Changeset 22


Ignore:
Timestamp:
05/28/14 16:11:25 (10 years ago)
Author:
lahlod
Message:

modifs Laura

Location:
trunk/src/scripts_Laura
Files:
3 added
1 edited

Legend:

Unmodified
Added
Removed

  • trunk/src/scripts_Laura/read_SSMIS_test.py

    r21 r22  
    323323 
    324324 
    325 ######################## 
    326 # EVOLUTION TEMPORELLE # 
    327 ######################## 
    328  
    329 ## ZONE1 = Autour de "Dome C" (lon=123.23;lat=-75.06) - mois: JUNE ## 
    330 ## ch17 ## 
    331 #bbzone_CH17_JUN = nonzero((lon17_JUN >= 120.23) & (lon17_JUN <= 126.23) & (lat17_JUN >= -78.06) & (lat17_JUN <= -72.06)) 
    332  
    333 ## ch18 ## 
    334 #bbzone_CH18_JUN = nonzero((lon18_JUN >= 120.23) & (lon18_JUN <= 126.23) & (lat18_JUN >= -78.06) & (lat18_JUN <= -72.06)) 
    335  
    336  
    337 ## ZONE2 = Autre zone de glace de mer / de continent (lon entre -40 et -60 // lat entre -75 et -85) ## 
    338 ## ch17 ## 
    339 bbzone_CH17_FEB = nonzero((lon17_FEB >= -60.) & (lon17_FEB <= -40.) & (lat17_FEB >= -85.) & (lat17_FEB <= -75.)) 
    340 bbzone_CH17_APR = nonzero((lon17_APR >= -60.) & (lon17_APR <= -40.) & (lat17_APR >= -85.) & (lat17_APR <= -75.)) 
    341 bbzone_CH17_MAY = nonzero((lon17_MAY >= -60.) & (lon17_MAY <= -40.) & (lat17_MAY >= -85.) & (lat17_MAY <= -75.)) 
    342 bbzone_CH17_JUN = nonzero((lon17_JUN >= -60.) & (lon17_JUN <= -40.) & (lat17_JUN >= -85.) & (lat17_JUN <= -75.)) 
    343 bbzone_CH17_JUL = nonzero((lon17_JUL >= -60.) & (lon17_JUL <= -40.) & (lat17_JUL >= -85.) & (lat17_JUL <= -75.)) 
    344  
    345 ## ch18 ## 
    346 #bbzone_CH18_JUN = nonzero((lon18_JUN >= -60.) & (lon18_JUN <= -40.) & (lat18_JUN >= -85.) & (lat18_JUN <= -75.)) 
    347  
    348 ## ch 16 ## 
    349 #bbzone_CH16_JUN = nonzero((lon16_JUN >= 120.23) & (lon16_JUN <= 126.23) & (lat16_JUN >= -78.06) & (lat16_JUN <= -72.06)) 
    350  
    351  
    352 ## FEBUARY ## 
    353 emis17_FEB_moy = np.zeros([28],float) 
    354 tb17_FEB_moy = np.zeros([28],float) 
    355 ts17_FEB_moy = np.zeros([28],float) 
    356 orog17_FEB_moy = np.zeros([28],float) 
    357 for ijr in range (0,28): 
    358      print 'jour=', ijr+1 
    359      ## ch17 ## 
    360      ind_jr17_FEB = np.where(jjr17_FEB[bbzone_CH17_FEB]==ijr+1)[0] 
    361      a = emis17_FEB[bbzone_CH17_FEB][ind_jr17_FEB] 
    362      b = tb17_FEB[bbzone_CH17_FEB][ind_jr17_FEB] 
    363      c = ts17_FEB[bbzone_CH17_FEB][ind_jr17_FEB] 
    364      d = orog17_FEB[bbzone_CH17_FEB][ind_jr17_FEB] 
    365      emis17_FEB_moy[ijr] = mean(a[nonzero((a!=-500.)&(a<=1.))]) 
    366      tb17_FEB_moy[ijr] = mean(b[nonzero((b!=-500.)&(b!=0.))]) 
    367      ts17_FEB_moy[ijr] = mean(c[nonzero((c!=-500.)&(c!=0.))]) 
    368      orog17_FEB_moy[ijr] = mean(d[nonzero((d!=-500.))]) 
    369  
    370  
    371 ## APRIL ## 
    372 emis17_APR_moy = np.zeros([30],float) 
    373 tb17_APR_moy = np.zeros([30],float) 
    374 ts17_APR_moy = np.zeros([30],float) 
    375 orog17_APR_moy = np.zeros([30],float) 
    376 for ijr in range (0,30): 
    377      print 'jour=', ijr+1 
    378      ind_jr17_APR = np.where(jjr17_APR[bbzone_CH17_APR]==ijr+1)[0] 
    379      a = emis17_APR[bbzone_CH17_APR][ind_jr17_APR] 
    380      b = tb17_APR[bbzone_CH17_APR][ind_jr17_APR] 
    381      c = ts17_APR[bbzone_CH17_APR][ind_jr17_APR] 
    382      d = orog17_APR[bbzone_CH17_APR][ind_jr17_APR] 
    383      emis17_APR_moy[ijr] = mean(a[nonzero((a!=-500.)&(a<=1.))]) 
    384      tb17_APR_moy[ijr] = mean(b[nonzero((b!=-500.)&(b!=0.))]) 
    385      ts17_APR_moy[ijr] = mean(c[nonzero((c!=-500.)&(c!=0.))]) 
    386      orog17_APR_moy[ijr] = mean(d[nonzero((d!=-500.))]) 
    387  
    388  
    389 ## MAY ## 
    390 emis17_MAY_moy = np.zeros([31],float) 
    391 tb17_MAY_moy = np.zeros([31],float) 
    392 ts17_MAY_moy = np.zeros([31],float) 
    393 orog17_MAY_moy = np.zeros([31],float) 
    394 for ijr in range (0,31): 
    395      print 'jour=', ijr+1 
    396      ind_jr17_MAY = np.where(jjr17_MAY[bbzone_CH17_MAY]==ijr+1)[0] 
    397      a = emis17_MAY[bbzone_CH17_MAY][ind_jr17_MAY] 
    398      b = tb17_MAY[bbzone_CH17_MAY][ind_jr17_MAY] 
    399      c = ts17_MAY[bbzone_CH17_MAY][ind_jr17_MAY] 
    400      d = orog17_MAY[bbzone_CH17_MAY][ind_jr17_MAY] 
    401      emis17_MAY_moy[ijr] = mean(a[nonzero((a!=-500.)&(a<=1.))]) 
