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Commit d88de8c0 authored by sbiri's avatar sbiri
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Update toy_ASFC.py

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toy_ASFC.py
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......@@ -19,13 +19,8 @@ from AirSeaFluxCode import AirSeaFluxCode
import time
from tabulate import tabulate
#%%
def reject_outliers(data, m=2):
x = np.copy(data)
x = np.where(np.abs(x-np.nanmean(x)) < m*np.nanstd(x), x, np.nan)
return x
def toy_ASFC(inF, outF, outS, gustIn, cskinIn, tolIn, meth, qmIn, LIn, stdIn):
def toy_ASFC(inF, outF, outS, sst_fl, gustIn, cskinIn, tolIn, meth, qmIn, LIn,
stdIn):
"""
Example routine of how to run AirSeaFluxCode with the test data given
and save output either as .csv or NetCDF
......@@ -57,6 +52,7 @@ def toy_ASFC(inF, outF, outS, gustIn, cskinIn, tolIn, meth, qmIn, LIn, stdIn):
latitude from input netCDF file
"""
out_var = ("tau", "sensible", "latent", "u10n", "t10n", "q10n")
if (inF == "data_all.csv"):
#%% load data_all
inDt = pd.read_csv("data_all.csv")
......@@ -78,10 +74,10 @@ def toy_ASFC(inF, outF, outS, gustIn, cskinIn, tolIn, meth, qmIn, LIn, stdIn):
hin = np.array([hu, ht, ht])
del hu, ht, inDt
#%% run AirSeaFluxCode
res = AirSeaFluxCode(spd, t, sst, lat=lat, hum=['rh', rh], P=p,
res = AirSeaFluxCode(spd, t, sst, sst_fl, lat=lat, hum=['rh', rh], P=p,
hin=hin, Rs=sw, tol=tolIn, gust=gustIn,
cskin=cskinIn, meth=meth, qmeth=qmIn, maxiter=30,
out_var="limited", L=LIn)
cskin=cskinIn, meth=meth, qmeth=qmIn, L=LIn,
maxiter=10, out_var = out_var)
flg = res["flag"]
elif (inF == 'era5_r360x180.nc'):
......@@ -120,18 +116,19 @@ def toy_ASFC(inF, outF, outS, gustIn, cskinIn, tolIn, meth, qmIn, LIn, stdIn):
flg = np.empty((len(tim),len(lon)*len(lat)), dtype="object")
# reshape input and run code
for x in range(len(tim)):
a = AirSeaFluxCode(
spd.reshape(len(tim), len(lon)*len(lat))[x, :],
a = AirSeaFluxCode(spd.reshape(len(tim), len(lon)*len(lat))[x, :],
T.reshape(len(tim), len(lon)*len(lat))[x, :],
sst.reshape(len(tim), len(lon)*len(lat))[x, :],
lat=latIn,
sst_fl, lat=latIn,
hum=['Td', Td.reshape(len(tim), len(lon)*len(lat))[x, :]],
P=p.reshape(len(tim), len(lon)*len(lat))[x, :], hin=hin,
P=p.reshape(len(tim), len(lon)*len(lat))[x, :],
hin=hin,
Rs=sw.reshape(len(tim), len(lon)*len(lat))[x, :],
Rl=lw.reshape(len(tim), len(lon)*len(lat))[x, :],
gust=gustIn, cskin=cskinIn, tol=tolIn, meth=meth, qmeth=qmIn,
maxiter=30, out_var="limited", L=LIn)
temp = a.iloc[:,:-1]
gust=gustIn, cskin=cskinIn, tol=tolIn,
meth=meth, qmeth=qmIn, maxiter=30, L=LIn,
out_var = out_var)
temp = a.iloc[:, :-1]
temp = temp.to_numpy()
flg[x, :] = a["flag"]
res[x, :, :] = temp
......@@ -155,9 +152,10 @@ def toy_ASFC(inF, outF, outS, gustIn, cskinIn, tolIn, meth, qmIn, LIn, stdIn):
tau = fid.createVariable('tau', 'f4', ('time','lat','lon'))
sensible = fid.createVariable('shf', 'f4', ('time','lat','lon'))
latent = fid.createVariable('lhf', 'f4', ('time','lat','lon'))
urefs = fid.createVariable('uref', 'f4', ('time','lat','lon'))
trefs = fid.createVariable('tref', 'f4', ('time','lat','lon'))
qrefs = fid.createVariable('qref', 'f4', ('time','lat','lon'))
monob = fid.createVariable('MO', 'f4', ('time','lat','lon'))
u10n = fid.createVariable('u10n', 'f4', ('time','lat','lon'))
t10n = fid.createVariable('t10n', 'f4', ('time','lat','lon'))
q10n = fid.createVariable('q10n', 'f4', ('time','lat','lon'))
flag = fid.createVariable('flag', 'U1', ('time','lat','lon'))
longitude[:] = lon
......@@ -166,9 +164,9 @@ def toy_ASFC(inF, outF, outS, gustIn, cskinIn, tolIn, meth, qmIn, LIn, stdIn):
tau[:] = res[:, :, 0].reshape((len(tim), len(lat), len(lon)))*msk
