diff --git a/modules/deeplearning/srcnn_l1b_l2.py b/modules/deeplearning/srcnn_l1b_l2.py
index ddee109c313ba90346b6b90060a5157393a62c5a..5f5d4e75325748cad9f18c38a0a96484467fddbb 100644
--- a/modules/deeplearning/srcnn_l1b_l2.py
+++ b/modules/deeplearning/srcnn_l1b_l2.py
@@ -674,8 +674,10 @@ def run_restore_static(directory, ckpt_dir):
 
 def run_evaluate_static(in_file, out_file, ckpt_dir):
     h5f = h5py.File(in_file, 'r')
-    grd_a = get_grid_values_all(h5f, data_params[0])
-    grd_b = get_grid_values_all(h5f, 'cloud_fraction')
+    grd_a = get_grid_values_all(h5f, 'temp_11_0um_nom')
+    grd_b = get_grid_values_all(h5f, 'refl_0_65um_nom')
+    grd_c = get_grid_values_all(h5f, 'cloud_fraction')
+
     leny, lenx = grd_a.shape
     x = np.arange(lenx)
     y = np.arange(leny)
@@ -683,11 +685,12 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
     y_up = np.arange(0, leny, 0.5)
 
     grd_a = resample_2d_linear_one(x, y, grd_a, x_up, y_up)
-    grd_a = normalize(grd_a, data_params[0], mean_std_dct)
+    grd_a = normalize(grd_a, 'temp_11_0um_nom', mean_std_dct)
 
-    grd_b = resample_2d_linear_one(x, y, grd_b, x_up, y_up)
+    grd_b = normalize(grd_b, 'refl_0_65um_nom', mean_std_dct)
+    grd_c = resample_2d_linear_one(x, y, grd_c, x_up, y_up)
 
-    data = np.stack([grd_a, grd_b], axis=2)
+    data = np.stack([grd_a, grd_b, grd_c], axis=2)
     data = np.expand_dims(data, axis=0)
 
     nn = SRCNN()