diff --git a/analysis_only.py b/analysis_only.py
index 840e603c24535935856591e3850aa12d270e50ba..648d2c8c91d83a07bc7e38583016d81cb3b0dcfe 100755
--- a/analysis_only.py
+++ b/analysis_only.py
@@ -6,12 +6,12 @@ import datetime as dt
from dartwrf.workflows import WorkFlows
-prior_path_exp = '/users/students/lehre/advDA_s2023/data/sample_ensemble/'
+prior_path_exp = '/lehre/advDA_s2023/data/sample_ensemble/'
prior_init_time = dt.datetime(2008,7,30,12)
prior_valid_time = dt.datetime(2008,7,30,13)
assim_time = prior_valid_time
-w = WorkFlows(exp_config='exp_template.py', server_config='srvx1.py')
+w = WorkFlows(exp_config='exp_template.py', server_config='teaching.py')
id = w.assimilate(assim_time, prior_init_time, prior_valid_time, prior_path_exp)
diff --git a/config/exp_template.py b/config/exp_template.py
index 07247d7bc7265df4acae16e4800290dedc84b9b2..1aaa091a4303f6d1d2ba8424de1ed56ac9b2fe86 100755
--- a/config/exp_template.py
+++ b/config/exp_template.py
@@ -5,13 +5,13 @@ Copy and customize it as you wish.
from dartwrf.utils import Experiment
exp = Experiment()
-exp.expname = "exp_test"
+exp.expname = "exp_2"
exp.model_dx = 2000
-exp.n_ens = 4
+exp.n_ens = 40
exp.do_quality_control = False
# Path to the nature run. From there, observations are generated. Wildcards "*" are allowed in this path.
-exp.nature_wrfout_pattern = '/users/students/lehre/advDA_s2023/data/sample_nature/wrfout_d01_%Y-%m-%d_%H:%M:%S'
+exp.nature_wrfout_pattern = '/lehre/advDA_s2023/data/sample_nature/wrfout_d01_%Y-%m-%d_%H:%M:%S'
# Path to sounding profiles for ensemble initialization. Not used in the Advanced DA course.
exp.input_profile = '/mnt/jetfs/home/lkugler/data/initial_profiles/wrf/ens/2022-03-31/raso.fc.<iens>.wrfprof'
@@ -31,7 +31,7 @@ exp.dart_nml = {'&assim_tools_nml':
output_members='.true.',
output_mean='.true.',
output_sd='.true.',
- stages_to_write='output',
+ stages_to_write=['output', 'preassim', 'postassim'],
),
'&quality_control_nml':
dict(outlier_threshold='-1',
diff --git a/config/original_exp_template.py b/config/original_exp_template.py
new file mode 100755
index 0000000000000000000000000000000000000000..9fb12c4e45335746aa699dadde52f072dc7e1edc
--- /dev/null
+++ b/config/original_exp_template.py
@@ -0,0 +1,178 @@
+"""
+This configuration file is designed for the course Advanced Data Assimilation at the University of Vienna.
+Copy and customize it as you wish.
+"""
+from dartwrf.utils import Experiment
+
+exp = Experiment()
+exp.expname = "exp_test11"
+exp.model_dx = 2000
+exp.n_ens = 10
+exp.do_quality_control = False
+
+# Path to the nature run. From there, observations are generated. Wildcards "*" are allowed in this path.
+exp.nature_wrfout_pattern = '/lehre/advDA_s2023/data/sample_nature/wrfout_d01_%Y-%m-%d_%H:%M:%S'
+
+# Path to sounding profiles for ensemble initialization. Not used in the Advanced DA course.
+exp.input_profile = '/mnt/jetfs/home/lkugler/data/initial_profiles/wrf/ens/2022-03-31/raso.fc.<iens>.wrfprof'
+
+# Configuration of DART. For details see the DART or DART-WRF documentation.