    402      tb17_MAY_moy[ijr] = mean(b[nonzero((b!=-500.)&(b!=0.))]) 
    403      ts17_MAY_moy[ijr] = mean(c[nonzero((c!=-500.)&(c!=0.))]) 
    404      orog17_MAY_moy[ijr] = mean(d[nonzero((d!=-500.))]) 
    405  
    406  
    407 ## JUNE ## 
    408 emis17_JUN_moy = np.zeros([30],float) 
    409 tb17_JUN_moy = np.zeros([30],float) 
    410 ts17_JUN_moy = np.zeros([30],float) 
    411 #orog17_JUN_moy = np.zeros([30],float) 
    412 #emis18_JUN_moy = np.zeros([30],float) 
    413 #tb18_JUN_moy = np.zeros([30],float) 
    414 #ts18_JUN_moy = np.zeros([30],float) 
    415 #emis16_JUN_moy = np.zeros([30],float) 
    416 #tb16_JUN_moy = np.zeros([30],float) 
    417 #ts16_JUN_moy = np.zeros([30],float) 
    418 for ijr in range (0,30): 
    419      print 'jour=', ijr+1 
    420      ind_jr17_JUN = np.where(jjr17_JUN[bbzone_CH17_JUN]==ijr+1)[0] 
    421      a = emis17_JUN[bbzone_CH17_JUN][ind_jr17_JUN] 
    422      b = tb17_JUN[bbzone_CH17_JUN][ind_jr17_JUN] 
    423      c = ts17_JUN[bbzone_CH17_JUN][ind_jr17_JUN] 
    424      d = orog17_JUN[bbzone_CH17_JUN][ind_jr17_JUN] 
    425      emis17_JUN_moy[ijr] = mean(a[nonzero((a!=-500.)&(a<=1.))]) 
    426      tb17_JUN_moy[ijr] = mean(b[nonzero((b!=-500.)&(b!=0.))]) 
    427      ts17_JUN_moy[ijr] = mean(c[nonzero((c!=-500.)&(c!=0.))]) 
    428 #     orog17_JUN_moy[ijr] = mean(d[nonzero((d!=-500.))]) 
    429      ## ch18 ## 
    430 #     ind_jr18 = np.where(jjr18_JUN[bbzone_CH18_JUN]==ijr+1)[0] 
    431 #     d = emis18_JUN[bbzone_CH18_JUN][ind_jr18] 
    432 #     e = tb18_JUN[bbzone_CH18_JUN][ind_jr18] 
    433 #     f = ts18_JUN[bbzone_CH18_JUN][ind_jr18] 
    434 #     emis18_JUN_moy[ijr] = mean(d[nonzero((d != -500.) & (d <= 1.))]) 
    435 #     tb18_JUN_moy[ijr] = mean(e[nonzero((e != -500.) & (e != 0.))]) 
    436 #     ts18_JUN_moy[ijr] = mean(f[nonzero((f != -500.) & (f != 0.))]) 
    437      ## ch16 ## 
    438 #     ind_jr16 = np.where(jjr16_JUN[bbzone_CH16_JUN]==ijr+1)[0] 
    439 #     g = emis16_JUN[bbzone_CH16_JUN][ind_jr16] 
    440 #     h = tb16_JUN[bbzone_CH16_JUN][ind_jr16] 
    441 #     l = ts16_JUN[bbzone_CH16_JUN][ind_jr16] 
    442 #     emis16_JUN_moy[ijr] = mean(g[nonzero((g != -500.) & (g <= 1.))]) 
    443 #     tb16_JUN_moy[ijr] = mean(h[nonzero((h != -500.) & (h != 0.))]) 
    444 #     ts16_JUN_moy[ijr] = mean(l[nonzero((l != -500.) & (l != 0.))]) 
    445  
    446  
    447 ## JULY ## 
    448 emis17_JUL_moy = np.zeros([31],float) 
    449 tb17_JUL_moy = np.zeros([31],float) 
    450 ts17_JUL_moy = np.zeros([31],float) 
    451 orog17_JUL_moy = np.zeros([31],float) 
    452 for ijr in range (0,31): 
    453      print 'jour=', ijr+1 
    454      ind_jr17_JUL = np.where(jjr17_JUL[bbzone_CH17_JUL]==ijr+1)[0] 
    455      a = emis17_JUL[bbzone_CH17_JUL][ind_jr17_JUL] 
    456      b = tb17_JUL[bbzone_CH17_JUL][ind_jr17_JUL] 
    457      c = ts17_JUL[bbzone_CH17_JUL][ind_jr17_JUL] 
    458      d = orog17_JUL[bbzone_CH17_JUL][ind_jr17_JUL] 
    459      emis17_JUL_moy[ijr] = mean(a[nonzero((a!=-500.)&(a<=1.))]) 
    460      tb17_JUL_moy[ijr] = mean(b[nonzero((b!=-500.)&(b!=0.))]) 
    461      ts17_JUL_moy[ijr] = mean(c[nonzero((c!=-500.)&(c!=0.))]) 
    462      orog17_JUL_moy[ijr] = mean(d[nonzero((d!=-500.))]) 
