lai/24.histogram+bias_mean.ncl
author Forrest Hoffman <forrest@climatemodeling.org>
Mon, 26 Jan 2009 22:08:20 -0500
changeset 0 0c6405ab2ff4
permissions -rw-r--r--
Initial commit of C-LAMP Diagnostics from Jeff Lee
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;********************************************************
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; histogram normalized by rain and compute correleration
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;********************************************************
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load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_code.ncl"
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load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_csm.ncl"
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load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/contributed.ncl"
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procedure pminmax(data:numeric,name:string)
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begin
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  print ("min/max " + name + " = " + min(data) + "/" + max(data))
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  if(isatt(data,"units")) then
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    print (name + " units = " + data@units)
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  end if
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end
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;
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; Main code.
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;
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begin
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;nclass = 18
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 nclass = 20
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;************************************************
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; read in data: observed
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;************************************************
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 diri1  = "/fis/cgd/cseg/people/jeff/clamp_data/lai/"
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;fili1  = "land_class_T42.nc"
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 fili1  = "land_class_T42_new.nc"
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 fili2  = "LAI_2000-2005_mean_T42.nc"
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 data_file_ob1 = addfile(diri1+fili1,"r")
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 data_file_ob2 = addfile(diri1+fili2,"r")
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 RAIN1 = tofloat(data_file_ob1->LAND_CLASS)               
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 NPP1  = data_file_ob2->LAI      
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;************************************************
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; read in data: model       
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;************************************************
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 diri2  = "/fis/cgd/cseg/people/jeff/clamp_data/model/"
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;fili3  = "i01.03cn_1545-1569_ANN_climo.nc"
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 fili3  = "i01.04casa_1605-1629_ANN_climo.nc"
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 data_file_model = addfile(diri2+fili3,"r")
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 NPP2  = data_file_model->TLAI      
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;************************************************
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; print min/max and unit
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;************************************************
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  pminmax(RAIN1,"RAIN1")
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  pminmax(NPP1,"NPP1")
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  pminmax(NPP2,"NPP2")
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  RAIN1_1D = ndtooned(RAIN1)
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  NPP1_1D  = ndtooned(NPP1)
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  NPP2_1D  = ndtooned(NPP2)
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;
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; Calculate some "nice" bins for binning the data in equally spaced
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; ranges.
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;
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; nbins       = nclass + 1         ; Number of bins to use.
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; nicevals    = nice_mnmxintvl(min(RAIN1_1D),max(RAIN1_1D),nbins,False)
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; nvals       = floattoint((nicevals(1) - nicevals(0))/nicevals(2) + 1)
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; range       = fspan(nicevals(0),nicevals(1),nvals)
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  nclassn     = nclass + 1
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  range       = fspan(0,nclassn-1,nclassn)
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; print (nicevals)
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; print (nvals)
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  print (range)
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; exit
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;
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; Use this range information to grab all the values in a
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; particular range, and then take an average.
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;
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  nr      = dimsizes(range)
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  nx      = nr-1
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  xvalues     = new((/2,nx/),typeof(RAIN1_1D))
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  xvalues(0,:) = range(0:nr-2) + (range(1:)-range(0:nr-2))/2.
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  dx           = xvalues(0,1) - xvalues(0,0)       ; range width
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  dx4          = dx/4                              ; 1/4 of the range
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  xvalues(1,:) = xvalues(0,:) - dx/5.
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  yvalues      = new((/2,nx/),typeof(RAIN1_1D))
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  mn_yvalues   = new((/2,nx/),typeof(RAIN1_1D))
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  mx_yvalues   = new((/2,nx/),typeof(RAIN1_1D))
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  do nd=0,1
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;
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; See if we are doing model or observational data.
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;
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    if(nd.eq.0) then
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      data     = RAIN1_1D
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      npp_data = NPP1_1D
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    else
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      data     = RAIN1_1D
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      npp_data = NPP2_1D
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    end if
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;
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; Loop through each range and check for values.
