| 1 | ; |
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| 2 | ; make energetics computations |
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| 3 | ; |
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| 4 | FUNCTION make_energetics, file_name, ncdf_db, TIME_1 = time_1, TIME_2 = time_2, ALL_DATA = all_data, ZMTYP = zmtyp |
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| 5 | |
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| 6 | @common |
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| 7 | @com_eg |
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| 8 | IF debug_w THEN print, ' ' |
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| 9 | IF debug_w THEN print, ' ENTER make_energetics...' |
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| 10 | IF debug_w THEN print, 'cmd_wrk.grid =', cmd_wrk.grid |
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| 11 | CASE cmd_wrk.grid OF |
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| 12 | 'T': source_model = 'opa' |
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| 13 | 'T#': source_model = 'opa#' |
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| 14 | 'T05': source_model = 'opa' |
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| 15 | 'T05#': source_model = 'opa#' |
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| 16 | ELSE: source_model = 'ipcc' |
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| 17 | ENDCASE |
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| 18 | |
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| 19 | ;; full vertical domain |
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| 20 | ;; imposes vert_type = '0' in plt_def |
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| 21 | vert_switch = 0 |
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| 22 | IF debug_w THEN BEGIN |
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| 23 | print, 'base_file_name:', base_file_name |
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| 24 | print, 'file_name:', file_name |
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| 25 | ENDIF |
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| 26 | ; |
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| 27 | ; Read T, S, U, V, W, taux, tauy |
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| 28 | ; |
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| 29 | print, ' Data size to read (M)= ', nxt*nyt*jpt*(5*nzt + 2)*1.e-6 |
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| 30 | |
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| 31 | CASE source_model OF |
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| 32 | 'opa': BEGIN |
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| 33 | tn = nc_read(file_name,'votemper', ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 34 | sn = nc_read(file_name,'vosaline', ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 35 | IF data_domain EQ 'pacific' THEN BEGIN |
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| 36 | file_namu = strmid(file_name, 0, strlen(file_name)-8)+'U_pac.nc' |
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| 37 | file_namv = strmid(file_name, 0, strlen(file_name)-8)+'V_pac.nc' |
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| 38 | file_namw = strmid(file_name, 0, strlen(file_name)-8)+'W_pac.nc' |
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| 39 | ENDIF ELSE BEGIN |
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| 40 | file_namu = strmid(file_name, 0, strlen(file_name)-4)+'U.nc' |
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| 41 | file_namv = strmid(file_name, 0, strlen(file_name)-4)+'V.nc' |
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| 42 | file_namw = strmid(file_name, 0, strlen(file_name)-4)+'W.nc' |
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| 43 | ENDELSE |
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| 44 | un = nc_read(file_namu,'vozocrtx', ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 45 | vn = nc_read(file_namv,'vomecrty', ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 46 | wn = nc_read(file_namw,'vovecrtz', ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 47 | tauxn = nc_read(file_namu,'sozotaux', ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 48 | tauyn = nc_read(file_namv,'sometauy', ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 49 | var_temp = 'votemper' |
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| 50 | file_temp = file_name |
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| 51 | END |
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| 52 | 'opa#': BEGIN |
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| 53 | tn = nc_read(file_name,'votemper', ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 54 | IF data_domain EQ 'pacific' THEN BEGIN |
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| 55 | file_nams = strmid(file_name, 0, strlen(file_name)-17)+'T_pac_vosaline.nc' |
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| 56 | file_namu = strmid(file_name, 0, strlen(file_name)-17)+'U_pac_vozocrtx.nc' |
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| 57 | file_namv = strmid(file_name, 0, strlen(file_name)-17)+'V_pac_vomecrty.nc' |
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| 58 | file_namw = strmid(file_name, 0, strlen(file_name)-17)+'W_pac_vovecrtz.nc' |
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| 59 | file_namsu = strmid(file_name, 0, strlen(file_name)-17)+'U_pac_sozotaux.nc' |
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| 60 | file_namsv = strmid(file_name, 0, strlen(file_name)-17)+'V_pac_sometauy.nc' |
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| 61 | ENDIF ELSE BEGIN |
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| 62 | file_nams = strmid(file_name, 0, strlen(file_name)-13)+'T_vosaline.nc' |
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| 63 | file_namu = strmid(file_name, 0, strlen(file_name)-13)+'U_vozocrtx.nc' |
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| 64 | file_namv = strmid(file_name, 0, strlen(file_name)-13)+'V_vomecrty.nc' |
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| 65 | file_namw = strmid(file_name, 0, strlen(file_name)-13)+'W_vovecrtz.nc' |
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| 66 | file_namsu = strmid(file_name, 0, strlen(file_name)-13)+'U_sozotaux.nc' |
