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Commit 493abb63 authored by lkugler's avatar lkugler
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dummy config for docs

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from dartwrf import utils
exp = utils.Experiment()
exp.expname = "exp_v1.22_P2_rr_VIS_obs20_loc10_oe3"
exp.model_dx = 2000
exp.n_ens = 40
exp.superob_km = False # False or int (spatial averaging of observations)
exp.use_existing_obsseq = False # False or pathname (use precomputed obs_seq.out files)
#exp.use_existing_obsseq = '/users/students/lehre/advDA_s2023/dartwrf_tutorial/very_cold_observation.out'
# path to the nature run, where we take observations from
exp.nature_wrfout = '/jetfs/scratch/lkugler/data/sim_archive/exp_v1.18_P1_nature/2008-07-30_06:00/1/wrfout_d01_%Y-%m-%d_%H:%M:%S'
exp.input_profile = '/mnt/jetfs/home/lkugler/data/initial_profiles/wrf/ens/2022-03-31/raso.fc.<iens>.wrfprof'
exp.dart_nml = {'&assim_tools_nml':
dict(filter_kind='1',
sampling_error_correction='.false.',
# obs_impact_filename='/jetfs/home/lkugler/DART-WRF/templates/impactfactor_T.txt',
),
'&filter_nml':
dict(ens_size=exp.n_ens,
num_output_state_members=exp.n_ens,
num_output_obs_members=exp.n_ens,
inf_flavor=['0', '0'],
output_members='.true.',
output_mean='.true.',
output_sd='.true.',
stages_to_write='output',
),
'&location_nml':
dict(horiz_dist_only='.true.',
),
'&model_nml':
dict(wrf_state_variables =
[['U', 'QTY_U_WIND_COMPONENT', 'TYPE_U', 'UPDATE','999',],
['V', 'QTY_V_WIND_COMPONENT', 'TYPE_V', 'UPDATE','999',],
['W', 'QTY_VERTICAL_VELOCITY', 'TYPE_W', 'UPDATE','999',],
['PH', 'QTY_GEOPOTENTIAL_HEIGHT', 'TYPE_GZ', 'UPDATE','999',],
['THM', 'QTY_POTENTIAL_TEMPERATURE','TYPE_T', 'UPDATE','999',],
['MU', 'QTY_PRESSURE', 'TYPE_MU', 'UPDATE','999',],
['QVAPOR','QTY_VAPOR_MIXING_RATIO', 'TYPE_QV', 'UPDATE','999',],
['QICE', 'QTY_ICE_MIXING_RATIO', 'TYPE_QI', 'UPDATE','999',],
['QCLOUD','QTY_CLOUDWATER_MIXING_RATIO','TYPE_QC', 'UPDATE','999',],
['CLDFRA','QTY_CLOUD_FRACTION', 'TYPE_CFRAC','UPDATE','999',],
['PSFC', 'QTY_SURFACE_PRESSURE', 'TYPE_PSFC', 'UPDATE','999',],
['T2', 'QTY_2M_TEMPERATURE', 'TYPE_T', 'UPDATE','999',],
['TSK', 'QTY_SKIN_TEMPERATURE', 'TYPE_T', 'UPDATE','999',],
['REFL_10CM','QTY_RADAR_REFLECTIVITY','TYPE_REFL', 'UPDATE','999',]]),
}
# n_obs can be 22500: 2km, 5776: 4km, 121: 30km, 256:16x16 (20km); 961: 10km resoltn
# if radar: then n_obs is for each observation height level
vis = dict(var_name='VIS 0.6µm', unit='[1]',
kind='MSG_4_SEVIRI_BDRF', sat_channel=1,
n_obs=256, obs_locations='square_array_evenly_on_grid',
# n_obs=1, obs_locations=[(44.141, -0.99)],
error_generate=0.03, error_assimilate=0.03,
loc_horiz_km=10)
wv62 = dict(var_name='Brightness temperature WV 6.2µm', unit='[K]',
kind='MSG_4_SEVIRI_TB', sat_channel=5,
n_obs=961, obs_locations='square_array_evenly_on_grid',
error_generate=1., error_assimilate=2.,
loc_horiz_km=20)
wv73 = dict(var_name='Brightness temperature WV 7.3µm', unit='[K]',
kind='MSG_4_SEVIRI_TB', sat_channel=6,
n_obs=961, obs_locations='square_array_evenly_on_grid',
error_generate=1., error_assimilate=3.,
loc_horiz_km=20)
ir108 = dict(var_name='Brightness temperature IR 10.8µm', unit='[K]',
kind='MSG_4_SEVIRI_TB', sat_channel=9,
n_obs=1, obs_locations='square_array_evenly_on_grid',
error_generate=5., error_assimilate=10.,
loc_horiz_km=32)
radar = dict(var_name='Radar reflectivity', unit='[dBz]',
kind='RADAR_REFLECTIVITY',
n_obs=5776, obs_locations='square_array_evenly_on_grid',
error_generate=2.5, error_assimilate=2.5,
heights=range(2000, 14001, 2000),
loc_horiz_km=20, loc_vert_km=2.5)
t = dict(var_name='Temperature', unit='[K]',
kind='RADIOSONDE_TEMPERATURE',
#n_obs=22500, obs_locations='square_array_evenly_on_grid',
n_obs=1, obs_locations=[(45., 0.)],
error_generate=0.2, error_assimilate=0.2,
heights=[1000,], #range(1000, 17001, 2000),
loc_horiz_km=50, loc_vert_km=2.5)
q = dict(var_name='Specific humidity', unit='[kg/kg]',
kind='RADIOSONDE_SPECIFIC_HUMIDITY', n_obs=1,
error_generate=0., error_assimilate=5*1e-5,
heights=[1000], #range(1000, 17001, 2000),
loc_horiz_km=0.1, loc_vert_km=2.5)
t2m = dict(var_name='SYNOP Temperature', unit='[K]',
kind='SYNOP_TEMPERATURE', n_obs=1,
error_generate=0.1, error_assimilate=0.1,
