1 | ! |
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2 | ! $Id: clouds_gno.F 1163 2009-05-20 14:11:21Z lguez $ |
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3 | ! |
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4 | C |
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5 | C================================================================================ |
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6 | C |
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7 | SUBROUTINE CLOUDS_GNO(klon,ND,R,RS,QSUB,PTCONV,RATQSC,CLDF) |
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8 | IMPLICIT NONE |
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9 | C |
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10 | C-------------------------------------------------------------------------------- |
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11 | C |
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12 | C Inputs: |
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13 | C |
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14 | C ND----------: Number of vertical levels |
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15 | C R--------ND-: Domain-averaged mixing ratio of total water |
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16 | C RS-------ND-: Mean saturation humidity mixing ratio within the gridbox |
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17 | C QSUB-----ND-: Mixing ratio of condensed water within clouds associated |
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18 | C with SUBGRID-SCALE condensation processes (here, it is |
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19 | C predicted by the convection scheme) |
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20 | C Outputs: |
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21 | C |
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22 | C PTCONV-----ND-: Point convectif = TRUE |
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23 | C RATQSC-----ND-: Largeur normalisee de la distribution |
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24 | C CLDF-----ND-: Fraction nuageuse |
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25 | C |
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26 | C-------------------------------------------------------------------------------- |
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27 | |
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28 | |
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29 | INTEGER klon,ND |
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30 | REAL R(klon,ND), RS(klon,ND), QSUB(klon,ND) |
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31 | LOGICAL PTCONV(klon,ND) |
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32 | REAL RATQSC(klon,ND) |
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33 | REAL CLDF(klon,ND) |
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34 | |
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35 | c -- parameters controlling the iteration: |
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36 | c -- nmax : maximum nb of iterations (hopefully never reached) |
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37 | c -- epsilon : accuracy of the numerical resolution |
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38 | c -- vmax : v-value above which we use an asymptotic expression for ERF(v) |
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39 | |
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40 | INTEGER nmax |
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41 | PARAMETER ( nmax = 10) |
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42 | REAL epsilon, vmax0, vmax(klon) |
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43 | PARAMETER ( epsilon = 0.02, vmax0 = 2.0 ) |
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44 | |
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45 | REAL min_mu, min_Q |
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46 | PARAMETER ( min_mu = 1.e-12, min_Q=1.e-12 ) |
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47 | |
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48 | INTEGER i,K, n, m |
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49 | REAL mu(klon), qsat(klon), delta(klon), beta(klon) |
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50 | real zu2(klon),zv2(klon) |
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51 | REAL xx(klon), aux(klon), coeff(klon), block(klon) |
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52 | REAL dist(klon), fprime(klon), det(klon) |
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53 | REAL pi, u(klon), v(klon), erfcu(klon), erfcv(klon) |
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54 | REAL xx1(klon), xx2(klon) |
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55 | real erf,kkk |
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56 | real sqrtpi,sqrt2,zx1,zx2,exdel |
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57 | c lconv = true si le calcul a converge (entre autre si qsub < min_q) |
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58 | LOGICAL lconv(klon) |
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59 | |
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60 | cym |
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61 | cldf(:,:)=0.0 |
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62 | |
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63 | pi = ACOS(-1.) |
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64 | sqrtpi=sqrt(pi) |
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65 | sqrt2=sqrt(2.) |
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66 | |
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67 | ptconv=.false. |
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68 | ratqsc=0. |
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69 | |
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70 | |
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71 | DO 500 K = 1, ND |
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72 | |
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73 | do i=1,klon ! vector |
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74 | mu(i) = R(i,K) |
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75 | mu(i) = MAX(mu(i),min_mu) |
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76 | qsat(i) = RS(i,K) |
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77 | qsat(i) = MAX(qsat(i),min_mu) |
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78 | delta(i) = log(mu(i)/qsat(i)) |
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79 | enddo ! vector |
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80 | |
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81 | C |
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82 | C *** There is no subgrid-scale condensation; *** |
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83 | C *** the scheme becomes equivalent to an "all-or-nothing" *** |
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84 | C *** large-scale condensation scheme. *** |
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85 | C |
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86 | |
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87 | C |
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88 | C *** Some condensation is produced at the subgrid-scale *** |
