source: trunk/src/paper01/fig3/ws_validation_scatter_2000_2009_v50.pro @ 70

;+
; .. _ws_validation_scatter_2000_2009_v50.pro:
;
; =======================================
; ws_validation_scatter_2000_2009_v50.pro
; =======================================
;
; DESCRIPTION
; ===========
;
; .. graphviz::
;
;    digraph ws_validation_scatter_2000_2009_v50 {
;       graph [
;       rankdir="LR",
;       ]
;
;       ws_erai [shape=ellipse,fontname=Courier,label="${PROJECT_ID}/ws_2000_2009_erai_v50.txt"];
;       ws_tropflux [shape=ellipse,fontname=Courier,label="${PROJECT_OD}/ws_2000_2009_trop_v50.txt"];
;       ws_oaflux [shape=ellipse,fontname=Courier,label="${PROJECT_OD}/ws_2000_2009_oaflx_v50.txt"];
;       ws_ncep [shape=ellipse,fontname=Courier,label="${PROJECT_OD}/ws_2000_2009_ncep_v50.txt"];
;       ws_ncep1 [shape=ellipse,fontname=Courier,label="${PROJECT_OD}/ws_2000_2009_ncep1_v50.txt"];
;       ws_erai_oafluxgrid [shape=ellipse,fontname=Courier,label="${PROJECT_ID}/erai_ws_19890101_20091231_oafluxgrid.nc"];
;       ws_tropflux_2 [shape=ellipse,fontname=Courier,label="${PROJECT_ID}/TropFlux_ws_19890101_20091231_v20.nc"];
;       oaflux_basic [shape=ellipse,fontname=Courier,label="${PROJECT_ID}/OAFlux_basic_variables_1985_2009.nc"];
;       uwind_ncep2 [shape=ellipse,fontname=Courier,label="${PROJECT_ID}/uwind_ncep2_oafluxgrid_19890101_20091231.nc"];
;       vwind_ncep2 [shape=ellipse,fontname=Courier,label="${PROJECT_ID}/bwind_ncep2_oafluxgrid_19890101_20091231.nc"];
;       ws_tmi [shape=ellipse,fontname=Courier,label="${PROJECT_ID}/zonal_wind_speed_oafluxgrid_30N30S.nc"];
;
;       figure [shape=ellipse,fontname=Courier,label="${PROJECT_OD}/ws_validation_scatter_2000_2009_v50.ps"];
;
;       ws_validation_scatter_2000_2009_v50 [shape=box,
;       fontname=Courier,
;       color=blue,
;       URL="http://forge.ipsl.jussieu.fr/tropflux/broswrer/trunk/src/paper01/fig3/ws_validation_scatter_2000_2009_v50.pro",
;       label="${TROPFLUX}/src/paper01/fig3/ws_validation_scatter_2000_2009_v50.pro"];
;
;       {ws_erai ws_erai_oafluxgrid ws_tropflux_2 oaflux_basic ws_ncep2 ws_tmi_2 ws_ncep1_2} -> {ws_validation_scatter_2000_2009_v50} -> {ws_tropflux ws_oaflux ws_tmi ws_ncep ws_ncep1 figure}
;    }
;
; SEE ALSO
; ========
;
; :ref:`project_profile.sh`
; :ref:`project_init.pro`
; :ref:`cm_project.pro`
;
; :func:`x_site_location`
; :func:`y_site_location`
;
; :ref:`read_variables_v2.pro`
; :ref:`statistics_3var_v1.pro`
;
; EXAMPLES
; ========
;
; ::
;
;  IDL> date1=19890101L
;  IDL> date2=20091231L
;  IDL> ws_validation_scatter_2000_2009_v50, date1, date2
;
; TODO
; ====
;
; make it work on cratos : missing data
;
; ++ mooring data in graphviz
;
; coding rules
;
; get rid of spwan
;
; complete description
;
; handle IO error
;
;
; EVOLUTIONS
; ==========
;
; $Id$
;
; - fplod 20110420T132401Z aedon.locean-ipsl.upmc.fr (Darwin)
;
;   * remove hard coding path
;   * add graphviz
;   * externalize functions
;
; - fplod 20110411T142955Z aedon.locean-ipsl.upmc.fr (Darwin)
;
;   * minimal header
;
;-
pro ws_validation_scatter_2000_2009_v50, date1, date2
@cm_general
@cm_project
reinitplt, /z,/invert
key_portrait = 1

openps, FILENAME = 'idl.ps'

