source: lmdz_wrf/trunk/tools/model_graphics_template.dat @ 929

### 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

# Scratch files
filescratch=false

# Scratch figures
figscratch=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 equivalent `surname' to each variable)
#   acc: temporal accumulated values
#   diff: differences between models
#   direct: no statistics
#   last: last temporal value
#   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 = last:tmean:xmean:diff:pinterp:combo

# 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
#   varcombo = [varn];[vark1]@...@[varkN]: variable as consecutive kinds of operation
varlast = 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:wss
vartmean = 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:wss
varxmean = ta:ua:va:hur
vardiff = ualmean:valmean:talmean:huslmean:uas:vas:ps:pr
varpinterp = ta:ua:va:hur
varcombo = ta;pinterp@last@xmean:ua;pinterp@last@xmean:va;pinterp@last@xmean:hur;pinterp@last@xmean

# Operations which attach 'mean' at the end of the variable name
varmeanname='Lmean:lmean:tmaen:xmean:ymean'

# 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
#   hovmsfc: Hovmoeller diagrams of 1 variable at the surface
#   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) [stvar1]#[stvar2]
#
#   ':' separated list of statitsics variable values are given as: [var]|[kind(including combo values)]
#     in figures with more than 1 variable, use '#' to separate them
drawplots = shadcount2Dsfc

# Figures which can be made directly without another model/experiment output
directplots = hovmsfc:map2Dsfc:map3D:shadcount2Dsfc

pltshadcount2Dsfc = huss|tmean#tas|tmean:vas|tmean#uas|tmean:ps|tmean#wss|tmean:pr|tmean#rsds|tmean:prw|tmean#clt|tmean:hfls|tmean#hfss|tmean:evspsbl|tmean#bils|tmean:zmaxth|tmean#stherm|tmean:wakeh|tmean#wakes|tmean:zmaxth|tmean#stherm|tmean:prls|tmean#prc|tmean:clt|tmean#cll|tmean:clm|tmean#clh|tmean:hurs|tmean#zmla|tmean:huss|last#tas|last:vas|last#uas|last:ps|last#wss|tmean:pr|last#rsds|last:prw|last#clt|last:hfls|last#hfss|last:evspsbl|last#bils|last:zmaxth|last#stherm|last:wakeh|last#wakes|last:zmaxth|last#stherm|last:prls|last#prc|last:clt|last#cll|last:clm|last#clh|last:hurs|last#zmla|last

pltdiffmap2Dsfc = uas:vas:ps:pr
pltdiffmap2Dz = uapxmean:vapxmean:tapxmean:huspxmean

# Specific variable-statistisc graphic parameters (if no value is given, they will be retrieved from 'variables_values.dat')
#  ':' separated list of specific parameters for plotting as:
#      [varname]|[statistics]|[minval]|[maxval]|[colorbar]|[cntformat]|[colorcnt]
#        [varname]: name of the variable
#        [statistics]: statistics (also combo)
#        [figure]: figure to be used
#        [minval]: minimum value
#        [maxval]: minimum value
#        [colorbar]: name of the colorbar (from matplotlib) to use
#        [cntformat]: format of the contour labels
#        [colorcnt]: color for the countor lines
specificvarplot = cll|last|shadcount2Dsfc|0.|1.|gist_gray|black:clh|last|shadcount2Dsfc|0.|1.|gist_gray|black

# Figures output kind
kindfig = pdf

# Map to use
mapval = lcc,l

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