def make_namelist_and_inflate(datein, prevdate):
# Determine if we need to copy in the previous inflation
# values. If so, do it and unzip them. If not, just
# write the namelist.
# Use inflate_start to find the times we don't need
# Make a list of all assim times
#start = datetime.strptime(date_start,'%Y%m%d%H')
#assim_dt = timedelta(minutes=int(fct_len))
start = 0
assim_dt = int(cycle_len)
# Start on the first actual assimilation time
curdate = start + (assim_dt * (assim_start))
no_adaptive_inf_dates = []
step = 1
# WRF dart param tells us which assimilation step to start using inflation
while step < inflate_start:
no_adaptive_inf_dates.append(curdate)
curdate = curdate + assim_dt
step = step + 1
print(no_adaptive_inf_dates)
# Now check to see if we are in the list of no inflation dates
if datein not in no_adaptive_inf_dates:
print("Using adaptive inflation values from previous time")
nmld['filter_nml']['inf_initial_from_restart'] = [True, True]
nmld['filter_nml']['inf_sd_initial_from_restart'] = [True, True]
prior_inf_mean = os.path.join(dir_longsave, '{:06d}_inf_ic_mean.nc'.format(prevdate))
prior_inf_sd = os.path.join(dir_longsave, '{:06d}_inf_ic_sd.nc'.format(prevdate))
if os.path.exists(prior_inf_mean):
os.system('cp {:s} {:s}/prior_inf_ic_old_mean.nc'.format(prior_inf_mean, dir_assim))
os.system('cp {:s} {:s}/prior_inf_ic_old_sd.nc'.format(prior_inf_sd, dir_assim))
else:
error_handler('Could not find {:s}'.format(prior_inf_file),'submit_filter')
else:
nmld['filter_nml']['inf_initial_from_restart'] = [False, False]
nmld['filter_nml']['inf_sd_initial_from_restart'] = [False, False]
print("Using initial values for inflation mean and std")
# now figure out the "date" we are at based on the CM1 namelist
cm1date = cm1nmld['param11']
start_date = datetime(cm1date['year'], cm1date['month'], cm1date['day'], cm1date['hour'],\
cm1date['minute'], cm1date['second'])
# Make sure num members is right
nmld['filter_nml']['ens_size'] = Ne
# Check to see if we need to copy in the sampling error correction
if nmld['assim_tools_nml']['sampling_error_correction']:
os.system('cp -f {:s}/../../../system_simulation/final_full_precomputed_tables/final_full.{:d} {:s}/final_full.{:d}'.format(dir_src_dart, Ne, dir_assim, Ne))
# Write the namelist
write_dart_namelist(nmld, date=start_date + timedelta(seconds=datein))
os.system('cp input.nml {:s}/input.nml'.format(dir_assim))
def make_namelist_and_inflate(datein, prevdate):
# Determine if we need to copy in the previous inflation
# values. If so, do it and unzip them. If not, just
# write the namelist.
# Use inflate_start to find the times we don't need
# Make a list of all assim times
#start = datetime.strptime(date_start,'%Y%m%d%H')
#assim_dt = timedelta(minutes=int(fct_len))
start = 0
assim_dt = int(cycle_len)
# Start on the first actual assimilation time
curdate = start + (assim_dt * (assim_start))
no_adaptive_inf_dates = []
step = 1
# WRF dart param tells us which assimilation step to start using inflation
while step < inflate_start:
no_adaptive_inf_dates.append(curdate)
curdate = curdate + assim_dt
step = step + 1
print(no_adaptive_inf_dates)
# Now check to see if we are in the list of no inflation dates
if datein not in no_adaptive_inf_dates:
print("Using adaptive inflation values from previous time")
nmld['filter_nml']['inf_initial_from_restart'] = [True, True]
nmld['filter_nml']['inf_sd_initial_from_restart'] = [True, True]
prior_inf_mean = os.path.join(dir_longsave,
'{:06d}_inf_ic_mean.nc'.format(prevdate))
prior_inf_sd = os.path.join(dir_longsave,
'{:06d}_inf_ic_sd.nc'.format(prevdate))
if os.path.exists(prior_inf_mean):
os.system('cp {:s} {:s}/prior_inf_ic_old_mean.nc'.format(
prior_inf_mean, dir_assim))
os.system('cp {:s} {:s}/prior_inf_ic_old_sd.nc'.format(
prior_inf_sd, dir_assim))
else:
error_handler('Could not find {:s}'.format(prior_inf_file),
'submit_filter')
else:
nmld['filter_nml']['inf_initial_from_restart'] = [False, False]
nmld['filter_nml']['inf_sd_initial_from_restart'] = [False, False]
print("Using initial values for inflation mean and std")
