1.1 --- /dev/null Thu Jan 01 00:00:00 1970 +0000
1.2 +++ b/all/09x.carbon_sink.ncl Mon Jan 26 22:08:20 2009 -0500
1.3 @@ -0,0 +1,890 @@
1.4 +;**************************************************************
1.5 +load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_code.ncl"
1.6 +load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_csm.ncl"
1.7 +load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/contributed.ncl"
1.8 +;**************************************************************
1.9 +procedure set_line(lines:string,nline:integer,newlines:string)
1.10 +begin
1.11 +; add line to ascci/html file
1.12 +
1.13 + nnewlines = dimsizes(newlines)
1.14 + if(nline+nnewlines-1.ge.dimsizes(lines))
1.15 + print("set_line: bad index, not setting anything.")
1.16 + return
1.17 + end if
1.18 + lines(nline:nline+nnewlines-1) = newlines
1.19 +; print ("lines = " + lines(nline:nline+nnewlines-1))
1.20 + nline = nline + nnewlines
1.21 + return
1.22 +end
1.23 +;**************************************************************
1.24 +; Main code.
1.25 +begin
1.26 +
1.27 + plot_type = "ps"
1.28 + plot_type_new = "png"
1.29 +
1.30 +;----------------------------------------------------------
1.31 +; edit current model for movel1_vs_model2
1.32 +
1.33 + if (isvar("compare")) then
1.34 + html_name2 = compare+"/table.html"
1.35 + html_new2 = html_name2 +".new"
1.36 + end if
1.37 +
1.38 +;----------------------------------------------------------
1.39 +; edit table.html for current model
1.40 +
1.41 + html_name = model_name+"/table.html"
1.42 + html_new = html_name +".new"
1.43 +
1.44 +;----------------------------------------------------------
1.45 +; get biome data: model
1.46 +
1.47 + biome_name_mod = "Model PFT Class"
1.48 +
1.49 + film_c = "class_pft_"+ model_grid +".nc"
1.50 + fm_c = addfile (dirs+film_c,"r")
1.51 + classmod = fm_c->CLASS_PFT
1.52 +
1.53 + delete (fm_c)
1.54 +
1.55 +; model data has 17 land-type classes
1.56 + nclass_mod = 17
1.57 +
1.58 +;------------------------------------
1.59 +; get model landfrac and area
1.60 +
1.61 + film_l = "lnd_"+ model_grid +".nc"
1.62 + fm_l = addfile (dirs+film_l,"r")
1.63 + landfrac = fm_l->landfrac
1.64 + area = fm_l->area
1.65 +
1.66 + delete (fm_l)
1.67 +
1.68 +; change area from km**2 to m**2
1.69 + area = area * 1.e6
1.70 +
1.71 +;-------------------------------------
1.72 +; take into account landfrac
1.73 +
1.74 +; area = area * landfrac
1.75 +
1.76 +; delete (landfrac)
1.77 +
1.78 +;---------------------------------------------------
1.79 +; read data: model, group 1
1.80 +
1.81 + fm = addfile (dirm+film4,"r")
1.82 +
1.83 + NPP1 = fm->NPP
1.84 +
1.85 + leafc = fm->LEAFC
1.86 + woodc = fm->WOODC
1.87 + frootc = fm->FROOTC
1.88 + VegC = leafc
1.89 + VegC = leafc + woodc + frootc
1.90 +
1.91 + litterc = fm->LITTERC
1.92 + cwdc = fm->CWDC
1.93 + LiCwC = litterc
1.94 + LiCwC = litterc + cwdc
1.95 +
1.96 + SoilC = fm->SOILC
1.97 +
1.98 + delete (fm)
1.99 +;---------------------------------------------------
1.100 +; read data: model, group 2
1.101 +
1.102 + fm = addfile (dirm+film5,"r")
1.103 +
1.104 + NPP2 = fm->NPP
1.105 + NEE2 = fm->NEE
1.106 + GPP2 = fm->GPP
1.107 +
1.108 + delete (fm)
1.109 +;---------------------------------------------------
1.110 +; Units for these variables are:
1.111 +
1.112 +;NPP1: g C/m^2/s
1.113 +;NPP2: g C/m^2/s
1.114 +;NEE2: g C/m^2/s
1.115 +;GPP2: g C/m^2/s
1.116 +
1.117 +;VegC: g C/m^2
1.118 +;LiCwC: g C/m^2
1.119 +;SoilC: g C/m^2
1.120 +
1.121 + nsec_per_year = 60*60*24*365
1.122 +
1.123 +; change unit to g C/m^2/year
1.124 +
1.125 + NPP1 = NPP1 * nsec_per_year * conform(NPP1,landfrac,(/1,2/))
1.126 + NPP2 = NPP2 * nsec_per_year * conform(NPP2,landfrac,(/1,2/))
1.127 + NEE2 = NEE2 * nsec_per_year * conform(NEE2,landfrac,(/1,2/))
1.128 + GPP2 = GPP2 * nsec_per_year * conform(GPP2,landfrac,(/1,2/))
1.129 +
1.130 + VegC = VegC * conform(VegC,landfrac,(/1,2/))
1.131 + LiCwC = LiCwC * conform(LiCwC,landfrac,(/1,2/))
1.132 + SoilC = SoilC * conform(SoilC,landfrac,(/1,2/))
1.133 +
1.134 + data_n = 8
1.135 +
1.136 +;*******************************************************************
1.137 +; Calculate "nice" bins for binning the data in equally spaced ranges
1.138 +;********************************************************************
1.139 +
1.140 +; using model biome class
1.141 + nclass = nclass_mod
1.142 +
1.143 + range = fspan(0,nclass,nclass+1)
1.144 +
1.145 +; print (range)
1.146 +; Use this range information to grab all the values in a
1.147 +; particular range, and then take an average.
