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Commit 66739e9b authored by sbiri's avatar sbiri
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Update run_ASFC.py

parent 606cdf48
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run_ASFC.py
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......@@ -2,8 +2,8 @@
example of running AirSeaFluxCode with
1. R/V data (data_all.nc) or
2. one day era5 hourly data (era5_r360x180.nc)
computes fluxes
outputs NetCDF4
compute fluxes
output NetCDF4
and statistics in stats.txt
@author: sbiri
......@@ -24,6 +24,34 @@ def reject_outliers(data, m=2):
def run_ASFC(inF, outF, gustIn, cskinIn, tolIn, meth):
"""
Parameters
----------
inF : str
input filename either data_all.nc or era5_r360x180.nc
outF : str
output filename
gustIn : float
gustiness option e.g. [1, 1.2, 800]
cskinIn : int
cool skin option input 0 or 1
tolIn : float
tolerance input option e.g. ['all', 0.01, 0.01, 5e-05, 0.01, 1, 1]
meth : str
parametrisation method option
Returns
-------
res : float
AirSeaFluxCode output
lon : float
longitude from input netCDF file
lat : float
latitude from input netCDF file
"""
if (inF == "data_all.nc"):
#%% load data_all
fid=nc.Dataset('data_all.nc')
......@@ -33,7 +61,6 @@ def run_ASFC(inF, outF, gustIn, cskinIn, tolIn, meth):
spd = np.array(fid.variables["spd"])
t = np.array(fid.variables["t"])
sst = np.array(fid.variables["sst"])
lat = np.array(fid.variables["lat"])
rh = np.array(fid.variables["rh"])
p = np.array(fid.variables["p"])
sw = np.array(fid.variables["sw"])
......@@ -46,7 +73,7 @@ def run_ASFC(inF, outF, gustIn, cskinIn, tolIn, meth):
#%% run AirSeaFluxCode
res = AirSeaFluxCode(spd, t, sst, lat=lat, hum=['rh', rh], P=p,
hin=hin, Rs=sw, tol=tolIn, gust=gustIn,
cskin=cskinIn, meth=meth, out=1, L="ERA5", n=30)
cskin=cskinIn, meth=meth, out=1, L="ecmwf", n=30)
#%% save NetCDF4
fid = nc.Dataset(outF,'w', format='NETCDF4')
fid.createDimension('lon', len(lon))
......@@ -85,6 +112,7 @@ def run_ASFC(inF, outF, gustIn, cskinIn, tolIn, meth):
itera = fid.createVariable('iter', 'i4', 'time')
dter = fid.createVariable('dter', 'f4', 'time')
dqer = fid.createVariable('dqer', 'f4', 'time')
dtwl = fid.createVariable('dter', 'f4', 'time')
qair = fid.createVariable('qair', 'f4', 'time')
qsea = fid.createVariable('qsea', 'f4', 'time')
Rl = fid.createVariable('Rl', 'f4', 'time')
......@@ -124,11 +152,12 @@ def run_ASFC(inF, outF, gustIn, cskinIn, tolIn, meth):
itera[:] = res[27]
dter[:] = res[28]
dqer[:] = res[29]
qair[:] = res[30]
qsea[:] = res[31]
Rl = res[32]
Rs = res[33]
Rnl = res[34]
dtwl[:] = res[30]
qair[:] = res[31]
qsea[:] = res[32]
Rl = res[33]
Rs = res[34]
Rnl = res[35]
longitude.long_name = 'Longitude'
longitude.units = 'degrees East'
latitude.long_name = 'Latitude'
......@@ -221,7 +250,7 @@ def run_ASFC(inF, outF, gustIn, cskinIn, tolIn, meth):
hin = np.array([10, 2, 2])
latIn = np.tile(lat, (len(lon), 1)).T.reshape(len(lon)*len(lat))
#%% run AirSeaFluxCode
res = np.zeros((len(tim),len(lon)*len(lat), 35))
res = np.zeros((len(tim),len(lon)*len(lat), 36))
# reshape input and run code
for x in range(len(tim)):
a = AirSeaFluxCode(spd.reshape(len(tim), len(lon)*len(lat))[x, :],
......@@ -234,7 +263,7 @@ def run_ASFC(inF, outF, gustIn, cskinIn, tolIn, meth):
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, qmeth='WMO',
meth=meth, n=30, L="ERA5")
meth=meth, n=30, L="ecmwf")
res[x, :, :] = a.T
del a
#%% save NetCDF4
......@@ -275,6 +304,7 @@ def run_ASFC(inF, outF, gustIn, cskinIn, tolIn, meth):