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89 | C *** *** |
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90 | C *** PDF = generalized log-normal distribution (GNO) *** |
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91 | C *** (k<0 because a lower bound is considered for the PDF) *** |
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92 | C *** *** |
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93 | C *** -> Determine x (the parameter k of the GNO PDF) such *** |
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94 | C *** that the contribution of subgrid-scale processes to *** |
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95 | C *** the in-cloud water content is equal to QSUB(K) *** |
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96 | C *** (equations (13), (14), (15) + Appendix B of the paper) *** |
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97 | C *** *** |
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98 | C *** Here, an iterative method is used for this purpose *** |
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99 | C *** (other numerical methods might be more efficient) *** |
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100 | C *** *** |
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101 | C *** NB: the "error function" is called ERF *** |
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102 | C *** (ERF in double precision) *** |
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103 | C |
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104 | |
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105 | c On commence par eliminer les cas pour lesquels on n'a pas |
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106 | c suffisamment d'eau nuageuse. |
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107 | |
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108 | do i=1,klon ! vector |
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109 | |
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110 | IF ( QSUB(i,K) .lt. min_Q ) THEN |
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111 | ptconv(i,k)=.false. |
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112 | ratqsc(i,k)=0. |
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113 | lconv(i) = .true. |
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114 | |
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115 | c Rien on a deja initialise |
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116 | |
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117 | ELSE |
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118 | |
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119 | lconv(i) = .FALSE. |
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120 | vmax(i) = vmax0 |
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121 | |
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122 | beta(i) = QSUB(i,K)/mu(i) + EXP( -MIN(0.0,delta(i)) ) |
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123 | |
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124 | c -- roots of equation v > vmax: |
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125 | |
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126 | det(i) = delta(i) + vmax(i)**2. |
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127 | if (det(i).LE.0.0) vmax(i) = vmax0 + 1.0 |
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128 | det(i) = delta(i) + vmax(i)**2. |
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129 | |
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130 | if (det(i).LE.0.) then |
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131 | xx(i) = -0.0001 |
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132 | else |
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133 | zx1=-sqrt2*vmax(i) |
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134 | zx2=SQRT(1.0+delta(i)/(vmax(i)**2.)) |
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135 | xx1(i)=zx1*(1.0-zx2) |
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136 | xx2(i)=zx1*(1.0+zx2) |
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137 | xx(i) = 1.01 * xx1(i) |
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138 | if ( xx1(i) .GE. 0.0 ) xx(i) = 0.5*xx2(i) |
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139 | endif |
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140 | if (delta(i).LT.0.) xx(i) = -0.5*SQRT(log(2.)) |
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141 | |
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142 | ENDIF |
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143 | |
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144 | enddo ! vector |
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145 | |
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146 | c---------------------------------------------------------------------- |
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147 | c Debut des nmax iterations pour trouver la solution. |
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148 | c---------------------------------------------------------------------- |
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149 | |
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150 | DO n = 1, nmax |
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151 | |
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152 | do i=1,klon ! vector |
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153 | if (.not.lconv(i)) then |
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154 | |
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155 | u(i) = delta(i)/(xx(i)*sqrt2) + xx(i)/(2.*sqrt2) |
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156 | v(i) = delta(i)/(xx(i)*sqrt2) - xx(i)/(2.*sqrt2) |
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157 | |
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158 | IF ( v(i) .GT. vmax(i) ) THEN |
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159 | |
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160 | IF ( ABS(u(i)) .GT. vmax(i) |
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161 | : .AND. delta(i) .LT. 0. ) THEN |
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162 | |
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163 | c -- use asymptotic expression of erf for u and v large: |
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164 | c ( -> analytic solution for xx ) |
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165 | exdel=beta(i)*EXP(delta(i)) |
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166 | aux(i) = 2.0*delta(i)*(1.-exdel) |
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167 | : /(1.+exdel) |
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168 | if (aux(i).lt.0.) then |
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169 | c print*,'AUX(',i,',',k,')<0',aux(i),delta(i),beta(i) |
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170 | aux(i)=0. |
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171 | endif |
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172 | xx(i) = -SQRT(aux(i)) |
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173 | block(i) = EXP(-v(i)*v(i)) / v(i) / sqrtpi |
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174 | dist(i) = 0.0 |
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175 | fprime(i) = 1.0 |
