1 | #!/usr/bin/env python |
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2 | # -*- coding: utf-8 -*- |
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3 | import string |
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4 | import numpy as np |
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5 | import matplotlib.pyplot as plt |
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6 | from pylab import * |
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7 | from mpl_toolkits.basemap import Basemap |
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8 | from mpl_toolkits.basemap import shiftgrid, cm |
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9 | from netCDF4 import Dataset |
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10 | import arctic_map # function to regrid coast limits |
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11 | import cartesian_grid_test # function to convert grid from polar to cartesian |
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12 | import scipy.special |
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13 | import ffgrid2 |
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14 | import map_ffgrid |
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15 | from matplotlib import colors |
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16 | from matplotlib.font_manager import FontProperties |
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17 | import map_cartesian_grid |
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18 | |
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19 | |
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20 | |
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21 | |
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22 | MONTH = np.array(['01', '02', '03', '04', '05', '06', '07', '08', '09', '10', '11', '12']) |
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23 | month = np.array(['JANUARY', 'FEBRUARY', 'MARCH', 'APRIL', 'MAY', 'JUNE', 'JULY', 'AUGUST', 'SEPTEMBER', 'OCTOBER', 'NOVEMBER', 'DECEMBER']) |
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24 | month_day = np.array([31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]) |
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25 | M = len(month) |
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26 | |
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27 | frequ = np.array([23, 30, 50, 89]) |
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28 | |
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29 | |
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30 | ################################# |
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31 | # read .dat files of AMSUA data # |
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32 | ################################# |
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33 | AS = np.zeros([len(frequ), M], float) |
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34 | AL = np.zeros([len(frequ), M], float) |
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35 | for ifr in range (0, len(frequ)): |
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36 | fichier = open('/net/argos/data/parvati/lahlod/ARCTIC/AMSUA_ice_class/AMSUA' + str(frequ[ifr]) + '_data_classification_parameters_ice_no-ice_2009.dat','r') |
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37 | numlines = 0 |
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38 | for line in fichier: numlines += 1 |
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39 | fichier.close() |
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40 | fichier = open('/net/argos/data/parvati/lahlod/ARCTIC/AMSUA_ice_class/AMSUA' + str(frequ[ifr]) + '_data_classification_parameters_ice_no-ice_2009.dat','r') |
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41 | nbtotal = numlines - 1 |
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42 | iligne = 0 |
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43 | tot_area_spec = np.zeros([nbtotal],float) |
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44 | tot_area_lamb = np.zeros([nbtotal],float) |
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45 | while (iligne < nbtotal) : |
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46 | line=fichier.readline() |
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47 | # exemple : line = "0.22 2.3 5.0 6" |
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48 | liste = line.split() |
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49 | # exemple : listeCoord ['0.22', '2.3', '5.0', '6'] (liste de chaine de caract?es) |
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50 | tot_area_spec[iligne] = float(liste[9]) |
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51 | tot_area_lamb[iligne] = float(liste[10]) |
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52 | iligne=iligne+1 |
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53 | fichier.close() |
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54 | vec = np.arange(0, nbtotal + 51, 50) |
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55 | area_s = np.zeros([M], float) |
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56 | area_l = np.zeros([M], float) |
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57 | for imo in range (0, M): |
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58 | area_s[imo] = tot_area_spec[imo + vec[imo]] |
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59 | area_l[imo] = tot_area_lamb[imo + vec[imo]] |
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60 | AS[ifr, :] = area_s[:] |
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61 | AL[ifr, :] = area_l[:] |
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62 | |
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63 | |
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64 | |
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65 | ################################# |
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66 | # read .dat files of AMSUB data # |
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67 | ################################# |
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68 | fichier_B = open('/net/argos/data/parvati/lahlod/ARCTIC/AMSUB_ice_class/AMSUB89_data_classification_parameters_ice_no-ice_2009.dat','r') |