+exp.dart_nml = {'&assim_tools_nml':
+ dict(filter_kind='1',
+ sampling_error_correction='.true.',
+ ),
+ '&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', '4'],
+ inf_initial=[1.04, 0.5],
+ inf_initial_from_restart='.false.',
+ output_members='.true.',
+ output_mean='.true.',
+ output_sd='.true.',
+ stages_to_write='output',
+ ),
+ '&quality_control_nml':
+ dict(outlier_threshold='-1',
+ ),
+ '&obs_def_radar_mod_nml':
+ dict(apply_ref_limit_to_obs = '.true.',
+ reflectivity_limit_obs = 5.0,
+ lowest_reflectivity_obs = 5.0,
+ apply_ref_limit_to_fwd_op = '.true.',
+ reflectivity_limit_fwd_op = 5.0,
+ lowest_reflectivity_fwd_op = 5.0,
+ microphysics_type = '5',
+ ),
+ '&location_nml':
+ dict(horiz_dist_only='.false.',
+ ),
+ '&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',],
+ ['QCLOUD','QTY_CLOUDWATER_MIXING_RATIO','TYPE_QC', 'UPDATE','999',],
+ ['QICE', 'QTY_ICE_MIXING_RATIO', 'TYPE_QI', 'UPDATE','999',],
+ # ['QRAIN','QTY_RAINWATER_MIXING_RATIO','TYPE_QR', 'UPDATE','999',],
+ # ['QSNOW','QTY_SNOW_MIXING_RATIO','TYPE_QS', 'UPDATE','999',],
+ # ['QGRAUP','QTY_GRAUPEL_MIXING_RATIO','TYPE_QG', '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',]],
+
+ wrf_state_bounds =
+ [['QVAPOR','0.0','NULL','CLAMP'],
+ ['QCLOUD','0.0','NULL','CLAMP'],
+ ['QICE','0.0','NULL','CLAMP'],
+ ['CLDFRA','0.0','1.0','CLAMP'],
+
+ # ['QRAIN','0.0','NULL','CLAMP'],
+ # ['QSNOW','0.0','NULL','CLAMP'],
+ # ['QGRAUP','0.0','NULL','CLAMP'],
+ ],
+ ),
+ '&ensemble_manager_nml':
+ dict(layout = 1,
+ tasks_per_node = 12,
+ communication_configuration = 1,
+ ),
+ }
+
+
+
+# n_obs is the number of observations
+# currently allowed values are 22500 for one observation approximately every 2km; 5776 for 4km, and 961 for 10km resolution; 256 for 20km; 121 for 30km
+# Note for radar, n_obs is the number of observations at each observation height level
+
+# oeinf is the observation inflation factor (1 means no inflation)
+oeinf = 1
+
+vis = dict(var_name='VIS 0.6µm', unit='[1]',
+ kind='MSG_4_SEVIRI_BDRF', sat_channel=1,
+ n_obs=961, obs_locations='square_array_evenly_on_grid',
+ # n_obs=1, obs_locations=[(44.141, -0.99)],
+ error_generate=0.03, error_assimilate=0.03*oeinf,
+ loc_horiz_km=20,
+ #height=4000, loc_vert_km=3
+ )
+
+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=1*oeinf,
+ loc_horiz_km=20,
+ #height=7000, loc_vert_km=3
+ )
+
+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',
+ # n_obs=1, obs_locations=[(44.141, -0.99)],
+ error_generate=1, error_assimilate=1*oeinf,
+ loc_horiz_km=20,
+ #height=10000, loc_vert_km=3
+ )
+
+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=961, obs_locations='square_array_evenly_on_grid',
+ # n_obs=2, obs_locations=[(45.332, 0.4735), (45.332, 0.53)],
+ heights=range(2000, 14001, 2000),
+ error_generate=2.5, error_assimilate=2.5*oeinf,
+ loc_horiz_km=20, loc_vert_km=3)
+
+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=50, loc_vert_km=2.5)
+
+t2m = dict(var_name='SYNOP Temperature', unit='[K]',
+ kind='SYNOP_TEMPERATURE',
+ n_obs=256, obs_locations='square_array_evenly_on_grid',
+ error_generate=0.3, error_assimilate=0.3,
+ loc_horiz_km=10, loc_vert_km=2)
+
+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 = [t]
+
+# the variables which will be replaced in the WRF initial conditions file
+exp.update_vars = ['U', 'V', 'W', 'THM', 'PH', 'MU', 'QVAPOR', 'QCLOUD', 'QICE', 'PSFC']
+#exp.update_vars = ['U', 'V', 'W', 'THM', 'PH', 'MU', 'QVAPOR', 'PSFC']
+#exp.update_vars = ['U', 'V', 'W', 'THM', 'PH', 'MU', 'QVAPOR', 'QCLOUD', 'QICE', 'QRAIN', 'QSNOW', 'QGRAUP', 'PSFC']