sensible[:] = res[:, :, 1].reshape((len(tim), len(lat), len(lon)))*msk
latent[:] = res[:, :, 2].reshape((len(tim), len(lat), len(lon)))*msk
urefs[:] = res[:, :, 3].reshape((len(tim), len(lat), len(lon)))*msk
trefs[:] = res[:, :, 4].reshape((len(tim), len(lat), len(lon)))*msk
qrefs[:] = res[:, :, 5].reshape((len(tim), len(lat), len(lon)))*msk
u10n[:] = res[:, :, 3].reshape((len(tim), len(lat), len(lon)))*msk
t10n[:] = res[:, :, 4].reshape((len(tim), len(lat), len(lon)))*msk
q10n[:] = res[:, :, 5].reshape((len(tim), len(lat), len(lon)))*msk
flag[:] = flg.reshape((len(tim), len(lat), len(lon)))
longitude.long_name = 'Longitude'
......@@ -183,20 +181,22 @@ def toy_ASFC(inF, outF, outS, gustIn, cskinIn, tolIn, meth, qmIn, LIn, stdIn):
sensible.units = 'W/m^2'
latent.long_name = 'Latent heat flux'
latent.units = 'W/m^2'
urefs.long_name = 'wind speed at ref height'
urefs.units = 'm/s'
trefs.long_name = 'temperature at ref height'
trefs.units = 'degrees Celsius'
qrefs.long_name = 'specific humidity at ref height'
qrefs.units = 'kgr/kgr'
u10n.long_name = '10m neutral wind speed'
u10n.units = 'm/s'
t10n.long_name = '10m neutral temperature'
t10n.units = 'degrees Celsius'
q10n.long_name = '10m neutral specific humidity'
q10n.units = 'kgr/kgr'
flag.long_name = ('flag "n" normal, "u": u10n < 0, "q": q10n < 0,'
'"l": zol<0.01, "m": missing, "i": points that'
'have not converged')
fid.close()
#%% delete variables
del longitude, latitude, Date, tau, sensible, latent
del urefs, trefs, qrefs
del tim, T, Td, p, lw, sw, lsm, spd, hin, latIn, icon, msk
# del longitude, latitude, Date, tau, sensible, latent, monob, cd, cdn
# del ct, ctn, cq, cqn, tsrv, tsr, qsr, usr, psim, psit, psiq, u10n, t10n
# del tv10n, q10n, zo, zot, zoq, urefs, trefs, qrefs, itera, dter, dqer
# del qair, qsea, Rl, Rs, Rnl, dtwl
# del tim, T, Td, p, lw, sw, lsm, spd, hin, latIn, icon, msk
else:
#%% save NetCDF4
fid = nc.Dataset(outF,'w', format='NETCDF4')
......@@ -209,9 +209,9 @@ def toy_ASFC(inF, outF, outS, gustIn, cskinIn, tolIn, meth, qmIn, LIn, stdIn):
tau = fid.createVariable('tau', 'f4', 'time')
sensible = fid.createVariable('shf', 'f4', 'time')
latent = fid.createVariable('lhf', 'f4', 'time')
urefs = fid.createVariable('uref', 'f4', 'time')
trefs = fid.createVariable('tref', 'f4', 'time')
qrefs = fid.createVariable('qref', 'f4', 'time')
u10n = fid.createVariable('u10n', 'f4', 'time')
t10n = fid.createVariable('t10n', 'f4', 'time')
q10n = fid.createVariable('q10n', 'f4', 'time')
flag = fid.createVariable('flag', 'U1', 'time')
longitude[:] = lon
......@@ -220,9 +220,9 @@ def toy_ASFC(inF, outF, outS, gustIn, cskinIn, tolIn, meth, qmIn, LIn, stdIn):
tau[:] = res["tau"]
sensible[:] = res["shf"]
latent[:] = res["lhf"]
urefs[:] = res["uref"]
trefs[:] = res["tref"]
qrefs[:] = res["qref"]
u10n[:] = res["u10n"]
t10n[:] = res["t10n"]
q10n[:] = res["q10n"]
flag[:] = res["flag"]
longitude.long_name = 'Longitude'
......@@ -237,21 +237,22 @@ def toy_ASFC(inF, outF, outS, gustIn, cskinIn, tolIn, meth, qmIn, LIn, stdIn):
sensible.units = 'W/m^2'
latent.long_name = 'Latent heat flux'
latent.units = 'W/m^2'
urefs.long_name = 'wind speed at ref height'
urefs.units = 'm/s'
trefs.long_name = 'temperature at ref height'
trefs.units = 'degrees Celsius'
qrefs.long_name = 'specific humidity at ref height'
qrefs.units = 'kgr/kgr'
u10n.long_name = '10m neutral wind speed'
u10n.units = 'm/s'
t10n.long_name = '10m neutral temperature'
t10n.units = 'degrees Celsius'
q10n.long_name = '10m neutral specific humidity'
q10n.units = 'kgr/kgr'
flag.long_name = ('flag "n" normal, "u": u10n < 0, "q": q10n < 0,'
'"l": zol<0.01, "m": missing, "i": points that'
'have not converged')
fid.close()
#%% delete variables
del longitude, latitude, Date, tau, sensible, latent
