diff --git a/config/cfg.py b/config/cfg.py
index 8a833a6659cd82e4498917e0e87079e07c6f0a5c..a74f175765168b542b0fa402f10d1aa81e011fcc 100755
--- a/config/cfg.py
+++ b/config/cfg.py
@@ -1,20 +1,21 @@
from dartwrf import utils
exp = utils.Experiment()
-exp.expname = "obs-cold_localization-narrow"
+exp.expname = "test_WV73_many_inf3"
exp.model_dx = 2000
-exp.n_ens = 10
+exp.n_ens = 20
exp.filter_kind = 1
-exp.prior_inflation = 0
-exp.post_inflation = 4
+exp.prior_inflation = 3
+exp.inf_initial = 4
+exp.post_inflation = 0
exp.sec = True
-exp.cov_loc_vert_km_horiz_km = (4, 40)
+exp.cov_loc_vert_km_horiz_km = False #(2, 10)
exp.superob_km = False # False or int (spatial averaging of observations)
exp.adjust_obs_impact = False
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'
+#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 = '/users/students/lehre/advDA_s2023/data/sample_nature/'
@@ -39,9 +40,9 @@ wv62 = dict(plotname='Brightness temperature WV 6.2µm', plotunits='[K]',
wv73 = dict(plotname='Brightness temperature WV 7.3µm', plotunits='[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.,
- cov_loc_radius_km=20)
+ n_obs=256, obs_locations='square_array_evenly_on_grid',
+ error_generate=2., error_assimilate=2.,
+ cov_loc_radius_km=10)
ir108 = dict(plotname='Brightness temperature IR 10.8µm', plotunits='[K]',
kind='MSG_4_SEVIRI_TB', sat_channel=9,
@@ -58,29 +59,30 @@ radar = dict(plotname='Radar reflectivity', plotunits='[dBz]',
t = dict(plotname='Temperature', plotunits='[K]',
kind='RADIOSONDE_TEMPERATURE',
- #n_obs=22500, obs_locations='square_array_evenly_on_grid',
+ #n_obs=961, 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),
- cov_loc_radius_km=50)
+ heights=range(700, 17701, 500),
+ cov_loc_radius_km=100)
q = dict(plotname='Specific humidity', plotunits='[kg/kg]',
kind='RADIOSONDE_SPECIFIC_HUMIDITY', n_obs=1,
error_generate=0., error_assimilate=5*1e-5,
- heights=[1000], #range(1000, 17001, 2000),
+ heights=[1500], #range(1000, 17001, 2000),
cov_loc_radius_km=0.1)
t2m = dict(plotname='SYNOP Temperature', plotunits='[K]',
- kind='SYNOP_TEMPERATURE', n_obs=1,
- error_generate=0.1, error_assimilate=0.1,
- cov_loc_radius_km=40)
+ kind='SYNOP_TEMPERATURE',
+ #n_obs=1, obs_locations=[(45., 0.)],
+ n_obs=256, obs_locations='square_array_evenly_on_grid',
+ error_generate=1, error_assimilate=1,
+ cov_loc_radius_km=10)
psfc = dict(plotname='SYNOP Pressure', plotunits='[Pa]',
kind='SYNOP_SURFACE_PRESSURE', n_obs=1,
error_generate=50., error_assimilate=100.,
cov_loc_radius_km=32)
-exp.observations = [t2m]
+exp.observations = [wv73]
exp.update_vars = ['U', 'V', 'W', 'THM', 'PH', 'MU', 'QVAPOR', 'QCLOUD', 'QICE', 'PSFC']
-#exp.update_vars = ['U', 'V', 'W', 'T', 'PH', 'MU', 'QVAPOR', 'PSFC']
diff --git a/dartwrf/assim_synth_obs.py b/dartwrf/assim_synth_obs.py
index 7fcc052fb996cee0e9342832c4ffbb2a0ebf7c06..3396f82d542abc84030fc5590b1bb980b87ede78 100755
--- a/dartwrf/assim_synth_obs.py
+++ b/dartwrf/assim_synth_obs.py
@@ -46,6 +46,7 @@ def set_DART_nml(just_prior_values=False):
"<sampling_error_correction>": '.true.' if exp.sec else '.false.',
"<prior_inflation>": str(exp.prior_inflation),
"<post_inflation>": str(exp.post_inflation),
+ "<inf_initial>": str(exp.inf_initial),
"<n_ens>": str(int(exp.n_ens)),
"<cov_loc_radian>": "0.00000001", # dummy value, used for types not mentioned below
"<list_obstypes>": "'" + "','".join(list_obstypes) + "'",
@@ -220,11 +221,11 @@ def archive_filteroutput(time):
