diff --git a/modules/deeplearning/cloud_fraction_fcn_abi.py b/modules/deeplearning/cloud_fraction_fcn_abi.py
index 717681f7508a49e7e3e3aecf018450119c4535a7..73593d9be3e2a5de043b2dcc5049d410783855fc 100644
--- a/modules/deeplearning/cloud_fraction_fcn_abi.py
+++ b/modules/deeplearning/cloud_fraction_fcn_abi.py
@@ -778,6 +778,8 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
 
     bt = get_grid_values_all(h5f, 'temp_11_0um_nom')
     refl = get_grid_values_all(h5f, 'refl_0_65um_nom')
+    bt = bt[0:2500, :]
+    refl = refl[0:2500, :]
     y_len, x_len = bt.shape[0], bt.shape[1]
     lons = get_grid_values_all(h5f, 'longitude')
     lats = get_grid_values_all(h5f, 'latitude')
@@ -788,15 +790,19 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
 
     # refl_lo = get_grid_values_all(h5f, 'refl_submin_ch01')
     refl_lo = get_grid_values_all(h5f, 'refl_0_65um_nom_min_sub')
+    relf_lo = refl_lo[0:2500, :]
     refl_lo = normalize(refl_lo, 'refl_0_65um_nom', mean_std_dct)
     # refl_hi = get_grid_values_all(h5f, 'refl_submax_ch01')
     refl_hi = get_grid_values_all(h5f, 'refl_0_65um_nom_max_sub')
+    refl_hi = refl_hi[0:2500, :]
     refl_hi = normalize(refl_hi, 'refl_0_65um_nom', mean_std_dct)
     # refl_std = get_grid_values_all(h5f, 'refl_substdev_ch01')
     refl_std = get_grid_values_all(h5f, 'refl_0_65um_nom_stddev_sub')
+    refl_std = refl_std[0:2500, :]
     refl_std = np.where(np.isnan(refl_std), 0, refl_std)
 
     cp = get_grid_values_all(h5f, label_param)
+    cp = cp[0:2500, :]
     cp = np.where(np.isnan(cp), 0, cp)
 
     # data = np.stack([bt, refl_lo, refl_hi, refl_std, cp], axis=2)