itera = fid.createVariable('iter', 'i4', ('time','lat','lon'))
dter = fid.createVariable('dter', 'f4', ('time','lat','lon'))
dqer = fid.createVariable('dqer', 'f4', ('time','lat','lon'))
dtwl = fid.createVariable('dtwl', 'f4', ('time','lat','lon'))
qair = fid.createVariable('qair', 'f4', ('time','lat','lon'))
qsea = fid.createVariable('qsea', 'f4', ('time','lat','lon'))
Rl = fid.createVariable('Rl', 'f4', ('time','lat','lon'))
......@@ -313,12 +343,13 @@ def run_ASFC(inF, outF, gustIn, cskinIn, tolIn, meth):
qrefs[:] = res[:, :, 26].reshape((len(tim), len(lat), len(lon)))*lsm
itera[:] = res[:, :, 27].reshape((len(tim), len(lat), len(lon)))*lsm
dter[:] = res[:, :, 28].reshape((len(tim), len(lat), len(lon)))*lsm
dqer[:] = res[:, :, 29].reshape((len(tim), len(lat), len(lon)))*lsm
qair[:] = res[:, :, 30].reshape((len(tim), len(lat), len(lon)))*lsm
qsea[:] = res[:, :, 31].reshape((len(tim), len(lat), len(lon)))*lsm
Rl = res[:, :, 32].reshape((len(tim), len(lat), len(lon)))
Rs = res[:, :, 33].reshape((len(tim), len(lat), len(lon)))
Rnl = res[:, :, 34].reshape((len(tim), len(lat), len(lon)))
dtwl[:] = res[:, :, 29].reshape((len(tim), len(lat), len(lon)))*lsm
dqer[:] = res[:, :, 30].reshape((len(tim), len(lat), len(lon)))*lsm
qair[:] = res[:, :, 31].reshape((len(tim), len(lat), len(lon)))*lsm
qsea[:] = res[:, :, 32].reshape((len(tim), len(lat), len(lon)))*lsm
Rl = res[:, :, 33].reshape((len(tim), len(lat), len(lon)))
Rs = res[:, :, 34].reshape((len(tim), len(lat), len(lon)))
Rnl = res[:, :, 35].reshape((len(tim), len(lat), len(lon)))
longitude.long_name = 'Longitude'
longitude.units = 'degrees East'
latitude.long_name = 'Latitude'
......@@ -385,40 +416,67 @@ def run_ASFC(inF, outF, gustIn, cskinIn, tolIn, meth):
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
del qair, qsea, Rl, Rs, Rnl, dtwl
del T, Td, tim, p, lw, sw, lsm, spd, hin, latIn
return res, lon, lat
#%% run function
start_time = time.perf_counter()
#------------------------------------------------------------------------------
inF = input("Give input file name (data_all.nc or era5_r360x180.nc): \n")
meth = input("Give prefered method: \n")
while meth not in ["S80", "S88", "LP82", "YT96", "UA", "LY04", "C30", "C35",
"C40", "ecmwf","Beljaars"]:
print("method unknown")
meth = input("Give prefered method: \n")
else:
meth = meth #[meth]
ext = meth+"_"
#------------------------------------------------------------------------------
gustIn = input("Give gustiness option (to use default press enter): \n")
if (gustIn == ''):
gustIn = None
ext = ext+'gust_'
else:
gustIn = np.asarray(eval(gustIn), dtype=float)
if ((np.all(gustIn) == 0)):
ext = ext+'nogust_'
else:
ext = ext+'gust_'
#------------------------------------------------------------------------------
cskinIn = input("Give cool skin option (to use default press enter): \n")
if (cskinIn == ''):
cskinIn = None
if ((cskinIn == None) and (meth == "S80" or meth == "S88" or meth == "LP82"
or meth == "YT96" or meth == "UA" or
meth == "LY04")):
cskinIn = 0
ext = ext+'noskin_'
elif ((cskinIn == None) and (meth == "C30" or meth == "C35" or meth == "C40"
or meth == "ecmwf" or meth == "Beljaars")):
cskinIn = 1
ext = ext+'skin_'
else:
cskinIn = int(cskinIn)
if (cskinIn == 0):
ext = ext+'noskin_'
elif (cskinIn == 1):
ext = ext+'skin_'
#------------------------------------------------------------------------------
tolIn = input("Give tolerance option (to use default press enter): \n")
