sys.argv[9]), int(sys.argv[10])
MODEL_NAME = str(sys.argv[11])
ENS_NUM = int(sys.argv[12])
LEAD_FINAL = int(sys.argv[13])
MONTH_NAME_TEMPLATE = '{}01'
MONTH_NAME = MONTH_NAME_TEMPLATE.format(calendar.month_abbr[INIT_FCST_MON])
print(f"*** LEAD FINAL: {LEAD_FINAL}")
BC_FCST_SYR, BC_FCST_EYR = int(sys.argv[14]), int(sys.argv[15])
if FCST_VAR == 'PRECTOT':
MASK_FILE = str(sys.argv[16])
else:
MASK_FILE = str(sys.argv[17])
MASK = read_nc_files(MASK_FILE, 'mask')
print(f"MASK: {MASK.shape}")
MONTHLY_BC_FCST_DIR = str(sys.argv[18])
MONTHLY_RAW_FCST_DIR = str(sys.argv[19])
SUBDAILY_RAW_FCST_DIR = str(sys.argv[20])
BASE_OUTDIR = str(sys.argv[21])
OUTDIR_TEMPLATE = '{}/{:04d}/ens{:01d}'
# All file formats
MONTHLY_BC_INFILE_TEMPLATE = '{}/{}.{}.{}_{:04d}_{:04d}.nc'
MONTHLY_RAW_INFILE_TEMPLATE = '{}/{:04d}/ens{:01d}/{}.cfsv2.{:04d}{:02d}.nc'
SUBDAILY_INFILE_TEMPLATE = '{}/{:04d}/ens{:01d}/{}.cfsv2.{:04d}{:02d}.nc'
SUBDAILY_OUTFILE_TEMPLATE = '{}/{}.{:04d}{:02d}.nc4'
MONTHLY_NMME_INFILE_TEMPLATE = '{}/{:04d}/ens{:01d}/{}.nmme.monthly.{:04d}{:02d}.nc'
MONTH_NAME, ens+1)
if op.isdir(OUTDIR):
pass
else:
MAKEDIR(OUTDIR)
print(f"OUTDIR is {OUTDIR}")
for LEAD_NUM in range(0, LEAD_FINAL):
## Loop from lead =0 to Final Lead
FCST_DATE = datetime(INIT_FCST_YEAR, INIT_FCST_MON, 1) + \
relativedelta(months=LEAD_NUM)
FCST_YEAR, FCST_MONTH = FCST_DATE.year, FCST_DATE.month
for VAR_NUM, VAR_VALUE in enumerate(VAR_NAME_LIST):
VAR = VAR_NAME_LIST[VAR_NUM]
INFILE = INFILE_TEMPLATE.format(INDIR, VAR, FCST_YEAR, \
FCST_MONTH)
TEMP = read_nc_files(INFILE, VAR)
if VAR == VAR_NAME_LIST[0]:
LATS, LONS = read_nc_files(INFILE, 'lat'), \
read_nc_files(INFILE, 'lon')
IN_DATA = np.empty((len(VAR_NAME_LIST), TEMP.shape[0], \
len(LATS), len(LONS)))
IN_DATA[VAR_NUM, ] = TEMP
### Finished reading all files now writing combined output
OUTFILE = OUTFILE_TEMPLATE.format(OUTDIR, FCST_YEAR, FCST_MONTH)
print(f"Now writing {OUTFILE}")
SDATE = datetime(FCST_YEAR, FCST_MONTH, 1, 6)
NUM_DAYS = TEMP.shape[0]
DATES = [
SDATE + relativedelta(hours=n * 6) for n in range(NUM_DAYS)
]
DIR = DIRA + DIRB
INFILE_TEMP = '{}/{}/{}/ens{}/{}.cfsv2.{:04d}{:02d}.nc'
DIRA1 = '/discover/nobackup/projects/fame/FORECASTS/GEOS5/BCSD_Test/'
DIRB1 = 'EXPERIMENTS/NMME/data/AF/PRECTOT_Monthly/'
DIR1 = DIRA1 + DIRB1
OUTFILE_TEMPLATE = '{}/{:04d}/{}/ens{}/nmme/{}.nmme.monthly.{:04d}{:02d}.nc'
OUTDIR_TEMPLATE = '{}/{:04d}/{}/ens{}/nmme/'
if not os.path.exists(DIR1):
os.makedirs(DIR1)
#reads sample file for lat and lon values
GEA1 = '/discover/nobackup/projects/usaf_lis/razamora/GHI_S2S/AFRICOM/'
GEB1 = 'data/CFSv2/RAW_CFSv2/Monthly/jan01/2008/ens10/jan01.cfsv2.200801.nc'
GE1 = GEA1 + GEB1