+#exp.update_vars = ['QVAPOR', 'QCLOUD', 'QICE', 'PSFC']
+
+exp.use_existing_obsseq = False
+# exp.use_existing_obsseq='/jetfs/home/lkugler/data/sim_archive/exp_v1.22_P2_rr_WV73_obs10_loc20_oe1/obs_seq_out/%Y-%m-%d_%H:%M_obs_seq.out'
+
+
+
+
diff --git a/config/teaching.py b/config/teaching.py
new file mode 100644
index 0000000000000000000000000000000000000000..ae45fc058670f42c22e28e6b296b7c1ffa824f7c
--- /dev/null
+++ b/config/teaching.py
@@ -0,0 +1,35 @@
+"""Cluster configuration file, see docstring of ClusterConfig class in dartwrf/utils.py for details"""
+from dartwrf import utils
+from dartwrf.exp_config import exp
+
+cluster = utils.ClusterConfig(exp)
+cluster.name = 'teaching'
+cluster.max_nproc = 6
+cluster.use_slurm = False
+
+# binaries
+cluster.python = 'python'
+cluster.python_verif = '/users/staff/lkugler/miniconda3/bin/python'
+cluster.ncks = '/headless/envs/rttov/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.exe'
+cluster.dart_modules = 'pip install scipy; '
+cluster.wrf_modules = ''
+
+# paths for data output
+cluster.wrf_rundir_base = utils.userhome+'/AdvDA/run_WRF/' # path for temporary files
+cluster.dart_rundir_base = utils.userhome+'/AdvDA/run_DART/' # path for temporary files
+cluster.archive_base = utils.userhome+'/data/sim_archive/'
+
+# paths used as input
+cluster.srcdir = '/users/staff/lkugler/AdvDA23/DART/WRF-4.3/run'
+cluster.dart_srcdir = '/headless/envs/DART/models/wrf/work'
+cluster.rttov_srcdir = '/headless/envs/rttov/rtcoef_rttov13/'
+cluster.dartwrf_dir = utils.userhome+'/AdvDA/DART-WRF/'
+cluster.geo_em_for_WRF_ideal = '/lehre/advDA_s2023/data/geo_em.d01.nc'
+
+# templates/run scripts
+cluster.namelist = cluster.dartwrf_dir+'/../templates/namelist.input'
+cluster.run_WRF = cluster.dartwrf_dir+'/run_ens.jet.sh'
+
+cluster.slurm_cfg = None
diff --git a/dartwrf/exp_config.py b/dartwrf/exp_config.py
index 58e71ed1b177b6febad8ad637033066a0816b91f..1aaa091a4303f6d1d2ba8424de1ed56ac9b2fe86 100644
--- a/dartwrf/exp_config.py
+++ b/dartwrf/exp_config.py
@@ -1,43 +1,52 @@
-from dartwrf import utils
-
-exp = utils.Experiment()
-exp.expname = "template_experiment"
+"""
+This configuration file is designed for the course Advanced Data Assimilation at the University of Vienna.
+Copy and customize it as you wish.
+"""
+from dartwrf.utils import Experiment
+
+exp = Experiment()
+exp.expname = "exp_2"
exp.model_dx = 2000
exp.n_ens = 40
-exp.superob_km = False # False or int (spatial averaging of observations, unit: km)
-exp.do_quality_control = False # bool
-
-# Use existing observations (path to obs_seq.out) or generate observations (False)
-exp.use_existing_obsseq = False
-#exp.use_existing_obsseq = '/users/students/lehre/advDA_s2023/dartwrf_tutorial/very_cold_observation.out'
+exp.do_quality_control = False
-# path from where observations can be generated
-exp.nature_wrfout_pattern = '/jetfs/home/lkugler/data/sim_archive/exp_v1.19_P3_wbub7_nat/*/1/wrfout_d01_%Y-%m-%d_%H:%M:%S'
+# Path to the nature run. From there, observations are generated. Wildcards "*" are allowed in this path.
+exp.nature_wrfout_pattern = '/lehre/advDA_s2023/data/sample_nature/wrfout_d01_%Y-%m-%d_%H:%M:%S'
-# for initialization profiles
+# Path to sounding profiles for ensemble initialization. Not used in the Advanced DA course.
exp.input_profile = '/mnt/jetfs/home/lkugler/data/initial_profiles/wrf/ens/2022-03-31/raso.fc.<iens>.wrfprof'
-
+# Configuration of DART. For details see the DART or DART-WRF documentation.