;; Give the location of mooring for validation of basic meteorological variables


sitelist=['8s67e','12s55e', '8s55e', '8s80.5e', '1.5s80.5e', '0n80.5e', '1.5n80.5e', '1.5s90e', $
           '0n90e', '1.5n90e', '4n90e','8n90e','12n90e', '15n90e', '5s95e', $
           '8s165e', '8s180w',  '8s155w', '8s125w', '8s110w', '8s95w',  '5s156e', '5s165e', '5s180w', '5s170w', $
          '5s155w', '5s140w', '5s125w', '5s110w', '5s95w', '2s156e', '2s165e', '2s180w', '2s170w', '2s155w', '2s140w', $
          '2s125w', '2s110w', '2s95w', '0n147e', '0n156e', '0n165e', '0n180w', '0n170w', '0n155w', '0n140w', '0n125w', $
          '0n110w', '0n95w', '2n147e', '2n156e', '2n165e', '2n180w', '2n170w', '2n155w', '2n140w', '2n125w', '2n110w', $
          '2n95w', '5n147e', '5n156e', '5n165e', '5n170w', '5n155w', '5n140w', '5n125w', '5n110w', '5n95w', $
          '8n156e', '8n165e', '8n180w', '8n170w', '9n140w', '8n125w', '8n110w', '8n95w', $
          '0n0e', '0n10w', '0n23w', '0n35w', '10s10w', '12n23w', '12n38w', '14s32w', '15n38w', '19s34w', '20n38w', $
          '21n23w', '4n23w', '4n38w', '6s10w', '8n38w', '8s30w']

ocean='global'

da1=10000101 & da2=10081231
nsmooth=1.    ;; statistics are with 7 day smoothed
;;   This program will create the following text files with statistics of respective variables
close,/all

fi_ws_erai=project_id_env+'ws_2000_2009_erai_v50.txt'
openw,1,fi_ws_erai
fi_ws_trop=project_id_env+'ws_2000_2009_trop_v50.txt'
openw,2,fi_ws_trop
fi_ws_oaflx=project_id_env+'ws_2000_2009_oaflx_v50.txt'
openw,3,fi_ws_oaflx
fi_ws_ncep=project_id_env+'ws_2000_2009_ncep_v50.txt'
openw,4,fi_ws_ncep
fi_ws_tmi=project_id_env+'ws_2000_2009_tmi_v50.txt'
openw,5,fi_ws_tmi
fi_ws_ncep1=project_id_env+'ws_2000_2009_ncep1_v50.txt'
openw,6,fi_ws_ncep1


printf,1, 'x     y      cor    bias     std     rmsd      mean_tao'
printf,2, 'x     y      cor    bias     std     rmsd      mean_tao'
printf,3, 'x     y      cor    bias     std     rmsd      mean_tao'
printf,4, 'x     y      cor    bias     std     rmsd      mean_tao'
printf,5, 'x     y      cor    bias     std     rmsd      mean_tao'
printf,6, 'x     y      cor    bias     std     rmsd      mean_tao'

