1.1 --- /dev/null Thu Jan 01 00:00:00 1970 +0000
1.2 +++ b/co2/17.metric_plot.ncl Mon Jan 26 22:08:20 2009 -0500
1.3 @@ -0,0 +1,241 @@
1.4 +; ***********************************************
1.5 +; xy_4.ncl
1.6 +; ***********************************************
1.7 +load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_code.ncl"
1.8 +load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_csm.ncl"
1.9 +load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/contributed.ncl"
1.10 +load "/fis/cgd/cseg/people/jeff/clamp/co2/metrics_table.ncl"
1.11 +;************************************************
1.12 +begin
1.13 +;************************************************
1.14 +; read in data: observed
1.15 +;************************************************
1.16 + diri = "/fis/cgd/cseg/people/jeff/clamp_data/co2/"
1.17 + fili = "co2_globalView_98.nc"
1.18 + g = addfile (diri+fili,"r")
1.19 + val = g->CO2_SEAS
1.20 + lon = g->LON
1.21 + lat = g->LAT
1.22 + sta = chartostring(g->STATION)
1.23 + delete (g)
1.24 +
1.25 +;print (sta(0))
1.26 +
1.27 + ncase = dimsizes(lat)
1.28 +;print (ncase)
1.29 +
1.30 +;**************************************************************
1.31 +; get only the lowest level at each station
1.32 +;**************************************************************
1.33 + lat_tmp = lat
1.34 + lat_tmp@_FillValue = 1.e+36
1.35 +
1.36 + do n = 0,ncase-1
1.37 + if (.not. ismissing(lat_tmp(n))) then
1.38 + indexes = ind(lat(n) .eq. lat .and. lon(n) .eq. lon)
1.39 + if (dimsizes(indexes) .gt. 1) then
1.40 + lat_tmp(indexes(1:)) = lat_tmp@_FillValue
1.41 + end if
1.42 + delete (indexes)
1.43 + end if
1.44 + end do
1.45 +
1.46 + indexes = ind(.not. ismissing(lat_tmp))
1.47 +;print (dimsizes(indexes))
1.48 +;print (indexes)
1.49 +
1.50 + lat_ob = lat(indexes)
1.51 + lon_ob = lon(indexes)
1.52 + val_ob = val(indexes,:)
1.53 +;printVarSummary (val_ob)
1.54 +;print (lat_ob +"/"+lon_ob)
1.55 +
1.56 +;************************************************
1.57 +; read in model data
1.58 +;************************************************
1.59 + diri2 = "/fis/cgd/cseg/people/jeff/clamp_data/model/"
1.60 +; fili2 = "b30.061m_401_425_MONS_climo_atm.nc"
1.61 + fili2 = "b30.061n_1995-2004_MONS_climo_atm.nc"
1.62 +
1.63 + g = addfile(diri2+fili2,"r")
1.64 + x = g->CO2
1.65 + xi = g->lon
1.66 + yi = g->lat
1.67 + xdim = dimsizes(x)
1.68 + nlev = xdim(1)
1.69 + y = x(:,0,:,:)
1.70 +; printVarSummary (y)
1.71 +
1.72 +; get the co2 at the lowest level
1.73 + y = x(:,nlev-1,:,:)
1.74 +
1.75 +; change to unit of observed (u mol/mol)
1.76 +; Model_units [=] kgCO2 / kgDryAir
1.77 +; 28.966 = molecular weight of dry air
1.78 +; 44. = molecular weight of CO2
1.79 +; u mol = 1e-6 mol
1.80 +
1.81 + factor = (28.966/44.) * 1e6
1.82 + y = y * factor
1.83 +
1.84 + y@_FillValue = 1.e36
1.85 + y@units = "u mol/mol"
1.86 +; y = where(y0 .lt. 287.,y@_FillValue,y)
1.87 +; printVarSummary (y)
1.88 +; print (min(y)+"/"+max(y))
1.89 +
1.90 +; interpolate into observed station
1.91 +; note: model is 0-360E, 90S-90N
1.92 +
1.93 +; to be able to handle observation at (-89.98,-24.80)
1.94 + print (yi(0))
1.95 + yi(0) = -90.
1.96 +
1.97 + i = ind(lon_ob .lt. 0.)
1.98 + lon_ob(i) = lon_ob(i) + 360.
1.99 +
1.100 + yo = linint2_points_Wrap(xi,yi,y,True,lon_ob,lat_ob,0)
1.101 +
1.102 + val_model = yo(pts|:,time|:)
1.103 +; printVarSummary (val_model)
1.104 +; print (min(val_model)+"/"+max(val_model))
1.105 +
1.106 +; remove annual mean
1.107 + val_model = val_model - conform(val_model,dim_avg(val_model),0)
1.108 +; print (min(val_model)+"/"+max(val_model))
1.109 +
1.110 + nzone = 1
1.111 + do z = 0,nzone-1
1.112 +
1.113 + if (z .eq. 0) then
1.114 +; maximum score for the zone, 60N-90N
1.115 + score_max = 5.0
1.116 +; index of stations in this zone
1.117 + ind_z = ind(lat_ob .ge. 60.)
1.118 +; print (ind_z)
1.119 +; print (lat_ob(ind_z)+"/"+lon_ob(ind_z))
1.120 +; print (val_ob(ind_z,:))
1.121 +; print (val_model(ind_z,:))
1.122 + end if
1.123 +
1.124 + if (z .eq. 1) then
1.125 +; maximum score for the zone, 30N-60N
1.126 + score_max = 5.0
1.127 +; index of stations in this zone
1.128 + ind_z = ind(lat_ob .ge. 30. .and. lat_ob .lt. 60.)
