From 7c7c37bd46bad35ab85ff99334dbb5b1b6c0599c Mon Sep 17 00:00:00 2001
From: lkugler <lukas.kugler@gmail.com>
Date: Tue, 16 Nov 2021 11:49:56 +0100
Subject: [PATCH] outdated scripts
---
scripts/assim_synth_obs_separate_obstypes.py | 378 -------------------
scripts/prepare_nature.py | 16 -
2 files changed, 394 deletions(-)
delete mode 100755 scripts/assim_synth_obs_separate_obstypes.py
delete mode 100755 scripts/prepare_nature.py
diff --git a/scripts/assim_synth_obs_separate_obstypes.py b/scripts/assim_synth_obs_separate_obstypes.py
deleted file mode 100755
index 9ae4a74..0000000
--- a/scripts/assim_synth_obs_separate_obstypes.py
+++ /dev/null
@@ -1,378 +0,0 @@
-import os, sys, shutil, warnings
-import datetime as dt
-import numpy as np
-from scipy.interpolate import interp1d
-
-from config.cfg import exp, cluster
-from utils import symlink, copy, sed_inplace, append_file, mkdir, try_remove, print
-import create_obsseq as osq
-import wrfout_add_geo
-
-earth_radius_km = 6370
-
-# fit of Fig 7, Harnisch 2016
-x_ci = [0, 5, 10.5, 13, 16]
-y_oe = [1, 4.5, 10, 12, 13] # Kelvin
-oe_73_linear = interp1d(x_ci, y_oe, assume_sorted=True)
-
-def oe_73(ci):
- if ci < 13:
- return oe_73_linear(ci)
- else:
- return 16.
-
-def cloudimpact_73(bt_mod, bt_obs):
- """
- follows Harnisch 2016
- """
- biascor_obs = 0
- bt_lim = 255 # Kelvin for 7.3 micron WV channel
-
- ci_obs = max(0, bt_lim-(bt_obs - biascor_obs))
- ci_mod = max(0, bt_lim-bt_mod)
- ci = (ci_obs+ci_mod)/2
- return ci
-
-def read_prior_obs(f_obs_prior):
- """
- docstring
- """
- obsseq = open(f_obs_prior, 'r').readlines()
- OBSs = []
- # read observations from obs_seq.final
- for i, line in enumerate(obsseq):
- if ' OBS ' in line:
- observed = float(obsseq[i+1].strip())
- truth = float(obsseq[i+2].strip())
- prior_ensmean = float(obsseq[i+3].strip())
- prior_enssd = float(obsseq[i+4].strip())
- prior_ens = []
- for j in range(5, 5+exp.n_ens):
- prior_ens.append(float(obsseq[i+j].strip()))
-
- OBSs.append(dict(observed=observed, truth=truth, prior_ens=np.array(prior_ens)))
- return OBSs
-
-def read_truth_obs_obsseq(f):
- """Reads observed and true values from obs_seq.out/final files."""
