Abstract Mars is one of the most plausible terraforming target since there are many similarities between Mars and Earth To evaluate the environment of
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- こうた ほうねん
- 5 years ago
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Transcription
1 : /02/10
2 Abstract Mars is one of the most plausible terraforming target since there are many similarities between Mars and Earth To evaluate the environment of terraformed Mars we simulated a climate of terraformed Mars using an atmospheric general circulation model Since the land to sea ratio would have a large influence on climate we simulated a climate with four different sea levels Our simulation demonstrated that global mean surface temperature increases as the sea level rises Since albedo of sea surface is smaller than that of land surface heating by solar radiation increases with increasing the area of sea Also global mean precipitation increases as the sea level rises At equilibrium precipitation should be balanced by evaporation and evaporation over oceans is greater than over the continents When the area of ocean is less than 50% large area of southern hemisphere become arid Since the martian two hemispheres geography differ in elevation the southern hemisphere become a large continent An arid climate in continental interiors is due to the difficulty in the long distance transport of water vapor To make a comfortable planet to live in the surface area of oceans should be larger than 50%
3 ( ) 85% 51% 35% 14% 4 50% 50%
4 i
5 ii A A A A
6 iii A A A B ( ) C ( ) D ( ) E ( ) F ( )
7 iv 2.1 ( : ( ) (a) 85% (b) 51% (c) 35% (d) 14% (K) (a) 85% (b) 51% (c) 35% (d) 14% (mm/ ) (mm/ ) (a) 85% (b) 51% (c) 35% (d) 14% (W/m 2 ) (W/m 2 ) (a) 85% (b) 51% (c) 35% (d) 14% peta watts (a) 85% (b) 51% (c) 35% (d) 14% (W/m 2 ) (W/m 2 ) (W/m 2 ) (W/m 2 ) (a) 85% (b) 51% (c) 35% (d) 14% (K) (a) 85% (b) 51% (c) 35% (d) 14%
8 v 3.7 (mm/ ) (a) 85% (b) 51% (c) 35% (d) 14% (Pa) (a) 85% (b) 51% (c) 35% (d) 14% (K) (a) 85% (b) 51% (c) 35% (d) 14% (mm/ ) (a) 85% (b) 51% (c) 35% (d) 14% % (mm/ ) (m/s) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l) % (mm/ ) (m/s) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l) % (mm/ ) (m/s) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l) % (mm/ ) (m/s) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l)
9 vi % (cm) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l) % (cm) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l) % (cm) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l) (a) 85% (b) 51% (c) 35% (d) 14% : : : : : : : : : : : : : : : 46 B-1 (cm) (a) 85% (b) 51% (c) 35% (d) 14% C-2 85% (a) (W/m 2 ) (b) (W/m 2 ) (c) (W/m 2 ) (d) (W/m 2 ) (e) (W/m 2 ) (f) (W/m 2 )
10 vii C-3 51% (a) (W/m 2 ) (b) (W/m 2 ) (c) (W/m 2 ) (d) (W/m 2 ) (e) (W/m 2 ) (f) (W/m 2 ) C-4 35% (a) (W/m 2 ) (b) (W/m 2 ) (c) (W/m 2 ) (d) (W/m 2 ) (e) (W/m 2 ) (f) (W/m 2 ) C-5 14% (a) (W/m 2 ) (b) (W/m 2 ) (c) (W/m 2 ) (d) (W/m 2 ) (e) (W/m 2 ) (f) (W/m 2 ) D-6 (K) : 85% : 51% : 35% 14% E-7 85% (K) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l)12 69 E-8 51% (K) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l)12 71 E-9 35% (K) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l)12 73
