diff --git a/openet/ptjpl/image.py b/openet/ptjpl/image.py
index 977e0de..90c3ba2 100644
--- a/openet/ptjpl/image.py
+++ b/openet/ptjpl/image.py
@@ -909,12 +909,12 @@ def from_image_id(cls, image_id, **kwargs):
 
     @classmethod
     def from_landsat_c2_sr(cls, sr_image, cloudmask_args={}, **kwargs):
-        """Returns a PT-JPL Image instance from a Landsat Collection 2 SR image
+        """Returns a PT-JPL Image instance from a Landsat C02 level 2 (SR) image
 
         Parameters
         ----------
-        sr_image : ee.Image
-            A raw Landsat Collection 2 SR image.
+        sr_image : ee.Image, str
+            A raw Landsat Collection 2 level 2 (SR) image or image ID.
         cloudmask_args : dict
             keyword arguments to pass through to cloud mask function
         kwargs : dict
@@ -964,7 +964,9 @@ def from_landsat_c2_sr(cls, sr_image, cloudmask_args={}, **kwargs):
         if 'cloud_score_flag' not in cloudmask_args.keys():
             cloudmask_args['cloud_score_flag'] = True
         if 'cloud_score_pct' not in cloudmask_args.keys():
-            cloudmask_args['cloud_score_pct'] = True
+            cloudmask_args['cloud_score_pct'] = 100
+        if 'filter_flag' not in cloudmask_args.keys():
+            cloudmask_args['filter_flag'] = False
         # QA_RADSAT band will need to be added above if applying saturated masking
         # if 'saturated_flag' not in cloudmask_args.keys():
         #     cloudmask_args['saturated_flag'] = False
@@ -1011,7 +1013,6 @@ def from_landsat_c2_sr(cls, sr_image, cloudmask_args={}, **kwargs):
         # Instantiate the class
         return cls(input_image, **kwargs)
 
-    # CGM - Copied from _crop_type() in the SIMS model.py
     @lazy_property
     def crop_type(self):
         """Crop type
@@ -1038,6 +1039,10 @@ def crop_type(self):
         ------
         ValueError for unsupported crop_type_sources
 
+        Notes
+        -----
+        Copied from _crop_type() in the OpenET SIMS model.py
+
         """
         properties = ee.Dictionary()
 
@@ -1072,7 +1077,8 @@ def crop_type(self):
             crop_type_img = ee.Image(self.crop_type_source).select(['cropland'])
             properties = properties.set('id', crop_type_img.get('system:id'))
         elif (type(self.crop_type_source) is str and
-                'projects/openet/crop_type' in self.crop_type_source.lower()):
+              (('projects/openet/crop_type' in self.crop_type_source.lower()) or
+               ('projects/openet/assets/crop_type' in self.crop_type_source.lower()))):
             # Use the crop_type image closest to the image date
             crop_coll = ee.ImageCollection(self.crop_type_source)
             cdl_year = (
diff --git a/openet/ptjpl/interpolate.py b/openet/ptjpl/interpolate.py
index 11ad046..9e03247 100644
--- a/openet/ptjpl/interpolate.py
+++ b/openet/ptjpl/interpolate.py
@@ -143,14 +143,18 @@ def from_scene_et_fraction(
     if type(et_reference_source) is str:
         # Assume a string source is an single image collection ID
         #   not an list of collection IDs or ee.ImageCollection
-        daily_et_ref_coll = ee.ImageCollection(et_reference_source) \
-            .filterDate(start_date, end_date) \
+        daily_et_ref_coll = (
+            ee.ImageCollection(et_reference_source)
+            .filterDate(start_date, end_date)
             .select([et_reference_band], ['et_reference'])
+        )
     # elif isinstance(et_reference_source, computedobject.ComputedObject):
     #     # Interpret computed objects as image collections
-    #     daily_et_reference_coll = et_reference_source \
-    #         .filterDate(self.start_date, self.end_date) \
+    #     daily_et_reference_coll = (
+    #         et_reference_source
+    #         .filterDate(self.start_date, self.end_date)
     #         .select([et_reference_band])
+    #     )
     else:
         raise ValueError(f'unsupported et_reference_source: {et_reference_source}')
 
@@ -212,7 +216,8 @@ def interpolate_prep(img):
     if 'count' in variables:
         aggregate_coll = openet.core.interpolate.aggregate_to_daily(
             image_coll=scene_coll.select(['mask']),
-            start_date=start_date, end_date=end_date)
+            start_date=start_date, end_date=end_date,
+        )
         # The following is needed because the aggregate collection can be
         #   empty if there are no scenes in the target date range but there
         #   are scenes in the interpolation date range.
@@ -232,7 +237,7 @@ def interpolate_prep(img):
         interp_method=interp_method,
         interp_days=interp_days,
         use_joins=use_joins,
-        compute_product=False
+        compute_product=False,
     )
 
     # Compute ET from ETf and ETr (if necessary)
@@ -506,8 +511,8 @@ def from_scene_et_actual(
         #     logging.debug('et_reference_resample was not set, default to nearest')
         #     # raise ValueError('et_reference_resample was not set')
 
-        # Assume a string source is an single image collection ID
-        #   not an list of collection IDs or ee.ImageCollection
+        # Assume a string source is a single image collection ID
+        #   not a list of collection IDs or ee.ImageCollection
         daily_et_ref_coll_id = model_args['et_reference_source']
         daily_et_ref_coll = (
             ee.ImageCollection(daily_et_ref_coll_id)
diff --git a/openet/ptjpl/tests/test_a_utils.py b/openet/ptjpl/tests/test_a_utils.py
index 8babc6b..6533630 100644
--- a/openet/ptjpl/tests/test_a_utils.py
+++ b/openet/ptjpl/tests/test_a_utils.py
@@ -47,7 +47,7 @@ def test_point_coll_value(image_id, image_date, xy, scale, expected, tol):
 
 def test_c_to_k(c=20, k=293.15, tol=0.000001):
     output = utils.constant_image_value(utils.c_to_k(ee.Image.constant(c)))
-    assert abs(output - k) <= tol
+    assert abs(output['constant'] - k) <= tol
 
 
 @pytest.mark.parametrize(
diff --git a/openet/ptjpl/tests/test_b_daily_integration.py b/openet/ptjpl/tests/test_b_daily_integration.py
index 325fb76..0ca2cb8 100644
--- a/openet/ptjpl/tests/test_b_daily_integration.py
+++ b/openet/ptjpl/tests/test_b_daily_integration.py
@@ -40,7 +40,7 @@ def test_day_angle_rad_from_doy_image(rn, hour_of_day, sunrise_hour,
         sunrise_hour=ee.Image.constant(sunrise_hour),
         daylight_hours=ee.Image.constant(daylight_hours),
     ))
-    assert abs(output - expected) <= tol
+    assert abs(output['constant'] - expected) <= tol
 