- obsseq = open(f, 'r').readlines()
- true = []
- obs = []
- # read observations from obs_seq.out
- for i, line in enumerate(obsseq):
- if ' OBS ' in line:
- observed = float(obsseq[i+1].strip())
- truth = float(obsseq[i+2].strip())
- true.append(truth)
- obs.append(observed)
- return true, obs
-
-def replace_errors_obsseqout(f, new_errors):
- """Replaces existing observation errors in obs_seq.final files
-
- new_errors (np.array) : standard deviation,
- shape must match the number of observations
- """
- obsseq = open(f, 'r').readlines()
-
- # find number of lines between two ' OBS ' lines:
- first_obs = None
- for i, line in enumerate(obsseq):
- if ' OBS ' in line:
- if first_obs is None:
- first_obs = i
- else:
- second_obs = i
- break
- lines_between = second_obs - first_obs
- lines_obserr_after_obsnr = lines_between - 1 # obserr line is one before ' OBS ' line
-
- # replace values in list obsseq
- i_obs = 0
- for i, line in enumerate(obsseq):
- if ' OBS ' in line:
- line_error_obs_i = i+lines_obserr_after_obsnr
-
- previous_err_var = obsseq[line_error_obs_i]
- new_err_obs_i = new_errors[i_obs]**2 # variance in obs_seq.out
- #print('previous err var ', previous_err_var, 'new error', new_err_obs_i)
- obsseq[line_error_obs_i] = ' '+str(new_err_obs_i)+' \n'
-
- i_obs += 1 # next iteration
-
- with open(f, 'w') as file:
- for line in obsseq:
- file.write(line)
- print('replaced obs errors in', f)
-
-
-def set_DART_nml(sat_channel=False, cov_loc_radius_km=32, cov_loc_vert_km=False,
- just_prior_values=False):
- """descr"""
- cov_loc_radian = cov_loc_radius_km/earth_radius_km
-
- if just_prior_values:
- template = cluster.scriptsdir+'/../templates/input.eval.nml'
- else:
- template = cluster.scriptsdir+'/../templates/input.nml'
- copy(template, cluster.dartrundir+'/input.nml')
-
- # options are overwritten with settings
- options = {'<n_ens>': str(int(exp.n_ens)),
- '<cov_loc_radian>': str(cov_loc_radian)}
-
- if cov_loc_vert_km:
- vert_norm_rad = earth_radius_km*cov_loc_vert_km/cov_loc_radius_km*1000
- options['<horiz_dist_only>'] = '.false.'
- options['<vert_norm_hgt>'] = str(vert_norm_rad)
- else:
- options['<horiz_dist_only>'] = '.true.'
- options['<vert_norm_hgt>'] = '50000.0' # dummy value
-
- for key, value in options.items():
- sed_inplace(cluster.dartrundir+'/input.nml', key, value)
-
- # input.nml for RTTOV
- if sat_channel > 0:
- if sat_channel in [1, 2, 3, 12]: # VIS channels
- rttov_nml = cluster.scriptsdir+'/../templates/obs_def_rttov.VIS.nml'
- else: # IR channels
- rttov_nml = cluster.scriptsdir+'/../templates/obs_def_rttov.IR.nml'
- append_file(cluster.dartrundir+'/input.nml', rttov_nml)
- else:
- # append any rttov segment, needs to exist anyway
- rttov_nml = cluster.scriptsdir+'/../templates/obs_def_rttov.IR.nml'
- append_file(cluster.dartrundir+'/input.nml', rttov_nml)
-
-def obs_operator_ensemble(istage):
- # assumes that prior ensemble is already linked to advance_temp<i>/wrfout_d01
- print('running obs operator on ensemble forecast')
- os.chdir(cluster.dartrundir)
-
- if sat_channel:
- list_ensemble_truths = []
-
- for iens in range(1, exp.n_ens+1):
- print('observation operator for ens #'+str(iens))
- # ens members are already linked to advance_temp<i>/wrfout_d01
- copy(cluster.dartrundir+'/advance_temp'+str(iens)+'/wrfout_d01',
- cluster.dartrundir+'/wrfout_d01')
- # DART may need a wrfinput file as well, which serves as a template for dimension sizes
- symlink(cluster.dartrundir+'/wrfout_d01', cluster.dartrundir+'/wrfinput_d01')