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176 | |
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177 | ELSE |
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178 | |
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179 | c -- erfv -> 1.0, use an asymptotic expression of erfv for v large: |
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180 | |
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181 | erfcu(i) = 1.0-ERF(u(i)) |
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182 | c !!! ATTENTION : rajout d'un seuil pour l'exponentiel |
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183 | aux(i) = sqrtpi*erfcu(i)*EXP(min(v(i)*v(i),100.)) |
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184 | coeff(i) = 1.0 - 1./2./(v(i)**2.) + 3./4./(v(i)**4.) |
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185 | block(i) = coeff(i) * EXP(-v(i)*v(i)) / v(i) / sqrtpi |
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186 | dist(i) = v(i) * aux(i) / coeff(i) - beta(i) |
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187 | fprime(i) = 2.0 / xx(i) * (v(i)**2.) |
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188 | : * ( coeff(i)*EXP(-delta(i)) - u(i) * aux(i) ) |
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189 | : / coeff(i) / coeff(i) |
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190 | |
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191 | ENDIF ! ABS(u) |
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192 | |
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193 | ELSE |
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194 | |
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195 | c -- general case: |
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196 | |
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197 | erfcu(i) = 1.0-ERF(u(i)) |
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198 | erfcv(i) = 1.0-ERF(v(i)) |
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199 | block(i) = erfcv(i) |
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200 | dist(i) = erfcu(i) / erfcv(i) - beta(i) |
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201 | zu2(i)=u(i)*u(i) |
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202 | zv2(i)=v(i)*v(i) |
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203 | if(zu2(i).gt.20..or. zv2(i).gt.20.) then |
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204 | c print*,'ATTENTION !!! xx(',i,') =', xx(i) |
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205 | c print*,'ATTENTION !!! klon,ND,R,RS,QSUB,PTCONV,RATQSC,CLDF', |
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206 | c .klon,ND,R(i,k),RS(i,k),QSUB(i,k),PTCONV(i,k),RATQSC(i,k), |
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207 | c .CLDF(i,k) |
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208 | c print*,'ATTENTION !!! zu2 zv2 =',zu2(i),zv2(i) |
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209 | zu2(i)=20. |
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210 | zv2(i)=20. |
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211 | fprime(i) = 0. |
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212 | else |
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213 | fprime(i) = 2. /sqrtpi /xx(i) /erfcv(i)**2. |
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214 | : * ( erfcv(i)*v(i)*EXP(-zu2(i)) |
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215 | : - erfcu(i)*u(i)*EXP(-zv2(i)) ) |
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216 | endif |
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217 | ENDIF ! x |
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218 | |
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219 | c -- test numerical convergence: |
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220 | |
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221 | ! if (beta(i).lt.1.e-10) then |
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222 | ! print*,'avant test ',i,k,lconv(i),u(i),v(i),beta(i) |
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223 | ! stop |
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224 | ! endif |
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225 | if (abs(fprime(i)).lt.1.e-11) then |
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226 | ! print*,'avant test fprime<.e-11 ' |
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227 | ! s ,i,k,lconv(i),u(i),v(i),beta(i),fprime(i) |
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228 | ! print*,'klon,ND,R,RS,QSUB', |
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229 | ! s klon,ND,R(i,k),rs(i,k),qsub(i,k) |
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230 | fprime(i)=sign(1.e-11,fprime(i)) |
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231 | endif |
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232 | |
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233 | |
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234 | if ( ABS(dist(i)/beta(i)) .LT. epsilon ) then |
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235 | c print*,'v-u **2',(v(i)-u(i))**2 |
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236 | c print*,'exp v-u **2',exp((v(i)-u(i))**2) |
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237 | ptconv(i,K) = .TRUE. |
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238 | lconv(i)=.true. |
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239 | c borne pour l'exponentielle |
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240 | ratqsc(i,k)=min(2.*(v(i)-u(i))**2,20.) |
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241 | ratqsc(i,k)=sqrt(exp(ratqsc(i,k))-1.) |
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242 | CLDF(i,K) = 0.5 * block(i) |
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243 | else |
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244 | xx(i) = xx(i) - dist(i)/fprime(i) |
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245 | endif |
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246 | c print*,'apres test ',i,k,lconv(i) |
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247 | |
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248 | endif ! lconv |
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249 | enddo ! vector |
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250 | |
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251 | c---------------------------------------------------------------------- |
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252 | c Fin des nmax iterations pour trouver la solution. |
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253 | ENDDO ! n |
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254 | c---------------------------------------------------------------------- |
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255 | |
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256 | 500 CONTINUE ! K |
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257 | |
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258 | RETURN |
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259 | END |
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260 | |
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261 | |
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262 | |
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