 
 @pytest.mark.parametrize(
diff --git a/openet/ptjpl/tests/test_b_daylight_hours.py b/openet/ptjpl/tests/test_b_daylight_hours.py
index e44497f..64e5510 100644
--- a/openet/ptjpl/tests/test_b_daylight_hours.py
+++ b/openet/ptjpl/tests/test_b_daylight_hours.py
@@ -38,7 +38,7 @@ def test_sha_deg_from_doy_lat(doy, latitude, expected, tol=0.000001):
         ee.Number(doy), ee.Image.constant(latitude)
     ))
     # output = utils.getinfo(dh.sha_deg_from_doy_lat(ee.Number(doy), ee.Number(latitude)))
-    assert abs(output - expected) <= tol
+    assert abs(output['constant'] - expected) <= tol
 
 
 @pytest.mark.parametrize(
diff --git a/openet/ptjpl/tests/test_b_landsat.py b/openet/ptjpl/tests/test_b_landsat.py
index 3360290..3574333 100644
--- a/openet/ptjpl/tests/test_b_landsat.py
+++ b/openet/ptjpl/tests/test_b_landsat.py
@@ -32,6 +32,11 @@ def sr_image(blue=0.2, green=0.2, red=0.2, nir=0.7, swir1=0.2, swir2=0.2, bt=300
 
 # Test the static methods of the class first
 # Do these need to be inside the TestClass?
+def test_Image_ndvi_band_name():
+    output = landsat.ndvi(sr_image()).getInfo()['bands'][0]['id']
+    assert output == 'ndvi'
+
+
 @pytest.mark.parametrize(
     'red, nir, expected',
     [
@@ -49,22 +54,22 @@ def sr_image(blue=0.2, green=0.2, red=0.2, nir=0.7, swir1=0.2, swir2=0.2, bt=300
 )
 def test_Image_ndvi_calculation(red, nir, expected, tol=0.000001):
     output = utils.constant_image_value(landsat.ndvi(sr_image(red=red, nir=nir)))
-    assert abs(output - expected) <= tol
+    assert abs(output['ndvi'] - expected) <= tol
 
 
-def test_Image_ndvi_band_name():
-    output = landsat.ndvi(sr_image()).getInfo()['bands'][0]['id']
-    assert output == 'ndvi'
+def test_Image_ndwi_band_name():
+    output = landsat.ndwi(sr_image()).getInfo()['bands'][0]['id']
+    assert output == 'ndwi'
 
 
 def test_Image_ndwi_calculation(green=0.2, nir=0.2, expected=0, tol=0.000001):
     output = utils.constant_image_value(landsat.ndwi(sr_image(green=green, nir=nir)))
-    assert abs(output - expected) <= tol
+    assert abs(output['ndwi'] - expected) <= tol
 
 
-def test_Image_ndwi_band_name():
-    output = landsat.ndwi(sr_image()).getInfo()['bands'][0]['id']
-    assert output == 'ndwi'
+def test_Image_mndwi_band_name():
+    output = landsat.mndwi(sr_image()).getInfo()['bands'][0]['id']
+    assert output == 'mndwi'
 
 
 @pytest.mark.parametrize(
@@ -76,12 +81,12 @@ def test_Image_ndwi_band_name():
 )
 def test_Image_mndwi_calculation(green, swir2, expected, tol=0.000001):
     output = utils.constant_image_value(landsat.mndwi(sr_image(green=green, swir2=swir2)))
-    assert abs(output - expected) <= tol
+    assert abs(output['mndwi'] - expected) <= tol
 
 
-def test_Image_mndwi_band_name():
-    output = landsat.mndwi(sr_image()).getInfo()['bands'][0]['id']
-    assert output == 'mndwi'
+def test_Image_wri_band_name():
+    output = landsat.wri(sr_image()).getInfo()['bands'][0]['id']
+    assert output == 'wri'
 
 
 @pytest.mark.parametrize(
@@ -95,12 +100,12 @@ def test_Image_wri_calculation(green, red, nir, swir2, expected, tol=0.000001):
     output = utils.constant_image_value(landsat.wri(
         sr_image(green=green, red=red, nir=nir, swir2=swir2)
     ))
-    assert abs(output - expected) <= tol
+    assert abs(output['wri'] - expected) <= tol
 
 
-def test_Image_wri_band_name():
-    output = landsat.wri(sr_image()).getInfo()['bands'][0]['id']
-    assert output == 'wri'
+def test_Image_emissivity_ptjpl_band_name():
+    output = landsat.emissivity_ptjpl(sr_image()).getInfo()['bands'][0]['id']
+    assert output == 'emissivity'
 
 
 @pytest.mark.parametrize(
@@ -121,11 +126,11 @@ def test_Image_wri_band_name():
 )
 def test_Image_emissivity_ptjpl_calculation(red, nir, expected, tol=0.000001):
     output = utils.constant_image_value(landsat.emissivity_ptjpl(sr_image(red=red, nir=nir)))
-    assert abs(output - expected) <= tol
+    assert abs(output['emissivity'] - expected) <= tol
 
 
-def test_Image_emissivity_disalexi_band_name():
-    output = landsat.emissivity_ptjpl(sr_image()).getInfo()['bands'][0]['id']
+def test_Image_emissivity_metric_band_name():
+    output = landsat.emissivity_metric(sr_image()).getInfo()['bands'][0]['id']
     assert output == 'emissivity'
 
 
@@ -146,12 +151,12 @@ def test_Image_emissivity_disalexi_band_name():
 )
 def test_Image_emissivity_metric_calculation(red, nir, expected, tol=0.000001):
     output = utils.constant_image_value(landsat.emissivity_metric(sr_image(red=red, nir=nir)))
-    assert abs(output - expected) <= tol
+    assert abs(output['emissivity'] - expected) <= tol
 
 
-def test_Image_emissivity_metric_band_name():
-    output = landsat.emissivity_metric(sr_image()).getInfo()['bands'][0]['id']
-    assert output == 'emissivity'
+def test_Image_lst_band_name():
+    output = landsat.lst(sr_image()).getInfo()['bands'][0]['id']
+    assert output == 'lst'
 
 
 @pytest.mark.parametrize(
@@ -163,12 +168,12 @@ def test_Image_emissivity_metric_band_name():
 )
 def test_Image_lst_calculation(red, nir, bt, expected, tol=0.000001):
     output = utils.constant_image_value(landsat.lst(sr_image(red=red, nir=nir, bt=bt)))
-    assert abs(output - expected) <= tol
+    assert abs(output['lst'] - expected) <= tol
 
 
-def test_Image_lst_band_name():
-    output = landsat.lst(sr_image()).getInfo()['bands'][0]['id']
-    assert output == 'lst'
+def test_Image_albedo_band_name():
+    output = landsat.albedo_metric(sr_image()).getInfo()['bands'][0]['id']
+    assert output == 'albedo'
 
