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ens_dart_param.py
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ens_dart_param.py
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#! /usr/bin/python
import os
#*******************************************************************************
#
# Use this file to modify all the parameters needed to run an experiment.
# Each experiment should have one of these files
#
#*******************************************************************************
exp_name='kdnr_ensemble' # Name of the experiment
#**************************************************************
#
# This set of flags controls some of the basic execution of
# the script for running a case study
#
#**************************************************************
flag_compress_diag = False # True to gzip the diag files in longsave
flag_keep_outs = True # True to preserve output files in each member's directory
flag_keep_diags = False # True to keep the Prior and Posterior Diag files
flag_obs_diag = False # perform observation diagnostics
flag_direct_netcdf_io = True # Use experimental DART IO to read/write
# directly from/to restart netcdf files
# THIS MUST BE TRUE FOR CM1_DART!
#**************************************************************
#
# This section sets the location of where files are to be
# created and where necessary files can be found
#
# If basic directory structure is followed, the only two things
# that need to be changed for all of these to work are the
# exp_name parameter at the very top of this file and the
# dir parameter below.
#**************************************************************
dir = '/home/disk/pvort/nobackup/lmadaus/cm1' # MAIN DIRECTORY
dir_dom = dir + '/DOMAINS/' + exp_name # Directory where main experiment is run
dir_longsave = dir_dom + '/longsave' # storage directory
dir_obs = dir_dom + '/obs' # repository of obs.
dir_utils = dir + '/UTILS/bin' # location of utility codes
dir_members = dir_dom + '/mems' # members directory
dir_assim = dir_dom + '/assimilation' # Directory where DART will be run
# Directories where CM1 and DART are found
dir_src_model = dir + '/r18/lab_cm1r18/run' # Where the model executable is located
dir_src_dart = dir + '/LAB_DART_CM1/models/cm1/work' # Where DART executables are located
#**************************************************************
#
# The following set of parameters change depending on the
# cluster that the experiment is being performed on.
#
# Currently, the scripts will automatically determine the
# But features like the queue name, the mpi_run_command, and the
# number of processors come from here
#**************************************************************
cluster_name = 'enkf' # name of cluster nodes
mpi_run_command = 'mpirun' # Command to run MPI
queue_members = 'MPI' # Queue to run members in
queue_filter = 'MPI' # Queue to run filter in
mpi_numprocs_member = 16 # Number of processors for member
mpi_numprocs_filter = 64 # Number of processors for filter
#mpi_numprocs_flag = ''
mpi_numprocs_flag = '-np %d' % mpi_numprocs_member # Flag for numprocs in code
# for member. Bluefire does
# blank for bluefire
queue_sub_governor = 5 # Maximum number of jobs to
# have submitted to the queue at
# one time. If none, will submit
# all members at once, otherwise
# will wait on submission until
# previous members finish
# Extra parameters for running on Bluefire
NCAR_GAU_ACCOUNT = 'XXXXXX' # Account to charge to at NCAR
ADVANCE_TIME_FILTER = '0:45' # Estimate of time for filter to run
ADVANCE_TIME_MEMBER = '0:20' # Estimate of time for a single member to run
ADVANCE_QUEUE_FILTER = queue_filter # Name of NCAR queue to use for filter
ADVANCE_QUEUE_MEMBER = queue_members # Name of NCAR queue to use for members
ADVANCE_CORES_FILTER = mpi_numprocs_filter # Number of cores to use (multiples of 32)
ADVANCE_CORES_MEMBER = mpi_numprocs_member # Number of cores to use (multiples of 32)
NCAR_ADVANCE_PTILE_FILTER = '16' # How many processes per core on Bluefire
NCAR_ADVANCE_PTILE_MEMBER = '16' # How many processes per core on Bluefire
#**************************************************************
#
# This set of parameters deals with parameters related to the
# ensemble itself
#
dt = 5. # model time step (in sec)
grid_resolutions = 1000.
out_int = 10*60 # Interval to write out files (in seconds)
cycle_len = 60*60 # Interval to write restart files (in seconds)
# This is also the cycling frequency
fcst_len = 300*60 # If 0 --> no forecasts will be produced beyone the cycling interval
# If <0 --> At each cycle, after dropping a restart file at cycle_len
# minutes, the forecast will continue until reaching the
# equivalent of exp_len minutes
# Else --> As above, but each forecast will be for an additional
# fcst_len minutes beyond cycle_len
exp_length = 10*3600 # TOTAL length of simulation (in seconds))
Ne = 50 # Number of ensemble members
assim_start = 1 # Cycle to start assimilation
assim_interval = 1 # how often to assimilate obs (1=every cycle)
inflate_start = 2 # Which assimlation step to start inflation
#**************************************************************
#
# Additional EnKF namelist parameters
# -- These will (in the future) control which variables are a
# part of the DART state vector
#
#**************************************************************
# assim_tools_nml section
# Horizontal localization and assimilation methods are here
assim_infl_meth = 1 # inflation method (see README file for options)
assim_meth = 1 # Type of filter to run
# (1=EAKF, 2=ENKF, 3=Kernel filter,
# 4=particle filter. 7=Boxcar kernel filter)
assim_loc_meth = 1 # select localization method (1=Gaspari-Cohn, 2=boxcar,
# 3=ramped boxcar)
adaptive_loc_threshold = 1600 # Used to dynamically shrink localization in areas of
# dense observations. If the number of observations within
# 2* the localization radius is greater than this value, it
# shrinks the localization radius until there are only
# this many observations within that radius.
assim_locrad = 15. # localization radius (km)
# cov_cutoff is the actual value put in as the localization radius. DART
# needs the radius specified in global radians. Do not edit this
# calculation here -- edit the assim_locrad above
#cov_cutoff = str(float(assim_locrad) / 2.0 / 6370.0)[0:5]
cov_cutoff = str(assim_locrad * 1000.)
# A few additional calcualtions
# Calculate the number of integration time steps
time_step=str((float(cycle_len)*60)/float(dt))
cycle_len_hrs=str(float(cycle_len)/60)