diff --git a/modules/deeplearning/srcnn_l1b_l2.py b/modules/deeplearning/srcnn_l1b_l2.py
index bb3bfbf3e805a3dfcfb861b2d723d54181c5d009..377e860818b5c2dba7c68dd19824e863e2b26159 100644
--- a/modules/deeplearning/srcnn_l1b_l2.py
+++ b/modules/deeplearning/srcnn_l1b_l2.py
@@ -49,14 +49,14 @@ mean_std_dct.update(mean_std_dct_l2)
 
 #params = ['temp_11_0um_nom', 'temp_12_0um_nom', 'refl_0_65um_nom', 'cloud_fraction']
 #data_params = ['temp_11_0um_nom', 'temp_12_0um_nom', 'refl_0_65um_nom']
-params = ['temp_11_0um_nom', 'temp_12_0um_nom', 'cloud_fraction']
+params = ['temp_11_0um_nom', 'temp_12_0um_nom', 'refl_0_65um_nom', 'cloud_fraction']
 data_params = ['temp_11_0um_nom']
 label_params = ['cloud_fraction']
 
 
 DO_ZERO_OUT = False
 
-label_idx = 2
+label_idx = 3
 label_param = params[label_idx]
 print('data_params: ', data_params)
 print('label_params: ', label_params)
@@ -231,9 +231,13 @@ class SRCNN:
             tmp = normalize(tmp, param, mean_std_dct, add_noise=add_noise, noise_scale=noise_scale)
             data_norm.append(tmp)
         # --------
+        idx = params.index('refl_0_65um_nom')
+        tmp = input_data[:, idx, 3:131, 3:131]
+        tmp = normalize(tmp, param, mean_std_dct, add_noise=add_noise, noise_scale=noise_scale)
+        data_norm.append(tmp)
+        # --------
         tmp = input_data[:, label_idx, 3:131:2, 3:131:2]
         tmp = resample_2d_linear(x_64, y_64, tmp, t, s)
-        #tmp = normalize(tmp, 'temp_11_0um_nom', mean_std_dct)
         data_norm.append(tmp)
         # ---------
         data = np.stack(data_norm, axis=3)