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69 | numlines = 0 |
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70 | for line in fichier_B: numlines += 1 |
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71 | |
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72 | fichier_B.close() |
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73 | fichier_B = open('/net/argos/data/parvati/lahlod/ARCTIC/AMSUB_ice_class/AMSUB89_data_classification_parameters_ice_no-ice_2009.dat','r') |
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74 | nbtotal = numlines - 1 |
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75 | iligne = 0 |
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76 | tot_area_spec_B = np.zeros([nbtotal],float) |
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77 | tot_area_lamb_B = np.zeros([nbtotal],float) |
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78 | while (iligne < nbtotal) : |
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79 | line=fichier_B.readline() |
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80 | # exemple : line = "0.22 2.3 5.0 6" |
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81 | liste = line.split() |
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82 | # exemple : listeCoord ['0.22', '2.3', '5.0', '6'] (liste de chaine de caract?es) |
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83 | tot_area_spec_B[iligne] = float(liste[9]) |
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84 | tot_area_lamb_B[iligne] = float(liste[10]) |
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85 | iligne=iligne+1 |
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86 | |
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87 | fichier_B.close() |
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88 | area_s_B = np.zeros([M], float) |
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89 | area_l_B = np.zeros([M], float) |
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90 | for imo in range (0, M): |
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91 | area_s_B[imo] = tot_area_spec_B[imo + vec[imo]] |
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92 | area_l_B[imo] = tot_area_lamb_B[imo + vec[imo]] |
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93 | |
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94 | |
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95 | |
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96 | ################################# |
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97 | # read .dat file of OSISAF data # |
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98 | ################################# |
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99 | fichier_osi = open('/net/argos/data/parvati/lahlod/ARCTIC/OSISAF_Ice_Types/OSISAF_daily_ice_no-ice_2009.dat','r') |
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100 | numlines = 0 |
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101 | for line in fichier_osi: numlines += 1 |
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102 | |
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103 | fichier_osi.close() |
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104 | fichier_osi = open('/net/argos/data/parvati/lahlod/ARCTIC/OSISAF_Ice_Types/OSISAF_daily_ice_no-ice_2009.dat','r') |
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105 | nbtotal = numlines - 1 |
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106 | iligne = 0 |
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107 | mo = np.zeros([nbtotal],object) |
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108 | tot_area_osi = np.zeros([nbtotal],float) |
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109 | while (iligne < nbtotal) : |
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110 | line=fichier_osi.readline() |
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111 | # exemple : line = "0.22 2.3 5.0 6" |
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112 | liste = line.split() |
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113 | # exemple : listeCoord ['0.22', '2.3', '5.0', '6'] (liste de chaine de caract?es) |
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114 | mo[iligne] = str(liste[0]) |
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115 | tot_area_osi[iligne] = float(liste[2]) |
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116 | iligne=iligne+1 |
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117 | |
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118 | fichier_osi.close() |
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119 | vec_osi = np.array([0, 31, 59, 90, 120, 151, 181, 212, 243, 273, 304, 334]) |
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120 | area_osi = np.zeros([M], float) |
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121 | for imo in range (0, M): |
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122 | area_osi[imo] = tot_area_osi[imo + vec_osi[imo]] |
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123 | |
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124 | |
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125 | |
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126 | ################################### |
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127 | # plot time evolution of ice area # |
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128 | ################################### |
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129 | ion() |
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130 | figure() |
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131 | plot(AS[0, :], 'c', label = 'AMSUA spec_23GHz') |
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132 | plot(AL[0, :], 'c--', label = 'AMSUA lamb_23GHz') |
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133 | plot(AS[1, :], 'r', label = 'AMSUA spec_30GHz') |
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134 | plot(AL[1, :], 'r--', label = 'AMSUA lamb_30GHz') |
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135 | plot(AS[2, :], 'm', label = 'AMSUA spec_50GHz') |
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136 | plot(AL[2, :], 'm--', label = 'AMSUA lamb_50GHz') |
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137 | plot(AS[3, :], 'g', label = 'AMSUA spec_89GHz') |