    463  
    464  
    465 ## plot evolution temporelle ## 
    466 ## FEBUARY ## 
    467 fig = plt.figure() 
    468 plt.subplot(3, 1, 1) 
    469 plt.title('FEBUARY') 
    470 plt.plot(arange(0, 28, 1), emis17_FEB_moy, c = 'b') 
    471 plt.ylabel('Emissivity') 
    472 xticks(arange(0, 28, 1), arange(1, 29, 1)) 
    473 xlim (0, 28) 
    474 grid(True) 
    475 plt.subplot(3, 1, 2) 
    476 plt.plot(arange(0, 28, 1), tb17_FEB_moy, c = 'g', label = 'Tb') 
    477 ylabel('Brightness temperature') 
    478 xticks(arange(0, 28, 1), arange(1, 29, 1)) 
    479 xlim (0, 28) 
    480 grid(True) 
    481 plt.subplot(3, 1, 3) 
    482 plt.plot(arange(0, 28, 1), ts17_FEB_moy, c = 'r', label = 'Ts') 
    483 plt.ylabel('Surface temperature') 
    484 xticks(arange(0, 28, 1), arange(1, 29, 1)) 
    485 xlim (0, 28) 
    486 grid(True) 
    487 fig.show() 
    488  
    489 ## from APRIL to JULY ## 
    490 emis1 = np.append(emis17_APR_moy, emis17_MAY_moy) 
    491 emis2 = np.append(emis1, emis17_JUN_moy) 
    492 emis17_moy = np.append(emis2, emis17_JUL_moy) 
    493 tb1 = np.append(tb17_APR_moy, tb17_MAY_moy) 
    494 tb2 = np.append(tb1, tb17_JUN_moy) 
    495 tb17_moy = np.append(tb2, tb17_JUL_moy) 
    496 ts1 = np.append(ts17_APR_moy, ts17_MAY_moy) 
    497 ts2 = np.append(ts1, ts17_JUN_moy) 
    498 ts17_moy = np.append(ts2, ts17_JUL_moy) 
    499 fig = plt.figure() 
    500 plt.subplot(3, 1, 1) 
    501 plt.plot(arange(0, 122, 1), emis17_moy, c = 'b') 
    502 plt.ylabel('Emissivity') 
    503 xticks(array([0, 30, 61, 91, 122]), date[1:]) 
    504 xlim (0, 122) 
    505 grid(True) 
    506 plt.subplot(3, 1, 2) 
    507 plt.plot(arange(0, 122, 1), tb17_moy, c = 'g', label = 'Tb') 
    508 ylabel('Brightness temperature') 
    509 xticks(array([0, 30, 61, 91, 122]), date[1:]) 
    510 xlim (0, 122) 
    511 grid(True) 
    512 plt.subplot(3, 1, 3) 
    513 plt.plot(arange(0, 122, 1), ts17_moy, c = 'r', label = 'Ts') 
    514 plt.ylabel('Surface temperature') 
    515 xticks(array([0, 30, 61, 91, 122]), date[1:]) 
    516 xlim (0, 122) 
    517 grid(True) 
    518 fig.show() 
    519  
    520 ## JUNE ## 
    521 ## ch17 - ch18 ## 
    522 fig=plt.figure() 
    523 plt.subplot(3,1,1) 
    524 plt.plot(arange(0,30,1),emis17_JUN_moy,label='91.66GHz-V',c='r') 
    525 plt.plot(arange(0,30,1),emis18_JUN_moy,label='91.66GHz-H',c='b') 
    526 plt.xticks(arange(1,31,1)) 
    527 grid(True) 
    528 ylabel('emissivity') 
    529 legend(loc=7) 
    530 plt.title('SSMIS - JUNE 2010') 
    531 plt.subplot(3,1,2) 
    532 plt.plot(arange(0,30,1),tb17_JUN_moy,label='91.66GHz-V',c='r') 
    533 plt.plot(arange(0,30,1),tb18_JUN_moy,label='91.66GHz-H',c='b') 
    534 plt.xticks(arange(1,31,1)) 
    535 grid(True) 
    536 ylabel('brightness temperature') 
    537 legend(loc=7) 
    538 plt.subplot(3,1,3) 
    539 plt.plot(arange(0,30,1),ts17_JUN_moy,label='91.66GHz-V',c='r') 
    540 plt.plot(arange(0,30,1),ts18_JUN_moy,label='91.66GHz-H',c='b') 
    541 plt.xticks(arange(1,31,1)) 
    542 grid(True) 
    543 ylabel('surface temperature') 
    544 legend(loc=7) 
    545 fig.show() 
    546 ## ch16 - ch17 ## 
    547 fig=plt.figure() 
    548 plt.subplot(3,1,1) 
    549 plt.plot(arange(0,30,1),emis16_JUN_moy,label='37GHz-V',c='r') 
    550 plt.plot(arange(0,30,1),emis17_JUN_moy,label='91.66GHz-V',c='g') 
    551 plt.xticks(arange(1,31,1)) 
    552 grid(True) 
    553 ylabel('emissivity') 
    554 legend(loc=7) 
    555 plt.title('SSMIS - JUNE 2010') 
    556 plt.subplot(3,1,2) 
    557 plt.plot(arange(0,30,1),tb16_JUN_moy,label='37GHz-V',c='r') 
    558 plt.plot(arange(0,30,1),tb17_JUN_moy,label='91.66GHz-V',c='g') 
    559 plt.xticks(arange(1,31,1)) 
    560 grid(True) 
    561 ylabel('brightness temperature') 
    562 legend(loc=7) 
    563 plt.subplot(3,1,3) 
    564 plt.plot(arange(0,30,1),ts16_JUN_moy,label='37GHz-V',c='r') 
    565 plt.plot(arange(0,30,1),ts17_JUN_moy,label='91.66GHz-V',c='g') 
    566 plt.xticks(arange(1,31,1)) 
    567 grid(True) 
    568 ylabel('surface temperature') 
    569 legend(loc=7) 
    570 fig.show() 
    571  
    572  
    573 ## calcul anomalie de Tb 
    574 ## FEBUARY ## 
    575 tb17_FEB_anom = np.zeros([28], float) 
    576 for ijr in range (0,28): 
    577      print 'jour=', ijr + 1 
    578      tb17_FEB_anom[ijr]=tb17_FEB_moy[ijr]-mean(tb17_FEB_moy) 
    579  
    580 ## APRIL ## 
    581 tb17_APR_anom = np.zeros([30], float) 
    582 for ijr in range (0,30): 
    583      print 'jour=', ijr + 1 
    584      tb17_APR_anom[ijr]=tb17_APR_moy[ijr]-mean(tb17_APR_moy) 
    585  
    586 ## MAY ## 
    587 bbnan = nonzero(isnan(tb17_MAY_moy) == False) 
    588 tb17_MAY_anom = np.zeros([31], float) 
    589 for ijr in range (0,31): 