11 viii E-10 14% (K) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l)12 75 F-11 85% (K) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l) F-12 51% (K) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l) F-13 35% (K) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l) F-14 14% (K) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l)
12 1 1 1 ( Kieffer et al 1992) 210K 6hPa 1/200 ( 1.1) 1.1: 1 [km] [AU] [m/s 2 ] [ ] [deg] [ ] [W/m 2 ] N 2 (78.08%) O 2 (20.95%) CO 2 (95.32%) N 2 (2.7%) Ar(1.6%) [K] [hpa]
13 1 2
14 DCPAM5( 2016; dcpam DCPAM5 2 Toon et al (1989) Chou and Lee (1996) Chou et al (2001) Manabe (1965) Relaxed Arakawa-Schubert (Moorthi and Suarez 1992) Mellor and Yamada level 2 (Mellor and Yamada ) 60m Manabe (1969) 2
15 : [km] 3396 [m/s 2 ] 3.72 [ ] [deg] [ ] 669 [W/m 2 ] 1370 N 2 + O 2 (CO 2 CH 4 ) [ ] T21( 21) Arakawa and Suarez (1983) 925
16 MOLA(Mars Orbiter Laser Altimeter) ( ) 2.1: ( : (a) 2000m ( 85%) (b) 0m ( 51%) (c) -2000m ( 35%) (d) -4000m ( 14%) ( 2.1) Matthews (1983)
17 2 6 (a) (b) (c) (d) 2.2: ( ) (a) 85% (b) 51% (c) 35% (d) 14% % 35% 14% 25 85% 35 3
18 (0.1) (0.3) ( 3.1) ( 14%) ( 85%) 10K ( 85%) ( 14%) 40K ( 3.1)
19 : 85% 51% 35% 14% [K] [W/m 2 ] [K] [K] [mm] ( 3.2) 3.2: 85% 51% 35% 14% [mm/ ]
20 % 35% ( ) 2 85% 51% 35% 51% 35% 14%
21 3 10 (a) (b) (c) (d) 3.1: (K) (a) 85% (b) 51% (c) 35% (d) 14%
22 % 51% 35% 30 14%
23 3 12 (a) (b) (c) (d) 3.2: (mm/ ) (mm/ ) (a) 85% (b) 51% (c) 35% (d) 14%
24 % 51% 35% %
25 3 14 (a) (b) (c) (d) 3.3: (W/m 2 ) (W/m 2 ) (a) 85% (b) 51% (c) 35% (d) 14%
26 3 15 (a) (b) (c) (d) 3.4: peta watts (a) 85% (b) 51% (c) 35% (d) 14%
27 ( ) ( ) 85% 51% 35% 14% ( 2.2) ( 3.2)
28 3 17 (a) (b) (c) (d) 3.5: (W/m 2 ) (W/m 2 ) (W/m 2 ) (W/m 2 ) (a) 85% (b) 51% (c) 35% (d) 14%
29 % 80 10K K 1.5
30 3 19 (a) (b) (c) (d) 3.6: (K) (a) 85% (b) 51% (c) 35% (d) 14%
31 % 51% 35% ( 3.8) 1
32 3 21 (a) (b) (c) (d) 3.7: (mm/ ) (a) 85% (b) 51% (c) 35% (d) 14%
33 3 22 (a) (b) (c) (d) 3.8: (Pa) (a) 85% (b) 51% (c) 35% (d) 14%
34 ( )
35 3 24 (a) (b) (c) (d) 3.9: (K) (a) 85% (b) 51% (c) 35% (d) 14%
36 ( ) ( )
37 3 26 (a) (b) (c) (d) 3.10: (mm/ ) (a) 85% (b) 51% (c) 35% (d) 14%
38 ( ) 4 6 ( ) 7 9 ( ) ( ) 85% ( 3.11) 51%( 3.12) 35%( 3.13) ( ) 14%( 3.14)
39 3 28 (a) (b) (c) (d) (e) (f)
40 3 29 (g) (h) (i) (j) (k) (l) 3.11: 85% (mm/ ) (m/s) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l)12
41 3 30 (a) (b) (c) (d) (e) (f)
42 3 31 (g) (h) (i) (j) (k) (l) 3.12: 51% (mm/ ) (m/s) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l)12
43 3 32 (a) (b) (c) (d) (e) (f)
44 3 33 (g) (h) (i) (j) (k) (l) 3.13: 35% (mm/ ) (m/s) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l)12
45 3 34 (a) (b) (c) (d) (e) (f)
46 3 35 (g) (h) (i) (j) (k) (l) 3.14: 14% (mm/ ) (m/s) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l)12
47 % 51% 35% 50 35% 14% ( )
48 3 37 (a) (b) (c) (d) (e) (f)
49 3 38 (g) (h) (i) (j) (k) (l) 3.15: 51% (cm) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l)12
50 3 39 (a) (b) (c) (d) (e) (f)
51 3 40 (g) (h) (i) (j) (k) (l) 3.16: 35% (cm) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l)12