1.148 +
1.149 + nx = dimsizes(range) - 1
1.150 +
1.151 +;==============================
1.152 +; put data into bins
1.153 +;==============================
1.154 +
1.155 +; using observed biome class
1.156 +; base = ndtooned(classob)
1.157 +; using model biome class
1.158 + base = ndtooned(classmod)
1.159 +
1.160 + area_1d = ndtooned(area)
1.161 +
1.162 +; output
1.163 +
1.164 + yvalues = new((/data_n,nx/),float) ; (per m2)
1.165 + yvalues_t = new((/data_n,nx/),float) ; (per biome)
1.166 +
1.167 +; Loop through each range, using base.
1.168 +
1.169 + do i=0,nx-1
1.170 +
1.171 + if (i.ne.(nx-1)) then
1.172 + idx = ind((base.ge.range(i)).and.(base.lt.range(i+1)))
1.173 + else
1.174 + idx = ind(base.ge.range(i))
1.175 + end if
1.176 +
1.177 + do n = 0,data_n-1
1.178 +
1.179 + if (n.eq.0) then
1.180 + data = ndtooned(area)
1.181 + end if
1.182 +
1.183 + if (n.eq.1) then
1.184 + data = ndtooned(NPP1)
1.185 + end if
1.186 +
1.187 + if (n.eq.2) then
1.188 + data = ndtooned(VegC)
1.189 + end if
1.190 +
1.191 + if (n.eq.3) then
1.192 + data = ndtooned(LiCwC)
1.193 + end if
1.194 +
1.195 + if (n.eq.4) then
1.196 + data = ndtooned(SoilC)
1.197 + end if
1.198 +
1.199 + if (n.eq.5) then
1.200 + data = ndtooned(NPP2)
1.201 + end if
1.202 +
1.203 + if (n.eq.6) then
1.204 + data = ndtooned(NEE2)
1.205 + end if
1.206 +
1.207 + if (n.eq.7) then
1.208 + data = ndtooned(GPP2)
1.209 + end if
1.210 +
1.211 +; Calculate sum and average
1.212 +
1.213 + if (.not.any(ismissing(idx))) then
1.214 + if (n.eq.0) then
1.215 + yvalues(n,i) = sum(data(idx))
1.216 + yvalues_t(n,i) = sum(data(idx))
1.217 + else
1.218 + yvalues(n,i) = avg(data(idx))
1.219 + yvalues_t(n,i) = sum(data(idx)*area_1d(idx))
1.220 + end if
1.221 + else
1.222 + yvalues(n,i) = yvalues@_FillValue
1.223 + yvalues_t(n,i) = yvalues@_FillValue
1.224 + end if
1.225 +
1.226 +;#############################################################
1.227 +; using model biome class:
1.228 +; set the following 4 classes to _FillValue:
1.229 +; (3)Needleleaf Deciduous Boreal Tree,
1.230 +; (8)Broadleaf Deciduous Boreal Tree,
1.231 +; (9)Broadleaf Evergreen Shrub,
1.232 +; (16)Wheat
1.233 +
1.234 + if (i.eq.3 .or. i.eq.8 .or. i.eq.9 .or. i.eq.16) then
1.235 + yvalues(n,i) = yvalues@_FillValue
1.236 + yvalues_t(n,i) = yvalues@_FillValue
1.237 + end if
1.238 +;#############################################################
1.239 +
1.240 + delete (data)
1.241 + end do
1.242 +
1.243 + delete (idx)
1.244 + end do
1.245 +
1.246 + delete (base)
1.247 + delete (area)
1.248 + delete (NPP1)
1.249 + delete (VegC)
