From 1fbfb3ae0dc1a445b7416ed1929079d5ba5b0cf3 Mon Sep 17 00:00:00 2001
From: lkugler <lukas.kugler@gmail.com>
Date: Mon, 29 Mar 2021 20:48:13 +0200
Subject: [PATCH] fix in using output as input
---
scripts/assim_synth_obs.py | 55 +++++++++++++++++++++++++++-----------
1 file changed, 39 insertions(+), 16 deletions(-)
diff --git a/scripts/assim_synth_obs.py b/scripts/assim_synth_obs.py
index cddbbac..6b626d1 100755
--- a/scripts/assim_synth_obs.py
+++ b/scripts/assim_synth_obs.py
@@ -1,5 +1,4 @@
-import os, sys, shutil
-import warnings
+import os, sys, shutil, warnings
import datetime as dt
import numpy as np
from scipy.interpolate import interp1d
@@ -201,6 +200,11 @@ def archive_diagnostics(archive_dir, time):
copy(cluster.dartrundir+'/obs_seq.final', fout)
print(fout, 'saved.')
+ try:
+ copy(cluster.dartrundir+'/obs_coords.pkl', archive_stage+'/obs_coords.pkl')
+ except Exception as e:
+ warnings.warn(str(e))
+
# try: # what are regression diagnostics?!
# print('archive regression diagnostics')
# copy(cluster.dartrundir+'/reg_diagnostics', archive_dir+'/reg_diagnostics')
@@ -208,10 +212,27 @@ def archive_diagnostics(archive_dir, time):
# warnings.warn(str(e))
def recycle_output():
- print('move output to input')
+ update_vars = ['U', 'V', 'T', 'PH', 'MU', 'QVAPOR', 'QCLOUD', 'QICE', 'QRAIN', 'U10', 'V10', 'T2', 'Q2', 'TSK', 'PSFC', 'CLDFRA']
+ updates = ','.join(update_vars)
+
+ print('recycle DART output to be used as input')
for iens in range(1, exp.n_ens+1):
- os.rename(cluster.dartrundir+'/filter_restart_d01.'+str(iens).zfill(4),
- cluster.dartrundir+'/advance_temp'+str(iens)+'/wrfout_d01')
+ dart_output = cluster.dartrundir+'/filter_restart_d01.'+str(iens).zfill(4)
+ dart_input = cluster.dartrundir+'/advance_temp'+str(iens)+'/wrfout_d01'
+
+ #print('check for non-monotonic vertical pressure')
+
+ # convert link to file in order to be able to update the content
+ if os.path.islink(dart_input):
+ l = os.readlink(dart_input)
+ os.remove(dart_input)
+ copy(l, dart_input)
+
+ # print('move DART output to input: '+dart_output+' -> '+dart_input)
+ # os.rename(dart_output, dart_input) # probably doesnt work
+
+ print('updating', updates, 'in', dart_input, 'from', dart_output)
+ os.system(cluster.ncks+' -A -v '+updates+' '+dart_output+' '+dart_input)
def archive_output(archive_stage):
print('archiving output')
@@ -219,11 +240,12 @@ def archive_output(archive_stage):
copy(cluster.dartrundir+'/input.nml', archive_stage+'/input.nml')
# single members
- # for iens in range(1, exp.n_ens+1):
- # savedir = archive_stage+'/'+str(iens)
- # mkdir(savedir)
- # filter_in = cluster.dartrundir+'/preassim_member_'+str(iens).zfill(4)+'.nc'
- # filter_out = cluster.dartrundir+'/filter_restart_d01.'+str(iens).zfill(4)
+ for iens in range(1, exp.n_ens+1):
+ #savedir = archive_stage+'/'+str(iens)
+ #mkdir(savedir)
+ # filter_in = cluster.dartrundir+'/preassim_member_'+str(iens).zfill(4)+'.nc'
+ filter_out = cluster.dartrundir+'/filter_restart_d01.'+str(iens).zfill(4)
+ copy(filter_out, archive_stage+'/filter_restart_d01.'+str(iens).zfill(4))
# copy mean and sd to archive
for f in ['output_mean.nc', 'output_sd.nc']:
@@ -260,11 +282,11 @@ if __name__ == "__main__":
n_stages = len(exp.observations)
for istage, obscfg in enumerate(exp.observations):
+ print('running observation stage', istage, obscfg)
- archive_stage = archive_time + '/assim_stage'+str(istage)
+ archive_stage = archive_time + '/assim_stage'+str(istage)+'/'
n_obs = obscfg['n_obs']
sat_channel = obscfg.get('sat_channel', False)
- obscfg['folder_obs_coords'] = archive_stage+'/obs_coords.pkl'
set_DART_nml(sat_channel=sat_channel,
cov_loc_radius_km=obscfg['cov_loc_radius_km'],
@@ -284,9 +306,10 @@ if __name__ == "__main__":
else:
obscfg['err_std'] = np.ones(n_obs) * obscfg['err_std'] # fixed stderr
- osq.create_obsseq_in(time, obscfg) # now with correct errors
- prepare_nature_dart(time)
- run_perfect_model_obs()
+ # create obs template file, now with correct errors
+ osq.create_obsseq_in(time, obscfg, archive_obs_coords=archive_stage+'/obs_coords.pkl')
+ prepare_nature_dart(time) # link WRF files to DART directory
+ run_perfect_model_obs() # actually create observations that are used to assimilate
assimilate()
dir_obsseq = cluster.archivedir()+'/obs_seq_final/assim_stage'+str(istage)
@@ -294,8 +317,8 @@ if __name__ == "__main__":
if istage < n_stages-1:
# recirculation: filter output -> input
- recycle_output()
archive_output(archive_stage)
+ recycle_output()
elif istage == n_stages-1:
# last assimilation, continue integration now
--
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