    590      print 'jour=', ijr + 1 
    591      tb17_MAY_anom[ijr]=tb17_MAY_moy[ijr]-mean(tb17_MAY_moy[bbnan]) 
    592  
    593 ## JUNE ## 
    594 tb17_JUN_anom = np.zeros([30],float) 
    595 #tb18_JUN_anom = np.zeros([30],float) 
    596 for ijr in range (0,30): 
    597      print 'jour=', ijr + 1 
    598      tb17_JUN_anom[ijr]=tb17_JUN_moy[ijr]-mean(tb17_JUN_moy) 
    599 #     tb18_JUN_anom[ijr]=tb18_JUN_moy[ijr]-mean(tb18_JUN_moy) 
    600  
    601 ## JULY ## 
    602 tb17_JUL_anom = np.zeros([31],float) 
    603 for ijr in range (0,30): 
    604      print 'jour=', ijr + 1 
    605      tb17_JUL_anom[ijr]=tb17_JUL_moy[ijr]-mean(tb17_JUL_moy) 
    606  
    607  
    608  
    609 a1 = np.append(tb17_APR_anom, tb17_MAY_anom) 
    610 a2 = np.append(a1, tb17_JUN_anom) 
    611 tb17_month_anom = np.append(a2, tb17_JUL_anom) 
    612  
    613  
    614 ## for APRIL to JULY ## 
    615 fig = plt.figure() 
    616 plt.plot(arange(0, 122, 1), tb17_month_anom, c = 'k') 
    617 plt.plot(arange(0, 122, 1), np.zeros([122]), '--', c = 'r') 
    618 ylabel('Tb anomaly (K)') 
    619 xlim(0, 122) 
    620 xticks(array([0, 30, 61, 91 122]), date[1:]) 
    621 grid(True) 
    622 plt.title('SSMIS - zone2') 
    623 fig.show() 
    624  
    625 ## FEBRUARY ## 
    626 fig = plt.figure() 
    627 plt.plot(arange(0, 28, 1), tb17_FEB_anom, c = 'k') 
    628 plt.plot(arange(0, 28, 1), np.zeros([28]), '--', c = 'r') 
    629 ylabel('Tb anomaly (K)') 
    630 xlim(0, 27) 
    631 xticks(arange(0, 28, 1), arange(1, 29, 1)) 
    632 grid(True) 
    633 plt.xlabel('FABRUARY') 
    634 plt.title('SSMIS - zone2') 
    635 fig.show() 
    636  
    637 ## JUNE ## 
    638 fig=plt.figure() 
    639 plt.plot(arange(0,30,1),tb17_JUN_anom,label='91.66Ghz-V',c='r') 
    640 plt.plot(arange(0,30,1),tb18_JUN_anom,label='91.66GHz-H',c='b') 
    641 plt.plot(arange(0,31,1),np.zeros([31]),'--',c='k') 
    642 ylabel('Tb anomaly') 
    643 legend() 
    644 twinx().plot(arange(0,30,1),ts17_JUN_moy,label='surface temperature',c='g') 
    645 ylabel('surface temperature') 
    646 plt.xticks(arange(0, 30, 1), arange(1, 31, 1)) 
    647 grid(True) 
    648 plt.title('SSMIS - JUNE 2010') 
    649 fig.show() 
    650  
    651  
    652  
    653  
    654 ################ 
    655 # CARTOGRAPHIE # 
    656 ################ 
    657 ## Etude sur l'Antarctique ## 
    658 dx=5. 
    659 dy=5. 
    660 x0, x1 = -180, 180 
    661 y0, y1 = -90, -30 
    662  
    663  
    664 ## FEBRUARY ## 
    665 bbtb_ch17_FEB = nonzero((tb17_FEB != -500.) & (tb17_FEB != 0.)) 
    666 OUTZCH17_FEB = np.zeros([len(np.arange(y0, y1+1, dy)),len(np.arange(x0, x1+1, dx)),28], float) 
    667 outzch17_FEB = np.zeros([len(np.arange(y0, y1+1, dy)),len(np.arange(x0, x1+1, dx))], float) 
    668 lonch17_FEB = np.zeros([len(np.arange(x0, x1+1, dx))], float) 
    669 latch17_FEB = np.zeros([len(np.arange(y0, y1+1, dy))], float) 
    670 for ijr in range(0,28): 
    671     print 'jour=', ijr+1 
    672     ## ch17 ## 
    673     ind_jr17_FEB = np.where(jjr17_FEB[bbtb_ch17_FEB] == ijr+1)[0] 
    674     xx = lon17_FEB[bbtb_ch17_FEB][ind_jr17_FEB] 
    675     yy = lat17_FEB[bbtb_ch17_FEB][ind_jr17_FEB] 
    676     zz = tb17_FEB[bbtb_ch17_FEB][ind_jr17_FEB] 
    677     zz0 = min(zz) 
    678     zz1 = max(zz) 
    679     outz, outx, outy = ffgrid2.ffgrid(xx, yy, zz, dx, dy, x0, x1, y0, y1, zz0, zz1) 
    680     outzch17_FEB = outz 
    681     lonch17_FEB = outx 
    682     latch17_FEB = outy 
    683     OUTZCH17_FEB[:,:,ijr] = outzch17_FEB[:,:] 
    684  
    685 ## APRIL ## 
    686 bbtb_ch17_APR = nonzero((tb17_APR != -500.) & (tb17_APR != 0.)) 
    687 OUTZCH17_APR = np.zeros([len(np.arange(y0, y1+1, dy)),len(np.arange(x0, x1+1, dx)),30], float) 
    688 outzch17_APR = np.zeros([len(np.arange(y0, y1+1, dy)),len(np.arange(x0, x1+1, dx))], float) 
    689 lonch17_APR = np.zeros([len(np.arange(x0, x1+1, dx))], float) 
    690 latch17_APR = np.zeros([len(np.arange(y0, y1+1, dy))], float) 
    691 for ijr in range(0,30): 
    692     print 'jour=', ijr+1 
    693     ## ch17 ## 
    694     ind_jr17_APR = np.where(jjr17_APR[bbtb_ch17_APR] == ijr+1)[0] 
    695     xx = lon17_APR[bbtb_ch17_APR][ind_jr17_APR] 
    696     yy = lat17_APR[bbtb_ch17_APR][ind_jr17_APR] 
    697     zz = tb17_APR[bbtb_ch17_APR][ind_jr17_APR] 
    698     zz0 = min(zz) 
    699     zz1 = max(zz) 
    700     outz, outx, outy = ffgrid2.ffgrid(xx, yy, zz, dx, dy, x0, x1, y0, y1, zz0, zz1) 
    701     outzch17_APR = outz 
    702     lonch17_APR = outx 
    703     latch17_APR = outy 
    704     OUTZCH17_APR[:,:,ijr] = outzch17_APR[:,:] 
    705  
    706 ## MAY ## 
    707 bbtb_ch17_MAY = nonzero((tb17_MAY != -500.) & (tb17_MAY != 0.)) 