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| 67 | file_namsv = strmid(file_name, 0, strlen(file_name)-13)+'V_sometauy.nc' |
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| 68 | ENDELSE |
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| 69 | sn = nc_read(file_nams,'vosaline', ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 70 | un = nc_read(file_namu,'vozocrtx', ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 71 | vn = nc_read(file_namv,'vomecrty', ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 72 | wn = nc_read(file_namw,'vovecrtz', ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 73 | tauxn = nc_read(file_namsu,'sozotaux', ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 74 | tauyn = nc_read(file_namsv,'sometauy', ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 75 | var_temp = 'votemper' |
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| 76 | file_temp = file_name |
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| 77 | source_model = 'opa' |
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| 78 | END |
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| 79 | 'ipcc': BEGIN |
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| 80 | base_file_name_grd = base_file_name+base_suffix |
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| 81 | tn = nc_read(base_file_name_grd+'_thetao.nc','thetao', ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 82 | sn = nc_read(base_file_name_grd+'_so.nc','so', ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 83 | un = nc_read(base_file_name_grd+'_uo.nc','uo', ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 84 | vn = nc_read(base_file_name_grd+'_vo.nc','vo', ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 85 | wn = nc_read(base_file_name_grd+'_wo.nc','wo', ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 86 | tauxn = nc_read(base_file_name_grd+'_tauu.nc','tauu', ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 87 | tauyn = nc_read(base_file_name_grd+'_tauv.nc','tauv', ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 88 | var_temp = 'thetao' |
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| 89 | file_temp = base_file_name_grd+'_thetao.nc' |
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| 90 | END |
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| 91 | ENDCASE |
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| 92 | |
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| 93 | t_unit = tn.units |
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| 94 | |
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| 95 | ; assign and free memory |
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| 96 | |
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| 97 | t = tn.data & tn = 0 |
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| 98 | s = sn.data & sn = 0 |
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| 99 | u = un.data & un = 0 |
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| 100 | v = vn.data & vn = 0 |
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| 101 | w = wn.data & wn = 0 |
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| 102 | tx = tauxn.data & tauxn = 0 |
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| 103 | ty = tauyn.data & tauyn = 0 |
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| 104 | |
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| 105 | rg = 9.81 |
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| 106 | |
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| 107 | print, ' read ok' |
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| 108 | |
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| 109 | ; rearrange data depending on source |
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| 110 | |
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| 111 | CASE source_model OF |
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| 112 | 'opa': BEGIN |
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| 113 | ; build mask |
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| 114 | IF valmask EQ 0. THEN BEGIN |
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| 115 | tmaskr = abs(s) gt 1.e-6 |
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| 116 | valmask = 1.e20 |
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| 117 | w(where (tmaskr EQ 0)) = valmask |
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| 118 | idxt = where (tmaskr EQ 0) |
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| 119 | t (where (tmaskr EQ 0)) = 0. |
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| 120 | s (where (tmaskr EQ 0)) = 0. |
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| 121 | tmaskr = 0 ; free memory |
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| 122 | ENDIF ELSE BEGIN |
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| 123 | idxt = where (t EQ valmask) |
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| 124 | IF idxt(0) NE -1 THEN t (idxt) = 0. |
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| 125 | IF idxt(0) NE -1 THEN s (idxt) = 0. |
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| 126 | ENDELSE |
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| 127 | |
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| 128 | ; transform W fields onto T grid |
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| 129 | maskw = w LT valmask/10. |
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| 130 | w_T = 0.5*( w*maskw + shift(w, 0, 0, -1, 0)*shift(maskw, 0, 0, -1, 0) ) |
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| 131 | w_T(*, *, (size(w))(3)-1, *) = w_T(*, *, (size(w))(3)-2, *) |
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| 132 | w = 0 |
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| 133 | maskw = 0 ; free memory |
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| 134 | |
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| 135 | END |
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| 136 | 'ipcc': BEGIN |
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| 137 | idx_t = where (t GT valmask/10) |
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| 138 | ; special case CCCMA |
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| 139 | IF strpos(cmd_wrk.exp, 'CCCMA') NE -1 THEN BEGIN |
