** WRFmeas: Introducing real measurements in WRF **
L. Fita, LMD. May 2013
more details in http://www.lmd.jussieu.fr/~lflmd/WRFmeas

With the new set of observations taking place in the HyMeX (http://www.hymex.org) experiment, (including lidar, iso-baric-baloons, flights...), a new way to validate WRF runs is open. These measurements used to be a very high temporal resolutions (seconds) with very specific characteristics. Thus, in the scope of the REMEMBER (http://climserv.ipsl.polytechnique.fr/hymex-remember) project and keeping in mind the HyMeX observational data-set WRFmeas, has been designed. Basically it envisages a way to introduce the necesary modifications in the WRF model in order to retrieve from model runs a similar observational data-set as if the measurement was tacking in real inside the simulation domain.

* LIDAR
A series of modules have been created in order to obatin a lidar output in the model. Mostly, all the vertical profile of a series of values at each time-step in a given grid point (closest to the station). It works similar as in the time-series capabilities. With an external ASCII file, user defines the locations and names of the station. Model will output and independent ASCII file for each station

 - lidarlist: ASCII file with the name and location of the stations (exactly as 'tslist')
#-----------------------------------------------#
# 24 characters for name | pfx |  LAT  |   LON  |
#-----------------------------------------------#
Athens                    ath    37.964   23.736
Rome                      rom    41.872   12.486
Girona                    gir    41.985    2.832

 - Variables: height, pressure, x-wind direction, y-wind direction, z-wind direction, potential temperature, water vapor mixing ratio, cloud mixing ratio, rain mixing ratio, snow mixing ratio, hail mixing ratio, ice mixing ratio, graupel mixing ratio, air density, cloud fraction
 - Modifcations of WRF code: All the modifcations are contained in this tar file (WRF v3.3): WRFmeas_lidar.tar.gz. To compile it, decompress, and compile with the precompilation flag (in the configure.wrf file, after -DNETCDF) -DWRFMEAS
 - Output in files [pfx].LIDAR.d[nn]:
[stname]             [iddom]  [idst] [pfx]   ( [real lat],   [real lon]) (  [x-grid point],  [y-grid point]) ( [WRF lat],  [WRF lon])  [WRF elevation] meters. simulation start time: [YYYY]-[MM]-[DD]_[HH]:[MI]:[SS]
new_time  [iddom]     [time since simulation start (h)]    [stid]   [xgrid]   [ygrid]   [psfc]   [rainc]   [rainnc]   [tot dry mas]
       k          z [m]        p [hPa]       u [ms-1]       v [ms-1]       w [ms-1]      t_pot [k]    qv [kgkg-1]    qc [kgkg-1]    qr [kgkg-1]    qs [kgkg-1]    qh [kgkg-1]    qi [kgkg-1]    qg [kgkg-1]  dens [kg m-3]     cldfra [1] __________
       [z level] [height] [pressure] [x-wind direction] [y-wind direction] [z-wind direction] [potential temperature] [water vapor mixing ratio] [cloud mixing ratio] [rain mixing ratio] [snow mixing ratio] [hail mixing ratio] [ice mixing ratio] [graupel mixing ratio] [air density] [cloud fraction]
       (...)
       [z_maxlevel] [height] [pressure] [x-wind direction] [y-wind direction] [z-wind direction] [potential temperature] [water vapor mixing ratio] [cloud mixing ratio] [rain mixing ratio] [snow mixing ratio] [hail mixing ratio] [ice mixing ratio] [graupel mixing ratio] [air density] [cloud fraction]
new_time  [iddom]     [time since simulation start (h)]    [stid]   [xgrid]   [ygrid]   [psfc]   [rainc]   [rainnc]   [tot dry mas]
       k          z [m]        p [hPa]       u [ms-1]       v [ms-1]       w [ms-1]      t_pot [k]    qv [kgkg-1]    qc [kgkg-1]    qr [kgkg-1]    qs [kgkg-1]    qh [kgkg-1]    qi [kgkg-1]    qg [kgkg-1]  dens [kg m-3]     cldfra [1] __________
       (...)

 - utils: 
  > LIDAR_ASCII_netCDF.py: Python to create a netCDF with all the ASCII content
  > plot_lidar.py: Python to plot the values from the netCDF file
  > nc_var_tools.py: python suit of netCDF utilities
  > drawing_tools.py: python suit of plotting utilities