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;
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    do i=0,nr-2
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      if (i.ne.(nr-2)) then
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         print("")
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         print("In range ["+range(i)+","+range(i+1)+")")
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        idx = ind((range(i).le.data).and.(data.lt.range(i+1)))
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      else
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         print("")
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         print("In range ["+range(i)+",)")
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        idx = ind(range(i).le.data)
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      end if
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;
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; Calculate average, and get min and max.
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;
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      if(.not.any(ismissing(idx))) then
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        yvalues(nd,i)    = avg(npp_data(idx))
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        mn_yvalues(nd,i) = min(npp_data(idx))
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        mx_yvalues(nd,i) = max(npp_data(idx))
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        count = dimsizes(idx)
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      else
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        count            = 0
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        yvalues(nd,i)    = yvalues@_FillValue
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        mn_yvalues(nd,i) = yvalues@_FillValue
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        mx_yvalues(nd,i) = yvalues@_FillValue
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      end if
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;
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; Print out information.
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;
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       print(nd + ": " + count + " points, avg = " + yvalues(nd,i))
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       print("Min/Max:  " + mn_yvalues(nd,i) + "/" + mx_yvalues(nd,i))
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;
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; Clean up for next time in loop.
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;
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      delete(idx)
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    end do
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    delete(data)
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    delete(npp_data)
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  end do
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;
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; Start the graphics.
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;
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  wks = gsn_open_wks("ps","xy")
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  res             = True
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  res@gsnMaximize = True
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  res@gsnDraw     = False
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  res@gsnFrame    = False
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  res@xyMarkLineMode = "Markers"
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  res@xyMarkerSizeF   = 0.014
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  res@xyMarker       = 16
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  res@xyMarkerColors = (/"Brown","Blue"/)
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; res@trYMinF        = min(mn_yvalues) - 10.
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; res@trYMaxF        = max(mx_yvalues) + 10.
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  res@trYMinF        = min(mn_yvalues) - 2
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  res@trYMaxF        = max(mx_yvalues) + 4
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; res@tiMainString  = "Observed vs i01.03cn"
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  res@tiMainString  = "Observed vs i01.04casa"
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  res@tiYAxisString = "Mean LAI (Leaf Area Index)"
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  res@tiXAxisString = "Land Cover Type"
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;
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; Add a boxed legend using the more simple method, which won't have
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; vertical lines going through the markers.
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;
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  res@pmLegendDisplayMode    = "Always"
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; res@pmLegendWidthF         = 0.1
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  res@pmLegendWidthF         = 0.08
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  res@pmLegendHeightF        = 0.05
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  res@pmLegendOrthogonalPosF = -1.17
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; res@pmLegendOrthogonalPosF = -1.00  ;(downward)
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; res@pmLegendParallelPosF   =  0.18
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  res@pmLegendParallelPosF   =  0.23  ;(rightward)
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; res@lgPerimOn              = False
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  res@lgLabelFontHeightF     = 0.015
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; res@xyExplicitLegendLabels = (/"observed","model_i01.03cn"/)
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  res@xyExplicitLegendLabels = (/"observed","model_i01.04casa"/)
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  xy = gsn_csm_xy(wks,xvalues,yvalues,res)
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  max_bar = new((/2,nx/),graphic)
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  min_bar = new((/2,nx/),graphic)
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  max_cap = new((/2,nx/),graphic)
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  min_cap = new((/2,nx/),graphic)
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  lnres = True
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  line_colors = (/"brown","blue"/)
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  do nd=0,1
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    lnres@gsLineColor = line_colors(nd)
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    do i=0,nx-1
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      if(.not.ismissing(mn_yvalues(nd,i)).and. \
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         .not.ismissing(mx_yvalues(nd,i))) then
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;
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; Attach the vertical bar, both above and below the marker.
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;
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        x1 = xvalues(nd,i)
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        y1 = yvalues(nd,i)
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        y2 = mn_yvalues(nd,i)
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        min_bar(nd,i) = gsn_add_polyline(wks,xy,(/x1,x1/),(/y1,y2/),lnres)
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        y2 = mx_yvalues(nd,i)
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        max_bar(nd,i) = gsn_add_polyline(wks,xy,(/x1,x1/),(/y1,y2/),lnres)
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;
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; Attach the horizontal cap line, both above and below the marker.