    708 OUTZCH17_MAY = np.zeros([len(np.arange(y0, y1+1, dy)),len(np.arange(x0, x1+1, dx)),31], float) 
    709 outzch17_MAY = np.zeros([len(np.arange(y0, y1+1, dy)),len(np.arange(x0, x1+1, dx))], float) 
    710 lonch17_MAY = np.zeros([len(np.arange(x0, x1+1, dx))], float) 
    711 latch17_MAY = np.zeros([len(np.arange(y0, y1+1, dy))], float) 
    712 for ijr in range(0,31): 
    713     print 'jour=', ijr+1 
    714     ## ch17 ## 
    715     ind_jr17_MAY = np.where(jjr17_MAY[bbtb_ch17_MAY] == ijr+1)[0] 
    716     xx = lon17_MAY[bbtb_ch17_MAY][ind_jr17_MAY] 
    717     yy = lat17_MAY[bbtb_ch17_MAY][ind_jr17_MAY] 
    718     zz = tb17_MAY[bbtb_ch17_MAY][ind_jr17_MAY] 
    719     zz0 = min(zz) 
    720     zz1 = max(zz) 
    721     outz, outx, outy = ffgrid2.ffgrid(xx, yy, zz, dx, dy, x0, x1, y0, y1, zz0, zz1) 
    722     outzch17_MAY = outz 
    723     lonch17_MAY = outx 
    724     latch17_MAY = outy 
    725     OUTZCH17_MAY[:,:,ijr] = outzch17_MAY[:,:] 
    726  
    727 ## JUNE ## 
    728 ## ch17 ## 
    729 bbtb_ch17_JUN = nonzero((tb17_JUN != -500.) & (tb17_JUN != 0.)) 
    730 OUTZCH17_JUN = np.zeros([len(np.arange(y0, y1+1, dy)),len(np.arange(x0, x1+1, dx)),30], float) 
    731 outzch17_JUN = np.zeros([len(np.arange(y0, y1+1, dy)),len(np.arange(x0, x1+1, dx))], float) 
    732 lonch17_JUN = np.zeros([len(np.arange(x0, x1+1, dx))], float) 
    733 latch17_JUN = np.zeros([len(np.arange(y0, y1+1, dy))], float) 
    734 ## ch18 ## 
    735 bbemis_ch18_JUN=nonzero((emis18_JUN!=-500.)&(emis18_JUN<1.)&(emis18_JUN>0.)) 
    736 bbtb_ch18_JUN=nonzero((tb18_JUN!=-500.)&(tb18_JUN!=0.)) 
    737 OUTZCH18_JUN = np.zeros([len(np.arange(y0, y1+1, dy)),len(np.arange(x0, x1+1, dx)),30], float) 
    738 outzch18_JUN = np.zeros([len(np.arange(y0, y1+1, dy)),len(np.arange(x0, x1+1, dx))], float) 
    739 lonch18_JUN=np.zeros([len(np.arange(x0, x1+1, dx))], float) 
    740 latch18_JUN=np.zeros([len(np.arange(y0, y1+1, dy))], float) 
    741 for ijr in range(0,30): 
    742     print 'jour=', ijr+1 
    743     ## ch17 ## 
    744     ind_jr17_JUN = np.where(jjr17_JUN[bbtb_ch17_JUN] == ijr+1)[0] 
    745     xx = lon17_JUN[bbtb_ch17_JUN][ind_jr17_JUN] 
    746     yy = lat17_JUN[bbtb_ch17_JUN][ind_jr17_JUN] 
    747     zz = tb17_JUN[bbtb_ch17_JUN][ind_jr17_JUN] 
    748     zz0 = min(zz) 
    749     zz1 = max(zz) 
    750     outz, outx, outy = ffgrid2.ffgrid(xx, yy, zz, dx, dy, x0, x1, y0, y1, zz0, zz1) 
    751     outzch17_JUN = outz 
    752     lonch17_JUN = outx 
    753     latch17_JUN = outy 
    754     OUTZCH17_JUN[:,:,ijr] = outzch17_JUN[:,:] 
    755     ## ch18 ## 
    756     ind_jr18_JUN = np.where(jjr18_JUN[bbtb_ch18_JUN] == ijr+1)[0] 
    757     xx = lon18_JUN[bbtb_ch18_JUN][ind_jr18_JUN] 
    758     yy = lat18_JUN[bbtb_ch18_JUN][ind_jr18_JUN] 
    759     zz = tb18_JUN[bbtb_ch18_JUN][ind_jr18_JUN] 
    760     zz0 = min(zz) 
    761     zz1 = max(zz) 
    762     outz, outx, outy = ffgrid2.ffgrid(xx, yy, zz, dx, dy, x0, x1, y0, y1, zz0, zz1) 
    763     outzch18_JUN = outz 
    764     lonch18_JUN = outx 
    765     latch18_JUN = outy 
    766     OUTZCH18_JUN[:,:,ijr] = outzch18_JUN[:,:] 
    767  
    768 ## JULY ## 
    769 bbtb_ch17_JUL = nonzero((tb17_JUL != -500.) & (tb17_JUL != 0.)) 