;; first reading the whole ERAI uncorrected and corrected data

file=project_id_env+'erai_ws_19890101_20091231_oafluxgrid.nc'
initncdf, file
u=read_ncdf('u10',date1,date2,file=file,/nostr)
v=read_ncdf('v10',date1,date2,file=file,/nostr)
unc=sqrt(u*u+v*v)
help, unc

file=project_id_env+'TropFlux_ws_19890101_20091231_v20.nc'
initncdf, file
cor=read_ncdf('ws',date1,date2,file=file,/nostr)
help, cor

file=project_id_env+'OAFlux_basic_variables_1985_2009.nc'
initncdf, file
oaf=read_ncdf("wind", date1, date2, file=file,/nostr)
help, oaf

fi=project_id_env+'uwind_ncep2_oafluxgrid_19890101_20091231.nc'
initncdf, fi
u=read_ncdf("u", date1-1, date2, file=fi,/nostr)
fi=project_id_env+'vwind_ncep2_oafluxgrid_19890101_20091231.nc'
initncdf, fi
v=read_ncdf("v", date1-1, date2, file=fi,/nostr)
nce=sqrt(u*u+v*v)
help, nce

fi=project_id_env+'zonal_wind_speed_oafluxgrid_30N30S.nc'
initncdf, fi
u=read_ncdf("u", date1, date2, file=fi,/nostr)
fi=project_id_env+'meridional_wind_speed_oafluxgrid_30N30S.nc'
initncdf, fi
v=read_ncdf("v", date1, date2, file=fi,/nostr)
ws_tmi=sqrt(u*u+v*v)
help, ws_tmi

file=project_id_env+'wind_ncep1_19890101_20091231.nc'
initncdf, file
u=read_ncdf("u", date1, date2, file=file,/nostr)
v=read_ncdf("v", date1, date2, file=file,/nostr)
nce1=sqrt(u*u+v*v)
help, nce1

nn=n_elements(sitelist)
for n=0, nn-1 do begin

;; reading data from mooring

    site=sitelist(n) & csite=site
    print, csite
    x=x_site_location(site)
    y=y_site_location(site)
    if (y ge 0. and y le 30.) then y=y+360.
    dx=0.5 & dy=0.5 & box=[y-dy, y+dy, x-dx, x+dx]
    read_variables_v2, csite,date1,date2,nsmooth, $
         at, sw,rh,sst,wu,wv,ws, lh

    ws=alog(10./0.000152)/alog(4./0.000152)*ws

;;  extracting the corrected and uncorrected ERAI data at the locations
    nsmooth=1.

    extract_flux_tropflux,unc,box, $
        tropflux
    uncr=tropflux

     extract_flux_tropflux,cor,box, $
        tropflux
     corr=tropflux

     extract_flux_tropflux,oaf,box, $
        tropflux
     oafl=tropflux

     extract_flux_tropflux,nce,box, $
        tropflux
     ncep=tropflux

     extract_flux_tropflux,ws_tmi,box, $
        tropflux
     tmi=tropflux

     extract_flux_tropflux,nce1,box, $
        tropflux
     ncep1=tropflux

    ind=where(finite(ws)) & ws=ws(ind) & uncr_ws=uncr(ind)  & corr_ws=corr(ind)
    oafl=oafl(ind) & ncep=ncep(ind) & tmi=tmi(ind) & ncep1=ncep1(ind)

    mean_tao=total(ws)/n_elements(ws)

    statistics_3var_v1, ws, uncr_ws, corr_ws, $
         cor1, cor2, bias1, bias2, std1, std2, rmsd1, rmsd2

    printf, 1, x, y, cor1, bias1, std1, rmsd1, mean_tao, format='(f6.2, 3x, f6.2, 3x, f5.2,3x,f5.2,3x,f4.2,3x,f4.2,3x,f5.2)'
    printf, 2, x, y, cor2, bias2, std2, rmsd2, mean_tao, format='(f6.2, 3x, f6.2, 3x, f5.2,3x,f5.2,3x,f4.2,3x,f4.2,3x,f5.2)'