 
 @pytest.mark.parametrize(
@@ -181,9 +186,4 @@ def test_Image_albedo_calculation(blue, green, red, nir, swir1, swir2, expected,
     output = utils.constant_image_value(landsat.albedo_metric(
         sr_image(blue=blue, green=green, red=red, nir=nir, swir1=swir1, swir2=swir2)
     ))
-    assert abs(output - expected) <= tol
-
-
-def test_Image_albedo_band_name():
-    output = landsat.albedo_metric(sr_image()).getInfo()['bands'][0]['id']
-    assert output == 'albedo'
+    assert abs(output['albedo'] - expected) <= tol
diff --git a/openet/ptjpl/tests/test_b_meteorology.py b/openet/ptjpl/tests/test_b_meteorology.py
index 4358e81..9396886 100644
--- a/openet/ptjpl/tests/test_b_meteorology.py
+++ b/openet/ptjpl/tests/test_b_meteorology.py
@@ -68,8 +68,8 @@ def test_pascal_to_kilopascal(P_Pa, expected, tol=0.000001):
 def test_meteorology_svp(Ta_C, Ea_kPa, expected, tol=0.000001):
     # CGM - This test uses images due to .updateMask() call in meteorology
     SVP, VPD, RH = meteorology.meteorology(ee.Image.constant(Ta_C), ee.Image.constant(Ea_kPa))
-    output = utils.constant_image_value(SVP)
-    assert abs(output - expected) <= tol
+    output = utils.constant_image_value(SVP.rename(['svp']))
+    assert abs(output['svp'] - expected) <= tol
 
 
 @pytest.mark.parametrize(
@@ -82,11 +82,11 @@ def test_meteorology_svp(Ta_C, Ea_kPa, expected, tol=0.000001):
 def test_meteorology_vpd(Ta_C, Ea_kPa, expected, tol=0.000001):
     # CGM - This test uses images due to .updateMask() call in meteorology
     SVP, VPD, RH = meteorology.meteorology(ee.Image.constant(Ta_C), ee.Image.constant(Ea_kPa))
-    output = utils.constant_image_value(VPD)
-    if expected is None and output is None:
+    output = utils.constant_image_value(VPD.rename(['vpd']))
+    if expected is None and output['vpd'] is None:
         assert True
     else:
-        assert abs(output - expected) <= tol
+        assert abs(output['vpd'] - expected) <= tol
 
 
 @pytest.mark.parametrize(
@@ -99,8 +99,8 @@ def test_meteorology_vpd(Ta_C, Ea_kPa, expected, tol=0.000001):
 def test_meteorology_rh(Ta_C, Ea_kPa, expected, tol=0.000001):
     # CGM - This test uses images due to .updateMask() call in meteorology
     SVP, VPD, RH = meteorology.meteorology(ee.Image.constant(Ta_C), ee.Image.constant(Ea_kPa))
-    output = utils.constant_image_value(RH)
-    assert abs(output - expected) <= tol
+    output = utils.constant_image_value(RH.rename(['rh']))
+    assert abs(output['rh'] - expected) <= tol
 
 
 @pytest.mark.parametrize(
diff --git a/openet/ptjpl/tests/test_b_vegetation.py b/openet/ptjpl/tests/test_b_vegetation.py
index 7003b42..5f7f653 100644
--- a/openet/ptjpl/tests/test_b_vegetation.py
+++ b/openet/ptjpl/tests/test_b_vegetation.py
@@ -7,7 +7,7 @@
 
 def test_savi_from_ndvi(ndvi=0.5, expected=0.5 * 0.45 + 0.132, tol=0.000001):
     output = utils.constant_image_value(vegetation.savi_from_ndvi(ee.Image.constant(ndvi)))
-    assert abs(output - expected) <= tol
+    assert abs(output['constant'] - expected) <= tol
 
 
 @pytest.mark.parametrize(
@@ -20,14 +20,14 @@ def test_savi_from_ndvi(ndvi=0.5, expected=0.5 * 0.45 + 0.132, tol=0.000001):
 )
 def test_fAPAR_from_savi(savi, expected, tol=0.000001):
     output = utils.constant_image_value(vegetation.fAPAR_from_savi(ee.Image.constant(savi)))
-    assert abs(output - expected) <= tol
+    assert abs(output['constant'] - expected) <= tol
 
 
 @pytest.mark.parametrize(
     'ndvi, expected', [[0.5, (0.45 * 0.5 + 0.132) * 1.3632 - 0.048]])
 def test_fAPAR_from_ndvi(ndvi, expected, tol=0.000001):
     output = utils.constant_image_value(vegetation.fAPAR_from_ndvi(ee.Image.constant(ndvi)))
-    assert abs(output - expected) <= tol
+    assert abs(output['constant'] - expected) <= tol
 
 
 @pytest.mark.parametrize(
@@ -40,4 +40,4 @@ def test_fAPAR_from_ndvi(ndvi, expected, tol=0.000001):
 )
 def test_fIPAR_from_ndvi(ndvi, expected, tol=0.000001):
     output = utils.constant_image_value(vegetation.fIPAR_from_ndvi(ee.Image.constant(ndvi)))
-    assert abs(output - expected) <= tol
+    assert abs(output['constant'] - expected) <= tol
diff --git a/openet/ptjpl/tests/test_c_ptjpl.py b/openet/ptjpl/tests/test_c_ptjpl.py
index 30bc49c..6813eda 100644
--- a/openet/ptjpl/tests/test_c_ptjpl.py
+++ b/openet/ptjpl/tests/test_c_ptjpl.py
@@ -34,9 +34,9 @@ def test_Model_Rns_calculation(Rn, LAI, water_mask, expected, tol=0.001):
         water_mask=ee.Image.constant(water_mask)
     ))
     if expected is None:
-        assert output is None
+        assert output['constant'] is None
     else:
-        assert abs(output - expected) <= tol
+        assert abs(output['constant'] - expected) <= tol
 
 
 # @pytest.mark.parametrize(
@@ -53,7 +53,7 @@ def test_Model_Rns_calculation(Rn, LAI, water_mask, expected, tol=0.001):
 #         Rn=ee.Image.constant(Rn), fIPAR=ee.Image.constant(fIPAR),
 #         Rns=ee.Image.constant(Rns), W=ee.Image.constant(W),
 #         water_mask=ee.Image.constant(water_mask)))
-#     assert abs(output - expected) <= tol
+#     assert abs(output['constant'] - expected) <= tol
 
 
 # @pytest.mark.parametrize(
@@ -83,5 +83,5 @@ def test_Model_Rns_calculation(Rn, LAI, water_mask, expected, tol=0.001):
 #     )
 #     output = utils.constant_image_value(output_image)
 #     logging.debug(f'\n  Target values: {expected}')
-#     logging.debug(f'  Output values: {output}')
-#     assert abs(output - expected) <= tol
+#     logging.debug(f'  Output values: {output['constant']}')
+#     assert abs(output['constant'] - expected) <= tol
diff --git a/openet/ptjpl/tests/test_d_image.py b/openet/ptjpl/tests/test_d_image.py
index e03bcea..fad91aa 100644
--- a/openet/ptjpl/tests/test_d_image.py
+++ b/openet/ptjpl/tests/test_d_image.py
@@ -241,7 +241,7 @@ def test_Image_nldas_interpolate(band, time, interp_flag, xy, expected, tol=0.00
     output = utils.point_image_value(
         ptjpl.Image.nldas_interpolate(band, ee.Date(time), interp_flag), xy
     )
-    assert abs(output - expected) <= tol
+    assert abs(output[band] - expected) <= tol
 
 
 @pytest.mark.parametrize(
@@ -260,7 +260,7 @@ def test_Image_ea_sources(ea_source, xy, expected, tol=0.01):
     # m._start_date = ee.Date(start_date)
     # m._end_date =  m._start_date.advance(1, 'day')
     output = utils.point_image_value(ee.Image(m.ea), xy)
-    assert abs(output - expected) <= tol
+    assert abs(output['ea'] - expected) <= tol
 
 
 def test_Image_ea_sources_exception():
@@ -284,7 +284,7 @@ def test_Image_LWin_sources(LWin_source, xy, expected, tol=0.01):
     # m._start_date = ee.Date(start_date)
     # m._end_date =  m._start_date.advance(1, 'day')
     output = utils.point_image_value(ee.Image(m.LWin), xy)
-    assert abs(output - expected) <= tol
+    assert abs(output['LWin'] - expected) <= tol
 
 
 def test_Image_LWin_sources_exception():
@@ -308,7 +308,7 @@ def test_Image_rs_sources(rs_source, xy, expected, tol=0.0001):
     # m._start_date = ee.Date(start_date)
     # m._end_date =  m._start_date.advance(1, 'day')
     output = utils.point_image_value(ee.Image(m.rs), xy)
-    assert abs(output - expected) <= tol
+    assert abs(output['rs'] - expected) <= tol
 
 
 def test_Image_rs_sources_exception():
@@ -332,7 +332,7 @@ def test_Image_ta_sources(ta_source, xy, expected, tol=0.0001):
     # m._start_date = ee.Date(start_date)
     # m._end_date =  m._start_date.advance(1, 'day')
     output = utils.point_image_value(ee.Image(m.ta), xy)
-    assert abs(output - expected) <= tol
+    assert abs(output['Ta'] - expected) <= tol
 
 
 def test_Image_ta_sources_exception():
@@ -356,7 +356,7 @@ def test_Image_windspeed_sources(windspeed_source, xy, expected, tol=0.0001):
     # m._start_date = ee.Date(start_date)
     # m._end_date =  m._start_date.advance(1, 'day')
     output = utils.point_image_value(ee.Image(m.U), xy)
-    assert abs(output - expected) <= tol
+    assert abs(output['U'] - expected) <= tol
 
 
 def test_Image_windspeed_sources_exception():
@@ -385,13 +385,13 @@ def test_Image_topt_sources(topt_source, xy, expected, tol=0.001):
     # m._start_date = ee.Date(start_date)
     # m._end_date =  m._start_date.advance(1, 'day')
     output = utils.point_image_value(ee.Image(m.Topt), xy)
-    assert abs(output - expected) <= tol
+    assert abs(output['Topt'] - expected) <= tol
 
 
 def test_Image_topt_floor(topt_source=15, ta_source=40, tol=0.001):
     m = default_image_obj(topt_source=topt_source, ta_source=ta_source+273.15, floor_Topt=True)
     output = utils.point_image_value(ee.Image(m.Topt), TEST_POINT)
-    assert abs(output - ta_source) <= tol
+    assert abs(output['Topt'] - ta_source) <= tol
 
 
 def test_Image_topt_sources_exception():
@@ -420,7 +420,7 @@ def test_Image_faparmax_sources(faparmax_source, xy, expected, tol=0.0001):
     # m._start_date = ee.Date(start_date)
     # m._end_date =  m._start_date.advance(1, 'day')
     output = utils.point_image_value(ee.Image(m.fAPARmax), xy)
-    assert abs(output - expected) <= tol
+    assert abs(output['fAPARmax'] - expected) <= tol
 
 
 def test_Image_faparmax_sources_exception():
@@ -440,22 +440,23 @@ def test_Image_SWin_properties():
 
 def test_Image_SWin_value():
     """Test that a non-zero value is returned for the default inputs"""
-    assert utils.constant_image_value(default_image_obj().SWin) > 0
+    output = utils.constant_image_value(ee.Image(default_image_obj().SWin))
+    assert output['SWin'] > 0
 
 
 def test_Image_LE_defaults(expected=517.674, tol=0.001):
     output = utils.constant_image_value(ee.Image(default_image_obj().LE))
-    assert abs(output - expected) <= tol
+    assert abs(output['LE'] - expected) <= tol
 
 
 def test_Image_PET_defaults(expected=718.188, tol=0.001):
     output = utils.constant_image_value(ee.Image(default_image_obj().PET))
-    assert abs(output - expected) <= tol
+    assert abs(output['PET'] - expected) <= tol
 
 
 def test_Image_ESI_defaults(expected=0.721, tol=0.001):
     output = utils.constant_image_value(ee.Image(default_image_obj().ESI))
-    assert abs(output - expected) <= tol
+    assert abs(output['ESI'] - expected) <= tol
 
 
 def test_Image_et_properties():
@@ -469,7 +470,7 @@ def test_Image_et_properties():
 
 def test_Image_et_defaults(expected=6.128, tol=0.001):
     output = utils.constant_image_value(ee.Image(default_image_obj().et))
-    assert abs(output - expected) <= tol
+    assert abs(output['et'] - expected) <= tol
 
 
 # CGM - Test if there are any conditions that should return nodata
@@ -480,10 +481,9 @@ def test_Image_et_defaults(expected=6.128, tol=0.001):
 #     ]
 # )
 # def test_Image_et_nodata(albedo, emissivity, lst, ndvi, expected):
-#     output_img = default_image_obj(albedo=albedo, emissivity=emissivity,
-#                                    lst=lst, ndvi=ndvi)
+#     output_img = default_image_obj(albedo=albedo, emissivity=emissivity, lst=lst, ndvi=ndvi)
 #     output = utils.constant_image_value(ee.Image(output_img.et))
-#     assert output is None
+#     assert output['et'] is None
 
 
 def test_Image_et_reference_properties():
@@ -500,8 +500,12 @@ def test_Image_et_reference_properties():
     [
         ['IDAHO_EPSCOR/GRIDMET', 'etr', 1, TEST_POINT, 12.9],
         ['IDAHO_EPSCOR/GRIDMET', 'etr', 0.85, TEST_POINT, 12.9 * 0.85],
-        ['projects/earthengine-legacy/assets/projects/climate-engine/cimis/daily',
-         'ETr_ASCE', 1, TEST_POINT, 11.7839],
+        ['projects/openet/assets/reference_et/california/cimis/daily/v1',
+         'etr', 1, TEST_POINT, 11.7893],
+        ['projects/openet/reference_et/california/cimis/daily/v1',
+         'etr', 1, TEST_POINT, 11.7893],
+        ['projects/earthengine-legacy/assets/projects/openet/reference_et/california/cimis/daily/v1',
+         'etr', 1, TEST_POINT, 11.7893],
         [10, 'FOO', 1, TEST_POINT, 10.0],
         [10, 'FOO', 0.85, TEST_POINT, 8.5],
     ]
@@ -511,14 +515,14 @@ def test_Image_et_reference_sources(source, band, factor, xy, expected, tol=0.00
     output = utils.point_image_value(default_image_obj(
         et_reference_source=source, et_reference_band=band,
         et_reference_factor=factor).et_reference, xy)
-    assert abs(output - expected) <= tol
+    assert abs(output['et_reference'] - expected) <= tol
 
 
 # # DEADBEEF - Current implementation does not use etr_source for computing etr
 # def test_Image_etr_values(etr_source=15, etr_factor=0.85, tol=0.0001):
 #     output = utils.constant_image_value(default_image_obj(
 #         etr_source=etr_source, etr_factor=etr_factor).etr)
-#     assert abs(output - etr_source * etr_factor) <= tol
+#     assert abs(output['constant'] - etr_source * etr_factor) <= tol
 
 
 def test_Image_et_fraction_properties():
@@ -531,17 +535,15 @@ def test_Image_et_fraction_properties():
 
 
 # def test_Image_et_fraction_defaults(expected=0.721, tol=0.001):
-#     output = utils.constant_image_value(
-#         ee.Image(default_image_obj().et_fraction))
-#     assert abs(output - expected) <= tol
+#     output = utils.constant_image_value(ee.Image(default_image_obj().et_fraction))
+#     assert abs(output['et_fraction'] - expected) <= tol
 
 
 # # DEADBEEF - Current implementation does not use etr_source for computing etr
-# def test_Image_etf_values(etr_source=15, etr_factor=0.85, expected=13.335,
-#                           tol=0.0001):
+# def test_Image_etf_values(etr_source=15, etr_factor=0.85, expected=13.335, tol=0.0001):
 #     output = utils.constant_image_value(default_image_obj(
 #         etr_source=etr_source, etr_factor=etr_factor).etf)
-#     assert abs(output - expected / (etr_source * etr_factor)) <= tol
+#     assert abs(output['etf'] - expected / (etr_source * etr_factor)) <= tol
 
 
 # CGM - Can't check mask, time, and calculate() until ET is working
@@ -555,7 +557,7 @@ def test_Image_mask_properties():
 
 
 def test_Image_mask_values():
-    assert utils.constant_image_value(default_image_obj().mask) == 1
+    assert utils.constant_image_value(default_image_obj().mask)['mask'] == 1
 
 
 def test_Image_time_properties():
@@ -570,7 +572,7 @@ def test_Image_time_properties():
 def test_Image_time_values():
     """The time band should have the 0 UTC time in it for interpolation"""
     assert utils.constant_image_value(
-        default_image_obj().time) == utils.millis(SCENE_0UTC_DT)
+        default_image_obj().time)['time'] == utils.millis(SCENE_0UTC_DT)
 
 
 def test_Image_calculate_properties():
@@ -602,9 +604,9 @@ def test_Image_calculate_values():
     """Test if the calculate method returns values"""
     output_img = default_image_obj().calculate(['et'])
     # output_img = default_image_obj().calculate(['et', 'et_reference', 'et_fraction'])
-    assert utils.constant_image_value(output_img.select(['et'])) > 0
-    # assert utils.constant_image_value(output_img.select(['et_reference'])) > 0
-    # assert utils.constant_image_value(output_img.select(['et_fraction'])) > 0
+    assert utils.constant_image_value(output_img.select(['et']))['et'] > 0
+    # assert utils.constant_image_value(output_img.select(['et_reference']))['et_reference'] > 0
+    # assert utils.constant_image_value(output_img.select(['et_fraction']))['et_fraction'] > 0
 
 
 def test_Image_calculate_variables_valueerror():
@@ -617,6 +619,7 @@ def test_Image_from_landsat_c2_sr_default_image():
     """Test that the classmethod is returning a class object"""
     output = ptjpl.Image.from_landsat_c2_sr(
         ee.Image('LANDSAT/LC08/C02/T1_L2/LC08_038031_20130828')
+        # 'LANDSAT/LC08/C02/T1_L2/LC08_038031_20130828'
     )
     assert type(output) == type(default_image_obj())
 
@@ -624,8 +627,8 @@ def test_Image_from_landsat_c2_sr_default_image():
 @pytest.mark.parametrize(
     'image_id',
     [
-        # 'LANDSAT/LT04/C02/T1_L2/LT04_044033_19830812',
-        # 'LANDSAT/LT05/C02/T1_L2/LT05_044033_20110716',
+        'LANDSAT/LT04/C02/T1_L2/LT04_044033_19830812',
+        'LANDSAT/LT05/C02/T1_L2/LT05_044033_20110716',
         'LANDSAT/LE07/C02/T1_L2/LE07_044033_20170708',
         'LANDSAT/LC08/C02/T1_L2/LC08_044033_20170716',
         'LANDSAT/LC09/C02/T1_L2/LC09_044033_20220127',
@@ -640,7 +643,8 @@ def test_Image_from_landsat_c2_sr_landsat_image(image_id):
 def test_Image_from_landsat_c2_sr_exception():
     """Test instantiating the class for an invalid image ID"""
     with pytest.raises(Exception):
-        utils.getinfo(ptjpl.Image.from_landsat_c2_sr(ee.Image('DEADBEEF'))._index)
+        # Intentionally using .getInfo() since utils.getinfo() might catch the exception
+        ptjpl.Image.from_landsat_c2_sr(ee.Image('FOO')).ndvi.getInfo()
 
 
 def test_Image_from_landsat_c2_sr_scaling():
@@ -655,44 +659,55 @@ def test_Image_from_landsat_c2_sr_scaling():
               'system:time_start': ee.Number(sr_img.get('system:time_start'))})
     )
 
-    output = utils.constant_image_value(ptjpl.Image.from_landsat_c2_sr(input_img).albedo)
-    assert abs(output - 0.1) <= 0.01
+    # LST correction and cloud score masking do not work with a constant image
+    #   and must be explicitly set to False
+    output = utils.constant_image_value(ptjpl.Image.from_landsat_c2_sr(
+        input_img, c2_lst_correct=False,
+        cloudmask_args={'cloud_score_flag': False, 'filter_flag': False}).albedo)
+    assert abs(output['albedo'] - 0.1) <= 0.01
 
-    output = utils.constant_image_value(ptjpl.Image.from_landsat_c2_sr(input_img).LST)
-    assert abs(output - 300) <= 0.1
+    output = utils.constant_image_value(ptjpl.Image.from_landsat_c2_sr(
+        input_img, c2_lst_correct=False,
+        cloudmask_args={'cloud_score_flag': False, 'filter_flag': False}).LST)
+    assert abs(output['lst'] - 300) <= 0.1
 
 
 def test_Image_from_landsat_c2_sr_cloud_mask_args():
     """Test if the cloud_mask_args parameter can be set (not if it works)"""
-    image_id = 'LANDSAT/LC08/C02/T1_L2/LC08_044033_20170716'
     output = ptjpl.Image.from_landsat_c2_sr(
-        image_id, cloudmask_args={'snow_flag': True, 'cirrus_flag': True}
+        'LANDSAT/LC08/C02/T1_L2/LC08_044033_20170716',
+        cloudmask_args={'snow_flag': True, 'cirrus_flag': True}
     )
     assert type(output) == type(default_image_obj())
 