1.250 + delete (LiCwC)
1.251 + delete (SoilC)
1.252 + delete (NPP2)
1.253 + delete (NEE2)
1.254 + delete (GPP2)
1.255 +
1.256 +;----------------------------------------------------------------
1.257 +; data for table1
1.258 +
1.259 + good = ind(.not.ismissing(yvalues(5,:)) .and. .not.ismissing(yvalues(1,:)))
1.260 +;print (good)
1.261 +
1.262 + area_g = yvalues(0,good)
1.263 + NPP1_g = yvalues(1,good)
1.264 + VegC_g = yvalues(2,good)
1.265 + LiCwC_g = yvalues(3,good)
1.266 + SoilC_g = yvalues(4,good)
1.267 + NPP2_g = yvalues(5,good)
1.268 + NEE2_g = yvalues(6,good)
1.269 + GPP2_g = yvalues(7,good)
1.270 +
1.271 + NPP_ratio = NPP2_g/NPP1_g
1.272 +
1.273 + n_biome = dimsizes(NPP1_g)
1.274 +
1.275 +;-----------------------------------------------------------------
1.276 +; data for table2
1.277 +
1.278 +; change unit from g to Pg (Peta gram)
1.279 + factor_unit = 1.e-15
1.280 +
1.281 + NPP1_t = yvalues_t(1,good) * factor_unit
1.282 + VegC_t = yvalues_t(2,good) * factor_unit
1.283 + LiCwC_t = yvalues_t(3,good) * factor_unit
1.284 + SoilC_t = yvalues_t(4,good) * factor_unit
1.285 + NEE2_t = yvalues_t(6,good) * factor_unit
1.286 + GPP2_t = yvalues_t(7,good) * factor_unit
1.287 +
1.288 + delete (yvalues)
1.289 + delete (yvalues_t)
1.290 +
1.291 +;-------------------------------------------------------------
1.292 +; html table1 data
1.293 +
1.294 +; column (not including header column)
1.295 +
1.296 + col_head = (/"Area (1.e12m2)" \
1.297 + ,"NPP (gC/m2/yr)" \
1.298 + ,"VegC (gC/m2)" \
1.299 + ,"Litter+CWD (gC/m2)" \
1.300 + ,"SoilC (gC/m2)" \
1.301 + ,"NPP_ratio" \
1.302 + ,"NEE (gC/m2/yr)" \
1.303 + ,"GPP (gC/m2/yr)" \
1.304 + /)
1.305 +
1.306 + ncol = dimsizes(col_head)
1.307 +
1.308 +; row (not including header row)
1.309 +
1.310 +; using model biome class:
1.311 + row_head = (/"Not Vegetated" \
1.312 + ,"Needleleaf Evergreen Temperate Tree" \
1.313 + ,"Needleleaf Evergreen Boreal Tree" \
1.314 +; ,"Needleleaf Deciduous Boreal Tree" \
1.315 + ,"Broadleaf Evergreen Tropical Tree" \
1.316 + ,"Broadleaf Evergreen Temperate Tree" \
1.317 + ,"Broadleaf Deciduous Tropical Tree" \
1.318 + ,"Broadleaf Deciduous Temperate Tree" \
1.319 +; ,"Broadleaf Deciduous Boreal Tree" \
1.320 +; ,"Broadleaf Evergreen Shrub" \
1.321 + ,"Broadleaf Deciduous Temperate Shrub" \
1.322 + ,"Broadleaf Deciduous Boreal Shrub" \
1.323 + ,"C3 Arctic Grass" \
1.324 + ,"C3 Non-Arctic Grass" \
1.325 + ,"C4 Grass" \
1.326 + ,"Corn" \
1.327 +; ,"Wheat" \
1.328 + ,"All Biome" \
1.329 + /)
1.330 + nrow = dimsizes(row_head)
1.331 +
1.332 +; arrays to be passed to table.
