019-01-01T12:00-0500', 26.810735, 173.931802, -28.764, -28.764),
-         ('2019-01-01T13:00-0500', 26.482495, 189.371536, -8.475, -8.475),
-         ('2019-01-01T14:00-0500', 23.170447, 204.13681, 15.120, 15.120),
-         ('2019-01-01T15:00-0500', 17.296785, 217.446538, 39.562, 39.562),
-         ('2019-01-01T16:00-0500',  9.461862, 229.102218, 61.587, 32.339),
-         ('2019-01-01T17:00-0500',  0.524817, 239.330401, 79.530, 5.490)],
-        dtype=[
-            ('Time', '<M8[h]'), ('ApparentElevation', '<f8'),
-            ('SolarAzimuth', '<f8'), ('TrueTracking', '<f8'),
-            ('Backtracking', '<f8')])
+    index = pd.date_range('2019-01-01T08:00', '2019-01-01T17:00', freq='h')
+    index = index.tz_localize('Etc/GMT+5')
+    expected_data = pd.DataFrame(index=index, data=[
+        ( 2.404287, 122.79177, -84.440, -10.899),
+        (11.263058, 133.288729, -72.604, -25.747),
+        (18.733558, 145.285552, -59.861, -59.861),
+        (24.109076, 158.939435, -45.578, -45.578),
+        (26.810735, 173.931802, -28.764, -28.764),
+        (26.482495, 189.371536, -8.475, -8.475),
+        (23.170447, 204.13681, 15.120, 15.120),
+        (17.296785, 217.446538, 39.562, 39.562),
+        ( 9.461862, 229.102218, 61.587, 32.339),
+        ( 0.524817, 239.330401, 79.530, 5.490),
+    ], columns=['ApparentElevation', 'SolarAzimuth',
+                'TrueTracking', 'Backtracking'])
     expected_axis_tilt = 9.666
     expected_slope_angle = -2.576
     slope_azimuth, slope_tilt = 180.0, 10.0
@@ -492,16 +492,16 @@ def test_slope_aware_backtracking():
         90.0-expected_data['ApparentElevation'], expected_data['SolarAzimuth'],
         axis_tilt, axis_azimuth, max_angle=90.0, backtrack=True, gcr=0.5,
         cross_axis_tilt=cross_axis_tilt)
-    np.testing.assert_allclose(
-        sat['tracker_theta'], expected_data['Backtracking'],
-        rtol=1e-3, atol=1e-3)
+    assert_series_equal(sat['tracker_theta'],
+                        expected_data['Backtracking'].rename('tracker_theta'),
+                        check_less_precise=True)
     truetracking = tracking.singleaxis(
         90.0-expected_data['ApparentElevation'], expected_data['SolarAzimuth'],
         axis_tilt, axis_azimuth, max_angle=90.0, backtrack=False, gcr=0.5,
         cross_axis_tilt=cross_axis_tilt)
-    np.testing.assert_allclose(
-        truetracking['tracker_theta'], expected_data['TrueTracking'],
-        rtol=1e-3, atol=1e-3)
+    assert_series_equal(truetracking['tracker_theta'],
+                        expected_data['TrueTracking'].rename('tracker_theta'),
+                        check_less_precise=True)
 
 
 def test_singleaxis_aoi_gh1221():
diff --git a/setup.cfg b/setup.cfg
index 5074148f4f..17b6782a34 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -21,4 +21,21 @@ exclude = pvlib/_version.py docs dist
 
 [tool:pytest]
 junit_family=xunit2
-testpaths = pvlib/tests
\ No newline at end of file
+testpaths = pvlib/tests
+filterwarnings =
+    # warning messages to suppress from pytest output.  useful in cases
+    # where a dependency hasn't addressed a deprecation yet, and there's
+    # nothing we can do to fix it ourselves.
+    # syntax is: action:message:category:module:lineno
+    # `message` is a regex matching start of warning message
+    # https://docs.python.org/3/library/warnings.html#the-warnings-filter
+
+    ignore:Using or importing the ABCs:DeprecationWarning:.*patsy:
+
+    # deprecation warnings from numpy 1.20
+    ignore:`np.long` is a deprecated alias:DeprecationWarning:.*numba:
+    ignore:`np.int` is a deprecated alias:DeprecationWarning:.*(numba|scipy):
+    ignore:`np.bool` is a deprecated alias:DeprecationWarning:.*numba:
+    # warnings from netcdf4, but reported as coming from pvlib
+    ignore:`np.bool` is a deprecated alias:DeprecationWarning:.*(ecmwf_macc|forecast):
+    ignore:tostring\(\) is deprecated:DeprecationWarning:.*ecmwf_macc: