diff --git a/dp/generate_climos.py b/dp/generate_climos.py
index a1c1b6f..755aea6 100644
--- a/dp/generate_climos.py
+++ b/dp/generate_climos.py
@@ -442,11 +442,12 @@ def convert_flux_var_units(input_file, climo_data):
         flux_variable = input_file.variables[flux_var]
         units = Unit.from_udunits_str(flux_variable.units)
 
-        if units in [Unit('kg / m**2 / s'), Unit('mm / s')]:
-            logger.info("Converting {} variable to units mm/day".format(flux_var))
+        precip_units = [Unit('kg / m**2 / s'), Unit('mm / s'), Unit('g / cm**2 / s'), Unit('cm / s')]
+        if units in precip_units:
             # Update units attribute
             attributes['units'] = (units * Unit('s / day')).to_udunits_str()
-            # Multiply values by 86400 to convert from mm/s to mm/day
+            logger.info(f"Converting {flux_var} variable to units {attributes['units']}")
+            # Multiply values by 86400 to convert from mm/s to mm/day or from cm/s to cm/day
             seconds_per_day = 86400
 
             if hasattr(flux_variable, 'scale_factor') or hasattr(flux_variable, 'add_offset'):
@@ -463,7 +464,7 @@ def convert_flux_var_units(input_file, climo_data):
                 # This is not a packed file; modify the values proper
                 # Extract variable
                 var_only = cdo.select('name={}'.format(flux_var), input=climo_data)
-                # Multiply values by 86400 to convert from mm/s to mm/day
+                # Multiply values by 86400 to convert from mm/s to mm/day or from cm/s to cm/day
                 var_only = cdo.mulc(str(seconds_per_day), input=var_only)
                 # Replace pr in all-variables file
                 climo_data = cdo.replace(input=[climo_data, var_only])
diff --git a/dp/generate_prsn.py b/dp/generate_prsn.py
index f2b5f01..7d6ec20 100644
--- a/dp/generate_prsn.py
+++ b/dp/generate_prsn.py
@@ -95,6 +95,7 @@ def create_prsn_netcdf_from_source(src, dst, to_delete=['original_name, comment'
 
     prsn_var.standard_name = 'snowfall_flux'
     prsn_var.long_name = 'Precipitation as Snow'
+    prsn_var.units = 'g cm-2 s-1'
 
     for item in set(to_delete):
         if hasattr(prsn_var, item):
@@ -163,12 +164,9 @@ def convert_temperature_units(data, units_from, units_to):
 
 def check_pr_units(pr_units):
     '''Ensure we have expected pr units'''
-    valid_units = [
-        Unit('kg / m**2 / s'),
-        Unit('mm / s'),
-        Unit('kg / d / m**2'),
-        Unit('kg / m**2 / d')
-    ]
+    valid_units = ['kg / m**2 / s', 'kg / m**2 / d', 'kg / d / m**2', 'mm / s', 'mm / d', \
+    'g / cm**2 / s', 'g / cm**2 / d', 'g / d / cm**2', 'cm / s', 'cm / d']
+    valid_units = [Unit(u) for u in valid_units]
     units = Unit.from_udunits_str(pr_units)
     return units in valid_units
 
@@ -222,7 +220,12 @@ def process_to_prsn(variables, output_dataset, max_chunk_len):
             }
         means = np.mean([chunk_data['tasmin'], chunk_data['tasmax']], axis=0)
         prsn_data = np.where(means < freezing, chunk_data['pr'], 0)
-        output_dataset.variables['prsn'][chunk] = prsn_data
+
+        prsn_units_from = ureg.parse_units('kg/m^2/s')
+        prsn_units_to = ureg.parse_units('g/cm^2/s')
+
+        output_dataset.variables['prsn'][chunk] = prsn_data * \
+        Q_(1.0, prsn_units_from).to(prsn_units_to).magnitude
 
 
 def generate_prsn_file(filepaths, chunk_size, outdir, output_file=None):
diff --git a/tests/test_generate_prsn.py b/tests/test_generate_prsn.py
index 037390d..5baa418 100644
--- a/tests/test_generate_prsn.py
+++ b/tests/test_generate_prsn.py
@@ -11,7 +11,10 @@
     pr_freezing_from_units, create_prsn_netcdf_from_source, \
     create_filepath_from_source, has_required_vars, matching_datasets, \
     check_pr_units, process_to_prsn, convert_temperature_units
+from pint import UnitRegistry
 
+ureg = UnitRegistry()
+Q_ = ureg.Quantity
 
 @pytest.mark.parametrize('arrays', [
     ({'shape1': np.arange(10).reshape(2, 5), 'shape2': np.arange(10).reshape(2, 5)}),
@@ -67,7 +70,7 @@ def test_create_prsn_netcdf_from_source(tiny_dataset, fake_dataset):
     assert np.shape(fake_dataset.variables['prsn']) == (11688, 4, 2)
     assert fake_dataset.variables['prsn'].standard_name == 'snowfall_flux'
     assert fake_dataset.variables['prsn'].long_name == 'Precipitation as Snow'
-
+    assert fake_dataset.variables['prsn'].units == 'g cm-2 s-1'
 
 @pytest.mark.parametrize('tiny_dataset, new_var, expected', [
     ('downscaled_pr', 'prsn', 'prsn_day_BCCAQ2_ACCESS1-0_ACCESS1-0+historical+rcp45+r1i1p1_r1i1p1_19600101-19911231.nc'),
@@ -151,6 +154,13 @@ def test_process_to_prsn(pr, tasmin, tasmax, fake_dataset):
     for array in result:
         assert len(array) == 0
 
+    # Test conversion from mm to cm
+    pr_mm = pr_dataset.variables['pr'][:]
+    pr_units_from = ureg.parse_units('kg/m^2/s')
+    pr_units_to = ureg.parse_units('g/cm^2/s')
+    pr_cm = pr_mm * Q_(1.0, pr_units_from).to(pr_units_to).magnitude
+    assert pr_cm == pytest.approx(pr_mm/10.0)
+
 
 @pytest.mark.parametrize('units_from, units_to, expected', [
     ('degC', 'K', 273.15),