1.129 +; print (ind_z)
1.130 +; print (lat_ob(ind_z)+"/"+lon_ob(ind_z))
1.131 +; print (val_ob(ind_z,:))
1.132 +; print (val_model(ind_z,:))
1.133 + end if
1.134 +
1.135 + if (z .eq. 2) then
1.136 +; maximum score for the zone, EQ-30N
1.137 + score_max = 5.0
1.138 +; index of stations in this zone
1.139 + ind_z = ind(lat_ob .ge. 0. .and. lat_ob .lt. 30.)
1.140 +; print (ind_z)
1.141 +; print (lat_ob(ind_z)+"/"+lon_ob(ind_z))
1.142 +; print (val_ob(ind_z,:))
1.143 +; print (val_model(ind_z,:))
1.144 + end if
1.145 +
1.146 + if (z .eq. 3) then
1.147 +; maximum score for the zone, 90S-EQ
1.148 + score_max = 5.0
1.149 +; index of stations in this zone
1.150 + ind_z = ind(lat_ob .lt. 0. )
1.151 +; print (ind_z)
1.152 +; print (lat_ob(ind_z)+"/"+lon_ob(ind_z))
1.153 +; print (val_ob(ind_z,:))
1.154 +; print (val_model(ind_z,:))
1.155 + end if
1.156 +
1.157 + npts = dimsizes(ind_z)
1.158 + print (npts)
1.159 +
1.160 + amp_ob = new((/npts/),float)
1.161 + amp_model = new((/npts/),float)
1.162 +
1.163 + amp_ratio_sta = new((/npts/),float)
1.164 + ccr_sta = new((/npts/),float)
1.165 + M_sta = new((/npts/),float)
1.166 + score_sta = new((/npts/),float)
1.167 +
1.168 + do n=0,npts-1
1.169 + amp_ob(n) = max(val_ob(ind_z(n),:)) - min(val_ob(ind_z(n),:))
1.170 + amp_model(n) = max(val_model(ind_z(n),:)) - min(val_model(ind_z(n),:))
1.171 +
1.172 + amp_ratio_sta(n) = amp_model(n)/amp_ob(n)
1.173 + ccr_sta(n) = esccr(val_ob(ind_z(n),:),val_model(ind_z(n),:),0)
1.174 + M_sta(n) = 1.-abs(amp_ratio_sta(n)-1.)
1.175 + score_sta(n) = (ccr_sta(n)*ccr_sta(n) + M_sta(n))*0.5 * score_max
1.176 +
1.177 + print (sta(ind_z(n))+"/"+lat(ind_z(n))+"/"+lon(ind_z(n))+"/"+amp_ratio_sta(n)+"/"+ccr_sta(n)+"/"+M_sta(n)+"/"+score_sta(n))
1.178 + end do
1.179 +
1.180 + amp_ratio_zone = avg(amp_ratio_sta)
1.181 + ccr_zone = avg(ccr_sta)
1.182 + M_zone = 1.- (sum(abs(amp_model-amp_ob)/(amp_model+amp_ob))/npts)
1.183 + score_zone = (ccr_zone*ccr_zone + M_zone)*0.5 * score_max
1.184 +
1.185 + print (npts+"/"+amp_ratio_zone+"/"+ccr_zone+"/"+M_zone+"/"+score_zone)
1.186 +;****************************************************************************
1.187 +; Cases [Model]
1.188 + case = (/ "Lat", "Lon", "AR" /)
1.189 + nCase = dimsizes(case ) ; # of Cases [Cases]
1.190 +
1.191 +; variables compared
1.192 + var = sta(ind_z)
1.193 + nVar = dimsizes(var) ; # of Variables
1.194 +
1.195 +; "Case A"
1.196 + CA_ratio = (/lat(ind_z)/)
1.197 +
1.198 +; "Case B"
1.199 + CB_ratio = (/lon(ind_z)/)
1.200 +
1.201 +; "Case C"
1.202 + CC_ratio = (/amp_ratio_sta/)
1.203 +
1.204 +
1.205 +; arrays to be passed to taylor_diagram. It will calculate the x xnd y coordinates.
1.206 + ratio = new ((/nCase, nVar/),typeof(CA_ratio) )
1.207 +
1.208 + ratio(0,:) = CA_ratio
1.209 + ratio(1,:) = CB_ratio
1.210 + ratio(2,:) = CC_ratio
1.211 +
1.212 +;**************************************************
1.213 +; fill an array for a "taylor metrics table"
1.214 +;**************************************************
1.215 +
1.216 +; season = (/ "ANN" /)
1.217 +; nSeason = dimsizes(season)
1.218 + season = (/ "" /)
1.219 + nSeason = dimsizes(season)
1.220 +
1.221 + table = new ( (/nCase,nVar/), typeof(ratio) )
1.222 + table(0,:) = CA_ratio
1.223 + table(1,:) = CB_ratio
1.224 + table(2,:) = CC_ratio
1.225 +
1.226 + tt_opt = True
1.227 + tt_opt@pltType= "ps" ; "eps" [default], "pdf", "ps"
1.228 + ; "png", "gif" [if you have ImageMajik 'convert']
1.229 +
1.230 + tt_opt@tableTitle = "Station in 60N_90N"
1.231 +
1.232 + varSource =var
1.233 +
1.234 + metrics_table("metrics", varSource, case , table, tt_opt)
1.235 +
1.236 + delete (ind_z)
1.237 + delete (amp_model)
1.238 + delete (amp_ob)
1.239 + delete (amp_ratio_sta)
1.240 + delete (ccr_sta)
1.241 + delete (M_sta)
1.242 + delete (score_sta)
1.243 + end do
1.244 +end