    770 OUTZCH17_JUL = np.zeros([len(np.arange(y0, y1+1, dy)),len(np.arange(x0, x1+1, dx)),31], float) 
    771 outzch17_JUL = np.zeros([len(np.arange(y0, y1+1, dy)),len(np.arange(x0, x1+1, dx))], float) 
    772 lonch17_JUL = np.zeros([len(np.arange(x0, x1+1, dx))], float) 
    773 latch17_JUL = np.zeros([len(np.arange(y0, y1+1, dy))], float) 
    774 for ijr in range(0,31): 
    775     print 'jour=', ijr+1 
    776     ## ch17 ## 
    777     ind_jr17_JUL = np.where(jjr17_JUL[bbtb_ch17_JUL] == ijr+1)[0] 
    778     xx = lon17_JUL[bbtb_ch17_JUL][ind_jr17_JUL] 
    779     yy = lat17_JUL[bbtb_ch17_JUL][ind_jr17_JUL] 
    780     zz = tb17_JUL[bbtb_ch17_JUL][ind_jr17_JUL] 
    781     zz0 = min(zz) 
    782     zz1 = max(zz) 
    783     outz, outx, outy = ffgrid2.ffgrid(xx, yy, zz, dx, dy, x0, x1, y0, y1, zz0, zz1) 
    784     outzch17_JUL = outz 
    785     lonch17_JUL = outx 
    786     latch17_JUL = outy 
    787     OUTZCH17_JUL[:,:,ijr] = outzch17_JUL[:,:] 
    788  
    789  
    790 ## calcul de la climatologie moyenne sur le mois et anomalie en chaque lon/lat ## 
    791 ## FEBRUARY ## 
    792 mean_outzch17_FEB = np.zeros([len(latch17_FEB), len(lonch17_FEB)], float) 
    793 for ilon in range (0,len(lonch17_FEB)): 
    794     for ilat in range (0,len(latch17_FEB)): 
    795         mean_outzch17_FEB[ilat,ilon] = mean(OUTZCH17_FEB[ilat,ilon,:]) 
    796  
    797 tbch17_anom_FEB = np.zeros([len(latch17_FEB),len(lonch17_FEB),28], float) 
    798 for ijr in range (0,28): 
    799     tbch17_anom_FEB[:,:,ijr] = OUTZCH17_FEB[:,:,ijr] - mean_outzch17_FEB[:,:] 
    800  
    801 ## APRIL ## 
    802 mean_outzch17_APR = np.zeros([len(latch17_APR), len(lonch17_APR)], float) 
    803 for ilon in range (0,len(lonch17_APR)): 
    804     for ilat in range (0,len(latch17_APR)): 
    805         mean_outzch17_APR[ilat,ilon] = mean(OUTZCH17_APR[ilat,ilon,:]) 
    806  
    807 tbch17_anom_APR = np.zeros([len(latch17_APR),len(lonch17_APR),30], float) 
    808 for ijr in range (0,30): 
    809     tbch17_anom_APR[:,:,ijr] = OUTZCH17_APR[:,:,ijr] - mean_outzch17_APR[:,:] 
    810  
    811 ## MAY ## 
    812 mean_outzch17_MAY = np.zeros([len(latch17_MAY), len(lonch17_MAY)], float) 
    813 for ilon in range (0,len(lonch17_MAY)): 
    814     for ilat in range (0,len(latch17_MAY)): 
    815         mean_outzch17_MAY[ilat,ilon] = mean(OUTZCH17_MAY[ilat,ilon,:]) 
    816  
    817 tbch17_anom_MAY = np.zeros([len(latch17_MAY),len(lonch17_MAY),31], float) 
    818 for ijr in range (0,31): 
    819     tbch17_anom_MAY[:,:,ijr] = OUTZCH17_MAY[:,:,ijr] - mean_outzch17_MAY[:,:] 
    820  
    821  
    822 ## JUNE ## 
    823 ## ch17 ## 
    824 mean_outzch17_JUN = np.zeros([len(latch17_JUN), len(lonch17_JUN)], float) 
    825 for ilon in range (0,len(lonch17_JUN)): 
    826     for ilat in range (0,len(latch17_JUN)): 
    827         mean_outzch17_JUN[ilat,ilon] = OUTZCH17_JUN[ilat,ilon,:].mean() 
    828  
    829 tbch17_anom_JUN = np.zeros([len(latch17_JUN),len(lonch17_JUN),30], float) 
    830 for ijr in range (0,30): 
    831     tbch17_anom_JUN[:,:,ijr] = OUTZCH17_JUN[:,:,ijr] - mean_outzch17_JUN[:,:] 
    832  
    833 ## ch18 ## 
    834 mean_outzch18_JUN = np.zeros([len(latch18_JUN), len(lonch18_JUN)], float) 
    835 for ilon in range (0,len(lonch18_JUN)): 
    836     for ilat in range (0,len(latch18_JUN)): 
    837         mean_outzch18_JUN[ilat,ilon] = OUTZCH18_JUN[ilat,ilon,:].mean() 
    838  
    839 tbch18_anom_JUN = np.zeros([len(latch18_JUN),len(lonch18_JUN),30], float) 
    840 for ijr in range (0,30): 
    841     tbch18_anom_JUN[:,:,ijr] = OUTZCH18_JUN[:,:,ijr] - mean_outzch18_JUN[:,:] 
    842  
    843  
    844  
    845 for ijr in range (23, 30): 
    846      figure() 
    847      plt.ion() 
    848      m = Basemap(llcrnrlon=-60, urcrnrlon=-40, llcrnrlat=-85, urcrnrlat=-75, projection='cyl', resolution='c', fix_aspect=True) 
    849      m.drawcoastlines(linewidth = 1) 
    850      m.drawparallels(np.arange(-85., 75., 2)) 
    851      m.drawmeridians(np.arange(-60., -40., 2)) 
    852      #m.fillcontinents() 
    853      clevs = arange(-25., 5., 0.1) 
    854      xii,yii = m(*np.meshgrid(lonch17_JUN, latch17_JUN)) 
    855      cs = m.contourf(xii, yii, tbch17_anom_JUN[:,:,ijr], clevs, cmap=cm.s3pcpn_l_r) 
    856      cbar = colorbar(cs) 
    857      cbar.set_label('Tb anomaly SSMIS CH17 - JUNE') 
    858      xticks(np.arange(-60., -40., 2)) 
    859      yticks(np.arange(-85., 75., 2)) 
    860      plt.savefig('/usr/home/lahlod/twice_d/figures_output_ANTARC/SSMIS/mean_tb_anomaly_map_'+str(ijr+1)+'JUN_ch17_SSMIS_Zoom_zone2') 
    861  
    862  
    863 figure() 
    864 plt.ion() 
    865 m = Basemap(llcrnrlon=-180, urcrnrlon=180, llcrnrlat=-90, urcrnrlat=-30, projection='cyl', resolution='c', fix_aspect=True) 
    866 m.drawcoastlines(linewidth = 1) 
    867 m.drawparallels(np.arange(-90., -30., 20)) 
    868 m.drawmeridians(np.arange(-180., 180., 20)) 
    869 #m.fillcontinents() 
    870 xii,yii = m(*np.meshgrid(lonch17_FEB, latch17_FEB)) 
    871 plt.xticks(arange(-180, 200, 20)) 
    872 plt.yticks(arange(-90, -30, 20)) 
    873 ## ch17 ## 
    874 clevs = arange(150., 270., 1.) 
    875 cs = m.contourf(xii, yii, mean_outzch17_FEB, clevs, cmap=cm.s3pcpn_l_r) 
    876 cbar = colorbar(cs) 
    877 cbar.set_label('Mean Tb FEB [CH17] - SSMIS') 
    878 ## BIAIS ch17-ch18 ##  
    879 biais_JUN = mean_outzch17_JUN - mean_outzch18_JUN 
    880 clevs = arange(0., 45., 1.) 