52 3 41 (a) (b) (c) (d) (e) (f)
53 3 42 (g) (h) (i) (j) (k) (l) 3.17: 14% (cm) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l)12
54 ( net/note/clim/koppen.pdf) 300mm 100mm ( /) 300mm 100mm 4.1:
55 % ( ) 85%
56 4 45 (a) (b) (c) (d) 4.2: (a) 85% (b) 51% (c) 35% (d) 14% : : : : : : :
57 % 50% 4.3: : : : : : : : :
58 ( )
59 48 dcpam Ruby Ruby-DCL Gphys
60 49 A A-1 51% require "numru/ggraph" include NumRu vname0 = PRCP ys = 23 ye = 25 yyy = gphys0 = GPhys::NetCDF_IO.open(vname0+.nc,vname0) gphys0 = gphys0/1000.0*60.0*60.0*24.0* gphys0.units = Units[ mm/day ] gphysw = GPhys::NetCDF_IO.open(vname0+".nc", lat_weight ) weight = gphysw.val weight = weight / weight.sum(0) gphysy0 = gphys0.cut( time =>yyy*(ys-1)+1..yyy*(ys-1)+yyy).mean( time ) for i in ys+1..ye gphysy0 = gphysy0 + gphys0.cut( time =>yyy*(i-1)+1..yyy*(i-1)+yyy).mean( time ) end
61 50 gphysy0 = gphysy0/(ye-ys+1) gphysy0 = (gphysy0*weight.reshape!(1,gphysw.shape[0])).sum( lat ).mean( lon ) puts gphysy0
62 51 A-2 51% require "numru/ggraph" include NumRu vname0 = PRCP vname1 = EvapA ys = 23 ye = 25 yyy = gphys0 = GPhys::NetCDF_IO.open(vname0+.nc,vname0) gphys0 = gphys0/1000.0*60.0*60.0*24.0* gphys0.units = Units[ mm/day ] gphys1 = GPhys::NetCDF_IO.open(vname1+.nc,vname1) gphys1 = (gphys1/(2.5*10**6*1000.0))*60.0*60.0*24.0* gphys1.units = Units[ mm/day ] gphysy0 = gphys0.cut( time =>yyy*(ys-1)+1..yyy*(ys-1)+yyy).mean( time ) gphysy1 = gphys1.cut( time =>yyy*(ys-1)+1..yyy*(ys-1)+yyy).mean( time ) for i in ys+1..ye gphysy0 = gphysy0 + gphys0.cut( time =>yyy*(i-1)+1..yyy*(i-1)+yyy).mean( time ) gphysy1 = gphysy1 + gphys1.cut( time =>yyy*(i-1)+1..yyy*(i-1)+yyy).mean( time ) end gphysy0 = gphysy0/(ye-ys+1) gphysy1 = gphysy1/(ye-ys+1) gphysy0 = gphysy0.mean( lon ) gphysy1 = gphysy1.mean( lon ) DCL.gropn(4) DCL.sgpset( isub, 96) DCL.sgpset( lfull,true) DCL.uzfact(0.6)
63 52 GGraph.set_fig( viewport =>[0.25,0.7,0.15,0.6]) GGraph.set_axes( ytitle => ) GGraph.line(gphysy0,true, min =>0, max =>10, index =>45, legend =>true, title => wa GGraph.line(gphysy1,false, index =>25, legend => Evap ) DCL.grcls
64 53 A-3 51% require "numru/ggraph" include NumRu vname1 = PRCP vname2 = Decl ts = 24*669+1 te = 24* gphysw = GPhys::NetCDF_IO.open(vname1+".nc", lat_weight ) weight = gphysw.val weight = weight / weight.sum(0) gphys1 = GPhys::NetCDF_IO.open(vname1+".nc", vname1) gphys1 = gphys1/1000.0*60.0*60.0*24.0* gphys1.units = Units[ mm/day ] gphys2 = GPhys::NetCDF_IO.open(vname2+"_rank nc", vname2) DCL.gropn(4) DCL.sgpset( isub, 96) DCL.sgpset( lfull,true) DCL.uzfact(0.6) GGraph.set_fig( viewport =>[0.25,0.7,0.15,0.6]) GGraph.tone( gphys1.mean( lon ).cut(true,ts..te), true, max =>25, min =>1, exchang GGraph.line( gphys2.cut(ts..te), false, index =>9 ) GGraph.color_bar DCL.grcls
65 54 A-4 51% require "numru/ggraph" include NumRu vname0 = PRCP vname00 = sp_for_mars_t021_mgs_sl0000 vname1 = ys = 23 ye = 25 yyy = gphys = GPhys::IO.open(vname0+.nc,vname0 ) gphys = gphys/1000.0* * gphys.units = Units[ mm/day ] gphystopo = GPhys::IO.open(vname00+.nc, sfcindex ) gphysm = gphys.cut( time =>yyy*(ys-1)+1..yyy*(ys-1)+yyy).mean( time ) for i in ys+1..ye gphysm = gphysm + gphys.cut( time =>yyy*(i-1)+1..yyy*(i-1)+yyy).mean( time ) end gphysm = gphysm/(ye-ys+1) DCL.gropn(4) DCL.sgpset( isub, 96) DCL.sgpset( lfull,true) DCL.uzfact(0.6) DCL.udpset( LMSG,false) GGraph.set_fig( viewport =>[0.15,0.85,0.15,0.6]) GGraph.tone( gphysm,true, min =>1, max =>20, annotate =>false ) GGraph.set_contour_levels( levels =>[0,0.001], index =>[6,6]) GGraph.contour( gphystopo,false )