# now figure out the "date" we are at based on the CM1 namelist
cm1date = cm1nmld['param11']
start_date = datetime(cm1date['year'], cm1date['month'], cm1date['day'], cm1date['hour'],\
cm1date['minute'], cm1date['second'])
# Make sure num members is write
nmld['filter_nml']['ens_size'] = Ne
write_dart_namelist(nmld, date=start_date + timedelta(seconds=datein))
os.system('cp input.nml {:s}/input.nml'.format(dir_assim))
def run_dart_to_cm1(mem, start):
""" If starting post-DART, run dart_to_wrf to populate the
wrfinput file. """
# Refresh with new WRF_dart_param variables
#from WRF_dart_param import *
print "Running dart_to_wrf"
# We know the member number, so mv the new dart state vector
# for that member number into the working directory
if os.path.exists('%s/wrfdart/filter_ic_new.%04d' % (dir_wrf_dom, mem)):
os.system('cp %s/wrfdart/filter_ic_new.%04d dart_wrf_vector' %
(dir_wrf_dom, mem))
else:
error_handler('Could not find update ic file wrfdart/filter_ic_new.%04d' % mem, \
'run_dart_to_wrf')
# Write a new dart namelist for this time
nml_good = write_dart_namelist(mem)
if not nml_good:
error_handler('Trouble writing input.nml for member %d' % mem,
'run_dart_to_wrf')
# Loop through each domain to be sure that wrfinput files are present
for dn in range(max_dom + 1)[1:]:
os.system('cp %s/archive_bdy/%s_wrfinput_d01 wrfinput_d01' %
(dir_wrf_dom, start.strftime('%Y%m%d%H')))
if not os.path.exists('wrfinput_d%02d' % dn):
error_handler('Could not find wrfinput_d%02d for mem %d' % (dn,mem), \
'run_dart_to_wrf')
# Link in the dart_to_wrf executable
os.system('ln -sf %s/dart_to_wrf .' % dir_src_dart)
# Run the executable for the current member
if os.path.exists('dtw.out'):
os.system('rm dtw.out')
os.system('./dart_to_wrf >> dtw.out')
# Check for errors in the dart_to_wrf_sequence
darterror = False
logfile = open('dtw.out', 'r')
for line in logfile:
if re.search('error', str(line)):
darterror = True
# Error out if errors found
if darterror:
error_handler('Error creating wrfinput files from filter_ic_new.%04d' % (mem), \
'run_dart_to_wrf')
else:
# If no errors, just clean up the directory
os.system('rm -f dart_wrf_vector')
os.system('rm -f dart_to_wrf')
os.system('rm input.nml')
def run_dart_to_cm1(mem,start):
""" If starting post-DART, run dart_to_wrf to populate the
wrfinput file. """
# Refresh with new WRF_dart_param variables
#from WRF_dart_param import *
print "Running dart_to_wrf"
# We know the member number, so mv the new dart state vector
# for that member number into the working directory
if os.path.exists('%s/wrfdart/filter_ic_new.%04d' % (dir_wrf_dom, mem)):
os.system('cp %s/wrfdart/filter_ic_new.%04d dart_wrf_vector' % (dir_wrf_dom, mem))
else:
error_handler('Could not find update ic file wrfdart/filter_ic_new.%04d' % mem, \
'run_dart_to_wrf')
# Write a new dart namelist for this time
nml_good = write_dart_namelist(mem)
if not nml_good:
error_handler('Trouble writing input.nml for member %d' % mem, 'run_dart_to_wrf')
# Loop through each domain to be sure that wrfinput files are present
for dn in range(max_dom+1)[1:]:
os.system('cp %s/archive_bdy/%s_wrfinput_d01 wrfinput_d01' % (dir_wrf_dom,start.strftime('%Y%m%d%H')))
if not os.path.exists('wrfinput_d%02d' % dn):
error_handler('Could not find wrfinput_d%02d for mem %d' % (dn,mem), \
'run_dart_to_wrf')
# Link in the dart_to_wrf executable
os.system('ln -sf %s/dart_to_wrf .' % dir_src_dart)
# Run the executable for the current member
if os.path.exists('dtw.out'):
os.system('rm dtw.out')
os.system('./dart_to_wrf >> dtw.out')
# Check for errors in the dart_to_wrf_sequence
darterror = False
logfile = open('dtw.out','r')
for line in logfile:
if re.search('error',str(line)):
darterror = True
# Error out if errors found
if darterror:
error_handler('Error creating wrfinput files from filter_ic_new.%04d' % (mem), \
'run_dart_to_wrf')
else:
# If no errors, just clean up the directory
os.system('rm -f dart_wrf_vector')
os.system('rm -f dart_to_wrf')
os.system('rm input.nml')
def run_cm1_to_dart(mem, end):
""" Run wrf_to_dart to prepare for assimilation"""
print "Beginning wrf_to_dart."