-
- # add geodata, if istage>0, wrfout is DART output (has coords)
- if istage == 0:
- wrfout_add_geo.run(cluster.dartrundir+'/geo_em.d01.nc', cluster.dartrundir+'/wrfout_d01')
-
- # run perfect_model obs (forward operator)
- os.system('mpirun -np 12 ./perfect_model_obs > /dev/null')
-
- # truth values in obs_seq.out are H(x) values
- true, _ = read_truth_obs_obsseq(cluster.dartrundir+'/obs_seq.out')
- list_ensemble_truths.append(true)
-
- n_obs = len(list_ensemble_truths[0])
- np_array = np.full((exp.n_ens, n_obs), np.nan)
- for i in range(exp.n_ens):
- np_array[i, :] = list_ensemble_truths[i]
- return np_array
- else:
- raise NotImplementedError()
-
-def obs_operator_nature(time):
- print('what are the true values in obs space of nature run')
- prepare_nature_dart(time)
- run_perfect_model_obs()
- true, _ = read_truth_obs_obsseq(cluster.dartrundir+'/obs_seq.out')
- return true
-
-
-def link_nature_to_dart_truth(time):
- # get wrfout_d01 from nature run
- shutil.copy(time.strftime(exp.nature_wrfout),
- cluster.dartrundir+'/wrfout_d01')
- # DART may need a wrfinput file as well, which serves as a template for dimension sizes
- symlink(cluster.dartrundir+'/wrfout_d01', cluster.dartrundir+'/wrfinput_d01')
-
-
-def prepare_nature_dart(time):
- link_nature_to_dart_truth(time)
- wrfout_add_geo.run(cluster.dartrundir+'/geo_em.d01.nc', cluster.dartrundir+'/wrfout_d01')
-
-
-def calc_obserr_WV73(Hx_nature, Hx_prior):
-
- n_obs = len(Hx_nature)
- OEs = np.ones(n_obs)
- for iobs in range(n_obs):
-
- bt_y = Hx_nature[iobs]
- bt_x_ens = Hx_prior[:, iobs]
- CIs = [cloudimpact_73(bt_x, bt_y) for bt_x in bt_x_ens]
- mean_CI = np.mean(CIs)
-
- oe_nature = oe_73(mean_CI)
- print('oe_nature:', oe_nature, ', bt_y:', bt_y, ', mean_CI:', mean_CI)
- OEs[iobs] = oe_nature
- return OEs
-
-def run_perfect_model_obs():
- os.chdir(cluster.dartrundir)
- try_remove(cluster.dartrundir+'/obs_seq.out')
- if not os.path.exists(cluster.dartrundir+'/obs_seq.in'):
- raise RuntimeError('obs_seq.in does not exist in '+cluster.dartrundir)
- os.system('mpirun -np 12 ./perfect_model_obs > log.perfect_model_obs')
- if not os.path.exists(cluster.dartrundir+'/obs_seq.out'):
- raise RuntimeError('obs_seq.out does not exist in '+cluster.dartrundir,
- '\n look for '+cluster.dartrundir+'log.perfect_model_obs')
-
-def assimilate(nproc=96):
- print('running filter')
- os.chdir(cluster.dartrundir)
- try_remove(cluster.dartrundir+'/obs_seq.final')
- os.system('mpirun -genv I_MPI_PIN_PROCESSOR_LIST=0-'+str(int(nproc)-1)+' -np '+str(int(nproc))+' ./filter > log.filter')
-
-def archive_diagnostics(archive_dir, time):
- print('archive obs space diagnostics')
- mkdir(archive_dir)
- fout = archive_dir+time.strftime('/%Y-%m-%d_%H:%M_obs_seq.final')
- 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')
- # except Exception as e:
- # warnings.warn(str(e))
-
-def recycle_output():
- 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):
- 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')
- mkdir(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)
- 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']:
- copy(cluster.dartrundir+'/'+f, archive_stage+'/'+f)
-
-
-if __name__ == "__main__":
-
- """Generate observations (obs_seq.out file)
- as defined in config/cfg.py
- for a certain timestamp (argument) of the nature run (defined in config/clusters.py)
-
- Workflow:
- for each assimilation stage (one obs_seq.in and e.g. one observation type):
