diff --git a/aosstower/level_b1/nc.py b/aosstower/level_b1/nc.py
index e170050deb37de9345ee1af745c0317d347c6315..949b25822f196a50ec5e5c57f2fed07cbfa5e647 100644
--- a/aosstower/level_b1/nc.py
+++ b/aosstower/level_b1/nc.py
@@ -39,6 +39,11 @@ def get_data(input_files):
     frame = pd.DataFrame(_get_data(input_files))
     frame = frame.set_index('stamp')
     frame = frame.mask(frame == -99999.).fillna(value=np.nan)
+
+    for col_name in frame.columns:
+        if col_name in schema.unit_conversions:
+            conv_func = schema.unit_conversions[col_name]
+            frame[col_name] = conv_func(frame[col_name])
     return frame
 
 
diff --git a/aosstower/schema.py b/aosstower/schema.py
index f03f7c093223c5e0da490c8bce68d787a90733ea..afb060f57548729d0503cfe2a24accb78e9f58d2 100644
--- a/aosstower/schema.py
+++ b/aosstower/schema.py
@@ -241,7 +241,7 @@ database = dict(
         'accumulated_precipitation',
         'accum_precip',
         'Precipitation accumulated since 0Z',
-        'mm',
+        'mm',  # data comes from instrument as inches but we typically want millimeters
         '0',
         '254',
         None,
@@ -273,3 +273,6 @@ database_dict = {k: v._asdict() for k, v in database.items()}
 met_vars = {'air_temp', 'dewpoint', 'rh', 'solar_flux', 'pressure', 'precip', 'accum_precip',
             'wind_speed', 'wind_dir', 'gust'}
 engr_vars = set(database.keys()) - met_vars
+
+unit_conversions = {}
+unit_conversions['accum_precip'] = lambda x: x * 25.4