LONS = read_nc_files(GE1, 'lon')
LATS = read_nc_files(GE1, 'lat')
print("Read coarse res lat lon")
for mm in range(2, len(MONTH)):
YR1 = 2007
for YR in range(0, 13):
YR1 = YR1+1
for ens in range(1, 13):
for ld in range(0, 9):
mm1 = mm+1+ld
xpreci = np.empty([1, 720, 1440])
print("Processing: Year=", YR1)
print("MONTH=", MONTH[mm])
print("ens=", ens)
cmdargs = str(sys.argv)
VAR_NAME = str(
sys.argv[1]
) ## this is the name of the variable to create the observational climatology for (precip or tmp)
lat1, lat2, lon1, lon2 = int(sys.argv[2]), int(sys.argv[3]), int(
sys.argv[4]), int(sys.argv[5])
#lat1, lat2, lon1, lon2 = 5, 19, 30, 41
INDIR = str(
sys.argv[6]
) ## This is the location of observed data, that is on the same grid as the NMME data
INFILE_template = '{}/all_forc_var_{:04d}{:02d}.nc4'
CLIM_SYR, CLIM_EYR = int(sys.argv[7]), int(sys.argv[8])
MASK_FILE = str(sys.argv[9])
LATS = read_nc_files(MASK_FILE, 'lat')
LONS = read_nc_files(MASK_FILE, 'lon')
OUTDIR = str(sys.argv[10])
if not os.path.exists(OUTDIR):
os.makedirs(OUTDIR)
#MAKEDIR(OUTDIR)
OUTFILE_template = '{}/{}_obs_clim.nc'
#print(VAR_NAME)
#print(lat1)
#print(lat2)
#print(lon1)
#print(lon2)
#print(INDIR)
#print(MASK_FILE)
#print(OUTDIR)
# Directory and file addresses
FCST_CLIM_INDIR = str(sys.argv[18])
OBS_CLIM_INDIR = str(sys.argv[19])
FCST_INDIR = str(sys.argv[20])
# Observation climatology filename templates:
OBS_CLIM_FILE_TEMPLATE = '{}/{}_obs_clim.nc'
FCST_CLIM_FILE_TEMPLATE = '{}/{}/{}_fcst_clim.nc'
MONTH_NAME_TEMPLATE = '{}01'
# GEOS5 filename TEMPLATE:
FCST_INFILE_TEMPLATE = '{}/{:04d}/ens{:01d}/{}.nmme.monthly.{:04d}{:02d}.nc'
# Input mask
MASK_FILE = str(sys.argv[21])
MASK = read_nc_files(MASK_FILE, 'mask')[0, ]
LATS = read_nc_files(MASK_FILE, 'lat')
LONS = read_nc_files(MASK_FILE, 'lon')
### Output directory
OUTFILE_TEMPLATE = '{}/{}.{}.{}_{:04d}_{:04d}.nc'
OUTDIR = str(sys.argv[22])
if not os.path.exists(OUTDIR):
os.makedirs(OUTDIR)
ENSS = int(sys.argv[23])
ENSF = int(sys.argv[24])
print(f"Ensemble number is {ENS_NUMF}")
NUM_YRS = (CLIM_EYR - CLIM_SYR) + 1
TINY = ((1 / (NUM_YRS)) / ENS_NUMF) / 2
MODEL_NAME = str(sys.argv[11])
ENS_NUM = int(sys.argv[12])
LEAD_FINAL = int(sys.argv[13])
MONTH_NAME_template = '{}01'
MONTH_NAME = MONTH_NAME_template.format(calendar.month_abbr[INIT_FCST_MON])
BC_FCST_SYR, BC_FCST_EYR = int(sys.argv[14]), int(sys.argv[15])
# NEED TO MODIFY THE BELOW PATHS ...
if (FCST_VAR == 'PRECTOT'):
# MASK_FILE='/discover/nobackup/sshukla2/scripts/BCSD/CHIRPS_0.25_MASK.nc'
MASK_FILE = str(sys.argv[16])
else:
# MASK_FILE = '/discover/nobackup/sshukla2/scripts/BCSD/CHIRPS_MASK.nc'
MASK_FILE = str(sys.argv[17])
MASK = read_nc_files(MASK_FILE, 'mask')[0, ]
