source: lmdz_wrf/trunk/tools/model_graphics_template.dat @ 915

### ASCII file to manage `model_graphics.bash' from different models and experiments 
#  from each one
#
#  1: Variables choice using its CF name
#  2: Kind of statisitcs to apply to the variable
#  3: Kind of plot for the variable
#  4: Kind of difference among models/experiments
#
# Different assumptions are made:
#  - model outputs are organized as ${ifold}/${model}/${exp}
#  - script outputs will be organized as ${ofold}/${model}/${exp}
#  - when diagnostic might be required a new file will be created
#  - WRF outputs will have added 'WRFtime' variable
#
# NOTE: in this file all the values are ':' separated lists without '

# python HOME
HOMEpy = ${HOME}/etudes/WRF_LMDZ/svn/LMDZ_WRF/tools

# Srcatch
scratch=false

# Debug
debug=false

# Folder with the files
##ifold = /bdd/PCER/workspace/lfita/etudes/WRF_LMDZ/WaquaL/WRF_LMDZ
ifold = /home/lluis/etudes/WRF_LMDZ/WaquaL_highres/tests/model_graphics

# Output folder
##ofold = /bdd/PCER/workspace/lfita/etudes/WRF_LMDZ/WaquaL/WRF_LMDZ
ofold = /home/lluis/etudes/WRF_LMDZ/WaquaL_highres/tests/model_graphics

# Experiments (model runs)
#   WRF: WRF
#   LMDZ: LMDZ model
#   WRF_LMDZ: LMDZ physics coupled to WRF
#models=WRF:WRF_LMDZ:LMDZ
models=WRF

# Experiments (labels of each experiment)
WRFexps = control:pbl1
LMDZexps = AR40:NPv31
WRF_LMDZexps = AR40:NPv31

# Headers of the files to use
WRFheaders = wrfout
WRF_LMDZheaders = wrfout
LMDZheaders = histins

# Kind of calculations (adding the euiqvalent `surname' to each variable)
#   acc: temporal accumulated values
#   diff: differences between models
#   direct: no statistics
#   Lmean: latitudinal mean values
#   Lsec: latitudinal section (latitudinal value must be given, [var]@[lat]) 
#   lmean: longitudinal mean values
#   lsec: longitudinal section (longitudinal value must be given, [var]@[lat])
#   pinterp: pressure interpolation (to the given $plevels, see below)
#   tmean: temporal mean values
#   xmean: x-axis mean values
#   ymean: y-axis mean values
#   zsum: vertical aggregated values
varkinds = direct:tmean:xmean:diff:pinterp

# variables (providing CF-name, script must provide equivalent variable for each model)
#   in foudre values from: ${HOME}/UNSW-CCRC-WRF/tools/postprocess/GMS-UC/WRF4G/util/postprocess/wrfncxnj/wrfncxnj.table
#   must exist on the table $pyHOME/variables_values.dat
vardirect = tas:uas:vas:ps:pr:pracc:rsds:prw:evspsbl:hfss:hfls:hurs:huss:zmla:hufs:wakes:lwakeh:stherm:zmaxth:clt:cll:clm:clh:prc:prls:bils
vartmean = prc:prls:zmla:hfss:hfls:evspsbl:bils:uas:vas:tas:ps:clt:cll:clm:clh:prw:huss:pr:wakes:wakeh:stherm:zmaxth
varxmean = ta:ua:va:hur
vardiff = ualmean:valmean:talmean:huslmean:uas:vas:ps:pr
varpinterp = ta:ua:va:hur

# Pressure levels
#   Common vertical pressure levels to compute vertical differences
plevels = 100000.:97500.:95000.:92500.:90000.:85000.:80000.:75000.:70000.:65000.:60000.:55000.:50000.:45000.:40000.:35000.:30000.:25000.:20000.:15000.:10000.:5000.:2500.:1000.:500.:250.
# Kind of plots
#   diffmap2Dsfc: 2D map of surface differences values of 1 variable
#   diffmap2Dz: 2D map of 3D differences values of 1 variable
#   hovm: Hovmoeller diagrams of 1 variable
#   map2Dsfc: 2D map of surface values of 1 variable
#   map3D: 2D map of 3D values of 1 variable
#   shadcount2D: 2D map of shadow (1st variable) and countour (2nd variable) [var1]@[var2] (no `surname' = 'direct')
shadcount2D = huslmean@talmean:valmean@ualmean:tas@ps:uas@vas:pr@rsds:prw@huss:prls@prc:hfls@hfss:evspsbl@bils:zmaxth@stherm:wakeh@wakes:zmaxth@stherm:prls@prc:clt@cll:clh@clm
diffmap2Dsfc = uas:vas:ps:pr
diffmap2Dz = ualmean:valmean:talmean:huslmean

# Figures output 
kindfig = pdf

# Generic
errmsg = ERROR--error--ERROR--error
warnmsg = WARNING--warning--WARNING--warning