def writeRec9():
PRES = 1013.0 # Sea level presure (replicate Sara's file)
# total accumulated rainfall from past hour (replicate Sara's file)
RAIN = 0.0
SC = 0 # snow cover
RADSW = 0.0 # SW radiation at surface (replicate Sara's file)
RADLW = 0.0 # LW radiation at top (replicate Sara's file)
VAPMR = 0.0 # Vagour mixing ratio (replicate Sara's file)
for t in range(nfiles):
print("Processing file " + filenames[t])
dateTime = parse(date) + dt.timedelta(hours=t * 6)
MYR = dateTime.year # Year of data block
MMO = dateTime.month # Month of data block
MDAY = dateTime.day # Day of data block
MHR = dateTime.hour # Hour of data block
# GRIB file processing:
f = open(filePaths[t], 'r') # Open GRIB file
gribapi.grib_multi_support_on() # Turn on multi-message support
mcount = gribapi.grib_count_in_file(f) # number of messages in file
[gribapi.grib_new_from_file(f)
for i in range(mcount)] # Get handles for all messages
f.close() # Close GRIB file
# Initialse 3D arrays for holding required fields:
HGTgrd = np.zeros(shape=(Nj, Ni, NZ))
TMPgrd = np.zeros(shape=(Nj, Ni, NZ))
Ugrd = np.zeros(shape=(Nj, Ni, NZ))
Vgrd = np.zeros(shape=(Nj, Ni, NZ))
Wgrd = np.zeros(shape=(Nj, Ni, NZ))
RHgrd = np.zeros(shape=(Nj, Ni, NZ))
# Loop through included levels and store the values in the appropriate k index of the 3D arrays
for k in range(NZ):
HGTvals = gribapi.grib_get_values(int(gidHGT[k]))
HGTgrd[:, :, k] = np.reshape(HGTvals, (Nj, Ni), 'C')
TMPvals = gribapi.grib_get_values(int(gidTMP[k]))
TMPgrd[:, :, k] = np.reshape(TMPvals, (Nj, Ni), 'C')
Uvals = gribapi.grib_get_values(int(gidU[k]))
Ugrd[:, :, k] = np.reshape(Uvals, (Nj, Ni), 'C')
Vvals = gribapi.grib_get_values(int(gidV[k]))
Vgrd[:, :, k] = np.reshape(Vvals, (Nj, Ni), 'C')
Wvals = gribapi.grib_get_values(int(gidW[k]))
Wgrd[:, :, k] = np.reshape(Wvals, (Nj, Ni), 'C')
RHvals = gribapi.grib_get_values(int(gidRH[k]))
RHgrd[:, :, k] = np.reshape(RHvals, (Nj, Ni), 'C')
WSgrd = np.sqrt(Ugrd**2 + Vgrd**2) # Calculate wins speed (pythagoras)
# Calculate wind direction:
# radians, between [-pi,pi], positive anticlockwise from positive x-axis
WDgrd = np.arctan2(Vgrd, Ugrd)
# degrees, between [-180,180], positive anticlockwise from positive x-axis
WDgrd *= 180 / np.pi
# degrees, between [0,360], positive anticlockwise from negative x-axis (Since we specify the direction the wind is blowing FROM, not TO)