)
try: # not necessary for next forecast run
- for iens in range(1, exp.n_ens + 1):
- copy(
- cluster.dartrundir + "/postassim_member_" + str(iens).zfill(4) + ".nc",
- archive_assim + "/postassim_member_" + str(iens).zfill(4) + ".nc",
- )
+ ftypes = ['preassim', 'postassim']
+ for ftype in ftypes:
+ for iens in range(1, exp.n_ens + 1):
+ fname = "/"+ftype+"_member_" + str(iens).zfill(4) + ".nc"
+ copy(cluster.dartrundir + fname, archive_assim + fname)
for f in ["output_mean.nc", "output_sd.nc"]: # copy mean and sd to archive
copy(cluster.dartrundir + "/" + f, archive_assim + "/" + f)
@@ -258,26 +259,32 @@ def get_parametrized_error(obscfg, osf_prior):
NotImplementedError('sat_channel not implemented', obscfg.get("sat_channel"))
-def set_obserr_assimilate_in_obsseqout(oso, osf_prior, outfile="./obs_seq.out"):
+def set_obserr_assimilate_in_obsseqout(oso, outfile="./obs_seq.out"):
""""Overwrite existing variance values in obs_seq.out files
Args:
oso (ObsSeq): python representation of obs_seq.out file, will be modified and written to file
- osf_prior (ObsSeq): python representation of obs_seq.final (output of filter in evaluate-mode without posterior)
- contains prior values; used for parameterized errors
Returns:
None (writes to file)
+
+ Variables:
+ osf_prior (ObsSeq): python representation of obs_seq.final (output of filter in evaluate-mode without posterior)
+ contains prior values; used for parameterized errors
"""
+
for obscfg in exp.observations:
- kind_str = obscfg['kind']
- kind = osq.obs_kind_nrs[kind_str]
+ kind_str = obscfg['kind'] # e.g. 'RADIOSONDE_TEMPERATURE'
+ kind = osq.obs_kind_nrs[kind_str] # e.g. 263
- # modify each kind separately, one after each other
+ # modify observation error of each kind sequentially
where_oso_iskind = oso.df.kind == kind
- where_osf_iskind = osf_prior.df.kind == kind
-
+
if obscfg["error_assimilate"] == False:
+ osf_prior = obsseq.ObsSeq(cluster.dartrundir + "/obs_seq.final") # this file will be generated by `evaluate()`
+
+ where_osf_iskind = osf_prior.df.kind == kind
+
assim_err = get_parametrized_error(obscfg, osf_prior.df[where_osf_iskind])
oso.df.loc[where_oso_iskind, 'variance'] = assim_err**2
#assert np.allclose(assim_err, oso.df['variance']**2) # check
@@ -287,7 +294,9 @@ def set_obserr_assimilate_in_obsseqout(oso, osf_prior, outfile="./obs_seq.out"):
oso.to_dart(outfile)
-def qc_obs(time, oso, osf_prior):
+def qc_obs(time, oso):
+ osf_prior = obsseq.ObsSeq(cluster.dartrundir + "/obs_seq.final")
+
# obs should be superobbed already!
for i, obscfg in enumerate(exp.observations):
if i > 0:
@@ -372,9 +381,6 @@ def evaluate(assim_time,
copy(cluster.dartrundir + "/obs_seq.final", fout)
print(fout, "saved.")
- osf = obsseq.ObsSeq(cluster.dartrundir + "/obs_seq.final")
- return osf
-
def generate_obsseq_out(time):
@@ -470,7 +476,7 @@ def prepare_inflation_2(time, prior_init_time):
if os.path.isfile(f_prior):
copy(f_prior, f_new)
print(f_prior, 'copied to', f_new)
- else:
+ else: # no prior inflation file at the first assimilation
warnings.warn(f_prior + ' does not exist. Using default file instead.')
copy(f_default, f_new)
@@ -521,9 +527,14 @@ def main(time, prior_init_time, prior_valid_time, prior_path_exp):
None
"""
nproc = cluster.max_nproc
+ do_QC = getattr(exp, "reject_smallFGD", False) # True: triggers additional evaluations of prior & posterior
+ # for which observation type do we have a parametrized observation error?
