zi = np.empty((runCnt)) * np.nan
Ti = np.empty((runCnt)) * np.nan
Gamma = np.empty((runCnt)) * np.nan #inversion strength
zCL = np.empty((runCnt)) * np.nan
wStar = np.empty((runCnt)) * np.nan
zCLend = np.empty((runCnt)) * np.nan
Omega = np.empty((runCnt)) * np.nan #cumulative BL temperature based on zCLend
Phi = np.empty((runCnt)) * np.nan #cumulative fire heat
for nCase, Case in enumerate(RunList):
if Case in plume.exclude_runs:
continue
print('Examining case: %s ' % Case)
#----------get preignition temperature profile-----------------
csdict = plume.load_CS_prep_Profiles(Case)
T0 = np.load(plume.wrfdir + 'interp/profT0' + Case + '.npy')
U0 = np.load(plume.wrfdir + 'interp/profU0' + Case + '.npy')
#----------check for interpolated data----------------------------
avepath = plume.wrfdir + 'interp/wrfave_' + Case + '.npy'
if os.path.isfile(avepath):
print('Averaged data found at: %s' % avepath)
avedict = np.load(
avepath, allow_pickle=True).item() # load here the above pickle
else:
sys.exit(
'ERROR: no averaged data found - run prep_plumes.py via submit_interp.sh first on Cedar!'
)
(runCnt)
) * np.nan #cumulative vertical temperature (Km) - the questionable denominator term
thetaS = np.empty((runCnt)) * np.nan
thetaCL = np.empty((runCnt)) * np.nan
profile = np.empty((runCnt, len(interpZ))) * np.nan
quartiles = np.empty((runCnt, len(interpZ), 2)) * np.nan
sounding = np.empty(
(runCnt, len(interpZ))) * np.nan #storage for interpolated soundings
gradT0interp = np.empty(
(runCnt, len(interpZ) - 1)) * np.nan #storage for temperature gradient
#======================repeat main analysis for all runs first===================
#loop through all LES cases
for nCase, Case in enumerate(RunList):
csdict = plume.load_CS_prep_Profiles(
Case) #load data cross-wind integrated smoke and all other data
T0 = np.load(plume.wrfdir + 'interp/profT0' + Case +
'.npy') #load initial temperature profile
U0 = np.load(plume.wrfdir + 'interp/profU0' + Case +
'.npy') #load intial wind profile
#create an interpolated profile of temperature
if Case[-1:] == 'T' or Case[-1:] == 'E':
levels = plume.lvltall
if Case[-1:] == 'E':
pmlvl = np.arange(
0, 4001, 40) #extra tall domain for the concentrations only
else:
pmlvl = levels
else:
levels = plume.lvl