 
+def test_Image_from_landsat_c2_sr_cloud_score_mask_arg():
+    """Test if the cloud_score_flag parameter can be set in cloudmask_args"""
+    output = ptjpl.Image.from_landsat_c2_sr(
+        'LANDSAT/LC08/C02/T1_L2/LC08_044033_20170716',
+        cloudmask_args={'cloud_score_flag': True, 'cloud_score_pct': 50})
+    assert type(output) == type(default_image_obj())
+
+
 def test_Image_from_landsat_c2_sr_c2_lst_correct_arg():
     """Test if the c2_lst_correct parameter can be set (not if it works)"""
-    image_id = 'LANDSAT/LC08/C02/T1_L2/LC08_031034_20160702'
-    output = ptjpl.Image.from_landsat_c2_sr(image_id, c2_lst_correct=True)
+    output = ptjpl.Image.from_landsat_c2_sr(
+        'LANDSAT/LC08/C02/T1_L2/LC08_031034_20160702', c2_lst_correct=True)
     assert type(output) == type(default_image_obj())
 
 
 def test_Image_from_landsat_c2_sr_c2_lst_correct_fill():
     """Test if the c2_lst_correct fills the LST holes in Nebraska"""
     image_id = 'LANDSAT/LC08/C02/T1_L2/LC08_031034_20160702'
-    point_xy = [-102.08284, 37.81728]
+    xy = [-102.08284, 37.81728]
+
     # CGM - Is the uncorrected test needed?
     uncorrected = utils.point_image_value(
-        ptjpl.Image.from_landsat_c2_sr(image_id, c2_lst_correct=False).LST,
-        point_xy)
-    assert uncorrected is None
-    # assert uncorrected['lst'] is None
+        ptjpl.Image.from_landsat_c2_sr(image_id, c2_lst_correct=False).LST, xy)
+    assert uncorrected['lst'] is None
     corrected = utils.point_image_value(
-        ptjpl.Image.from_landsat_c2_sr(image_id, c2_lst_correct=True).LST,
-        point_xy)
-    assert corrected > 0
-    # assert corrected['lst'] > 0
+        ptjpl.Image.from_landsat_c2_sr(image_id, c2_lst_correct=True).LST, xy)
+    assert corrected['lst'] > 0
     # # Exact test values copied from openet-core
     # assert abs(corrected['lst'] - 306.83) <= 0.25
 
@@ -722,12 +737,13 @@ def test_Image_from_method_kwargs():
 # CGM - Copied from SIMS test_b_model.py
 def test_Model_crop_type_source_exception():
     with pytest.raises(ValueError):
-        utils.getinfo(default_image_obj(crop_type_source='FOO').crop_type)
+        # Intentionally using .getInfo() since utils.getinfo() might catch the exception
+        default_image_obj(crop_type_source='FOO').crop_type.getInfo()
 
 
 def test_Model_crop_type_constant_value():
     output = utils.constant_image_value(default_image_obj(crop_type_source=10).crop_type)
-    assert output == 10
+    assert output['crop_type'] == 10
 
 
 @pytest.mark.parametrize(
@@ -758,19 +774,17 @@ def test_Model_crop_type_source_cdl_image():
 def test_Model_crop_type_source_cdl_image_exception():
     """Requesting a CDL image that doesn't exist should raise an EE exception"""
     with pytest.raises(Exception):
-        utils.getinfo(default_image_obj(crop_type_source='USDA/NASS/CDL/2099'))
-        # CGM - The exception is raised in the _crop_type() method which is
-        #   in the init.  If crop_type is a lazy property then it is necessary
-        #   to request the property in order to raise the exception.
-        # utils.getinfo(default_model_obj(
-        #     crop_type_source='USDA/NASS/CDL/2099').crop_type)
+        # Intentionally using .getInfo() since utils.getinfo() might catch the exception
+        default_image_obj(crop_type_source='USDA/NASS/CDL/2099').crop_type.getInfo()
 
 
 @pytest.mark.parametrize(
     'crop_type_source',
     [
-        'projects/openet/crop_type/v2021a',
-        'projects/earthengine-legacy/assets/projects/openet/crop_type/v2021a',
+        'projects/openet/assets/crop_type/v2023a',
+        'projects/openet/assets/crop_type/v2021a',
+        # 'projects/openet/crop_type/v2021a',
+        # 'projects/earthengine-legacy/assets/projects/openet/crop_type/v2021a',
     ]
 )
 def test_Model_crop_type_source_openet_crop_type(crop_type_source):
@@ -784,15 +798,17 @@ def test_Model_crop_type_source_openet_crop_type(crop_type_source):
     [
         ['USDA/NASS/CDL', TEST_POINT, 36],
         ['USDA/NASS/CDL/2016', TEST_POINT, 36],
-        ['projects/openet/crop_type/v2021a', TEST_POINT, 47],
-        ['projects/earthengine-legacy/assets/projects/openet/crop_type/v2021a', TEST_POINT, 47],
+        ['projects/openet/assets/crop_type/v2023a', TEST_POINT, 47],
+        ['projects/openet/assets/crop_type/v2021a', TEST_POINT, 47],
+        # ['projects/openet/crop_type/v2021a', TEST_POINT, 47],
+        # ['projects/earthengine-legacy/assets/projects/openet/crop_type/v2021a', TEST_POINT, 47],
     ]
 )
 def test_Model_crop_type_values(crop_type_source, xy, expected):
     output = utils.point_image_value(
         default_image_obj(crop_type_source=crop_type_source).crop_type, xy
     )
-    assert output == expected
+    assert output['crop_type'] == expected
 
 
 @pytest.mark.parametrize(
@@ -809,7 +825,7 @@ def test_Model_crop_mask_constant_value(crop_type_source, expected):
     output = utils.constant_image_value(
         default_image_obj(crop_type_source=crop_type_source).crop_mask
     )
-    assert output == expected
+    assert output['crop_mask'] == expected
 
 
 def test_Model_crop_pm_adjust_source_exception():
@@ -821,28 +837,29 @@ def test_Model_crop_pm_adjust_constant_value():
     output = utils.constant_image_value(
         default_image_obj(crop_pm_adjust_source=2, crop_type_source=36).crop_pm_adjust
     )
-    assert output == 2
+    assert output['crop_pm_adjust'] == 2
 
 
 @pytest.mark.parametrize(
     'crop_pm_adjust_source, xy, expected',
     [
-        ['projects/openet/ptjpl/ancillary/alpha/gridmet_1980-2020_dgs',
+        ['projects/openet/assets/ptjpl/ancillary/alpha/gridmet_1980-2020_dgs',
          TEST_POINT, 1.3024652077503645],
+        # ['projects/openet/ptjpl/ancillary/alpha/gridmet_1980-2020_dgs',
+        #  TEST_POINT, 1.3024652077503645],
     ]
 )
 def test_Model_crop_pm_adjust_values(crop_pm_adjust_source, xy, expected, tol=0.001):
     output = utils.point_image_value(
         default_image_obj(crop_pm_adjust_source=crop_pm_adjust_source).crop_pm_adjust, xy
     )
-    assert abs(output - expected) <= tol
+    assert abs(output['crop_pm_adjust'] - expected) <= tol
 