- 1) prepare nature run for DART
- optional: 2) calculate obs-error from parametrization
- 3) create obs_seq.in with obs-errors from 2)
- 4) generate actual observations (obs_seq.out) with obs_seq.in from 3)
-
- - calculate obs-error from parametrization
- 1) create obs_seq.in with obs error=0
- 2) calculate y_nat = H(x_nature) and y_ens = H(x_ensemble)
- 3) calculate obs error as function of y_nat, y_ensmean
-
- Assumptions:
- - x_ensemble is already linked for DART to advance_temp<iens>/wrfout_d01
- """
-
- time = dt.datetime.strptime(sys.argv[1], '%Y-%m-%d_%H:%M')
- archive_time = cluster.archivedir+time.strftime('/%Y-%m-%d_%H:%M/')
-
- os.chdir(cluster.dartrundir)
- os.system('rm -f obs_seq.in obs_seq.out obs_seq.final') # remove any existing observation files
-
- 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)+'/'
- n_obs = obscfg['n_obs']
- n_obs_3d = n_obs * len(obscfg['heights'])
- sat_channel = obscfg.get('sat_channel', False)
- error_generate = obscfg['error_generate']
- error_assimilate = obscfg['error_assimilate']
-
- set_DART_nml(sat_channel=sat_channel,
- cov_loc_radius_km=obscfg['cov_loc_radius_km'],
- cov_loc_vert_km=obscfg.get('cov_loc_vert_km', False))
-
- # create obs template file, now with correct errors
- osq.create_obsseq_in(time, obscfg, obs_errors=error_generate,
- 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
-
- # debug option: overwrite time in prior files
- # for iens in range(1,41):
- # os.system('ncks -A -v Times '+cluster.dartrundir+'/wrfout_d01 '+cluster.dartrundir+'/advance_temp'+str(iens)+'/wrfout_d01')
-
- if error_assimilate == False:
- # use error parametrization for assimilation-obs.errors
-
- if sat_channel != 6:
- raise NotImplementedError('sat channel '+str(sat_channel))
-
- # depends on obs_seq.out produced before by run_perfect_model_obs()
- Hx_nat, _ = read_truth_obs_obsseq(cluster.dartrundir+'/obs_seq.out')
-
- Hx_prior = obs_operator_ensemble(istage) # files are already linked to DART directory
- error_assimilate = calc_obserr_WV73(Hx_nat, Hx_prior)
-
- else:
- # overwrite error values in obs_seq.out
- error_assimilate = np.zeros(n_obs_3d) + error_assimilate # ensure shape
-
- replace_errors_obsseqout(cluster.dartrundir+'/obs_seq.out', error_assimilate)
- assimilate()
- dir_obsseq = cluster.archivedir+'/obs_seq_final/assim_stage'+str(istage)
- archive_diagnostics(dir_obsseq, time)
-
- if istage < n_stages-1:
- # recirculation: filter output -> input
- archive_output(archive_stage)
- recycle_output()
-
- elif istage == n_stages-1:
- # last assimilation, continue integration now
- archive_output(archive_stage)
-
- else:
- RuntimeError('this should never occur?!')
diff --git a/scripts/prepare_nature.py b/scripts/prepare_nature.py
deleted file mode 100755
index b0ed8cc..0000000
--- a/scripts/prepare_nature.py
+++ /dev/null
@@ -1,16 +0,0 @@
-import os, sys, shutil
-import datetime as dt
-from config.cfg import exp, cluster
-from utils import symlink, copy
-
-time = dt.datetime.strptime(sys.argv[1], '%Y-%m-%d_%H:%M')
-
-# get wrfout_d01 from nature run
-shutil.copy(time.strftime(exp.nature_wrfout),
- cluster.dartrundir+'/wrfout_d01')
-
-import wrfout_add_geo
-wrfout_add_geo.run(cluster.dartrundir+'/geo_em.d01.nc', cluster.dartrundir+'/wrfout_d01')
-
-# DART may need a wrfinput file as well, which serves as a template for dimension sizes
-symlink(cluster.dartrundir+'/wrfout_d01', cluster.dartrundir+'/wrfinput_d01')
--
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