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| 140 | ; transform W fields onto T grid |
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| 141 | maskw = w LT valmask/10. |
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| 142 | w_T = 0.5*( w*maskw + shift(w, 0, 0, -1, 0)*shift(maskw, 0, 0, -1, 0) ) |
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| 143 | w_T(*, *, (size(w))(3)-1, *) = w_T(*, *, (size(w))(3)-2, *) |
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| 144 | w = 0 |
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| 145 | w_T(idx_t) = valmask |
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| 146 | maskw = 0 ; free memory |
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| 147 | ENDIF ELSE w_T = w |
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| 148 | |
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| 149 | idx_2d = where (u(*, *, 0, 0) GT valmask/10.) |
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| 150 | IF idx_2d(0) NE -1 THEN tx(idx_2d) = valmask |
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| 151 | idx_2d = where (v(*, *, 0, 0) GT valmask/10.) |
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| 152 | IF idx_2d(0) NE -1 THEN ty(idx_2d) = valmask |
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| 153 | idx = where (t LT valmask/10.) |
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| 154 | IF t_unit NE "C" THEN BEGIN |
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| 155 | IF idx(0) NE -1 THEN t(idx) = t(idx)-273.15 |
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| 156 | ENDIF |
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| 157 | idx1 = n_elements(idx_t) |
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| 158 | idx_w = where (w_T GT valmask/10) |
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| 159 | idx2 = n_elements(idx_w) |
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| 160 | IF idx1 NE idx2 THEN BEGIN |
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| 161 | print, ' *** WARNING wo and thetao do not have same masks !', idx1, idx2, min(idx_t -idx_w), max(idx_t- idx_w) |
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| 162 | print, ' *** Setting wo to zero on all masked points' |
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| 163 | w_T(idx_w) = 0. |
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| 164 | ENDIF ELSE print, ' check these are 0 (W,T): ', min(idx_t -idx_w), max(idx_t- idx_w) |
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| 165 | w = 0 & idx = 0 & idx_t = 0 & idx_w = 0 ; free memory |
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| 166 | idxt=where(t GT valmask/10.) |
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| 167 | idxs=where(s GT valmask/10.) |
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| 168 | IF source_model EQ 'ipcc' THEN print, ' check these are 0 (T,S): ', min(idxt -idxs), max(idxt-idxs) |
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| 169 | IF idxt[0] NE -1 THEN t(idxt)=0. |
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| 170 | IF idxs[0] NE -1 THEN s(idxs)=0. |
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| 171 | idxs = 0 ; free memory |
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| 172 | |
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| 173 | END |
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| 174 | ENDCASE |
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| 175 | |
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| 176 | |
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| 177 | ; compute potential density rho |
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| 178 | |
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| 179 | print, ' compute rho...' |
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| 180 | |
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| 181 | |
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| 182 | sr=sqrt(abs(s)) |
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| 183 | r1=((((6.536332E-9*t-1.120083E-6)*t+1.001685E-4)*t $ |
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| 184 | -9.095290E-3)*t+6.793952E-2)*t+999.842594 |
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| 185 | r2=(((5.3875E-9*t-8.2467E-7)*t+7.6438E-5)*t-4.0899E-3)*t+8.24493E-1 |
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| 186 | r3=(-1.6546E-6*t+1.0227E-4)*t-5.72466E-3 |
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| 187 | rhop = ( ( 4.8314E-4*s + r3*sr +r2)*s +r1) |
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| 188 | print, ' rhop min/max', min(rhop), max(rhop) |
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| 189 | IF idxt[0] NE -1 THEN rhop(idxt) = valmask |
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| 190 | sr = 0 & r1 = 0 & r2 = 0 & r3 = 0 & t = 0 & s = 0 ; free memory |
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| 191 | |
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| 192 | ; compute mean profiles on T grid |
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| 193 | |
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| 194 | vargrid = 'T' |
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| 195 | IF valmask NE 0 THEN BEGIN |
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| 196 | rho_s = grossemoyenne(rhop, 'xyt', boite = zbox, NaN = valmask) |
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| 197 | ENDIF ELSE rho_s = grossemoyenne(rhop, 'xyt', boite = zbox) |
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| 198 | |
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| 199 | rho_s4d = replicate(1, nxt*nyt)#rho_s |
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| 200 | rho_s4d = reform(rho_s4d[*]#replicate(1, jpt), nxt, nyt, nzt, jpt, /overwrite) |
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| 201 | |
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| 202 | |
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| 203 | ; compute mean stability = d(rho_s)/dz (on W grid) |
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| 204 | |
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| 205 | rho_diff = (rho_s-shift(rho_s,-1))/shift(e3w, -1) |
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| 206 | rho_diff = shift(temporary(rho_diff), 1) |