 
 # def test_Model_crop_pm_adjust_band():
 #     output = utils.constant_image_value(default_image_obj(
-#         crop_pm_adjust_source=2,
-#         crop_type_source=36).crop_pm_adjust)
-#     assert output == 2
+#         crop_pm_adjust_source=2, crop_type_source=36).crop_pm_adjust)
+#     assert output['crop_pm_adjust'] == 2
 
 
 @pytest.mark.parametrize(
@@ -850,10 +867,14 @@ def test_Model_crop_pm_adjust_values(crop_pm_adjust_source, xy, expected, tol=0.
     [
         [True, 2, TEST_POINT, 2 * 6.128485756837151],
         [False, 2, TEST_POINT, 6.128485756837151],
-        [True, 'projects/openet/ptjpl/ancillary/alpha/gridmet_1980-2020_dgs',
+        [True, 'projects/openet/assets/ptjpl/ancillary/alpha/gridmet_1980-2020_dgs',
          TEST_POINT, 6.128485756837151 * 1.302],
-        [False, 'projects/openet/ptjpl/ancillary/alpha/gridmet_1980-2020_dgs',
+        [False, 'projects/openet/assets/ptjpl/ancillary/alpha/gridmet_1980-2020_dgs',
          TEST_POINT, 6.128485756837151],
+        # [True, 'projects/openet/ptjpl/ancillary/alpha/gridmet_1980-2020_dgs',
+        #  TEST_POINT, 6.128485756837151 * 1.302],
+        # [False, 'projects/openet/ptjpl/ancillary/alpha/gridmet_1980-2020_dgs',
+        #  TEST_POINT, 6.128485756837151],
     ]
 )
 def test_Model_et_crop_pm_adjust_flag(crop_pm_adjust_flag, crop_pm_adjust_source,
@@ -861,4 +882,4 @@ def test_Model_et_crop_pm_adjust_flag(crop_pm_adjust_flag, crop_pm_adjust_source
     output = utils.point_image_value(default_image_obj(
         crop_pm_adjust_flag=crop_pm_adjust_flag,
         crop_pm_adjust_source=crop_pm_adjust_source).et, xy)
-    assert abs(output - expected) <= tol
+    assert abs(output['et'] - expected) <= tol
diff --git a/openet/ptjpl/tests/test_e_collection.py b/openet/ptjpl/tests/test_e_collection.py
index 0b366cb..d3b2a2c 100644
--- a/openet/ptjpl/tests/test_e_collection.py
+++ b/openet/ptjpl/tests/test_e_collection.py
@@ -31,7 +31,9 @@
         'et_reference_source': 'IDAHO_EPSCOR/GRIDMET',
         'et_reference_band': 'eto',
         'et_reference_factor': 0.85,
-        'et_reference_resample': 'nearest'},
+        'et_reference_resample': 'nearest',
+        'cloudmask_args': {'cloud_score_flag': False, 'filter_flag': False},
+    },
     'filter_args': {},
     # 'interp_args': {},
 }
@@ -65,7 +67,7 @@ def test_Collection_init_default_parameters():
     m = ptjpl.Collection(**args)
     assert m.variables is None
     assert m.cloud_cover_max == 70
-    assert m.model_args == {}
+    # assert m.model_args == {}
     assert m.filter_args == {}
     # assert m.interp_args == {}
 
diff --git a/openet/ptjpl/tests/test_e_interpolate.py b/openet/ptjpl/tests/test_e_interpolate.py
index 76f6d5d..afef6b7 100644
--- a/openet/ptjpl/tests/test_e_interpolate.py
+++ b/openet/ptjpl/tests/test_e_interpolate.py
@@ -23,8 +23,10 @@ def scene_coll(variables, et_fraction=0.4, et=5, ndvi=0.6):
     ee.ImageCollection
 
     """
-    img = ee.Image('LANDSAT/LC08/C02/T1_L2/LC08_044033_20170716') \
+    img = (
+        ee.Image('LANDSAT/LC08/C02/T1_L2/LC08_044033_20170716')
         .select(['SR_B3']).double().multiply(0)
+    )
     mask = img.add(1).updateMask(1).uint8()
 
     time1 = ee.Number(ee.Date.fromYMD(2017, 7, 8).millis())
@@ -33,8 +35,10 @@ def scene_coll(variables, et_fraction=0.4, et=5, ndvi=0.6):
 
     # Mask and time bands currently get added on to the scene collection
     #   and images are unscaled just before interpolating in the export tool
-    scene_img = ee.Image([img.add(et_fraction), img.add(et), img.add(ndvi), mask])\
+    scene_img = (
+        ee.Image([img.add(et_fraction), img.add(et), img.add(ndvi), mask])
         .rename(['et_fraction', 'et', 'ndvi', 'mask'])
+    )
     scene_coll = ee.ImageCollection([
         scene_img.addBands([img.add(time1).rename('time')]) \
             .set({'system:index': 'LE07_044033_20170708',
@@ -65,7 +69,7 @@ def test_from_scene_et_fraction_daily_values(tol=0.0001):
         t_interval='daily')
 
     TEST_POINT = (-121.5265, 38.7399)
-    output = utils.point_coll_value(output_coll, TEST_POINT, scale=10)
+    output = utils.point_coll_value(output_coll, TEST_POINT, scale=30)
     assert abs(output['ndvi']['2017-07-10'] - 0.6) <= tol
     assert abs(output['et_fraction']['2017-07-10'] - 0.4) <= tol
     assert abs(output['et_reference']['2017-07-10'] - 8.0) <= tol
@@ -89,7 +93,7 @@ def test_from_scene_et_fraction_monthly_values(tol=0.0001):
         t_interval='monthly')
 
     TEST_POINT = (-121.5265, 38.7399)
-    output = utils.point_coll_value(output_coll, TEST_POINT, scale=10)
+    output = utils.point_coll_value(output_coll, TEST_POINT, scale=30)
     assert abs(output['ndvi']['2017-07-01'] - 0.6) <= tol
     assert abs(output['et_fraction']['2017-07-01'] - 0.4) <= tol
     assert abs(output['et_reference']['2017-07-01'] - 236.5) <= tol
@@ -110,7 +114,7 @@ def test_from_scene_et_fraction_custom_values(tol=0.0001):
         t_interval='custom')
 
     TEST_POINT = (-121.5265, 38.7399)
-    output = utils.point_coll_value(output_coll, TEST_POINT, scale=10)
+    output = utils.point_coll_value(output_coll, TEST_POINT, scale=30)
     assert abs(output['ndvi']['2017-07-01'] - 0.6) <= tol
     assert abs(output['et_fraction']['2017-07-01'] - 0.4) <= tol
     assert abs(output['et_reference']['2017-07-01'] - 236.5) <= tol
@@ -135,7 +139,7 @@ def test_from_scene_et_actual_daily_values(tol=0.0001):
         t_interval='daily')
 
     TEST_POINT = (-121.5265, 38.7399)
-    output = utils.point_coll_value(output_coll, TEST_POINT, scale=10)
+    output = utils.point_coll_value(output_coll, TEST_POINT, scale=30)
     assert abs(output['et_fraction']['2017-07-10'] - 0.5970309972763062) <= tol
     assert abs(output['et_reference']['2017-07-10'] - 8) <= tol
     assert abs(output['et']['2017-07-10'] - 4.776247978210449) <= tol
@@ -162,7 +166,7 @@ def test_from_scene_et_actual_monthly_values(tol=0.0001):
         t_interval='monthly')
 