1.333 + text = new ((/nrow, ncol/),string )
1.334 +
1.335 + do i=0,nrow-2
1.336 + text(i,0) = sprintf("%.1f",area_g(i)*1.e-12)
1.337 + text(i,1) = sprintf("%.1f",NPP1_g(i))
1.338 + text(i,2) = sprintf("%.1f",VegC_g(i))
1.339 + text(i,3) = sprintf("%.1f",LiCwC_g(i))
1.340 + text(i,4) = sprintf("%.1f",SoilC_g(i))
1.341 + text(i,5) = sprintf("%.2f",NPP_ratio(i))
1.342 + text(i,6) = sprintf("%.1f",NEE2_g(i))
1.343 + text(i,7) = sprintf("%.1f",GPP2_g(i))
1.344 + end do
1.345 +
1.346 +;-------------------------------------------------------
1.347 +; create html table1
1.348 +
1.349 + header_text = "<H1>NEE and Carbon Stocks and Fluxes: Model "+model_name+"</H1>"
1.350 +
1.351 + header = (/"<HTML>" \
1.352 + ,"<HEAD>" \
1.353 + ,"<TITLE>CLAMP metrics</TITLE>" \
1.354 + ,"</HEAD>" \
1.355 + ,header_text \
1.356 + /)
1.357 + footer = "</HTML>"
1.358 +
1.359 + table_header = (/ \
1.360 + "<table border=1 cellspacing=0 cellpadding=3 width=60%>" \
1.361 + ,"<tr>" \
1.362 + ," <th bgcolor=DDDDDD >Biome Type</th>" \
1.363 + ," <th bgcolor=DDDDDD >"+col_head(0)+"</th>" \
1.364 + ," <th bgcolor=DDDDDD >"+col_head(1)+"</th>" \
1.365 + ," <th bgcolor=DDDDDD >"+col_head(2)+"</th>" \
1.366 + ," <th bgcolor=DDDDDD >"+col_head(3)+"</th>" \
1.367 + ," <th bgcolor=DDDDDD >"+col_head(4)+"</th>" \
1.368 + ," <th bgcolor=DDDDDD >"+col_head(5)+"</th>" \
1.369 + ," <th bgcolor=DDDDDD >"+col_head(6)+"</th>" \
1.370 + ," <th bgcolor=DDDDDD >"+col_head(7)+"</th>" \
1.371 + ,"</tr>" \
1.372 + /)
1.373 + table_footer = "</table>"
1.374 + row_header = "<tr>"
1.375 + row_footer = "</tr>"
1.376 +
1.377 + lines = new(50000,string)
1.378 + nline = 0
1.379 +
1.380 + set_line(lines,nline,header)
1.381 + set_line(lines,nline,table_header)
1.382 +
1.383 +;----------------------------
1.384 +;row of table
1.385 +
1.386 + do n = 0,nrow-2
1.387 + set_line(lines,nline,row_header)
1.388 +
1.389 + txt0 = row_head(n)
1.390 + txt1 = text(n,0)
1.391 + txt2 = text(n,1)
1.392 + txt3 = text(n,2)
1.393 + txt4 = text(n,3)
1.394 + txt5 = text(n,4)
1.395 + txt6 = text(n,5)
1.396 + txt7 = text(n,6)
1.397 + txt8 = text(n,7)
1.398 +
1.399 + set_line(lines,nline,"<th>"+txt0+"</th>")
1.400 + set_line(lines,nline,"<th>"+txt1+"</th>")
1.401 + set_line(lines,nline,"<th>"+txt2+"</th>")
1.402 + set_line(lines,nline,"<th>"+txt3+"</th>")
1.403 + set_line(lines,nline,"<th>"+txt4+"</th>")
1.404 + set_line(lines,nline,"<th>"+txt5+"</th>")
1.405 + set_line(lines,nline,"<th>"+txt6+"</th>")
1.406 + set_line(lines,nline,"<th>"+txt7+"</th>")
1.407 + set_line(lines,nline,"<th>"+txt8+"</th>")
1.408 +
1.409 + set_line(lines,nline,row_footer)
1.410 + end do
1.411 +;----------------------------
1.412 + set_line(lines,nline,table_footer)
1.413 + set_line(lines,nline,footer)
1.414 +
1.415 +; Now write to an HTML file.
1.416 +
1.417 + output_html = "table_per_m2.html"
1.418 +
1.419 + idx = ind(.not.ismissing(lines))
1.420 + if(.not.any(ismissing(idx))) then
1.421 + asciiwrite(output_html,lines(idx))
1.422 + else
1.423 + print ("error?")
1.424 + end if
1.425 +
1.426 + delete (idx)
1.427 +
1.428 + delete (col_head)
1.429 + delete (row_head)
1.430 + delete (text)
1.431 + delete (table_header)
1.432 +
1.433 +;-----------------------------------------------------------------
1.434 +; html table2 data
1.435 +
1.436 +; column (not including header column)
1.437 +
1.438 + col_head = (/"NPP (PgC/yr)" \
1.439 + ,"VegC (PgC)" \
1.440 + ,"Litter+CWD (PgC)" \
1.441 + ,"SoilC (PgC)" \
1.442 + ,"NEE (PgC/yr)" \
1.443 + ,"GPP (PgC/yr)" \
1.444 + ,"NPP timeseries" \
1.445 + ,"NEE timeseries" \
1.446 + ,"Fire timeseries" \
1.447 + /)
1.448 +
1.449 + ncol = dimsizes(col_head)
1.450 +
1.451 +; row (not including header row)
1.452 +
1.453 +; using model biome class:
1.454 + row_head = (/"Not Vegetated" \
1.455 + ,"Needleleaf Evergreen Temperate Tree" \
1.456 + ,"Needleleaf Evergreen Boreal Tree" \
1.457 +; ,"Needleleaf Deciduous Boreal Tree" \
1.458 + ,"Broadleaf Evergreen Tropical Tree" \
1.459 + ,"Broadleaf Evergreen Temperate Tree" \
1.460 + ,"Broadleaf Deciduous Tropical Tree" \
1.461 + ,"Broadleaf Deciduous Temperate Tree" \
1.462 +; ,"Broadleaf Deciduous Boreal Tree" \
1.463 +; ,"Broadleaf Evergreen Shrub" \
1.464 + ,"Broadleaf Deciduous Temperate Shrub" \
1.465 + ,"Broadleaf Deciduous Boreal Shrub" \
1.466 + ,"C3 Arctic Grass" \
1.467 + ,"C3 Non-Arctic Grass" \
1.468 + ,"C4 Grass" \
1.469 + ,"Corn" \
1.470 +; ,"Wheat" \
1.471 + ,"All Biome" \
1.472 + /)
1.473 + nrow = dimsizes(row_head)
1.474 +
1.475 +; arrays to be passed to table.
