inf_initial + preassim archive

config/cfg.py

 from dartwrf import utils
 
 exp = utils.Experiment()
-exp.expname = "obs-cold_localization-narrow"
+exp.expname = "obs-T_inflation-1.1"
 exp.model_dx = 2000
 exp.n_ens = 10
 
 exp.filter_kind = 1
 exp.prior_inflation = 0
+exp.inf_initial = 1.1
 exp.post_inflation = 4
 exp.sec = True
 exp.cov_loc_vert_km_horiz_km = (4, 40)
@@ -14,7 +15,7 @@ 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/'
@@ -58,11 +59,11 @@ 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=1, obs_locations=[(45., 0.)],
+         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)
+         cov_loc_radius_km=30)
 
 q = dict(plotname='Specific humidity', plotunits='[kg/kg]',
          kind='RADIOSONDE_SPECIFIC_HUMIDITY', n_obs=1,
@@ -80,7 +81,6 @@ psfc = dict(plotname='SYNOP Pressure', plotunits='[Pa]',
             error_generate=50., error_assimilate=100.,
             cov_loc_radius_km=32)
 
-exp.observations = [t2m]
+exp.observations = [t]
 exp.update_vars = ['U', 'V', 'W', 'THM', 'PH', 'MU', 'QVAPOR', 'QCLOUD', 'QICE', 'PSFC']
-#exp.update_vars = ['U', 'V', 'W', 'T', 'PH', 'MU', 'QVAPOR', 'PSFC']
 

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)

templates/input.nml

@@ -60,7 +60,7 @@
    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                 = <inf_initial>,                0.90,
    inf_lower_bound             = 1.0,                     1.0,
    inf_upper_bound             = 1000000.0,               1000000.0,
    inf_damping                 = 0.9,                     1.0,