    statistics_3var_v1, ws, oafl, ncep, $
         cor1, cor2, bias1, bias2, std1, std2, rmsd1, rmsd2
    printf, 3, x, y, cor1, bias1, std1, rmsd1, mean_tao, format='(f6.2, 3x, f6.2, 3x, f5.2,3x,f5.2,3x,f4.2,3x,f4.2,3x,f5.2)'
    printf, 4, x, y, cor2, bias2, std2, rmsd2, mean_tao, format='(f6.2, 3x, f6.2, 3x, f5.2,3x,f6.2,3x,f4.2,3x,f4.2,3x,f5.2)'

    statistics_3var_v1, ws, tmi, ncep1, $
         cor1, cor2, bias1, bias2, std1, std2, rmsd1, rmsd2
    printf, 5, x, y, cor1, bias1, std1, rmsd1, mean_tao, format='(f6.2, 3x, f6.2, 3x, f5.2,3x,f5.2,3x,f4.2,3x,f4.2,3x,f5.2)'
    printf, 6, x, y, cor2, bias2, std2, rmsd2, mean_tao, format='(f6.2, 3x, f6.2, 3x, f5.2,3x,f5.2,3x,f4.2,3x,f4.2,3x,f5.2)'

endfor
close,/all
fi_ws_erai=project_id_env+'ws_2000_2009_erai_v50.txt'
res=read_ascii(fi_ws_erai,data_start=1)
ff=res.field1
lat=reform(ff(0,*))
lon=reform(ff(1,*))
cor_era=reform(ff(2,*))   & cor_erai=total(cor_era)/n_elements(cor_era)
bias_era=reform(ff(3,*))  & bias_erai=total(bias_era)/n_elements(bias_era)
std_era=reform(ff(4,*))   & std_erai=total(std_era)/n_elements(std_era)
rmsd_era=reform(ff(5,*))  & rmsd_erai=total(rmsd_era)/n_elements(rmsd_era)
mean_tao=reform(ff(6,*))  & mean_erai=bias_era+mean_tao

print, ''
print, 'ERAI'
print, cor_erai, bias_erai, std_erai, rmsd_erai
cstat=string(cor_erai, bias_erai, std_erai, rmsd_erai, format='(f4.2,1x,f6.2,1x,f4.2,1x,f4.2)')
splot, mean_tao, mean_erai, title='WS - TAO Vs ERAI', subtitle='', $
     charsize=1.1, xtitle='TAO WS', ytitle='ERAI WS', small=[2,3,1], psym=2, $
     xrange=[2,10], yrange=[2,10], xmin=1,ymin=1
xyouts, 2.5,9.4, cstat, charsize=0.9
xyouts, 2.5,8.5, 'cor   bias   std   rmsd', charsize=0.9

oplot, [2,10], [2,10]
ab=linfit(mean_tao, mean_erai,yfit=yfit)
a=float(ab(0)) & b=float(ab(1))
oplot, mean_tao, yfit, color=250, thick=2

fi_ws_trop=project_id_env+'ws_2000_2009_trop_v50.txt'
res=read_ascii(fi_ws_trop,data_start=1)
ff=res.field1
lat=reform(ff(0,*))
lon=reform(ff(1,*))
cor_tro=reform(ff(2,*))   & cor_trop=total(cor_tro)/n_elements(cor_tro)
bias_tro=reform(ff(3,*))  & bias_trop=total(bias_tro)/n_elements(bias_tro)
std_tro=reform(ff(4,*))   & std_trop=total(std_tro)/n_elements(std_tro)
rmsd_tro=reform(ff(5,*))  & rmsd_trop=total(rmsd_tro)/n_elements(rmsd_tro)
mean_tao=reform(ff(6,*))  & mean_trop=bias_tro+mean_tao

print, ''
print, 'TropFlux'
print, cor_trop, bias_trop, std_trop, rmsd_trop
cstat=string(cor_trop, bias_trop, std_trop, rmsd_trop, format='(f4.2,1x,f6.2,1x,f4.2,1x,f4.2)')