1.476 + text = new ((/nrow, ncol/),string )
1.477 +
1.478 + do i=0,nrow-2
1.479 + text(i,0) = sprintf("%.1f",NPP1_t(i))
1.480 + text(i,1) = sprintf("%.1f",VegC_t(i))
1.481 + text(i,2) = sprintf("%.1f",LiCwC_t(i))
1.482 + text(i,3) = sprintf("%.1f",SoilC_t(i))
1.483 + text(i,4) = sprintf("%.1f",NEE2_t(i))
1.484 + text(i,5) = sprintf("%.1f",GPP2_t(i))
1.485 + text(i,6) = "<a href=./NPP_monthly_biome_"+i+".png>monthly_plot</a> <br> <a href=./NPP_annual_biome_"+i+".png>annual_plot</a>"
1.486 + text(i,7) = "<a href=./NEE_monthly_biome_"+i+".png>monthly_plot</a> <br> <a href=./NEE_annual_biome_"+i+".png>annual_plot</a>"
1.487 + text(i,8) = "--"
1.488 + end do
1.489 +
1.490 + text(nrow-1,0) = sprintf("%.1f",sum(NPP1_t))
1.491 + text(nrow-1,1) = sprintf("%.1f",sum(VegC_t))
1.492 + text(nrow-1,2) = sprintf("%.1f",sum(LiCwC_t))
1.493 + text(nrow-1,3) = sprintf("%.1f",sum(SoilC_t))
1.494 + text(nrow-1,4) = sprintf("%.1f",sum(NEE2_t))
1.495 + text(nrow-1,5) = sprintf("%.1f",sum(GPP2_t))
1.496 + text(nrow-1,6) = "<a href=./NPP_monthly_global.png>monthly_plot</a> <br> <a href=./NPP_annual_global.png>annual_plot</a>"
1.497 + text(nrow-1,7) = "<a href=./NEE_monthly_global.png>monthly_plot</a> <br> <a href=./NEE_annual_global.png>annual_plot</a>"
1.498 + text(nrow-1,8) = "--"
1.499 +
1.500 +;**************************************************
1.501 +; create html table2
1.502 +;**************************************************
1.503 +
1.504 + header_text = "<H1>NEE and Carbon Stocks and Fluxes (per biome): Model "+model_name+"</H1>"
1.505 +
1.506 + header = (/"<HTML>" \
1.507 + ,"<HEAD>" \
1.508 + ,"<TITLE>CLAMP metrics</TITLE>" \
1.509 + ,"</HEAD>" \
1.510 + ,header_text \
1.511 + /)
1.512 + footer = "</HTML>"
1.513 +
1.514 + table_header = (/ \
1.515 + "<table border=1 cellspacing=0 cellpadding=3 width=60%>" \
1.516 + ,"<tr>" \
1.517 + ," <th bgcolor=DDDDDD >Biome Type</th>" \
1.518 + ," <th bgcolor=DDDDDD >"+col_head(0)+"</th>" \
1.519 + ," <th bgcolor=DDDDDD >"+col_head(1)+"</th>" \
1.520 + ," <th bgcolor=DDDDDD >"+col_head(2)+"</th>" \
1.521 + ," <th bgcolor=DDDDDD >"+col_head(3)+"</th>" \
1.522 + ," <th bgcolor=DDDDDD >"+col_head(4)+"</th>" \
1.523 + ," <th bgcolor=DDDDDD >"+col_head(5)+"</th>" \
1.524 + ," <th bgcolor=DDDDDD >"+col_head(6)+"</th>" \
1.525 + ," <th bgcolor=DDDDDD >"+col_head(7)+"</th>" \
1.526 + ," <th bgcolor=DDDDDD >"+col_head(8)+"</th>" \
1.527 + ,"</tr>" \
1.528 + /)
1.529 + table_footer = "</table>"
1.530 + row_header = "<tr>"
1.531 + row_footer = "</tr>"
1.532 +
1.533 + lines = new(50000,string)
1.534 + nline = 0
1.535 +
1.536 + set_line(lines,nline,header)
1.537 + set_line(lines,nline,table_header)
1.538 +;-----------------------------------------------
1.539 +;row of table
1.540 +
1.541 + do n = 0,nrow-1
1.542 + set_line(lines,nline,row_header)
1.543 +
1.544 + txt0 = row_head(n)
1.545 + txt1 = text(n,0)
1.546 + txt2 = text(n,1)
1.547 + txt3 = text(n,2)
1.548 + txt4 = text(n,3)
1.549 + txt5 = text(n,4)