# Check to be sure that the date in wrfinput_d01 matches the end time
for dn in range(max_dom + 1)[1:]:
# Use ncdump to get the time from the wrfinput_d?? file
ncout = os.popen('ncdump -v Times wrfinput_d%02d' % dn)
timeline = ncout.readlines()[-2]
wrfin_timestring = re.search('"(\d{4}-\d{2}-\d{2}_\d{2}:\d{2}:\d{2})"',
timeline).groups()[0]
wrfin_time = datetime.strptime(wrfin_timestring, '%Y-%m-%d_%H:%M:%S')
# Make sure the wrfinput file is at the right time
if wrfin_time != end:
error_handler('wrfinput_d%02d time (%s) does not match assim time (%s) for mem %d' \
% (dn,wrfin_time.strftime('%Y%m%d%H'), end.strftime('%Y%m%d%H'), mem), \
'run_wrf_to_dart')
# Write a new dart namelist for this time
nml_good = write_dart_namelist(mem)
if not nml_good:
error_handler('Trouble writing input.nml for member %d' % mem,
'run_wrf_to_dart')
# Link in the dart_to_wrf executable
os.system('ln -sf %s/wrf_to_dart .' % dir_src_dart)
# Run the executable for the current member
if os.path.exists('wtd.out'):
os.system('rm wtd.out')
os.system('./wrf_to_dart >> wtd.out')
# Check for errors in the wrf_to_dart sequence
darterror = False
logfile = open('wtd.out', 'r')
for line in logfile:
if re.search('error', str(line)):
darterror = True
# Error out if errors found
if darterror or not os.path.exists('dart_wrf_vector'):
error_handler('Error creating dart_wrf_vector from wrfinput on mem %d' % (mem), \
'run_wrf_to_dart')
else:
# If no errors, just clean up the directory
os.system('mv -f dart_wrf_vector %s/wrfdart/filter_ic_old.%04d' %
(dir_wrf_dom, mem))
os.system('rm -f wrf_to_dart')
os.system('rm input.nml')
def run_cm1_to_dart(mem,end):
""" Run wrf_to_dart to prepare for assimilation"""
print "Beginning wrf_to_dart."
# Check to be sure that the date in wrfinput_d01 matches the end time
for dn in range(max_dom+1)[1:]:
# Use ncdump to get the time from the wrfinput_d?? file
ncout = os.popen('ncdump -v Times wrfinput_d%02d' % dn)
timeline = ncout.readlines()[-2]
wrfin_timestring = re.search('"(\d{4}-\d{2}-\d{2}_\d{2}:\d{2}:\d{2})"',timeline).groups()[0]
wrfin_time = datetime.strptime(wrfin_timestring,'%Y-%m-%d_%H:%M:%S')
# Make sure the wrfinput file is at the right time
if wrfin_time != end:
error_handler('wrfinput_d%02d time (%s) does not match assim time (%s) for mem %d' \
% (dn,wrfin_time.strftime('%Y%m%d%H'), end.strftime('%Y%m%d%H'), mem), \
'run_wrf_to_dart')
# Write a new dart namelist for this time
nml_good = write_dart_namelist(mem)
if not nml_good:
error_handler('Trouble writing input.nml for member %d' % mem, 'run_wrf_to_dart')
# Link in the dart_to_wrf executable
os.system('ln -sf %s/wrf_to_dart .' % dir_src_dart)
# Run the executable for the current member
if os.path.exists('wtd.out'):
os.system('rm wtd.out')
os.system('./wrf_to_dart >> wtd.out')
# Check for errors in the wrf_to_dart sequence
darterror = False
logfile = open('wtd.out','r')
for line in logfile:
if re.search('error',str(line)):
darterror = True
# Error out if errors found
if darterror or not os.path.exists('dart_wrf_vector'):
