diff --git a/modules/util/util.py b/modules/util/util.py
index 44a034e22ec15a47b2d23b316e65655f24c57945..848e988feb15ebbb2cfd305e16d3c86dd2b489c1 100644
--- a/modules/util/util.py
+++ b/modules/util/util.py
@@ -12,6 +12,7 @@ import pickle
 from netCDF4 import Dataset
 from util.setup import ancillary_path
 from scipy.interpolate import RectBivariateSpline, interp2d
+from scipy.ndimage import gaussian_filter
 
 LatLonTuple = namedtuple('LatLonTuple', ['lat', 'lon'])
 
@@ -1426,6 +1427,18 @@ def resample_2d_linear_one(x, y, z, x_new, y_new):
     return f(x_new, y_new)
 
 
+# Gaussian filter suitable for model training Data Pipeline
+# z: input array. Must have dimensions: [BATCH_SIZE, Y, X]
+# sigma: Standard deviation for Gaussian kernel
+# returns stacked 2d arrays of same input dimension
+def smooth_2d(z, sigma=1.0):
+    z_smoothed = []
+    for j in range(z.shape[0]):
+        z_j = z[j, :, :]
+        z_smoothed.append(gaussian_filter(z_j, sigma=sigma))
+    return np.stack(z_smoothed)
+
+
 def get_training_parameters(day_night='DAY', l1b_andor_l2='both', satellite='GOES16', use_dnb=False):
     if day_night == 'DAY':
         train_params_l2 = ['cld_height_acha', 'cld_geo_thick', 'cld_temp_acha', 'cld_press_acha', 'supercooled_cloud_fraction',