del urefs, trefs, qrefs
del qair, qsea, Rl, Rs, Rnl, ug, rh, Rib
del t, date, p, sw, spd, hin, sst
# del longitude, latitude, Date, tau, sensible, latent, monob, cd, cdn
# del ct, ctn, cq, cqn, tsrv, tsr, qsr, usr, psim, psit, psiq, u10n, t10n
# del tv10n, q10n, zo, zot, zoq, urefs, trefs, qrefs, itera, dter, dqer
# del qair, qsea, Rl, Rs, Rnl, ug, rh, Rib
# del t, date, p, sw, spd, hin, sst
else:
#%% save as .csv
res.insert(loc=0, column='date', value=date)
......@@ -272,6 +273,8 @@ else:
meth = meth #[meth]
ext = meth+"_"
#------------------------------------------------------------------------------
sst_fl = input("Give SST flag (bulk/sin): \n")
#------------------------------------------------------------------------------
qmIn = input("Give prefered method for specific humidity: \n")
if (qmIn == ''):
qmIn = 'Buck2' # default
......@@ -285,7 +288,7 @@ else:
#------------------------------------------------------------------------------
gustIn = input("Give gustiness option (to switch it off enter 0;"
" to set your own input use the form [1, B, zi, ugmin]"
" i.e. [1, 1, 800, 0.2] or "
" i.e. [1, 1, 800, 0.01] or "
"to use default press enter): \n")
if (gustIn == ''):
gustIn = None
......@@ -364,8 +367,8 @@ elif (outS[-4:] != '.txt'):
#------------------------------------------------------------------------------
print("\n run_ASFC.py, started for method "+meth)
res, lon, lat = toy_ASFC(inF, outF, outS, gustIn, cskinIn, tolIn, meth, qmIn,
LIn, stdIn)
res, lon, lat = toy_ASFC(inF, outF, outS, sst_fl, gustIn, cskinIn, tolIn,
meth, qmIn, LIn, stdIn)
print("run_ASFC.py took ", np.round((time.perf_counter()-start_time)/60, 2),
"minutes to run")
......@@ -396,22 +399,19 @@ print("run_ASFC.py took ", np.round((time.perf_counter()-start_time)/60, 2),
# plt.savefig('./'+ttl[i][:3]+'_'+ext+'.png', dpi=300, bbox_inches='tight')
#%% generate txt file with statistics
if ((cskinIn == None) and (meth == "S80" or meth == "S88" or meth == "LP82"
or meth == "YT96" or meth == "UA" or
meth == "NCAR")):
if (cskinIn == None) and (meth in ["S80", "S88", "LP82", "YT96", "UA", "NCAR"]):
cskinIn = 0
elif ((cskinIn == None) and (meth == "C30" or meth == "C35"
or meth == "ecmwf" or meth == "Beljaars")):
elif (cskinIn == None) and (meth in ["C30", "C35", "ecmwf", "Beljaars"]):
cskinIn = 1
if (np.all(gustIn == None) and (meth == "C30" or meth == "C35")):
if np.all(gustIn == None) and (meth in ["C30", "C35"]):
gustIn = [1, 1.2, 600, 0.2]
elif (np.all(gustIn == None) and (meth == "UA" or meth == "ecmwf")):
elif np.all(gustIn == None) and (meth in ["UA", "ecmwf"]):
gustIn = [1, 1, 1000, 0.01]
elif np.all(gustIn == None):
gustIn = [1, 1.2, 600, 0.01]
elif ((np.size(gustIn) < 4) and (gustIn == 0)):
gustIn = [1, 1.2, 800, 0.01]
elif (np.size(gustIn) < 4) and (gustIn == 0):
gust = [0, 0, 0, 0]
if (tolIn == None):
if tolIn == None:
tolIn = ['all', 0.01, 0.01, 1e-05, 1e-3, 0.1, 0.1]
......@@ -422,7 +422,7 @@ print('input file name: {}, \n method: {}, \n gustiness: {}, \n cskin: {},'
qmIn, LIn),
file=open('./'+outS, 'a'))
ttl = np.asarray(["tau ", "shf ", "lhf ",
"urefs", "trefs", "qrefs"])
"u10n ", "t10n ", "q10n "])
header = ["var", "mean", "median", "min", "max", "5%", "95%"]
n = np.shape(res)
stats = np.copy(ttl)
......@@ -440,7 +440,7 @@ if (inF == 'era5_r360x180.nc'):
"2.2e")), file=open('./'+outS, 'a'))
print('-'*79+'\n', file=open('./'+outS, 'a'))
elif (inF == "data_all.csv"):
a = res.loc[:,"tau":"rh"].to_numpy(dtype="float64").T
a = res.loc[:, "tau":"q10n"].to_numpy(dtype="float64").T
stats = np.c_[stats, np.nanmean(a, axis=1)]
stats = np.c_[stats, np.nanmedian(a, axis=1)]
stats = np.c_[stats, np.nanmin(a, axis=1)]
......
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