1.550 + txt6 = text(n,5)
1.551 + txt7 = text(n,6)
1.552 + txt8 = text(n,7)
1.553 + txt9 = text(n,8)
1.554 +
1.555 + set_line(lines,nline,"<th>"+txt0+"</th>")
1.556 + set_line(lines,nline,"<th>"+txt1+"</th>")
1.557 + set_line(lines,nline,"<th>"+txt2+"</th>")
1.558 + set_line(lines,nline,"<th>"+txt3+"</th>")
1.559 + set_line(lines,nline,"<th>"+txt4+"</th>")
1.560 + set_line(lines,nline,"<th>"+txt5+"</th>")
1.561 + set_line(lines,nline,"<th>"+txt6+"</th>")
1.562 + set_line(lines,nline,"<th>"+txt7+"</th>")
1.563 + set_line(lines,nline,"<th>"+txt8+"</th>")
1.564 + set_line(lines,nline,"<th>"+txt9+"</th>")
1.565 +
1.566 + set_line(lines,nline,row_footer)
1.567 + end do
1.568 +;-----------------------------------------------
1.569 + set_line(lines,nline,table_footer)
1.570 + set_line(lines,nline,footer)
1.571 +
1.572 +; Now write to an HTML file.
1.573 +
1.574 + output_html = "table_per_biome.html"
1.575 +
1.576 + idx = ind(.not.ismissing(lines))
1.577 + if(.not.any(ismissing(idx))) then
1.578 + asciiwrite(output_html,lines(idx))
1.579 + else
1.580 + print ("error?")
1.581 + end if
1.582 +
1.583 + delete (idx)
1.584 +
1.585 +;---------------------------------------------------
1.586 +; read model data, time series:
1.587 +
1.588 + fm = addfile (dirm+film7,"r")
1.589 +
1.590 + NPP3 = fm->NPP
1.591 + NEE3 = fm->NEE
1.592 +;Fire = fm->COL_FIRE_CLOSS
1.593 +
1.594 + delete (fm)
1.595 +
1.596 +; Units for these variables are:
1.597 +
1.598 +;NPP3: g C/m^2/s
1.599 +;NEE3: g C/m^2/s
1.600 +;Fire: g C/m^2/s
1.601 +
1.602 + nsec_per_month = 60*60*24*30
1.603 +
1.604 +; change unit to g C/m^2/month
1.605 +
1.606 + NPP3 = NPP3 * nsec_per_month * conform(NPP3,landfrac,(/2,3/))
1.607 + NEE3 = NEE3 * nsec_per_month * conform(NEE3,landfrac,(/2,3/))
1.608 +;Fire = Fire * nsec_per_month * conform(Fire,landfrac,(/2,3/))
1.609 +
1.610 +;data_n = 3
1.611 + data_n = 2
1.612 +
1.613 + dsizes = dimsizes(NPP3)
1.614 + nyear = dsizes(0)
1.615 + nmonth = dsizes(1)
1.616 + ntime = nyear * nmonth
1.617 +
1.618 + year_start = 1979
1.619 + year_end = 2004
1.620 +
1.621 +;*******************************************************************
1.622 +; Calculate "nice" bins for binning the data in equally spaced ranges
1.623 +;********************************************************************
1.624 +
1.625 +; using model biome class
1.626 + nclass = nclass_mod
1.627 +
1.628 + range = fspan(0,nclass,nclass+1)
1.629 +
1.630 +; print (range)
1.631 +; Use this range information to grab all the values in a
1.632 +; particular range, and then take an average.
1.633 +
1.634 + nx = dimsizes(range) - 1
1.635 +
1.636 +;==============================
1.637 +; put data into bins
1.638 +;==============================
1.639 +
1.640 +; using observed biome class
1.641 +; base = ndtooned(classob)
1.642 +; using model biome class
1.643 + base = ndtooned(classmod)
1.644 +
1.645 +; output
1.646 +
1.647 + yvalues = new((/ntime,data_n,nx/),float)
1.648 +
1.649 +; Loop through each range, using base.