     TEST_POINT = (-121.5265, 38.7399)
-    output = utils.point_coll_value(output_coll, TEST_POINT, scale=10)
+    output = utils.point_coll_value(output_coll, TEST_POINT, scale=30)
     assert abs(output['et']['2017-07-01'] - 145.9705047607422) <= tol
     assert abs(output['et_reference']['2017-07-01'] - 236.5) <= tol
     assert abs(output['et_fraction']['2017-07-01'] - 145.9705047607422 / 236.5) <= tol
@@ -186,7 +190,7 @@ def test_from_scene_et_actual_custom_values(tol=0.0001):
         t_interval='custom')
 
     TEST_POINT = (-121.5265, 38.7399)
-    output = utils.point_coll_value(output_coll, TEST_POINT, scale=10)
+    output = utils.point_coll_value(output_coll, TEST_POINT, scale=30)
     assert abs(output['et']['2017-07-01'] - 145.9705047607422) <= tol
     assert abs(output['et_reference']['2017-07-01'] - 236.5) <= tol
     assert abs(output['et_fraction']['2017-07-01'] - 145.9705047607422 / 236.5) <= tol
@@ -210,7 +214,7 @@ def test_from_scene_et_actual_monthly_et_reference_factor(tol=0.0001):
         t_interval='monthly')
 
     TEST_POINT = (-121.5265, 38.7399)
-    output = utils.point_coll_value(output_coll, TEST_POINT, scale=10)
+    output = utils.point_coll_value(output_coll, TEST_POINT, scale=30)
     assert abs(output['et']['2017-07-01'] - 145.9705047607422) <= tol
     assert abs(output['et_reference']['2017-07-01'] - 236.5 * 0.5) <= tol
     assert abs(output['et_fraction']['2017-07-01'] - 145.9705047607422 / 236.5 / 0.5) <= tol
@@ -235,7 +239,7 @@ def test_from_scene_et_actual_monthly_et_reference_resample(tol=0.0001):
         t_interval='monthly')
 
     TEST_POINT = (-121.5265, 38.7399)
-    output = utils.point_coll_value(output_coll, TEST_POINT, scale=10)
+    output = utils.point_coll_value(output_coll, TEST_POINT, scale=30)
     assert abs(output['et']['2017-07-01'] - 145.9705047607422) <= tol
     assert abs(output['et_reference']['2017-07-01'] - 236.5) <= tol
     assert abs(output['et_fraction']['2017-07-01'] - 145.9705047607422 / 236.5) <= tol
@@ -263,7 +267,7 @@ def test_from_scene_et_actual_daily_et_fraction_max(tol=0.0001):
         t_interval='daily')
 
     TEST_POINT = (-121.5265, 38.7399)
-    output = utils.point_coll_value(output_coll, TEST_POINT, scale=10)
+    output = utils.point_coll_value(output_coll, TEST_POINT, scale=30)
     assert abs(output['et_fraction']['2017-07-10'] - 1.4) <= tol
 
 
diff --git a/openet/ptjpl/utils.py b/openet/ptjpl/utils.py
index e7550f0..fc5b001 100644
--- a/openet/ptjpl/utils.py
+++ b/openet/ptjpl/utils.py
@@ -13,40 +13,45 @@ def getinfo(ee_obj, n=4):
         try:
             output = ee_obj.getInfo()
         except ee.ee_exception.EEException as e:
-            if ('Earth Engine memory capacity exceeded' in str(e) or
-                    'Earth Engine capacity exceeded' in str(e)):
-                logging.info(f'    Resending query ({i}/10)')
-                logging.debug(f'    {e}')
-                sleep(i ** 2)
-            else:
-                raise e
+            logging.info(f'    Resending query ({i}/{n})')
+            logging.info(f'    {e}')
+            sleep(i ** 3)
+            # if ('Earth Engine memory capacity exceeded' in str(e) or
+            #         'Earth Engine capacity exceeded' in str(e)):
+            #     logging.info(f'    Resending query ({i}/{n})')
+            #     logging.debug(f'    {e}')
+            #     sleep(i ** 2)
+            # else:
+            #     raise e
+        except Exception as e:
+            logging.info(e)
+            break
 
         if output:
             break
 
-    # output = ee_obj.getInfo()
     return output
 
 
-# TODO: Import from common.utils
-# Should these be test fixtures instead?
-# I'm not sure how to make them fixtures and allow input parameters
+# TODO: Import from openet.core.utils instead of defining here
 def constant_image_value(image, crs='EPSG:32613', scale=1):
     """Extract the output value from a calculation done with constant images"""
-    return ee.Image(image).rename(['output']) \
-        .reduceRegion(
-            reducer=ee.Reducer.first(), scale=scale,
-            geometry=ee.Geometry.Rectangle([0, 0, 10, 10], crs, False)) \
-        .getInfo()['output']
+    rr_params = {
+        'reducer': ee.Reducer.first(),
+        'geometry': ee.Geometry.Rectangle([0, 0, 10, 10], crs, False),
+        'scale': scale,
+    }
+    return getinfo(ee.Image(image).reduceRegion(**rr_params))
 
 
 def point_image_value(image, xy, scale=1):
     """Extract the output value from a calculation at a point"""
-    return ee.Image(image).rename(['output']) \
-        .reduceRegion(
-            reducer=ee.Reducer.first(), geometry=ee.Geometry.Point(xy),
-            scale=scale) \
-        .getInfo()['output']
+    rr_params = {
+        'reducer': ee.Reducer.first(),
+        'geometry': ee.Geometry.Point(xy),
+        'scale': scale,
+    }
+    return getinfo(ee.Image(image).reduceRegion(**rr_params))
 
 
 def point_coll_value(coll, xy, scale=1):
@@ -61,10 +66,10 @@ def point_coll_value(coll, xy, scale=1):
         col_dict[k] = i + 4
         info_dict[k] = {}
     for row in output[1:]:
-        date = datetime.datetime.utcfromtimestamp(row[3] / 1000.0).strftime(
-            '%Y-%m-%d')
+        date = datetime.datetime.utcfromtimestamp(row[3] / 1000.0).strftime('%Y-%m-%d')
         for k, v in col_dict.items():
             info_dict[k][date] = row[col_dict[k]]
+
     return info_dict
     # return pd.DataFrame.from_dict(info_dict)
 
@@ -95,13 +100,11 @@ def date_to_time_0utc(date):
     -------
     ee.Number
 
-    Notes
-    -----
-    Extra operations are needed since update() does not set milliseconds to 0.
-
     """
-    return date.update(hour=0, minute=0, second=0).millis() \
-        .divide(1000).floor().multiply(1000)
+    return ee.Date.fromYMD(date.get('year'), date.get('month'), date.get('day')).millis()
+    # Extra operations are needed since update() does not set milliseconds to 0.
+    # return date.update(hour=0, minute=0, second=0).millis()\
+    #     .divide(1000).floor().multiply(1000)
 
 
 def is_number(x):