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',
+ sampling_error_correction='.true.',
),
'&filter_nml':
- dict(ens_size=exp.n_ens,
+ dict( ens_size=exp.n_ens,
num_output_state_members=exp.n_ens,
num_output_obs_members=exp.n_ens,
- inf_flavor=['0', '0'],
+ inf_flavor=['0', '4'],
+ inf_initial=[1.04, 0.5],
+ inf_initial_from_restart='.false.',
output_members='.true.',
output_mean='.true.',
output_sd='.true.',
- stages_to_write='output',
+ stages_to_write=['output', 'preassim', 'postassim'],
),
- '&quality_control_nml':
+ '&quality_control_nml':
dict(outlier_threshold='-1',
),
+ '&obs_def_radar_mod_nml':
+ dict(apply_ref_limit_to_obs = '.true.',
+ reflectivity_limit_obs = 5.0,
+ lowest_reflectivity_obs = 5.0,
+ apply_ref_limit_to_fwd_op = '.true.',
+ reflectivity_limit_fwd_op = 5.0,
+ lowest_reflectivity_fwd_op = 5.0,
+ microphysics_type = '5',
+ ),
'&location_nml':
- dict(horiz_dist_only='.true.',
+ dict(horiz_dist_only='.false.',
),
'&model_nml':
dict(wrf_state_variables =
@@ -47,38 +56,72 @@ exp.dart_nml = {'&assim_tools_nml':
['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',],
+ ['QICE', 'QTY_ICE_MIXING_RATIO', 'TYPE_QI', 'UPDATE','999',],
+ # ['QRAIN','QTY_RAINWATER_MIXING_RATIO','TYPE_QR', 'UPDATE','999',],
+ # ['QSNOW','QTY_SNOW_MIXING_RATIO','TYPE_QS', 'UPDATE','999',],
+ # ['QGRAUP','QTY_GRAUPEL_MIXING_RATIO','TYPE_QG', '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',]]),
+ ['REFL_10CM','QTY_RADAR_REFLECTIVITY','TYPE_REFL', 'UPDATE','999',]],
+
+ wrf_state_bounds =
+ [['QVAPOR','0.0','NULL','CLAMP'],
+ ['QCLOUD','0.0','NULL','CLAMP'],
+ ['QICE','0.0','NULL','CLAMP'],
+ ['CLDFRA','0.0','1.0','CLAMP'],
+
+ # ['QRAIN','0.0','NULL','CLAMP'],
+ # ['QSNOW','0.0','NULL','CLAMP'],
+ # ['QGRAUP','0.0','NULL','CLAMP'],
+ ],
+ ),
+ '&ensemble_manager_nml':
+ dict(layout = 1,
+ tasks_per_node = 12,
+ communication_configuration = 1,
+ ),
}
-# 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
+
+# n_obs is the number of observations
+# currently allowed values are 22500 for one observation approximately every 2km; 5776 for 4km, and 961 for 10km resolution; 256 for 20km; 121 for 30km
+# Note for radar, n_obs is the number of observations at each observation height level
+
+# oeinf is the observation inflation factor (1 means no inflation)
+oeinf = 1
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=961, 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)
+ error_generate=0.03, error_assimilate=0.03*oeinf,
+ loc_horiz_km=20,
+ #height=4000, loc_vert_km=3
+ )
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)
+ error_generate=1, error_assimilate=1*oeinf,
+ loc_horiz_km=20,
+ #height=7000, loc_vert_km=3
+ )
+
+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',
+ # n_obs=1, obs_locations=[(44.141, -0.99)],
+ error_generate=1, error_assimilate=1*oeinf,
+ loc_horiz_km=20,
+ #height=10000, loc_vert_km=3
+ )
ir108 = dict(var_name='Brightness temperature IR 10.8µm', unit='[K]',
kind='MSG_4_SEVIRI_TB', sat_channel=9,
@@ -88,10 +131,11 @@ ir108 = dict(var_name='Brightness temperature IR 10.8µm', unit='[K]',
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,
+ n_obs=961, obs_locations='square_array_evenly_on_grid',
+ # n_obs=2, obs_locations=[(45.332, 0.4735), (45.332, 0.53)],
heights=range(2000, 14001, 2000),
- loc_horiz_km=20, loc_vert_km=2.5)
+ error_generate=2.5, error_assimilate=2.5*oeinf,