splot, mean_tao, mean_trop, title='WS - TAO Vs TropFlux', subtitle='', $
     charsize=1.1, xtitle='TAO WS', ytitle='TropFlux WS', small=[2,3,2],/noer, psym=2, $
     xrange=[2,10], yrange=[2,10], xmin=1,ymin=1
oplot, [2,10], [2,10]
xyouts, 2.5,9.4, cstat, charsize=0.9
xyouts, 2.5,8.5, 'cor   bias   std   rmsd', charsize=0.9

ab=linfit(mean_tao, mean_trop,yfit=yfit)
a=float(ab(0)) & b=float(ab(1))
oplot, mean_tao, yfit, color=250, thick=2

fi_ws_oaflx=project_id_env+'ws_2000_2009_oaflx_v50.txt'
res=read_ascii(fi_ws_oaflx,data_start=1)
ff=res.field1
lat=reform(ff(0,*))
lon=reform(ff(1,*))
cor_oaf=reform(ff(2,*))   & cor_oafl=total(cor_oaf)/n_elements(cor_oaf)
bias_oaf=reform(ff(3,*))  & bias_oafl=total(bias_oaf)/n_elements(bias_oaf)
std_oaf=reform(ff(4,*))   & std_oafl=total(std_oaf)/n_elements(std_oaf)
rmsd_oaf=reform(ff(5,*))  & rmsd_oafl=total(rmsd_oaf)/n_elements(rmsd_oaf)
mean_tao=reform(ff(6,*))  & mean_oafl=bias_oaf+mean_tao

print, ''
print, 'OAFlux'
print, cor_oafl, bias_oafl, std_oafl, rmsd_oafl
cstat=string(cor_oafl, bias_oafl, std_oafl, rmsd_oafl, format='(f4.2,1x,f6.2,1x,f4.2,1x,f4.2)')

splot, mean_tao, mean_oafl, title='WS - TAO Vs OAFlux', subtitle='', $
     charsize=1.1, xtitle='TAO WS', ytitle='OAFlux WS', small=[2,3,3],/noer, psym=2, $
     xrange=[2,10], yrange=[2,10], xmin=1,ymin=1
oplot, [2,10], [2,10]
xyouts, 2.5,9.4, cstat, charsize=0.9
xyouts, 2.5,8.5, 'cor   bias   std   rmsd', charsize=0.9

ab=linfit(mean_tao, mean_oafl,yfit=yfit)
a=float(ab(0)) & b=float(ab(1))
oplot, mean_tao, yfit, color=250, thick=2



fi_ws_ncep=project_id_env+'ws_2000_2009_ncep_v50.txt'
res=read_ascii(fi_ws_ncep,data_start=1)
ff=res.field1
lat=reform(ff(0,*))
lon=reform(ff(1,*))
cor_nce=reform(ff(2,*))   & cor_ncep=total(cor_nce)/n_elements(cor_nce)
bias_nce=reform(ff(3,*))  & bias_ncep=total(bias_nce)/n_elements(bias_nce)
std_nce=reform(ff(4,*))   & std_ncep=total(std_nce)/n_elements(std_nce)
rmsd_nce=reform(ff(5,*))  & rmsd_ncep=total(rmsd_nce)/n_elements(rmsd_nce)
mean_tao=reform(ff(6,*))  & mean_ncep=bias_nce+mean_tao

print, ''
print, 'NCEP2'
print, cor_ncep, bias_ncep, std_ncep, rmsd_ncep
cstat=string(cor_ncep, bias_ncep, std_ncep, rmsd_ncep, format='(f4.2,1x,f6.2,1x,f4.2,1x,f4.2)')

splot, mean_tao, mean_ncep, title='WS - TAO Vs NCEP2', subtitle='', $
     charsize=1.1, xtitle='TAO WS', ytitle='NCEP2 WS', small=[2,3,4],/noer, psym=2, $
     xrange=[2,10], yrange=[2,10], xmin=1,ymin=1
oplot, [2,10], [2,10]
xyouts, 2.5,9.4, cstat, charsize=0.9
xyouts, 2.5,8.5, 'cor   bias   std   rmsd', charsize=0.9