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138 | plot(AL[3, :], 'g--', label = 'AMSUA lamb_89GHz') |
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139 | plot(area_s_B[:], 'b', label = 'AMSUB spec_89GHz') |
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140 | plot(area_l_B[:], 'b--', label = 'AMSUB lamb_89GHz') |
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141 | plot(area_osi + 1500000, 'k', label = 'OSISAF + 1.5e7 (correction)') |
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142 | fontP = FontProperties() |
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143 | fontP.set_size('small') |
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144 | legend(loc = 3, prop = fontP) |
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145 | ylabel('total ice area (in square km)') |
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146 | xticks(np.arange(0, M, 1), month, rotation = 25) |
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147 | xlim(-1, M) |
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148 | grid() |
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149 | plt.savefig('/usr/home/lahlod/twice_d/fig_output_ARCTIC/fig_output_sea_ice_study/total_ice_area/compar_total_ice_area_AMSUA_AMSUB_SPEC_LAMB_corrected_OSISAF_2009.png') |
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150 | |
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151 | |
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152 | |
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153 | ############################### |
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154 | # calculation of bias and std # |
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155 | ############################### |
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156 | a = np.zeros([M], float) |
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157 | b = np.zeros([M], float) |
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158 | c = np.zeros([M], float) |
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159 | d = np.zeros([M], float) |
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160 | e = np.zeros([M], float) |
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161 | f = np.zeros([M], float) |
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162 | g = np.zeros([M], float) |
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163 | h = np.zeros([M], float) |
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164 | i = np.zeros([M], float) |
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165 | j = np.zeros([M], float) |
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166 | for imo in range (0, M): |
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167 | a[imo] = (AS[0, imo] - area_osi[imo]) / area_osi[imo] |
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168 | b[imo] = (AL[0, imo] - area_osi[imo]) / area_osi[imo] |
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169 | c[imo] = (AS[1, imo] - area_osi[imo]) / area_osi[imo] |
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170 | d[imo] = (AL[1, imo] - area_osi[imo]) / area_osi[imo] |
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171 | e[imo] = (AS[2, imo] - area_osi[imo]) / area_osi[imo] |
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172 | f[imo] = (AL[2, imo] - area_osi[imo]) / area_osi[imo] |
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173 | g[imo] = (AS[3, imo] - area_osi[imo]) / area_osi[imo] |
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174 | h[imo] = (AL[3, imo] - area_osi[imo]) / area_osi[imo] |
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175 | i[imo] = (area_s_B[imo] - area_osi[imo]) / area_osi[imo] |
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176 | j[imo] = (area_l_B[imo] - area_osi[imo]) / area_osi[imo] |
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177 | |
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178 | |
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179 | figure() |
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180 | plot(a, 'c', label = 'AMSUA spec 23GHz') |
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181 | plot(b, 'c--', label = 'AMSUA lamb 23GHz') |
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182 | plot(c, 'r', label = 'AMSUA spec 30GHz') |
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183 | plot(d, 'r--', label = 'AMSUA lamb 30GHz') |
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184 | plot(e, 'm', label = 'AMSUA spec 50GHz') |
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185 | plot(f, 'm--', label = 'AMSUA lamb 50GHz') |
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186 | plot(g, 'g', label = 'AMSUA spec 89GHz') |
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187 | plot(h, 'g--', label = 'AMSUA lamb 89GHz') |
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188 | plot(i, 'b', label = 'AMSUB spec 89GHz') |
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189 | plot(j, 'b--', label = 'AMSUB lamb 89GHz') |
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190 | plot(np.arange(0, M, 1), np.zeros([M], float), 'k') |
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191 | fontP = FontProperties() |
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192 | fontP.set_size('small') |
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193 | legend(loc = 3, prop = fontP) |
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194 | ylabel('bias of total ice area') |
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195 | xticks(np.arange(0, M, 1), month, rotation = 25) |
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196 | xlim(-1, M) |
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197 | grid() |
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198 | plt.savefig('/usr/home/lahlod/twice_d/fig_output_ARCTIC/fig_output_sea_ice_study/total_ice_area/bias_total_ice_area_AMSU_OSI_2009.png') |
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199 | |
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200 | |
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201 | |
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202 | |
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203 | |
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