+ error_is_parametrized = [obscfg["error_assimilate"] == False for obscfg in exp.observations]
+
+ # create directory to run DART in
archive_time = cluster.archivedir + time.strftime("/%Y-%m-%d_%H:%M/")
- os.makedirs(cluster.dartrundir, exist_ok=True) # create directory to run DART in
+ os.makedirs(cluster.dartrundir, exist_ok=True)
os.chdir(cluster.dartrundir)
# link DART binaries to run_DART
@@ -539,18 +550,20 @@ def main(time, prior_init_time, prior_valid_time, prior_path_exp):
print("prepare prior ensemble")
prepare_prior_ensemble(time, prior_init_time, prior_valid_time, prior_path_exp)
- print(" 1) get observations with specified obs-error")
+ print(" get observations with specified obs-error")
oso = get_obsseq_out(time)
- print(" 2.1) evaluate prior for all observations (incl rejected)")
- osf_prior = evaluate(time, output_format="%Y-%m-%d_%H:%M_obs_seq.final-eval_prior_allobs")
+ # is any observation error parametrized?
+ if any(error_is_parametrized) or do_QC:
+ print(" (optional) evaluate prior for all observations (incl rejected)")
+ evaluate(time, output_format="%Y-%m-%d_%H:%M_obs_seq.final-eval_prior_allobs")
- print(" 2.2) assign observation-errors for assimilation ")
- set_obserr_assimilate_in_obsseqout(oso, osf_prior, outfile=cluster.dartrundir + "/obs_seq.out")
+ print(" assign observation-errors for assimilation ")
+ set_obserr_assimilate_in_obsseqout(oso, outfile=cluster.dartrundir + "/obs_seq.out")
- if getattr(exp, "reject_smallFGD", False):
+ if do_QC:
print(" 2.3) reject observations? ")
- qc_obs(time, oso, osf_prior)
+ qc_obs(time, oso)
if exp.prior_inflation == 2:
prepare_inflation_2(time, prior_init_time)
@@ -563,12 +576,13 @@ def main(time, prior_init_time, prior_valid_time, prior_path_exp):
if exp.prior_inflation == 2:
archive_inflation_2(time)
- print(" 4) evaluate posterior observations for all observations (incl rejected)")
- write_list_of_inputfiles_posterior(time)
- if getattr(exp, "reject_smallFGD", False):
+ if do_QC:
+ print(" 4) evaluate posterior observations for all observations (incl rejected)")
+ write_list_of_inputfiles_posterior(time)
+
copy(cluster.archivedir+'/obs_seq_out/'+time.strftime('%Y-%m-%d_%H:%M_obs_seq.out-beforeQC'),
cluster.dartrundir+'/obs_seq.out')
- evaluate(time, output_format="%Y-%m-%d_%H:%M_obs_seq.final-eval_posterior_allobs")
+ evaluate(time, output_format="%Y-%m-%d_%H:%M_obs_seq.final-eval_posterior_allobs")
if __name__ == "__main__":
diff --git a/templates/input.nml b/templates/input.nml
index 38edbde9bd8e107176766e6fadeb563c7d3f3670..2c987da02a3247b5cd5fcbdefdbd36e50724992c 100644
--- a/templates/input.nml
+++ b/templates/input.nml
@@ -51,19 +51,19 @@
output_timestamps = .false.,
trace_execution = .false.,
- stages_to_write = 'preassim', 'postassim'
+ stages_to_write = 'preassim', 'postassim', 'output'
output_members = .true.
output_mean = .true.
output_sd = .true.
write_all_stages_at_end = .false.
inf_flavor = <prior_inflation>, <post_inflation>,
- inf_initial_from_restart = .true., .false.,
- inf_sd_initial_from_restart = .true., .false.,
- inf_initial = 1.00, 0.90,
+ inf_initial_from_restart = .false., .false.,
+ inf_sd_initial_from_restart = .false., .false.,
+ inf_initial = <inf_initial>, 0.90,
inf_lower_bound = 1.0, 1.0,
inf_upper_bound = 1000000.0, 1000000.0,
- inf_damping = 0.9, 1.0,
+ inf_damping = 1.0, 1.0,
inf_sd_initial = 0.6, 0.0,
inf_sd_lower_bound = 0.6, 0.0,
inf_sd_max_change = 1.05, 1.05,