#Directory and file addresses
# In[14]:
# NEED TO MODIFY THE BELOW PATHS ...
##BASEDIR='/discover/nobackup/sshukla2/Misc'
##DAILY_RAW_FCST_DIR='/discover/nobackup/projects/fame/FORECASTS/GEOS5/Shrad_BCSD'
# FORCEDIR='/discover/nobackup/projects/fame/FORECASTS/GEOS5/BCSD_Test/FAME_May_data'
# INDIR2=${FORCEDIR}'/'
# DAILY_RAW_FCST_DIR=${FORCEDIR}'/RAW_'${fcstdatatype}
# OUTDIR2=${FORCEDIR}'/'${fcstdatatype}'/BCSD_DATA'
BASEDIR = str(sys.argv[18]) #$INDIR2
DAILY_RAW_FCST_DIR = str(sys.argv[19]) #$DAILY_RAW_FCST_DIR
BASEDIR1 = str(sys.argv[20]) #$OUTDIR2
OUTDIR_template = '{}/Daily/{:04d}/ens{:01d}'
if k >= 13:
k = k - 12
KY = 1
LEADS1[i, j] = k
LDYR[i, j] = KY
INFILE_TEMP = '{}/{}/prec.{}.mon_{}.{:04d}.nc'
OUTDIR_TEMPLATE = '{}/{}/{:04d}/ens{}/'
OUTFILE_TEMPLATE = '{}/{}.nmme.monthly.{:04d}{:02d}.nc'
if not os.path.exists(NMME_OUTPUT_DIR):
os.makedirs(NMME_OUTPUT_DIR)
## Read in example fine spatial resolution file for lat and lon over AFRICOM
EX_FCST_FILENAME = '/ex_raw_fcst_download.nc'
GE = SUPPLEMENTARY_DIR + EX_FCST_FILENAME
LONS = read_nc_files(GE, 'lon')
LATS = read_nc_files(GE, 'lat')
## Read in example coarse spatial resolution file for lat and lon over Globe
EX_NMME_FILENAME = '/ex_raw_nmme_download.nc'
GE1 = SUPPLEMENTARY_DIR + EX_NMME_FILENAME
LONI = read_nc_files(GE1, 'X')
LATI = read_nc_files(GE1, 'Y')
LON1 = LONI.copy()
for n, l in enumerate(LON1):
if l >= 180:
LON1[n] = LON1[n] - 360.
LONI = LON1
LON1 = LONI[0:180]
LON2 = LONI[180:]
LONI = np.hstack((LON2, LON1))
FCST_SYR, FCST_EYR = int(sys.argv[7]), int(sys.argv[8])
LEAD_FINAL = int(sys.argv[9])
ENS_NUM = int(sys.argv[10])
MONTH_NAME = calendar.month_abbr[INIT_FCST_MON].lower() + "01"
print("month name is:", MONTH_NAME)
CLIM_SYR, CLIM_EYR = int(sys.argv[11]), int(sys.argv[12])
## Both FCST_SYR and CLIM_SYR, and FCST_EYR and CLIM_EYR
## will be the same since we are using the entire hindcast for
# Directory and file addresses
INDIR = str(sys.argv[13])
INFILE_TEMPLATE = '{}/{}/{:04d}/ens{:01d}/{}.cfsv2.{:04d}{:02d}.nc'
#
OUTFILE_TEMPLATE = '{}/{}_fcst_clim.nc'
#
MASK_FILE = str(sys.argv[14])
LATS = read_nc_files(MASK_FILE, 'lat')
LONS = read_nc_files(MASK_FILE, 'lon')
OUTDIR = str(sys.argv[15])
if not os.path.exists(OUTDIR):
os.makedirs(OUTDIR)
print("Ready to create climatology for Variable {}".format(VAR))
print("Forecast Initialization month is {}".format(MONTH_NAME))
### First read all forecast data
FCST_TS = np.empty(
(LEAD_FINAL, ((CLIM_EYR - CLIM_SYR) + 1) * ENS_NUM, len(LATS), len(LONS)))
## Storing climatology of forecast for all years and ensemble members
for LEAD_NUM in range(0, LEAD_FINAL): ## Loop from lead =0 to Final Lead
SYR1 = 1982
SYR2 = 1991
SYR3 = 2019
SYR4 = 2011
SYR5 = 2017
SYR6 = 2018
EYR1 = 2020
EYR2 = 2010
EYR3 = 2018
EYR4 = 2017
EYR5 = 2016
GEA = '/discover/nobackup/projects/nca/razamora/GHI_S2S/AFRICOM/data/CFSv2/'
GEB = 'RAW_CFSv2/Monthly/jan01/2008/ens10/jan01.cfsv2.200801.nc'
GE = GEA + GEB
LONS = read_nc_files(GE, 'lon')
LATS = read_nc_files(GE, 'lat')
print("Read fine res lat lon")
GEA1 = '/discover/nobackup/projects/fame/FORECASTS/GEOS5/BCSD_Test/EXPERIMENTS/'
GEB1 = 'NMME/data/GEM-NEMO/prec.GEM-NEMO.mon_Dec_2019_2020.nc'
GE1 = GEA1 + GEB1
LONI = read_nc_files(GE1, 'X')
LATI = read_nc_files(GE1, 'Y')
LON1 = LONI.copy()
for n, l in enumerate(LON1):
if l >= 180:
LON1[n] = LON1[n] - 360.
LONI = LON1
LON1 = LONI[0:180]
LON2 = LONI[180:]