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| 207 | rho_diff(0) = 0. |
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| 208 | |
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| 209 | ; transform onto T grid |
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| 210 | |
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| 211 | rho_diff_T = 0.5*(rho_diff+shift(rho_diff, -1)) |
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| 212 | rho_diff_T((size(rho_diff))(1)-1) = rho_diff((size(rho_diff))(1)-2) |
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| 213 | |
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| 214 | stab_inv = ABS(1./rho_diff_T) |
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| 215 | |
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| 216 | rho_diff_T = 0 ; free memory |
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| 217 | |
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| 218 | ; remove first 2 levels (MXL too unstable) |
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| 219 | |
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| 220 | stab_inv[0:1] = 0. |
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| 221 | |
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| 222 | ; test: remove only top level |
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| 223 | |
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| 224 | ; stab_inv[0:0] = 0. |
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| 225 | |
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| 226 | ; compute [(rho-rho_s)**2]/stability |
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| 227 | |
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| 228 | stab_inv = replicate(1, nxt*nyt)#stab_inv |
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| 229 | stab_inv = reform(stab_inv[*]#replicate(1, jpt), nxt, nyt, nzt, jpt, /overwrite) |
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| 230 | |
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| 231 | int_val2 = ((rhop-rho_s4d)^2)*stab_inv |
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| 232 | IF idxt[0] NE -1 THEN int_val2(idxt) = 0. |
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| 233 | |
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| 234 | print, ' compute APE...' |
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| 235 | |
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| 236 | ape = 0.5*rg*grossemoyenne(int_val2, 'xyz', /integration) |
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| 237 | |
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| 238 | int_val2 = 0 ; free memory |
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| 239 | |
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| 240 | ape_wr = ape |
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| 241 | ape = ape*1.e-18 |
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| 242 | ; |
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| 243 | ; compute buoyancy forcing bfx = int[(rho-rho_s).w]dxdydz |
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| 244 | ; |
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| 245 | print, ' compute BF...' |
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| 246 | |
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| 247 | int_val = (rhop-rho_s4d)*(w_T) |
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| 248 | ; remove first 2 levels (MXL too unstable) |
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| 249 | IF idxt[0] NE -1 THEN int_val(idxt) = 0. |
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| 250 | int_val[*, *, 0:1, *] = 0. |
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| 251 | |
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| 252 | bfx = rg*grossemoyenne(int_val, 'xyz', /integration) |
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| 253 | |
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| 254 | int_val = 0 ; free memory |
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| 255 | |
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| 256 | bfx_wr = bfx |
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| 257 | bfx_b = bfx |
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| 258 | bfx = bfx*1.e-11 |
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| 259 | |
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| 260 | ; compute wind work = int(tau.um)dx.dy where um=u(over 30 m) |
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| 261 | |
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| 262 | print, ' compute WW...' |
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| 263 | |
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| 264 | umean=grossemoyenne(u,'z',boite=[0,30]) |
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| 265 | vmean=grossemoyenne(v,'z',boite=[0,30]) |
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| 266 | |
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| 267 | idx = where(tx GT valmask/10.) |
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| 268 | idy = where(ty GT valmask/10.) |
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| 269 | idxu = where(umean GT valmask/10.) |
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| 270 | idyv = where(vmean GT valmask/10.) |
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| 271 | |
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| 272 | IF idx[0] NE -1 THEN tx(idx) = 0. |
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| 273 | IF idy[0] NE -1 THEN ty(idy) = 0. |
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| 274 | IF idxu[0] NE -1 THEN umean(idxu) = 0. |
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| 275 | IF idyv[0] NE -1 THEN vmean(idyv) = 0. |
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| 276 | |
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| 277 | dot_prodx = tx*umean |
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| 278 | dot_prody = ty*vmean |
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| 279 | |
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| 280 | wwx = grossemoyenne(dot_prodx, 'xy', /integration) |
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| 281 | wwy = grossemoyenne(dot_prody, 'xy', /integration) |
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| 282 | ww = wwx + wwy |