error_handler('Error creating dart_wrf_vector from wrfinput on mem %d' % (mem), \
'run_wrf_to_dart')
else:
# If no errors, just clean up the directory
os.system('mv -f dart_wrf_vector %s/wrfdart/filter_ic_old.%04d' % (dir_wrf_dom,mem))
os.system('rm -f wrf_to_dart')
os.system('rm input.nml')
def post_model_cleanup(mem,start,end,fcst_end):
""" Function to move output files to appropriate places, handle
calculating tendency if desired and process auxilliary outputs """
print "Beginning post-model cleanup"
# First, verify that CM1 finished correctly
if start != 0:
# Find the second restart name
rst_files = [f for f in os.listdir('.') if\
f.startswith('cm1out_rst') and f.endswith('.nc')]
rst_files.sort()
# It's the seocnd file
restart_name = rst_files[1]
if not os.path.exists(restart_name):
error_handler('Restart file {:s} not found for member {:d}'.format(restart_name, mem),'post_model_cleanup')
# Check to be sure this is at the right time
with Dataset(restart_name,'r') as rstfile:
rst_time = rstfile.variables['time'][0]
if rst_time != end:
error_handler('Restart file {:s} not at correct time {:d} min. for member {:d}'.format(restart_name, int(end), mem),'post_model_cleanup')
# Also check for out file
if not os.path.exists('cm1out.nc'):
error_handler('Output file cm1out.nc not found for member {:d}'.format(mem), 'post_model_cleanup')
print "CM1 restart file found. Success!"
# Check the rsl.error files to be doubly sure
# INSERT CODE HERE
# Now run through a litany of possible post-processing things to be done
# Check if we're computing tendency
if flag_compute_tendency:
print "Computing altimeter tendency"
if not os.path.exists('wrf_tendency'):
os.system('ln -sf %s/wrf_tendency .' % dir_utils)
# Write a new dart namelist for this time
nml_good = write_dart_namelist(mem)
if not nml_good:
error_handler('Trouble writing input.nml for member %d' % mem, 'post_model_cleanup')
for dn in range(int(max_dom)+1)[1:]:
# Don't overwrite the wrfinput_d01 file
if dn > 1:
os.system('cp wrfinput_d01 wrfinput_d01_orig')
os.system('rm wrfinput_d01')
os.system('ln -sf wrfinput_d%02d wrfinput_d01' % dn)
os.system('ln -sf wrfout_d%02d_%s wrfout_d01' % (dn, end.strftime('%Y-%m-%d_%H:%M:%S')))
os.system('./wrf_tendency')
os.system('rm wrfout_d01 wrf_tendency')
if dn > 1:
os.system('rm wrfinput_d01')
os.system('mv wrfinput_d01_orig wrfinput_d01')
# Actual file turnaround goes here
print "Copying over files for restart."
# Save the previous file in case something goes wrong
if start != 0:
os.system('mv cm1out_rst_000001.nc prev_cm1out_rst_000001.nc')
# THIS IS WHERE THE ACTUAL SWITCHOVER GOES
print("Copying over restart:", restart_name)
os.system('cp {:s} cm1out_rst_000001.nc'.format(restart_name))
# Now remove all other restart files
rst_file = [f for f in os.listdir('.') if 'cm1out_rst' in f and not f.endswith('000001.nc')]
for f in rst_file:
os.system('rm -f {:s}'.format(f))
# Check to see if we keep the regular out files
if not flag_keep_outs:
print "Removing old out files."