1.650 +
1.651 + do i=0,nx-1
1.652 +
1.653 + if (i.ne.(nx-1)) then
1.654 + idx = ind((base.ge.range(i)).and.(base.lt.range(i+1)))
1.655 + else
1.656 + idx = ind(base.ge.range(i))
1.657 + end if
1.658 +
1.659 + do n = 0,data_n-1
1.660 +
1.661 + t = -1
1.662 + do m = 0,nyear-1
1.663 + do k = 0,nmonth-1
1.664 +
1.665 + t = t + 1
1.666 +
1.667 + if (n.eq.0) then
1.668 + data = ndtooned(NPP3(m,k,:,:))
1.669 + end if
1.670 +
1.671 + if (n.eq.1) then
1.672 + data = ndtooned(NEE3(m,k,:,:))
1.673 + end if
1.674 +
1.675 +; if (n.eq.2) then
1.676 +; data = ndtooned(Fire(m,k,:,:))
1.677 +; end if
1.678 +
1.679 +; Calculate average
1.680 +
1.681 + if (.not.any(ismissing(idx))) then
1.682 + yvalues(t,n,i) = sum(data(idx)*area_1d(idx))
1.683 + else
1.684 + yvalues(t,n,i) = yvalues@_FillValue
1.685 + end if
1.686 +
1.687 +;#############################################################
1.688 +; using model biome class:
1.689 +; set the following 4 classes to _FillValue:
1.690 +; (3)Needleleaf Deciduous Boreal Tree,
1.691 +; (8)Broadleaf Deciduous Boreal Tree,
1.692 +; (9)Broadleaf Evergreen Shrub,
1.693 +; (16)Wheat
1.694 +
1.695 + if (i.eq.3 .or. i.eq.8 .or. i.eq.9 .or. i.eq.16) then
1.696 + yvalues(t,n,i) = yvalues@_FillValue
1.697 + end if
1.698 +;#############################################################
1.699 +
1.700 + end do
1.701 + end do
1.702 +
1.703 + delete(data)
1.704 + end do
1.705 +
1.706 + delete(idx)
1.707 + end do
1.708 +
1.709 + delete (base)
1.710 + delete (NPP3)
1.711 + delete (NEE3)
1.712 +; delete (Fire)
1.713 +
1.714 +;----------------------------------------------------------------
1.715 +; data for tseries plot
1.716 +
1.717 + yvalues_g = new((/ntime,data_n,n_biome/),float)
1.718 +
1.719 + yvalues_g@units = "TgC/month"
1.720 +
1.721 +; change unit to Tg C/month
1.722 +; change unit from g to Tg (Tera gram)
1.723 + factor_unit = 1.e-12
1.724 +
1.725 + yvalues_g = yvalues(:,:,good) * factor_unit
1.726 +
1.727 +;*******************************************************************
1.728 +; general settings for line plot
1.729 +;*******************************************************************
1.730 +
1.731 +; res
1.732 + res = True
1.733 + res@xyDashPatterns = (/0/) ; make lines solid
1.734 + res@xyLineThicknesses = (/2.0/) ; make lines thicker
1.735 + res@xyLineColors = (/"blue"/) ; line color
1.736 +
1.737 + res@trXMinF = year_start
1.738 + res@trXMaxF = year_end + 1
1.739 +
1.740 + res@vpHeightF = 0.4 ; change aspect ratio of plot
1.741 +; res@vpWidthF = 0.8
1.742 + res@vpWidthF = 0.75
1.743 +
1.744 +; res@gsnMaximize = True
1.745 +
1.746 +;*******************************************************************
1.747 +; (A) 1 component in each biome: monthly
1.748 +;*******************************************************************
1.749 +
1.750 +; component = (/"NPP","NEE","Fire"/)
1.751 + component = (/"NPP","NEE"/)
1.752 +
1.753 +; for x-axis in xyplot
1.754 +
1.755 + timeI = new((/ntime/),integer)
1.756 + timeF = new((/ntime/),float)
1.757 + timeI = ispan(1,ntime,1)
1.758 + timeF = year_start + (timeI-1)/12.