    881 cs = m.contourf(xii, yii, biais_JUN, clevs, cmap=cm.s3pcpn_l_r) 
    882 cbar = colorbar(cs) 
    883 cbar.set_label('Bias [CH17-CH18] of Mean Tb JUNE - SSMIS') 
    884  
    885 ## VARIANCE ch17 - ch18 ## 
    886 std1 = np.zeros([len(latch17_JUN), len(lonch17_JUN)], float) 
    887 for ilat in range (0, len(latch17_JUN)): 
    888     for ilon in range (0, len(lonch17_JUN)): 
    889         std1[ilat, ilon] = (mean_outzch17_JUN[ilat, ilon]**2)-(mean_outzch18_JUN[ilat, ilon]**2) 
    890  
    891  
    892 N = len(lonch17_JUN)*len(latch17_JUN) 
    893 std_JUN = std1/N 
    894 clevs = arange(0., 25., 0.1) 
    895 cs = m.contourf(xii, yii, std_JUN, clevs, cmap=cm.s3pcpn_l_r) 
    896 cbar = colorbar(cs) 
    897 cbar.set_label('Stantard deviation [CH17-CH18] of Mean Tb JUNE - SSMIS') 
    898  
    899  
    900  
    901 ########################## 
    902 # DIAGRAMME DE HOVMOLLER # 
    903 ########################## 
    904 # shape(tbch17_anom_JUN) = [ilat, ilon, ijr] 
    905 ## FEBRUARY ## 
    906 bbtranche17_FEB = nonzero((latch17_FEB >= -85.) & (latch17_FEB <= -75)) 
    907 mean_tbch17_anom_FEB = np.zeros([len(lonch17_FEB), 28], float) 
    908 for ilon in range (0, len(lonch17_FEB)): 
    909     for ijr in range (0,28): 
    910         mean_tbch17_anom_FEB[ilon,ijr] = mean(tbch17_anom_FEB[bbtranche17_FEB][:,ilon,ijr]) 
    911  
    912 y_time, x_space = np.meshgrid(arange(0,28,1), lonch17_FEB) 
    913 fig = plt.figure() 
    914 plt.pcolor(x_space, y_time, mean_tbch17_anom_FEB, cmap=cm.s3pcpn_l_r, vmin = -10., vmax = 15.) 
    915 plt.axis([-180., 180., 0, 28]) 
    916 cb = plt.colorbar() 
    917 cb.set_label('Tb anomaly - SSMIS CH17') 
    918 plt.xticks(arange(-180.,200.,40)) 
    919 plt.yticks(arange(0, 28, 1), arange (1, 29, 1)) 
    920 plt.xlabel('longitude') 
    921 plt.ylabel('FEBRUARY 2010') 
    922  
    923 ## MAY ## 
    924 bbtranche17_MAY = nonzero((latch17_MAY >= -85.) & (latch17_MAY <= -75)) 
    925 mean_tbch17_anom_MAY = np.zeros([len(lonch17_MAY), 31], float) 
    926 for ilon in range (0, len(lonch17_MAY)): 
    927     for ijr in range (0,31): 
    928         mean_tbch17_anom_MAY[ilon,ijr] = mean(tbch17_anom_MAY[bbtranche17_MAY][:,ilon,ijr]) 
    929  
    930 y_time, x_space = np.meshgrid(arange(0,31,1), lonch17_MAY) 
    931 fig = plt.figure() 
    932 plt.pcolor(x_space, y_time, mean_tbch17_anom_MAY, cmap=cm.s3pcpn_l_r, vmin = -12., vmax = 25.) 
    933 plt.axis([-180., 180., 0, 30]) 
    934 cb = plt.colorbar() 
    935 cb.set_label('Tb anomaly - SSMIS CH17') 
    936 plt.xticks(arange(-180.,200.,40)) 
    937 plt.yticks(arange(0, 30, 1), arange(1,31,1)) 
    938 plt.xlabel('longitude') 
    939 plt.ylabel('MAY 2010') 
    940  
    941 ## JUNE ## 
    942 bbtranche17_JUN = nonzero((latch17_JUN >= -85.) & (latch17_JUN <= -75)) 
    943 mean_tbch17_anom_JUN = np.zeros([len(lonch17_JUN), 30], float) 
    944 for ilon in range (0, len(lonch17_JUN)): 
    945     for ijr in range (0,30): 
    946         mean_tbch17_anom_JUN[ilon,ijr] = tbch17_anom_JUN[bbtranche17_JUN][:,ilon,ijr].mean() 
    947  
    948  
    949 y_time, x_space = np.meshgrid(arange(0,30,1), lonch17_APR) 
    950 fig = plt.figure() 
    951 plt.pcolor(x_space, y_time, mean_tbch17_anom_APR, cmap=cm.s3pcpn_l_r, vmin = -30., vmax = 25.) 
    952 plt.axis([-180., 180., 0, 29]) 
    953 cb = plt.colorbar() 
    954 cb.set_label('Tb anomaly - SSMIS CH17') 
    955 plt.xticks(arange(-180.,220.,40)) 
    956 plt.yticks(arange(0, 30, 1), arange(1,31,1)) 
    957 plt.xlabel('longitude') 
    958 plt.ylabel('JUNE 2010') 
    959  
     325############### fichiers par mois pour deux canaux (polars H et V) ################################## 
     326 
     327########## 
     328## ch12 ## 
     329########## 
     330 
     331f1 = '/net/dedale/usr/dedale/surf/lelod/ANTARC/SSMIS_CH12_ANTARC_' 
     332f3 = '2010.DAT' 
     333month = np.array(['FEBRUARY', 'APRIL', 'MAY', 'JUNE', 'JULY']) 
     334numlines = np.zeros([len(month)],int) 
     335 
     336for imo in range (0, len(month)): 
     337     print month[imo]  
     338     f = f1 + str(month[imo]) + f3 
     339     fichier = open(f, 'r') 
     340     numlines[imo] = 0 
     341     for line in fichier: numlines[imo] += 1 
     342 
     343      fichier.close() 
     344 
     345 
     346imo = 0 # FEB  
     347fichier = open(f1 + str(month[imo]) + f3, 'r') 
     348ssmis = np.zeros([18, numlines[imo]], float) 
     349for iligne in range (0,numlines[imo]): 
     350    line = fichier.readline() 
     351    liste = line.split() 
     352    for j in range(0,18): 
     353        ssmis[j,iligne] = float(liste[j]) 
     354 
     355 
     356    fichier.close 
     357 
     358 
     359ssch12_FEB=ssmis 
     360lon12_FEB=ssch12_FEB[0,:] 
     361lat12_FEB=ssch12_FEB[1,:] 
     362jjr12_FEB=ssch12_FEB[4,:] 
     363ts12_FEB=ssch12_FEB[8,:] 