os.system('rm -f cm1out.nc')
# Archive the forecast if fcst_len != 0
if fcst_len:
os.system('mv cm1out.nc cm1out_m{:d}_{:06d}.nc'.format(mem,start))
def build_obs_structure(intime, rst_file, gridspace=16):
""" Function to specify what variables we want and how dense they should be """
#from make_namelist_dart import set_namelist_sectors, write_namelist
#from write_cm1_namelist import set_namelist_defaults
from namelist_utils import read_namelist, write_dart_namelist
# Generate the DART namelist structure so we
# can query (and modify) it
dartnml = read_namelist('input.nml')
cm1nml = read_namelist('namelist.input')
# Build the epoch from the cm1 namelist
param11 = cm1nml['param11']
startdate = datetime(param11['year'], param11['month'],\
param11['day'], param11['hour'],\
param11['minute'], param11['second'])
# Parse out the observations to assimilate
use_obs = dartnml['obs_kind_nml']['assimilate_these_obs_types']
# I'm just testing this for now
#use_obs = use_obs[0:2]
use_obs = ['LAND_SFC_PRESSURE']
print(use_obs)
# Put time as datetime
intime = startdate + timedelta(seconds=intime)
epoch = datetime(1601,1,1,0)
print("Indate:", intime)
# Figure out the grid structure
dx = cm1nml['param1']['dx']
dy = cm1nml['param1']['dy']
nx = cm1nml['param0']['nx']
ny = cm1nml['param0']['ny']
# Now figure out how many obs we'll need
gridspace *= 1000
obx = range(int(dx/2.),int(nx*dx),gridspace)
oby = range(int(dy/2.),int(ny*dx),gridspace)
#obx = [16000]
#oby = [16000]
total_obs = len(obx)*len(oby)*len(use_obs)
print("Total number of obs:", total_obs)
# Write a new dart namelist for the current time
delt = intime - epoch
#dartnml['perfect_model_obs_nml']['first_obs_days'] = str(delt.days)
#dartnml['perfect_model_obs_nml']['first_obs_seconds'] = str(delt.seconds)
#dartnml['perfect_model_obs_nml']['last_obs_days'] = str(delt.days)
#dartnml['perfect_model_obs_nml']['last_obs_seconds'] = str(delt.seconds)
#dartnml['perfect_model_obs_nml']['init_time_days'] = str(delt.days)
#dartnml['perfect_model_obs_nml']['init_time_seconds'] = str(delt.seconds)
dartnml['perfect_model_obs_nml']['obs_seq_in_file_name'] = 'obs_seq.in'
dartnml['perfect_model_obs_nml']['restart_in_file_name'] = rst_file
# Make sure we have the right io pattern
dartnml['io_filenames_nml']['restart_in_stub'] = 'notinuse'
dartnml['io_filenames_nml']['overwrite_input'] = False
dartnml['io_filenames_nml']['rpointer'] = True
dartnml['io_filenames_nml']['rpointer_file'] = 'input_filelist.txt'
# Write the pointer file
with open('input_filelist.txt', 'w') as pointerfile:
pointerfile.write(rst_file)
os.system('mv input_filelist.txt {:s}/'.format(dir_obs))
# Write the modified namelist
write_dart_namelist(dartnml)
# Set up the input file
with open('obs_seq_input.txt','w') as infile:
infile.write(str(total_obs)+'\n') # Total num obs
infile.write('0\n') # 0 copies
infile.write('0\n') # 0 QC values
for obtype in use_obs:
for x in obx:
for y in oby:
infile.write('0\n')
infile.write(obtype+'\n') # Identify ob type
infile.write('0\n') # Specify location
infile.write(str(x)+'\n') # X coordinate
infile.write(str(y)+'\n') # Y coordinate
infile.write('0\n') # Z coordinate
infile.write('{:d} {:d} {:d} {:d} {:d} {:d}\n'.format(\
intime.year, intime.month,\
intime.day, intime.hour,\
intime.minute, intime.second))
infile.write(str(error_var[obtype])+'\n') # Error variance
infile.write('obs_seq.in\n')
# Move these files to the obs dir
if os.path.exists(os.path.join(dir_obs, 'input.nml')):
os.system('rm -f {:s}'.format(os.path.join(dir_obs, 'input.nml')))
if os.path.exists(os.path.join(dir_obs, 'obs_seq_input.txt')):
os.system('rm -f {:s}'.format(os.path.join(dir_obs, 'obs_seq_input.txt')))
os.system('mv obs_seq_input.txt {:s}'.format(dir_obs))
os.system('cp input.nml {:s}'.format(dir_obs))
return None
def build_obs_structure(intime, rst_file, gridspace=4):