ab=linfit(mean_tao, mean_ncep,yfit=yfit)
a=float(ab(0)) & b=float(ab(1))
oplot, mean_tao, yfit, color=250, thick=2

fi_ws_tmi=project_id_env+'ws_2000_2009_tmi_v50.txt'
res=read_ascii(fi_ws_tmi,data_start=1)
ff=res.field1
lat=reform(ff(0,*))
lon=reform(ff(1,*))
cor_tm=reform(ff(2,*))   & cor_tmi=total(cor_tm)/n_elements(cor_tm)
bias_tm=reform(ff(3,*))  & bias_tmi=total(bias_tm)/n_elements(bias_tm)
std_tm=reform(ff(4,*))   & std_tmi=total(std_tm)/n_elements(std_tm)
rmsd_tm=reform(ff(5,*))  & rmsd_tmi=total(rmsd_tm)/n_elements(rmsd_tm)
mean_tao=reform(ff(6,*))  & mean_tmi=bias_tm+mean_tao

print, ''
print, 'Qscat'
print, cor_tmi, bias_tmi, std_tmi, rmsd_tmi
cstat=string(cor_tmi, bias_tmi, std_tmi, rmsd_tmi, format='(f4.2,1x,f6.2,1x,f4.2,1x,f4.2)')

splot, mean_tao, mean_tmi, title='WS - TAO Vs Qscat', subtitle='', $
     charsize=1.1, xtitle='TAO WS', ytitle='TMI WS', small=[2,3,5],/noer, psym=2, $
     xrange=[2,10], yrange=[2,10], xmin=1,ymin=1
oplot, [2,10], [2,10]
xyouts, 2.5,9.4, cstat, charsize=0.9
xyouts, 2.5,8.5, 'cor   bias   std   rmsd', charsize=0.9

ab=linfit(mean_tao, mean_tmi,yfit=yfit)
a=float(ab(0)) & b=float(ab(1))
oplot, mean_tao, yfit, color=250, thick=2


fi_ws_ncep1=project_id_env+'ws_2000_2009_ncep1_v50.txt'
res=read_ascii(fi_ws_ncep1,data_start=1)
ff=res.field1
lat=reform(ff(0,*))
lon=reform(ff(1,*))
cor_nce=reform(ff(2,*))   & cor_ncep=total(cor_nce)/n_elements(cor_nce)
bias_nce=reform(ff(3,*))  & bias_ncep=total(bias_nce)/n_elements(bias_nce)
std_nce=reform(ff(4,*))   & std_ncep=total(std_nce)/n_elements(std_nce)
rmsd_nce=reform(ff(5,*))  & rmsd_ncep=total(rmsd_nce)/n_elements(rmsd_nce)
mean_tao=reform(ff(6,*))  & mean_ncep=bias_nce+mean_tao

print, ''
print, 'NCEP'
print, cor_ncep, bias_ncep, std_ncep, rmsd_ncep
cstat=string(cor_ncep, bias_ncep, std_ncep, rmsd_ncep, format='(f4.2,1x,f6.2,1x,f4.2,1x,f4.2)')

splot, mean_tao, mean_ncep, title='WS - TAO Vs NCEP', subtitle='', $
     charsize=1.1, xtitle='TAO WS', ytitle='NCEP WS', small=[2,3,6],/noer, psym=2, $
     xrange=[2,10], yrange=[2,10], xmin=1,ymin=1
oplot, [2,10], [2,10]
xyouts, 2.5,9.4, cstat, charsize=0.9
xyouts, 2.5,8.5, 'cor   bias   std   rmsd', charsize=0.9

ab=linfit(mean_tao, mean_ncep,yfit=yfit)
a=float(ab(0)) & b=float(ab(1))
oplot, mean_tao, yfit, color=250, thick=2

closeps

fig=project_od_env+'ws_validation_scatter_2000_2009_v50.ps'
spawn, 'mv '+psdir+'idl.ps '+fig
spawn, 'gv '+fig
end