     364emis12_FEB=ssch12_FEB[14,:] 
     365tb12_FEB=ssch12_FEB[13,:] 
     366tup12_FEB=ssch12_FEB[16,:] 
     367tdn12_FEB=ssch12_FEB[15,:] 
     368trans12_FEB=ssch12_FEB[17,:] 
     369orog12_FEB=ssch12_FEB[11,:] 
     370 
     371imo = 1 # APR  
     372fichier = open(f1 + str(month[imo]) + f3, 'r') 
     373ssmis = np.zeros([18, numlines[imo]], float) 
     374for iligne in range (0,numlines[imo]): 
     375    line = fichier.readline() 
     376    liste = line.split() 
     377    for j in range(0,18): 
     378        ssmis[j,iligne] = float(liste[j]) 
     379 
     380 
     381    fichier.close 
     382 
     383ssch12_APR=ssmis 
     384lon12_APR=ssch12_APR[0,:] 
     385lat12_APR=ssch12_APR[1,:] 
     386jjr12_APR=ssch12_APR[4,:] 
     387ts12_APR=ssch12_APR[8,:] 
     388emis12_APR=ssch12_APR[14,:] 
     389tb12_APR=ssch12_APR[13,:] 
     390tup12_APR=ssch12_APR[16,:] 
     391tdn12_APR=ssch12_APR[15,:] 
     392trans12_APR=ssch12_APR[17,:] 
     393orog12_APR=ssch12_APR[11,:] 
     394 
     395 
     396imo = 4 # JUL  
     397fichier = open(f1 + str(month[imo]) + f3, 'r') 
     398ssmis = np.zeros([18, numlines[imo]], float) 
     399for iligne in range (0,numlines[imo]): 
     400    line = fichier.readline() 
     401    liste = line.split() 
     402    for j in range(0,18): 
     403        ssmis[j,iligne] = float(liste[j]) 
     404 
     405 
     406    fichier.close 
     407 
     408ssch12_JUL=ssmis 
     409lon12_JUL=ssch12_JUL[0,:] 
     410lat12_JUL=ssch12_JUL[1,:] 
     411jjr12_JUL=ssch12_JUL[4,:] 
     412ts12_JUL=ssch12_JUL[8,:] 
     413emis12_JUL=ssch12_JUL[14,:] 
     414tb12_JUL=ssch12_JUL[13,:] 
     415tup12_JUL=ssch12_JUL[16,:] 
     416tdn12_JUL=ssch12_JUL[15,:] 
     417trans12_JUL=ssch12_JUL[17,:] 
     418orog12_JUL=ssch12_JUL[11,:] 
     419 
     420 
     421########## 
     422## ch13 ## 
     423########## 
     424 
     425f1 = '/net/dedale/usr/dedale/surf/lelod/ANTARC/SSMIS_CH13_ANTARC_' 
     426f3 = '2010.DAT' 
     427month = np.array(['FEBRUARY', 'APRIL', 'MAY', 'JUNE', 'JULY']) 
     428numlines = np.zeros([len(month)],int) 
     429 
     430for imo in range (0, len(month)): 
     431     print month[imo]  
     432     f = f1 + str(month[imo]) + f3 
     433     fichier = open(f, 'r') 
     434     numlines[imo] = 0 
     435     for line in fichier: numlines[imo] += 1 
     436 
     437      fichier.close() 
     438 
     439 
     440imo = 0 # FEB  
     441fichier = open(f1 + str(month[imo]) + f3, 'r') 
     442ssmis = np.zeros([18, numlines[imo]], float) 
     443for iligne in range (0,numlines[imo]): 
     444    line = fichier.readline() 
     445    liste = line.split() 
     446    for j in range(0,18): 
     447        ssmis[j,iligne] = float(liste[j]) 
     448 
     449 
     450    fichier.close 
     451 
     452 
     453ssch13_FEB=ssmis 
     454lon13_FEB=ssch13_FEB[0,:] 
     455lat13_FEB=ssch13_FEB[1,:] 
     456jjr13_FEB=ssch13_FEB[4,:] 
     457ts13_FEB=ssch13_FEB[8,:] 
     458emis13_FEB=ssch13_FEB[14,:] 
     459tb13_FEB=ssch13_FEB[13,:] 
     460tup13_FEB=ssch13_FEB[16,:] 
     461tdn13_FEB=ssch13_FEB[15,:] 
     462trans13_FEB=ssch13_FEB[17,:] 
     463orog13_FEB=ssch13_FEB[11,:] 
     464 
     465imo = 1 # APR  
     466fichier = open(f1 + str(month[imo]) + f3, 'r') 
     467ssmis = np.zeros([18, numlines[imo]], float) 
     468for iligne in range (0,numlines[imo]): 
     469    line = fichier.readline() 
     470    liste = line.split() 
     471    for j in range(0,18): 
     472        ssmis[j,iligne] = float(liste[j]) 
     473 
     474 
     475    fichier.close 
     476 
     477ssch13_APR=ssmis 
     478lon13_APR=ssch13_APR[0,:] 
     479lat13_APR=ssch13_APR[1,:] 
     480jjr13_APR=ssch13_APR[4,:] 
     481ts13_APR=ssch13_APR[8,:] 
     482emis13_APR=ssch13_APR[14,:] 
     483tb13_APR=ssch13_APR[13,:] 
     484tup13_APR=ssch13_APR[16,:] 
     485tdn13_APR=ssch13_APR[15,:] 
     486trans13_APR=ssch13_APR[17,:] 
     487orog13_APR=ssch13_APR[11,:] 
     488 
     489 
     490imo = 4 # JUL  
     491fichier = open(f1 + str(month[imo]) + f3, 'r') 
     492ssmis = np.zeros([18, numlines[imo]], float) 
     493for iligne in range (0,numlines[imo]): 
     494    line = fichier.readline() 
     495    liste = line.split() 
     496    for j in range(0,18): 
     497        ssmis[j,iligne] = float(liste[j]) 
     498 
     499 
     500    fichier.close 
     501 
     502ssch13_JUL=ssmis 
     503lon13_JUL=ssch13_JUL[0,:] 
     504lat13_JUL=ssch13_JUL[1,:] 
     505jjr13_JUL=ssch13_JUL[4,:] 
     506ts13_JUL=ssch13_JUL[8,:] 
     507emis13_JUL=ssch13_JUL[14,:] 
     508tb13_JUL=ssch13_JUL[13,:] 
     509tup13_JUL=ssch13_JUL[16,:] 
     510tdn13_JUL=ssch13_JUL[15,:] 
     511trans13_JUL=ssch13_JUL[17,:] 
     512orog13_JUL=ssch13_JUL[11,:] 
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