66 55 GGraph.color_bar DCL.grcls
67 56 A-5 51% require "numru/ggraph" include NumRu vname0 = PRCP vname1 = U vname2 = V vname00 = sp_for_mars_t021_mgs_sl0000 ys = 23 ye = 25 yyy = jan = 62 feb = mar = apr = may = jun = jul = aug = sep = oct = nov = dec = gphys = GPhys::IO.open(vname0+.nc,vname0) gphys = gphys/1000.0* * gphys.units = Units[ mm/day ] gphysu = GPhys::IO.open(vname1+.nc,vname1 ) gphysv = GPhys::IO.open(vname2+.nc,vname2 ) gphystopo = GPhys::IO.open(vname00+.nc, sfcindex ) months = [0,jan,feb,mar,apr,may,jun,jul,aug,sep,oct,nov]
68 57 monthe = [jan,feb,mar,apr,may,jun,jul,aug,sep,oct,nov,dec] tuki = ["Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"] DCL.swpset("iposx",50) DCL.swpset("iposy",50) DCL.swpset("lwait0",false) DCL.swpset("lwait1",false) DCL.swpset("lwait",false) DCL.swpset("ldump",true) DCL.gropn(4) DCL.sgpset( isub, 96) DCL.sgpset( lfull,true) DCL.uzfact(0.6) DCL.udpset( LMSG,false) GGraph.set_fig( viewport =>[0.15,0.85,0.15,0.6]) months.zip(monthe,tuki).each do ms,me,t gphysm = gphys.cut( time =>yyy*(ys-1)+ms+1..yyy*(ys-1)+me).mean( time ) gphysmu = gphysu.cut( time =>yyy*(ys-1)+ms+1..yyy*(ys-1)+me).mean( time ) gphysmv = gphysv.cut( time =>yyy*(ys-1)+ms+1..yyy*(ys-1)+me).mean( time ) for i in ys+1..ye gphysm = gphysm + gphys.cut( time =>yyy*(i-1)+ms+1..yyy*(i-1)+me).mean( time gphysmu = gphysmu + gphysu.cut( time =>yyy*(i-1)+ms+1..yyy*(i-1)+me).mean( time gphysmv = gphysmv + gphysv.cut( time =>yyy*(i-1)+ms+1..yyy*(i-1)+me).mean( time end gphysm = gphysm/(ye-ys+1) gphysmu = gphysmu/(ye-ys+1) gphysmv = gphysmv/(ye-ys+1) GGraph.tone( gphysm,true, min =>1, max =>45, title =>t, annotate =>false ) GGraph.vector( gphysmu,gphysmv,false, index =>755, flow_vect =>true, factor =>2.0 GGraph.set_contour_levels( levels =>[0,0.001], index =>[9]) GGraph.contour( gphystopo,false, ) GGraph.color_bar( landscape =>true) end DCL.grcls
69 58 A-6 51% require "numru/ggraph" include NumRu vname0 = Temp vname2 = PRCP vname00 = sp_for_mars_t021_mgs_sl0000 ys = 23 ye = 25 yyy = jan = 62 feb = mar = apr = may = jun = jul = aug = sep = oct = nov = dec = months = [0,jan,feb,mar,apr,may,jun,jul,aug,sep,oct,nov] monthe = [jan,feb,mar,apr,may,jun,jul,aug,sep,oct,nov,dec] number = [0,1,2,3,4,5,6,7,8,9,10,11] lats = [ , , , , , , ,-47.0 lons = [0,5.625,11.25,16.875,22.5,28.125,33.75,39.375,45,50.625,56.25,61.875,67.5,7 i = [0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,2
