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6. Figures and Tables
Table 1
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Period 1960 - 2000 |
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84.32
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22.62
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15.78
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20.17
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20.17
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71.12
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10.20
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36.47
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23.89
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73.87
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50.12
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8.46
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32.07
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10.60
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90.39
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Normality 80-81 |
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79.24
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21.67
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24.44
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12.28
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12.28
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91.81
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13.77
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51.50
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37.63
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54.13
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22.08
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0.64
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6.24
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2.69
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62.71
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Niño 82-83 |
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84.32
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17.81
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20.21
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27.58
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27.58
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54.91
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8.38
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42.79
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5.27
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30.69
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50.14
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5.09
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55.63
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13.06
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35.95
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Niño 86-87 |
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87.32
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23.63
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10.79
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5.82
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5.82
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66.11
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9.66
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38.00
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12.57
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42.79
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38.16
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8.52
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37.65
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1.05
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44.36
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Niña 88-89 |
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77.99
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17.73
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13.57
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12.66
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12.66
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71.55
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12.67
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27.37
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6.05
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27.46
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51.91
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12.69
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47.06
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8.95
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60.78
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Normality 90-91 |
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93.41
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11.87
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8.45
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5.61
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5.61
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80.19
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14.09
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32.38
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32.54
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45.69
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32.98
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7.63
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10.50
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0.03
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43.52
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Normality 95-96 |
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89.57
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18.01
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20.27
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7.42
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7.42
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87.30
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13.70
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38.00
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29.76
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58.28
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64.86
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8.86
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25.86
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3.69
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63.92
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Niño 97-98 |
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89.93
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15.47
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20.05
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7.32
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7.32
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51.78
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6.80
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40.74
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2.73
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11.63
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64.81
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16.82
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54.78
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41.04
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51.79
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Figure 1 - CCA for the period 1960 - 2000
Figure 1: The tree first three heterogeneous correlation maps and their respective expansion coefficients below. SCF is the Squared Covariance Fraction while r[A,B] is the relation between expansion coefficients.
Figure 2 - Normality '80 - '81
Figure 6 - Normality '90 - '91
Figure 7 - Normality '95 - '96
Figure 9 - Comparison between TCC and Local VR radiation
Figure 10 - Comparison between ABL Height and Local VR radiation data
Table 2 - Inter-annual coefficients (1997 // 1998)
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To achieve the 1997/1998 ENSO impact from regional to local scale, inter-annual and inter-seasonal projection coefficients are calculated over the regional and local coupled geophysical variables. We specialized the computation for the inter-annual coefficient variation between 1997//1998 for the seasonal period SON (September-October-November) and DJF (December-January- February).
Table 3 - Inter- seasonal coefficients (real // expected)
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Inter-seasonal variations for transition JJA (June-July-August), SON and DJF seasonal periods from the second half of 1997 to the first season of 1998 was calculated to shown the inter-seasonal coupled evolution over projected normality values as pre-filtering the anomalies values