WDgrd += 180
# degrees, between [-360,0], positive clockwise from negative x-axis (Since wind direction is positive clockwise)
WDgrd = -WDgrd
# degrees, between [-270,90], positive clockwise from positive y-axis (Since wind direction is from North)
WDgrd += 90
# degrees, between [0,360], positive clockwise from positive y-axis (DONE!)
WDgrd = np.mod(WDgrd, 360)
if t > 0:
dateTime = parse(date) + dt.timedelta(hours=(t * 6) - 3)
print('interpolating')
print(dateTime)
MYR = dateTime.year # Year of data block
MMO = dateTime.month # Month of data block
MDAY = dateTime.day # Day of data block
MHR = dateTime.hour # Hour of data block
HGTgrd = np.mean(np.array([HGTgrd + HGTgrd_ini]), axis=0)
TMPgrd = np.mean(np.array([TMPgrd + TMPgrd_ini]), axis=0)
Wgrd = np.mean(np.array([Wgrd + Wgrd_ini]), axis=0)
RHgrd = np.mean(np.array([RHgrd + RHgrd_ini]), axis=0)
WDgrd = np.mean(np.array([WDgrd + WDgrd_ini]), axis=0)
WSgrd = np.mean(np.array([WSgrd + WSgrd_ini]), axis=0)
inds = HGTgrd.argsort(axis=2)
HGTgrd = take_along_axis(HGTgrd, inds, axis=2)
TMPgrd = take_along_axis(TMPgrd, inds, axis=2)
Wgrd = take_along_axis(Wgrd, inds, axis=2)
RHgrd = take_along_axis(RHgrd, inds, axis=2)
WSgrd = take_along_axis(WSgrd, inds, axis=2)
WDgrd = take_along_axis(WDgrd, inds, axis=2)
# Loop over grid cells:
for j in range(NY):
JX = j + 1 # J-index of grid cell
for i in range(NX):
IX = i + 1 # i-index of grid cell
fout.write(
('{:4d}' + '{:02d}' * 3 + '{:3d}' * 2 +
'{:7.1f}{:5.2f}{:2d}' + '{:8.1f}' * 2 + '\n').format(
MYR, MMO, MDAY, MHR, IX, JX, PRES, RAIN, SC,
RADSW, RADLW))
for k in range(NZ):
PRES2 = levsIncl[k] # Pressure (mb)
# Elevation (m above sea level)
Z = int(HGTgrd[iLatMinGRIB + j, iLonMinGRIB + i, k])
# Temperature (Kelvin)
TEMPK = TMPgrd[iLatMinGRIB + j, iLonMinGRIB + i, k]
# Wind direction (degrees)
WD = int(WDgrd[iLatMinGRIB + j, iLonMinGRIB + i, k])
# Wind speed (m/s)
WS = WSgrd[iLatMinGRIB + j, iLonMinGRIB + i, k]
# Vertical velocity (m/s)
W = Wgrd[iLatMinGRIB + j, iLonMinGRIB + i, k]
# Relative humidity (%)
RH = int(RHgrd[iLatMinGRIB + j, iLonMinGRIB + i, k])
fout.write((
'{:4d}{:6d}{:6.1f}{:4d}{:5.1f}{:6.2f}{:3d}{:5.2f}\n'
).format(PRES2, Z, TEMPK, WD, WS, W, RH, VAPMR))
# Release all messages:
for i in range(mcount):
gribapi.grib_release(i + 1)
# GRIB file processing:
dateTime = parse(date) + dt.timedelta(hours=t * 6)
print('processing')
print(dateTime)
MYR = dateTime.year # Year of data block
MMO = dateTime.month # Month of data block
MDAY = dateTime.day # Day of data block
MHR = dateTime.hour # Hour of data block
f = open(filePaths[t], 'r') # Open GRIB file
gribapi.grib_multi_support_on() # Turn on multi-message support
mcount = gribapi.grib_count_in_file(f) # number of messages in file
[gribapi.grib_new_from_file(f)
for i in range(mcount)] # Get handles for all messages
f.close() # Close GRIB file
# Initialse 3D arrays for holding required fields:
HGTgrd = np.zeros(shape=(Nj, Ni, NZ))
TMPgrd = np.zeros(shape=(Nj, Ni, NZ))
Ugrd = np.zeros(shape=(Nj, Ni, NZ))
Vgrd = np.zeros(shape=(Nj, Ni, NZ))
Wgrd = np.zeros(shape=(Nj, Ni, NZ))
RHgrd = np.zeros(shape=(Nj, Ni, NZ))
# Loop through included levels and store the values in the appropriate k index of the 3D arrays
for k in range(NZ):
HGTvals = gribapi.grib_get_values(int(gidHGT[k]))
HGTgrd[:, :, k] = np.reshape(HGTvals, (Nj, Ni), 'C')
TMPvals = gribapi.grib_get_values(int(gidTMP[k]))
TMPgrd[:, :, k] = np.reshape(TMPvals, (Nj, Ni), 'C')
Uvals = gribapi.grib_get_values(int(gidU[k]))
Ugrd[:, :, k] = np.reshape(Uvals, (Nj, Ni), 'C')
Vvals = gribapi.grib_get_values(int(gidV[k]))
Vgrd[:, :, k] = np.reshape(Vvals, (Nj, Ni), 'C')
Wvals = gribapi.grib_get_values(int(gidW[k]))
Wgrd[:, :, k] = np.reshape(Wvals, (Nj, Ni), 'C')
RHvals = gribapi.grib_get_values(int(gidRH[k]))
RHgrd[:, :, k] = np.reshape(RHvals, (Nj, Ni), 'C')
HGTgrd_ini = HGTgrd
TMPgrd_ini = TMPgrd
Wgrd_ini = Wgrd
RHgrd_ini = RHgrd
WSgrd = np.sqrt(Ugrd**2 + Vgrd**2) # Calculate wins speed (pythagoras)
# Calculate wind direction:
# radians, between [-pi,pi], positive anticlockwise from positive x-axis
WDgrd = np.arctan2(Vgrd, Ugrd)
# degrees, between [-180,180], positive anticlockwise from positive x-axis
WDgrd *= 180 / np.pi
# degrees, between [0,360], positive anticlockwise from negative x-axis (Since we specify the direction the wind is blowing FROM, not TO)