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| 283 | |
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| 284 | ww_wr = ww |
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| 285 | ww_b = ww |
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| 286 | ww = ww*1.e-11 |
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| 287 | wwx = wwx*1.e-11 |
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| 288 | wwy = wwy*1.e-11 |
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| 289 | |
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| 290 | ; compute forcing efficiency: stddev(B)/stddev(W) |
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| 291 | |
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| 292 | bfx_1mm = trends(bfx_b, 412, 't') |
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| 293 | bfx_sc = mean_sc |
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| 294 | ww_1mm = trends(ww_b, 412, 't') |
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| 295 | ww_sc = mean_sc |
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| 296 | efficiency = sqrt((moment(bfx_1mm))[1])/sqrt((moment(ww_1mm))[1]) |
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| 297 | efficiency_sc = sqrt((moment(bfx_sc[0:11]))[1])/sqrt((moment(ww_sc[0:11]))[1]) |
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| 298 | |
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| 299 | ; plotting stuff |
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| 300 | |
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| 301 | ps = 0 |
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| 302 | |
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| 303 | red = [0, 255, 0, 0, 0, 255] |
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| 304 | green = [0, 0, 255, 0, 0, 0] |
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| 305 | blue = [0, 0, 0, 255, 0, 255] |
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| 306 | red = [0, red, red, red, red, red, red, red ] |
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| 307 | green = [0, green, green, green, green, green, green, green] |
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| 308 | blue = [0, blue, blue, blue, blue, blue, blue, blue ] |
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| 309 | tvlct, red, green, blue |
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| 310 | |
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| 311 | IF cmd_wrk.out EQ 'ps' THEN ps = 1 |
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| 312 | |
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| 313 | IF ps EQ 1 THEN openps |
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| 314 | |
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| 315 | pltt, ape, 't', petit = [2, 4, 1], landscape = 1, /rempli, /BASICMARGES, title = 'APE (full) '+cmd_wrk.exp |
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| 316 | pltt, ww, 't', petit = [2, 4, 2], min = -2, max = 5, /noerase, /rempli, /BASICMARGES, title = 'Wind work (full) '+cmd_wrk.exp |
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| 317 | pltt, bfx, 't', petit = [2, 4, 8], min = -2, max = 5, color = 4, /noerase, /rempli, /BASICMARGES, title = 'B (full)' |
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| 318 | |
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| 319 | ape_1mm = trends(ape, 412, 't') |
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| 320 | pltt, ape_1mm, 't', petit = [2, 4, 3], /noerase, /rempli, /BASICMARGES, title = 'APE (inter)' |
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| 321 | jpt_b = jpt |
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| 322 | jpt = 24 |
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| 323 | pltt, mean_sc[0:23], 't', petit = [2, 4, 5], /noerase, /rempli, /BASICMARGES, title = 'APE (seasonal cycle x 2)' |
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| 324 | |
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| 325 | jpt = jpt_b |
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| 326 | |
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| 327 | ww_1mm = trends(ww, 412, 't') |
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| 328 | tmp = mean_sc |
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| 329 | wwx_1mm = trends(wwx, 412, 't') |
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| 330 | |
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| 331 | pltt, ww_1mm, 't', petit = [2, 4, 4], color = 2, /noerase, /rempli, /BASICMARGES, title = 'Interannual W (red) B (blue) [efficiency = '+string(strcompress(efficiency))+']' |
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| 332 | pltt, bfx_1mm*1.e-11, 't', petit = [2, 4, 4], /ov1d, color = 4, thick = 2, /noerase, /rempli, /BASICMARGES |
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| 333 | |
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| 334 | jpt_b = jpt |
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| 335 | jpt = 24 |
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| 336 | pltt, tmp[0:23], 't', petit = [2, 4, 6], min = -1, max = 3.5, /noerase, /rempli, /BASICMARGES, title = 'Seasonal Cycle x 2 (W total: black, B: blue, Wx/y: red/green)' |
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| 337 | pltt, mean_sc[0:23], 't', petit = [2, 4, 6], /ov1d, color = 2, thick = 2, /noerase, /rempli, /BASICMARGES |
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| 338 | wwy_1mm = trends(wwy, 412, 't') |
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| 339 | pltt, mean_sc[0:23], 't', petit = [2, 4, 6], /ov1d, color = 3, thick = 2, /noerase, /rempli, /BASICMARGES |
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| 340 | pltt, bfx_sc[0:23]*1.e-11, 't', petit = [2, 4, 6], /ov1d, color = 4, thick = 1, /noerase, /rempli, /BASICMARGES |
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| 341 | jpt = jpt_b |
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| 342 | |
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| 343 | ; compute and plot sst in nino 3 |
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| 344 | |
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| 345 | maxdepth = 10 |
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| 346 | IF gdept(0) GT maxdepth THEN maxdepth = gdept(0) |
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| 347 | |