+ loc_horiz_km=20, loc_vert_km=3)
t = dict(var_name='Temperature', unit='[K]',
kind='RADIOSONDE_TEMPERATURE',
@@ -102,25 +146,33 @@ t = dict(var_name='Temperature', unit='[K]',
loc_horiz_km=50, loc_vert_km=2.5)
q = dict(var_name='Specific humidity', unit='[kg/kg]',
- kind='RADIOSONDE_SPECIFIC_HUMIDITY',
- n_obs=961, obs_locations='square_array_evenly_on_grid',
+ 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)
+ loc_horiz_km=50, loc_vert_km=2.5)
t2m = dict(var_name='SYNOP Temperature', unit='[K]',
kind='SYNOP_TEMPERATURE',
- n_obs=961, obs_locations='square_array_evenly_on_grid',
- error_generate=0.1, error_assimilate=0.1,
- loc_horiz_km=40, loc_vert_km=2.5)
+ n_obs=256, obs_locations='square_array_evenly_on_grid',
+ error_generate=0.3, error_assimilate=0.3,
+ loc_horiz_km=10, loc_vert_km=2)
psfc = dict(var_name='SYNOP Pressure', unit='[Pa]',
- kind='SYNOP_SURFACE_PRESSURE',
- n_obs=961, obs_locations='square_array_evenly_on_grid',
+ 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.observations = [t]
+
+# the variables which will be replaced in the WRF initial conditions file
exp.update_vars = ['U', 'V', 'W', 'THM', 'PH', 'MU', 'QVAPOR', 'QCLOUD', 'QICE', 'PSFC']
+#exp.update_vars = ['U', 'V', 'W', 'THM', 'PH', 'MU', 'QVAPOR', 'PSFC']
+#exp.update_vars = ['U', 'V', 'W', 'THM', 'PH', 'MU', 'QVAPOR', 'QCLOUD', 'QICE', 'QRAIN', 'QSNOW', 'QGRAUP', 'PSFC']
+#exp.update_vars = ['QVAPOR', 'QCLOUD', 'QICE', 'PSFC']
+
+exp.use_existing_obsseq = False
+# exp.use_existing_obsseq='/jetfs/home/lkugler/data/sim_archive/exp_v1.22_P2_rr_WV73_obs10_loc20_oe1/obs_seq_out/%Y-%m-%d_%H:%M_obs_seq.out'
+
+
diff --git a/dartwrf/server_config.py b/dartwrf/server_config.py
index bd9c6b174c46f698408e0759df8241ef430fad5d..ae45fc058670f42c22e28e6b296b7c1ffa824f7c 100755
--- a/dartwrf/server_config.py
+++ b/dartwrf/server_config.py
@@ -3,39 +3,33 @@ from dartwrf import utils
from dartwrf.exp_config import exp
cluster = utils.ClusterConfig(exp)
-cluster.name = 'jet'
-cluster.max_nproc = 12
-cluster.use_slurm = True
-cluster.size_jobarray = 40
+cluster.name = 'teaching'
+cluster.max_nproc = 6
+cluster.use_slurm = False
# 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
-"""
+cluster.python = 'python'
+cluster.python_verif = '/users/staff/lkugler/miniconda3/bin/python'
+cluster.ncks = '/headless/envs/rttov/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.exe'
+cluster.dart_modules = 'pip install scipy; '
+cluster.wrf_modules = ''
# 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/'
+cluster.wrf_rundir_base = utils.userhome+'/AdvDA/run_WRF/' # path for temporary files
+cluster.dart_rundir_base = utils.userhome+'/AdvDA/run_DART/' # path for temporary files
+cluster.archive_base = utils.userhome+'/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/'
+cluster.srcdir = '/users/staff/lkugler/AdvDA23/DART/WRF-4.3/run'
+cluster.dart_srcdir = '/headless/envs/DART/models/wrf/work'
+cluster.rttov_srcdir = '/headless/envs/rttov/rtcoef_rttov13/'
+cluster.dartwrf_dir = utils.userhome+'/AdvDA/DART-WRF/'
+cluster.geo_em_for_WRF_ideal = '/lehre/advDA_s2023/data/geo_em.d01.nc'
-# 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'
+# templates/run scripts
+cluster.namelist = cluster.dartwrf_dir+'/../templates/namelist.input'
+cluster.run_WRF = cluster.dartwrf_dir+'/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"}
+cluster.slurm_cfg = None