""" Function to specify what variables we want and how dense they should be """
#from make_namelist_dart import set_namelist_sectors, write_namelist
#from write_cm1_namelist import set_namelist_defaults
from namelist_utils import read_namelist, write_dart_namelist
# Generate the DART namelist structure so we
# can query (and modify) it
dartnml = read_namelist('input.nml')
cm1nml = read_namelist('namelist.input')
# Build the epoch from the cm1 namelist
param11 = cm1nml['param11']
startdate = datetime(param11['year'], param11['month'],\
param11['day'], param11['hour'],\
param11['minute'], param11['second'])
# Parse out the observations to assimilate
use_obs = dartnml['obs_kind_nml']['assimilate_these_obs_types']
# I'm just testing this for now
#use_obs = use_obs[0:2]
#use_obs = ['LAND_SFC_U_WIND_COMPONENT', 'LAND_SFC_V_WIND_COMPONENT', 'LAND_SFC_TEMPERATURE',
# 'LAND_SFC_SPECIFIC_HUMIDITY']
use_obs = [
'TEMPERATURE_2M', 'SURFACE_PRESSURE', 'SPECIFIC_HUMIDITY_2M',
'V_WIND_10M', 'U_WIND_10M'
]
print(use_obs)
# Put time as datetime
intime = startdate + timedelta(seconds=intime)
epoch = datetime(1601, 1, 1, 0)
print("Indate:", intime)
# Figure out the grid structure
dx = cm1nml['param1']['dx']
dy = cm1nml['param1']['dy']
nx = cm1nml['param0']['nx']
ny = cm1nml['param0']['ny']
# Now figure out how many obs we'll need
gridspace *= 1000
obx = range(int(dx / 2.), int(nx * dx), gridspace)
oby = range(int(dy / 2.), int(ny * dx), gridspace)
#obx = [16000]
#oby = [16000]
total_obs = len(obx) * len(oby) * len(use_obs)
print("Total number of obs:", total_obs)
# Write a new dart namelist for the current time
delt = intime - epoch
#dartnml['perfect_model_obs_nml']['first_obs_days'] = str(delt.days)
#dartnml['perfect_model_obs_nml']['first_obs_seconds'] = str(delt.seconds)
#dartnml['perfect_model_obs_nml']['last_obs_days'] = str(delt.days)
#dartnml['perfect_model_obs_nml']['last_obs_seconds'] = str(delt.seconds)
#dartnml['perfect_model_obs_nml']['init_time_days'] = str(delt.days)
#dartnml['perfect_model_obs_nml']['init_time_seconds'] = str(delt.seconds)
dartnml['perfect_model_obs_nml']['obs_seq_in_file_name'] = 'obs_seq.in'
dartnml['perfect_model_obs_nml']['restart_in_file_name'] = rst_file
# Make sure we have the right io pattern
dartnml['io_filenames_nml']['restart_in_stub'] = 'notinuse'
dartnml['io_filenames_nml']['overwrite_input'] = False
dartnml['io_filenames_nml']['rpointer'] = True
dartnml['io_filenames_nml']['rpointer_file'] = 'input_filelist.txt'
# Write the pointer file
with open('input_filelist.txt', 'w') as pointerfile:
pointerfile.write(rst_file)
os.system('mv input_filelist.txt {:s}/'.format(dir_obs))
# Write the modified namelist
write_dart_namelist(dartnml)
# Set up the input file
with open('obs_seq_input.txt', 'w') as infile:
infile.write(str(total_obs) + '\n') # Total num obs
infile.write('0\n') # 0 copies
infile.write('0\n') # 0 QC values
for obtype in use_obs:
for x in obx:
for y in oby:
infile.write('0\n')
infile.write(obtype + '\n') # Identify ob type
infile.write('0\n') # Specify location
infile.write(str(x) + '\n') # X coordinate
infile.write(str(y) + '\n') # Y coordinate
infile.write(str(heights[obtype]) + '\n') # Z coordinate
infile.write('{:d} {:d} {:d} {:d} {:d} {:d}\n'.format(\
intime.year, intime.month,\
intime.day, intime.hour,\
intime.minute, intime.second))
infile.write(str(error_var[obtype]) +
'\n') # Error variance
infile.write('obs_seq.in\n')
# Move these files to the obs dir
if os.path.exists(os.path.join(dir_obs, 'input.nml')):
os.system('rm -f {:s}'.format(os.path.join(dir_obs, 'input.nml')))
if os.path.exists(os.path.join(dir_obs, 'obs_seq_input.txt')):
os.system('rm -f {:s}'.format(
os.path.join(dir_obs, 'obs_seq_input.txt')))
os.system('mv obs_seq_input.txt {:s}'.format(dir_obs))
os.system('cp input.nml {:s}'.format(dir_obs))
return None