1.759 + timeF@long_name = "year"
1.760 +
1.761 + plot_data = new((/ntime/),float)
1.762 + plot_data@long_name = "TgC/month"
1.763 +
1.764 + do n = 0, data_n-1
1.765 + do m = 0, n_biome-1
1.766 +
1.767 + plot_name = component(n)+"_monthly_biome_"+ m
1.768 +
1.769 + wks = gsn_open_wks (plot_type,plot_name)
1.770 +
1.771 + title = component(n)+ ": "+ row_head(m)
1.772 + res@tiMainString = title
1.773 + res@tiMainFontHeightF = 0.025
1.774 +
1.775 + plot_data(:) = yvalues_g(:,n,m)
1.776 +
1.777 + plot=gsn_csm_xy(wks,timeF,plot_data,res)
1.778 +
1.779 + delete (wks)
1.780 + delete (plot)
1.781 +
1.782 + system("convert "+plot_name+"."+plot_type+" "+plot_name+"."+plot_type_new+";"+ \
1.783 + "rm "+plot_name+"."+plot_type)
1.784 + end do
1.785 + end do
1.786 +
1.787 + do n = 0, data_n-1
1.788 +
1.789 + plot_name = component(n)+"_monthly_global"
1.790 +
1.791 + wks = gsn_open_wks (plot_type,plot_name)
1.792 +
1.793 + title = component(n)+ ": Global"
1.794 + res@tiMainString = title
1.795 + res@tiMainFontHeightF = 0.025
1.796 +
1.797 + do k = 0,ntime-1
1.798 + plot_data(k) = sum(yvalues_g(k,n,:))
1.799 + end do
1.800 +
1.801 + plot=gsn_csm_xy(wks,timeF,plot_data,res)
1.802 +
1.803 + delete (wks)
1.804 + delete (plot)
1.805 +
1.806 + system("convert "+plot_name+"."+plot_type+" "+plot_name+"."+plot_type_new+";"+ \
1.807 + "rm "+plot_name+"."+plot_type)
1.808 + end do
1.809 +
1.810 + delete (plot_data)
1.811 + delete (timeI)
1.812 + delete (timeF)
1.813 +
1.814 +;*******************************************************************
1.815 +; (B) 1 component in each biome: annually
1.816 +;*******************************************************************
1.817 +
1.818 + yvalues_a = new((/nyear,data_n,n_biome/),float)
1.819 + yvalues_g!0 = "time"
1.820 + yvalues_g!1 = "case"
1.821 + yvalues_g!2 = "record"
1.822 +
1.823 + yvalues_a = month_to_annual(yvalues_g,0)
1.824 +
1.825 + delete (yvalues_g)
1.826 +
1.827 +; for x-axis in xyplot
1.828 +
1.829 + timeI = new((/nyear/),integer)
1.830 + timeF = new((/nyear/),float)
1.831 + timeI = ispan(1,nyear,1)
1.832 + timeF = year_start + (timeI-1)
1.833 + timeF@long_name = "year"
1.834 +
1.835 + plot_data = new((/nyear/),float)
1.836 + plot_data@long_name = "TgC/year"
1.837 +
1.838 + do n = 0, data_n-1
1.839 + do m = 0, n_biome-1
1.840 +
1.841 + plot_name = component(n)+"_annual_biome_"+ m
1.842 +
1.843 + wks = gsn_open_wks (plot_type,plot_name)
1.844 +
1.845 + title = component(n)+ ": "+ row_head(m)
1.846 + res@tiMainString = title
1.847 + res@tiMainFontHeightF = 0.025
1.848 +
1.849 + plot_data(:) = yvalues_a(:,n,m)
1.850 +
1.851 + plot=gsn_csm_xy(wks,timeF,plot_data,res)
1.852 +
1.853 + delete (wks)
1.854 + delete (plot)
1.855 +
1.856 + system("convert "+plot_name+"."+plot_type+" "+plot_name+"."+plot_type_new+";"+ \
1.857 + "rm "+plot_name+"."+plot_type)
1.858 + end do
1.859 + end do
1.860 +
1.861 + do n = 0, data_n-1
1.862 +
1.863 + plot_name = component(n)+"_annual_global"
1.864 +
1.865 + wks = gsn_open_wks (plot_type,plot_name)
1.866 +
1.867 + title = component(n)+ ": Global"
1.868 + res@tiMainString = title
1.869 + res@tiMainFontHeightF = 0.025
1.870 +
1.871 + do k = 0,nyear-1
1.872 + plot_data(k) = sum(yvalues_a(k,n,:))
1.873 + end do
1.874 +
1.875 + plot=gsn_csm_xy(wks,timeF,plot_data,res)
1.876 +
1.877 + delete (wks)
1.878 + delete (plot)
1.879 +
1.880 + system("convert "+plot_name+"."+plot_type+" "+plot_name+"."+plot_type_new+";"+ \
1.881 + "rm "+plot_name+"."+plot_type)
1.882 + end do
1.883 +
1.884 +;****************************************
1.885 +; output plot and html
1.886 +;****************************************
1.887 + output_dir = model_name+"/carbon_sink"
1.888 +
1.889 + system("mv *.png *.html " + output_dir)
1.890 +;****************************************
1.891 +
1.892 +end
1.893 +