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| 348 | domdef, [210., 280., -5., 5., 0., maxdepth] |
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| 349 | tn = nc_read(file_temp,var_temp, ncdf_db, TIME_1 = time_1, TIME_2 = time_2) |
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| 350 | st = tn.data |
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| 351 | sst = grossemoyenne(st, 'xyz') |
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| 352 | sst_wr = sst |
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| 353 | sst = trends(sst, 412, 't') |
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| 354 | |
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| 355 | pltt, sst, 't', petit = [2, 4, 7], /noerase, /rempli, /BASICMARGES, title = 'Nino3 SSTA' |
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| 356 | |
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| 357 | correlation = C_CORRELATE(ape, sst, [0]) |
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| 358 | |
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| 359 | IF ps EQ 1 THEN BEGIN |
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| 360 | closeps |
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| 361 | printps |
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| 362 | ENDIF |
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| 363 | |
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| 364 | ; write to ascii file |
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| 365 | |
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| 366 | get_lun, nuldat |
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| 367 | filename = cmd_wrk.exp+'_'+cmd_wrk.date1+'_'+cmd_wrk.spec+'_'+cmd_wrk.plt+'_sst.asc' |
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| 368 | openw, nuldat, asciidir+filename |
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| 369 | print, ' -> writing nino 3 sst data to ', asciidir+filename & print, ' ' |
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| 370 | printf, nuldat, sst_wr, format = '(f8.3)' |
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| 371 | free_lun, nuldat & close, nuldat |
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| 372 | |
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| 373 | get_lun, nuldat |
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| 374 | filename = cmd_wrk.exp+'_'+cmd_wrk.date1+'_'+cmd_wrk.spec+'_'+cmd_wrk.plt+'_ape.asc' |
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| 375 | openw, nuldat, asciidir+filename |
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| 376 | print, ' -> writing ape data to ', asciidir+filename & print, ' ' |
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| 377 | printf, nuldat, ape_wr, format = '(g10.4)' |
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| 378 | free_lun, nuldat & close, nuldat |
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| 379 | |
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| 380 | get_lun, nuldat |
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| 381 | filename = cmd_wrk.exp+'_'+cmd_wrk.date1+'_'+cmd_wrk.spec+'_'+cmd_wrk.plt+'_ww.asc' |
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| 382 | openw, nuldat, asciidir+filename |
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| 383 | print, ' -> writing ww data to ', asciidir+filename & print, ' ' |
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| 384 | printf, nuldat, ww_wr, format = '(g10.4)' |
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| 385 | free_lun, nuldat & close, nuldat |
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| 386 | |
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| 387 | get_lun, nuldat |
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| 388 | filename = cmd_wrk.exp+'_'+cmd_wrk.date1+'_'+cmd_wrk.spec+'_'+cmd_wrk.plt+'_bf.asc' |
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| 389 | openw, nuldat, asciidir+filename |
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| 390 | print, ' -> writing bf data to ', asciidir+filename & print, ' ' |
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| 391 | printf, nuldat, bfx_wr, format = '(g10.4)' |
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| 392 | free_lun, nuldat & close, nuldat |
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| 393 | |
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| 394 | ; check that d(APE)/dt ~ ww |
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| 395 | |
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| 396 | dapedt = (ape-shift(ape, 1))/(86400.*30.) |
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| 397 | ; pltt, dapedt-(ww*1.e11),'t',petit=[1,2,1],/rempli,/portrait |
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| 398 | ; pltt, dapedt/(ww*1.e11),'t',petit=[1,2,2],/rempli,/portrait,/noerase |
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| 399 | print, ' d(APE)/dt / wind work correlation', C_CORRELATE(dapedt, ww, [0]) |
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| 400 | print, ' APE/nino3 sst correlation=', correlation |
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| 401 | print, ' B/W efficiency (interannual) = ', efficiency |
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| 402 | print, ' B/W efficiency (SC) = ', efficiency_sc |
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| 403 | |
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| 404 | ; stop |
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| 405 | |
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| 406 | field = {name: '', data: rhop, legend: '', units: '', origin: '', direc: '', dim: 0} |
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| 407 | |
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| 408 | field.origin = tn.origin |
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| 409 | field.dim = tn.dim - 1 |
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| 410 | |
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| 411 | field.direc = 'xyzt' |
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| 412 | |
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| 413 | return, field |
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| 414 | END |
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