WDgrd += 180
# degrees, between [-360,0], positive clockwise from negative x-axis (Since wind direction is positive clockwise)
WDgrd = -WDgrd
# degrees, between [-270,90], positive clockwise from positive y-axis (Since wind direction is from North)
WDgrd += 90
# degrees, between [0,360], positive clockwise from positive y-axis (DONE!)
WDgrd = np.mod(WDgrd, 360)
WDgrd_ini = WDgrd
WSgrd_ini = WSgrd
inds = HGTgrd.argsort(axis=2)
HGTgrd = take_along_axis(HGTgrd, inds, axis=2)
TMPgrd = take_along_axis(TMPgrd, inds, axis=2)
Wgrd = take_along_axis(Wgrd, inds, axis=2)
RHgrd = take_along_axis(RHgrd, inds, axis=2)
WSgrd = take_along_axis(WSgrd, inds, axis=2)
WDgrd = take_along_axis(WDgrd, inds, axis=2)
# Loop over grid cells:
for j in range(NY):
JX = j + 1 # J-index of grid cell
for i in range(NX):
IX = i + 1 # i-index of grid cell
fout.write(
('{:4d}' + '{:02d}' * 3 + '{:3d}' * 2 +
'{:7.1f}{:5.2f}{:2d}' + '{:8.1f}' * 2 + '\n').format(
MYR, MMO, MDAY, MHR, IX, JX, PRES, RAIN, SC, RADSW,
RADLW))
for k in range(NZ):
PRES2 = levsIncl[k] # Pressure (mb)
# Elevation (m above sea level)
Z = int(HGTgrd[iLatMinGRIB + j, iLonMinGRIB + i, k])
# Temperature (Kelvin)
TEMPK = TMPgrd[iLatMinGRIB + j, iLonMinGRIB + i, k]
# Wind direction (degrees)
WD = int(WDgrd[iLatMinGRIB + j, iLonMinGRIB + i, k])
# Wind speed (m/s)
WS = WSgrd[iLatMinGRIB + j, iLonMinGRIB + i, k]
# Vertical velocity (m/s)
W = Wgrd[iLatMinGRIB + j, iLonMinGRIB + i, k]
# Relative humidity (%)
RH = int(RHgrd[iLatMinGRIB + j, iLonMinGRIB + i, k])
fout.write(
('{:4d}{:6d}{:6.1f}{:4d}{:5.1f}{:6.2f}{:3d}{:5.2f}\n'
).format(PRES2, Z, TEMPK, WD, WS, W, RH, VAPMR))
# Release all messages:
for i in range(mcount):
gribapi.grib_release(i + 1)
def __len__(self):
"""Return total messages in GRIB file."""
return gribapi.grib_count_in_file(self.file_handle)
# SET FILENAMES
filePrefix = 'nam.t'
fileSuffix = 'z.afwaca00.tm00.grib2'
# fileSuffix = 'z.afwaca00.grb2.tm00'
filenames = []
filePaths = []
for i in range(nfiles):
filenames.append(filePrefix + '{:02d}'.format(i * 6) + fileSuffix)
filePaths.append(os.path.join(inDir, filenames[i]))
#####
# OPEN FIRST GRIB FILE, GET MESSAGE HANDLERS AND CLOSE
f = open(filePaths[0], 'r')
gribapi.grib_multi_support_on()
mcount = gribapi.grib_count_in_file(f) # number of messages in file
gids = [gribapi.grib_new_from_file(f) for i in range(mcount)]
f.close()
#####
# GET NAME AND LEVEL OF EACH MESSAGE
varNames = []
levels = []
for i in range(mcount):
gid = gids[i]
varNames.append(gribapi.grib_get(gid, 'shortName'))
levels.append(gribapi.grib_get(gid, 'level'))
#####
# GET REQUIRED GIDS (AT REQUIRED LEVELS)
gidPRMSL = varNames.index("prmsl") + 1 # Pressure reduced to mean sea level