if (tolIn == ''):
tolIn = None
tolIn = ['flux', 0.01, 1, 1]
else:
tolIn = eval(tolIn)
meth = input("Give prefered method: \n")
while meth not in ["S80", "S88", "LP82", "YT96", "UA", "LY04", "C30", "C35",
"C40", "ERA5","Beljaars"]:
print("method unknown")
meth = input("Give prefered method: \n")
else:
meth = meth #[meth]
ext = ext+'tol'+tolIn[0]
#------------------------------------------------------------------------------
outF = input("Give path and output file name: \n")
if (outF == ''):
outF = inF[:-3]+"_"+meth+".nc"
outF = "out_"+inF[:-3]+"_"+ext+".nc"
elif (outF[-3:] != '.nc'):
outF = outF+".nc"
else:
outF = outF
#------------------------------------------------------------------------------
print("\n run_ASFC.py, started for method "+meth)
res, lon, lat = run_ASFC(inF, outF, gustIn, cskinIn, tolIn, meth)
......@@ -440,14 +498,16 @@ if (inF == 'era5_r360x180.nc'):
plt.xlabel("Longitude")
plt.ylabel("Latitude")
plt.title(meth+', '+ttl[i])
plt.savefig('./'+ttl[i][:3]+'_'+meth+'.png', dpi=300, bbox_inches='tight')
plt.savefig('./'+ttl[i][:3]+'_'+ext+'.png', dpi=300, bbox_inches='tight')
elif (inF == "data_all.nc"):
ttl = ["tau (Nm$^{-2}$)", "shf (Wm$^{-2}$)", "lhf (Wm$^{-2}$)"]
for i in range(3):
plt.figure()
plt.plot(res[i],'.c', markersize=1)
plt.title(meth+', '+ttl[i])
plt.savefig('./'+ttl[i][:3]+'_'+meth+'.png', dpi=300, bbox_inches='tight')
plt.title(meth)
plt.xlabel("points")
plt.ylabel(ttl[i])
plt.savefig('./'+ttl[i][:3]+'_'+ext+'.png', dpi=300, bbox_inches='tight')
#%% generate txt file with statistic
if ((cskinIn == None) and (meth == "S80" or meth == "S88" or meth == "LP82"
......@@ -455,11 +515,11 @@ if ((cskinIn == None) and (meth == "S80" or meth == "S88" or meth == "LP82"
meth == "LY04")):
cskinIn = 0
elif ((cskinIn == None) and (meth == "C30" or meth == "C35" or meth == "C40"
or meth == "ERA5" or meth == "Beljaars")):
or meth == "ecmwf" or meth == "Beljaars")):
cskinIn = 1
if (np.all(gustIn == None) and (meth == "C30" or meth == "C35" or meth == "C40")):
gustIn = [1, 1.2, 600]
elif (np.all(gustIn == None) and (meth == "UA" or meth == "ERA5")):
elif (np.all(gustIn == None) and (meth == "UA" or meth == "ecmwf")):
gustIn = [1, 1, 1000]
elif np.all(gustIn == None):
gustIn = [1, 1.2, 800]
......@@ -477,7 +537,7 @@ ttl = np.asarray(["tau ", "shf ", "lhf ", "L ", "cd ", "cdn ",
"qsr ", "usr ", "psim ", "psit ", "psiq ", "u10n ",
"t10n ", "tv10n", "q10n ", "zo ", "zot ", "zoq ",
"urefs", "trefs", "qrefs", "itera", "dter ", "dqer ",
"qair ", "qsea ", "Rl ", "Rs ", "Rnl "])
"dtwl ", "qair ", "qsea ", "Rl ", "Rs ", "Rnl "])
header = ["var", "mean", "median", "min", "max", "5%", "95%"]
n = np.shape(res)
stats = np.copy(ttl)
......@@ -493,6 +553,7 @@ if (inF == 'era5_r360x180.nc'):
print(tabulate(stats, headers=header, tablefmt="github", numalign="left",
floatfmt=("s", "2.2e", "2.2e", "2.2e", "2.2e", "2.2e",
"2.2e")), file=open('./stats.txt', 'a'))
print('-'*79+'\n', file=open('./stats.txt', 'a'))
elif (inF == "data_all.nc"):
stats = np.c_[stats, np.nanmean(res, axis=1)]
stats = np.c_[stats, np.nanmedian(res, axis=1)]
......@@ -505,3 +566,8 @@ elif (inF == "data_all.nc"):
"2.2e")), file=open('./stats.txt', 'a'))
print('-'*79+'\n', file=open('./stats.txt', 'a'))
print('input file name: {}, \n method: {}, \n gustiness: {}, \n cskin: {},'
' \n tolerance: {}, \n output is written in: {}'.format(inF, meth,
gustIn, cskinIn,
tolIn, outF),
file=open('./readme.txt', 'w'))
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