loc_horiz_km=40, loc_vert_km=2.5)
psfc = dict(var_name='SYNOP Pressure', unit='[Pa]',
kind='SYNOP_SURFACE_PRESSURE', n_obs=1,
error_generate=50., error_assimilate=100.,
loc_horiz_km=32, loc_vert_km=5)
exp.observations = [vis]
exp.update_vars = ['U', 'V', 'W', 'THM', 'PH', 'MU', 'QVAPOR', 'QCLOUD', 'QICE', 'PSFC']
import os, sys
import datetime as dt
from dartwrf import utils
from cfg import exp
"""Configuration name docs
When coding, use attributes of a dictionary like this:
$ from cfg import exp, cluster
$ path = cluster.archivedir
attribute name | description
------------------------------------------------------
name any string (currently unused)
python path of python version to use
python_enstools path of python version to use for verification script (not provided)
ncks path to 'ncks' program; type 'which ncks' to find the path,
if it doesn't exist, try to load the module first ('module load nco')
ideal path to WRF's ideal.exe
wrfexe path to WRF's wrf.exe
wrf_rundir_base path for temporary files for WRF
dart_rundir_base path for temporary files for DART
archive_base path for long-time output storage
srcdir path to where WRF has been compiled, including the 'run' folder of WRF, e.g. /home/WRF-4.3/run
dart_srcdir path to DART compile directory, e.g. /home/DART-9.11.9/models/wrf/work
rttov_srcdir path to RTTOV compile directory, e.g. /home/RTTOV13/rtcoef_rttov13/
scriptsdir path where DART-WRF scripts reside, e.g. /home/DART-WRF/scripts
namelist path to a namelist template; strings like <hist_interval>, will be overwritten in scripts/prepare_namelist.py
run_WRF path to script which runs WRF on a node of the cluster
obs_impact_filename path to obs_impact_filename (see DART guide; module assim_tools_mod and program obs_impact_tool)
geo_em path to NetCDF file of WRF domain (see WRF guide)
slurm_cfg python dictionary, containing options of SLURM
defined in SLURM docs (https://slurm.schedmd.com/sbatch.html)
this configuration can be overwritten later on, for example:
'dict(cluster.slurm_cfg, **cfg_update)' where
'cfg_update = {"nodes": "2"}'
"""
cluster = utils.ClusterConfig(exp)
cluster.name = 'jet'
cluster.max_nproc = 12
cluster.use_slurm = True
cluster.size_jobarray = 40
# binaries
cluster.python = '/jetfs/home/lkugler/miniconda3/envs/DART/bin/python'
cluster.python_verif = '/jetfs/home/lkugler/miniconda3/envs/enstools/bin/python'
cluster.ncks = '/jetfs/spack/opt/spack/linux-rhel8-skylake_avx512/intel-2021.7.1/nco-5.1.0-izrhxv24jqco5epjhf5ledsqwanojc5m/bin/ncks'
cluster.ideal = '/jetfs/home/lkugler/bin/ideal-v4.3_v1.22.exe'
cluster.wrfexe = '/jetfs/home/lkugler/bin/wrf-v4.3_v1.22_ifort_20230413.exe'
cluster.dart_modules = 'module purge; module load netcdf-fortran/4.5.3-gcc-8.5.0-qsqbozc;'
cluster.wrf_modules = """module purge; module load intel-oneapi-compilers/2022.2.1-zkofgc5 hdf5/1.12.2-intel-2021.7.1-w5sw2dq netcdf-fortran/4.5.3-intel-2021.7.1-27ldrnt netcdf-c/4.7.4-intel-2021.7.1-lnfs5zz intel-oneapi-mpi/2021.7.1-intel-2021.7.1-pt3unoz
export HDF5=/jetfs/spack/opt/spack/linux-rhel8-skylake_avx512/intel-2021.7.1/hdf5-1.12.2-w5sw2dqpcq2orlmeowleamoxr65dhhdc
"""
# paths for data output
cluster.wrf_rundir_base = '/jetfs/home/lkugler/data/run_WRF/' # path for temporary files
cluster.dart_rundir_base = '/jetfs/home/lkugler/data/run_DART/' # path for temporary files
cluster.archive_base = '/jetfs/home/lkugler/data/sim_archive/'
# paths used as input
cluster.srcdir = '/jetfs/home/lkugler/data/compile/WRF-4.3/run'
cluster.dart_srcdir = '/jetfs/home/lkugler/data/compile/DART/DART-10.5.3/models/wrf/work'
cluster.rttov_srcdir = '/jetfs/home/lkugler/data/compile/RTTOV13/rtcoef_rttov13/'
cluster.dartwrf_dir = '/jetfs/home/lkugler/DART-WRF/'
# other inputs
cluster.geo_em_for_WRF_ideal = '/jetfs/home/lkugler/data/geo_em.d01.nc'
cluster.obs_impact_filename = cluster.dartwrf_dir+'/templates/impactfactor_T.txt'
cluster.namelist = cluster.dartwrf_dir+'/templates/namelist.input'
cluster.run_WRF = '/jetfs/home/lkugler/DART-WRF/dartwrf/run_ens.jet.sh'
cluster.slurm_cfg = {"account": "lkugler", "partition": "compute", #"nodelist": "jet07",
"ntasks": "1", "ntasks-per-core": "1", "mem": "50G",
"mail-type": "FAIL", "mail-user": "lukas.kugler@univie.ac.at"}
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