70 59 j =[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29 nlon = 64 nlat = 32 data = VArray.new( NArray.sfloat(nlon,nlat), {"long_name"=>"climate"}, "Climate" ) gphys = GPhys::IO.open(vname0+.nc,vname0) gphys2 = GPhys::IO.open(vname2+.nc,vname2) gphys2 = gphys2/1000.0* * gphys2.units = Units[ mm/day ] gphystopo = GPhys::IO.open(vname00+.nc, sfcindex ) gphyslon = gphys.axis( lon ) gphyslat = gphys.axis( lat ) r100 = 100.0/365.0 r300 = 300.0/365.0 gphysm = [] lons.zip(i).each do lon,i lats.zip(j).each do lat,j number.zip(months,monthe).each do k,ms,me gphysm[k] = gphys.cut( lat =>lat, lon =>lon, sig =>0.998, time =>yyy*(ys-1)+m for l in ys+1..ye gphysm[k] = gphysm[k]+gphys.cut( lat =>lat, lon =>lon, sig =>0.998, time => end gphysm[k] = gphysm[k]/(ye-ys+1) end gphysm2 = gphys2.cut( lat =>lat, lon =>lon, time =>yyy*(ys-1)+1..yyy*(ys-1)+yyy for l in ys+1..ye gphysm2 = gphysm2+gphys2.cut( lat =>lat, lon =>lon, time =>yyy*(l-1)+1..yyy*( end gphysm2 = gphysm2/(ye-ys+1)
71 60 if (gphysm.max < && gphysm.max <= ) then data[i,j] = 7 elsif (gphysm.max < && gphysm.max > ) then data[i,j] = 6 elsif (gphysm.max >= && gphysm2 < r300 && gphysm2 < r100) then data[i,j] = 2 elsif (gphysm.max >= && gphysm2 < r300 && gphysm2 > r100) then data[i,j] = 3 elsif (gphysm.max >= && gphysm2 >= r300 && gphysm.min >= ) then data[i,j] = 1 elsif (gphysm.max >= && gphysm2 >= r300 && <= gphysm.min && gphys data[i,j] = 4 elsif (gphysm.max >= && gphysm2 >= r300 && > gphysm.min) then data[i,j] = 5 else data[i,j] = 0 end end end gphys00 = GPhys.new( Grid.new(gphyslon,gphyslat), data ) DCL.gropn(4) DCL.sgpset( isub, 96) DCL.sgpset( lfull,true) DCL.uzfact(0.6) DCL.udpset( LMSG,false) GGraph.set_fig( viewport =>[0.15,0.85,0.15,0.6]) GGraph.set_tone_levels( levels =>[1,2,3,4,5,6,7], patterns =>[86999,75999,67999,559 GGraph.tone(gphys00,true) GGraph.set_contour_levels( levels =>[0,0.001], index =>[6,6]) GGraph.contour(gphystopo,false) GGraph.color_bar DCL.grcls
72 61
73 62 B ( ) B-1: (cm) (a) 85% (b) 51% (c) 35% (d) 14%
74 63 C ( ) (a) (b) (c) (d) (e) (f) C-2: 85% (a) (W/m 2 ) (b) (W/m 2 ) (c) (W/m 2 ) (d) (W/m 2 ) (e) (W/m 2 ) (f) (W/m 2 )
75 64 (a) (b) (c) (d) (e) (f) C-3: 51% (a) (W/m 2 ) (b) (W/m 2 ) (c) (W/m 2 ) (d) (W/m 2 ) (e) (W/m 2 ) (f) (W/m 2 )
76 65 (a) (b) (c) (d) (e) (f) C-4: 35% (a) (W/m 2 ) (b) (W/m 2 ) (c) (W/m 2 ) (d) (W/m 2 ) (e) (W/m 2 ) (f) (W/m 2 )
77 66 (a) (b) (c) (d) (e) (f) C-5: 14% (a) (W/m 2 ) (b) (W/m 2 ) (c) (W/m 2 ) (d) (W/m 2 ) (e) (W/m 2 ) (f) (W/m 2 )
78 67 D ( ) D-6: (K) : 85% : 51% : 35% 14%
79 68 E ( ) (a) (b) (c) (d) (e) (f)
80 69 (g) (h) (i) (j) (k) (l) E-7: 85% (K) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l)12
81 70 (a) (b) (c) (d) (e) (f)
82 71 (g) (h) (i) (j) (k) (l) E-8: 51% (K) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l)12
83 72 (a) (b) (c) (d) (e) (f)
84 73 (g) (h) (i) (j) (k) (l) E-9: 35% (K) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l)12
85 74 (a) (b) (c) (d) (e) (f)
86 75 (g) (h) (i) (j) (k) (l) E-10: 14% (K) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l)12
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90 79 (g) (h) (i) (j) (k) (l) F-12: 51% (K) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l)12
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92 81 (g) (h) (i) (j) (k) (l) F-13: 35% (K) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l)12
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94 83 (g) (h) (i) (j) (k) (l) F-14: 14% (K) (a)1 (b)2 (c)3 (d)4 (e)5 (f)6 (g)7 (h)8 (i)9 (j)10 (k)11 (l)12
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