diff --git a/modules/icing/util.py b/modules/icing/util.py
index 413d01ec40e58e41975e07e6a969200cc651514d..bc92b31ca8244d5a1fbb9a6e353319179826df76 100644
--- a/modules/icing/util.py
+++ b/modules/icing/util.py
@@ -4,7 +4,7 @@ import deeplearning.icing_cnn as icing_cnn
 from icing.pirep_goes import setup, time_filter_3
 from icing.moon_phase import moon_phase
 from util.util import get_time_tuple_utc, is_day, check_oblique, get_median, homedir, write_icing_file_nc4,\
-    write_icing_file_nc4_viirs,\
+    write_icing_file_nc4_viirs, get_training_parameters,\
     make_for_full_domain_predict, make_for_full_domain_predict_viirs_clavrx, prepare_evaluate
 from util.plot import make_icing_image
 from util.geos_nav import get_navigation, get_lon_lat_2d_mesh
@@ -15,43 +15,6 @@ import datetime
 # from scipy.signal import medfilt2d
 
 
-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',
-                           'cld_emiss_acha', 'conv_cloud_fraction', 'cld_reff_dcomp', 'cld_opd_dcomp', 'iwc_dcomp', 'lwc_dcomp']
-
-        if satellite == 'GOES16':
-            train_params_l1b = ['temp_10_4um_nom', 'temp_11_0um_nom', 'temp_12_0um_nom', 'temp_13_3um_nom', 'temp_3_75um_nom',
-                                'temp_6_2um_nom', 'temp_6_7um_nom', 'temp_7_3um_nom', 'temp_9_7um_nom',
-                                'refl_0_47um_nom', 'refl_0_65um_nom', 'refl_0_86um_nom', 'refl_1_38um_nom', 'refl_1_60um_nom']
-                                # 'refl_2_10um_nom']
-        elif satellite == 'H08':
-            train_params_l1b = ['temp_10_4um_nom', 'temp_12_0um_nom', 'temp_8_5um_nom', 'temp_3_75um_nom', 'refl_2_10um_nom',
-                                'refl_1_60um_nom', 'refl_0_86um_nom', 'refl_0_47um_nom']
-    else:
-        train_params_l2 = ['cld_height_acha', 'cld_geo_thick', 'cld_temp_acha', 'cld_press_acha', 'supercooled_cloud_fraction',
-                           'cld_emiss_acha', 'conv_cloud_fraction', 'cld_reff_acha', 'cld_opd_acha']
-
-        if use_dnb is True:
-            train_params_l2 = ['cld_height_acha', 'cld_geo_thick', 'cld_temp_acha', 'cld_press_acha', 'supercooled_cloud_fraction',
-                               'cld_emiss_acha', 'conv_cloud_fraction', 'cld_reff_dcomp', 'cld_opd_dcomp', 'iwc_dcomp', 'lwc_dcomp']
-
-        if satellite == 'GOES16':
-            train_params_l1b = ['temp_10_4um_nom', 'temp_11_0um_nom', 'temp_12_0um_nom', 'temp_13_3um_nom', 'temp_3_75um_nom',
-                                'temp_6_2um_nom', 'temp_6_7um_nom', 'temp_7_3um_nom', 'temp_9_7um_nom']
-        elif satellite == 'H08':
-            train_params_l1b = ['temp_10_4um_nom', 'temp_12_0um_nom', 'temp_8_5um_nom', 'temp_3_75um_nom']
-
-    if l1b_andor_l2 == 'both':
-        train_params = train_params_l1b + train_params_l2
-    elif l1b_andor_l2 == 'l1b':
-        train_params = train_params_l1b
-    elif l1b_andor_l2 == 'l2':
-        train_params = train_params_l2
-
-    return train_params, train_params_l1b, train_params_l2
-
-
 flt_level_ranges = {k: None for k in range(5)}
 flt_level_ranges[0] = [0.0, 2000.0]
 flt_level_ranges[1] = [2000.0, 4000.0]