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;
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        x1 = xvalues(nd,i) - dx4
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        x2 = xvalues(nd,i) + dx4
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        y1 = mn_yvalues(nd,i)
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        min_cap(nd,i) = gsn_add_polyline(wks,xy,(/x1,x2/),(/y1,y1/),lnres)
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        y1 = mx_yvalues(nd,i)
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        max_cap(nd,i) = gsn_add_polyline(wks,xy,(/x1,x2/),(/y1,y1/),lnres)
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      end if
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    end do
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  end do
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;
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; Here's how to do the legend by hand.
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;
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; mkres               = True    ; Marker resources
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; txres               = True    ; Text resources
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; mkres@gsMarkerIndex = 16
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; mkres@gsMarkerSizeF = 0.02
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; txres@txFontHeightF = 0.02
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; txres@txJust        = "CenterLeft"
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;
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; Change these values if you want to move the marker legend location.
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; These values are in the same data space as the plot. 
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;
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; xlg1_cen = 0.2
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; ylg1_cen = 900.
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; xlg2_cen = 0.2
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; ylg2_cen = 760.
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; mkres@gsMarkerColor = "brown"
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; lnres@gsLineColor   = "brown"
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; lg_mark_legend1 = gsn_add_polymarker(wks,xy,xlg1_cen,ylg1_cen,mkres)
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; lg_line_legend1 = gsn_add_polyline(wks,xy,(/xlg1_cen,xlg1_cen/), \
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;                                           (/ylg1_cen-60,ylg1_cen+60/),lnres)
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; lg_cap_legend11  = gsn_add_polyline(wks,xy,(/xlg1_cen-0.1,xlg1_cen+0.1/), \
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;                                           (/ylg1_cen-60,ylg1_cen-60/),lnres)
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; lg_cap_legend12  = gsn_add_polyline(wks,xy,(/xlg1_cen-0.1,xlg1_cen+0.1/), \
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;                                           (/ylg1_cen+60,ylg1_cen+60/),lnres)
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; tx_legend1 = gsn_add_text(wks,xy,"observed",xlg1_cen+0.15,ylg1_cen,txres)
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; mkres@gsMarkerColor = "blue"
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; lnres@gsLineColor   = "blue"
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; lg_mark_legend2 = gsn_add_polymarker(wks,xy,xlg2_cen,ylg2_cen,mkres)
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; lg_line_legend2 = gsn_add_polyline(wks,xy,(/xlg2_cen,xlg2_cen/), \
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;                                           (/ylg2_cen-60,ylg2_cen+60/),lnres)
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; lg_cap_legend21  = gsn_add_polyline(wks,xy,(/xlg2_cen-0.1,xlg2_cen+0.1/), \
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;                                           (/ylg2_cen-60,ylg2_cen-60/),lnres)
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; lg_cap_legend22  = gsn_add_polyline(wks,xy,(/xlg2_cen-0.1,xlg2_cen+0.1/), \
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;                                           (/ylg2_cen+60,ylg2_cen+60/),lnres)
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; tx_legend2 = gsn_add_text(wks,xy,"model_i01.03cn",xlg2_cen+0.15,ylg2_cen,txres)
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  draw(xy)
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  frame(wks)
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  system("convert xy.ps xy.png")
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 u = yvalues(0,:)
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 v = yvalues(1,:)
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 good = ind(.not.ismissing(u) .and. .not.ismissing(v))
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 uu = u(good)
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 vv = v(good)
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 nz = dimsizes(uu)
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 print (nz)
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 ccr = esccr(uu,vv,0)
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 print (ccr)
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;old eq
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;bias = sum(((vv-uu)/uu)^2)
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;M    = (1.- sqrt(bias/nz))*5.
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;new eq
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 bias = sum(abs(vv-uu)/(vv+uu))
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 M    = (1.- (bias/nz))*5.
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 print (bias)
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 print (M)
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end
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