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Commit b8115ade authored by sbiri's avatar sbiri
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Update AirSeaFluxCode.py, flux_subs.py, get_init.py, hum_subs.py, data_all.nc,... 

Update AirSeaFluxCode.py, flux_subs.py, get_init.py, hum_subs.py, data_all.nc, Documentation.pdf, era5_r360x180.nc, run_ASFC.py files
Deleted data_Mxtr.nc, data_mod.nc, data_trp.nc, data_xtr.nc files
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AirSeaFluxCode.py
View file @ b8115ade
......@@ -53,8 +53,8 @@ def AirSeaFluxCode(spd, T, SST, lat=None, hum=None, P=None,
"S80","S88","LP82","YT96","UA","LY04","C30","C35","C40","ERA5"
qmeth : str
is the saturation evaporation method to use amongst
"HylandWexler","Hardy","Preining","Wexler","GoffGratch","CIMO",
"MagnusTetens","Buck","Buck2","WMO","WMO2000","Sonntag","Bolton",
"HylandWexler","Hardy","Preining","Wexler","GoffGratch","WMO",
"MagnusTetens","Buck","Buck2","WMO2018","Sonntag","Bolton",
"IAPWS","MurphyKoop"]
default is Buck2
tol : float
......@@ -76,10 +76,10 @@ def AirSeaFluxCode(spd, T, SST, lat=None, hum=None, P=None,
Returns
-------
res : array that contains
1. momentum flux (W/m^2)
1. momentum flux (N/m^2)
2. sensible heat (W/m^2)
3. latent heat (W/m^2)
4. Monin-Obhukov length (mb)
4. Monin-Obhukov length (m)
5. drag coefficient (cd)
6. neutral drag coefficient (cdn)
7. heat exhange coefficient (ct)
......@@ -104,10 +104,15 @@ def AirSeaFluxCode(spd, T, SST, lat=None, hum=None, P=None,
26. temperature at reference height (tref)
27. specific humidity at reference height (qref)
28. number of iterations until convergence
ind : int
the indices in the matrix for the points that did not converge
after the maximum number of iterations
The code is based on bform.f and flux_calc.R modified by S. Biri
29. cool-skin temperature depression (dter)
30. cool-skin humidity depression (dqer)
31. specific humidity of air (qair)
32. specific humidity at sea surface (qsea)
33. downward longwave radiation (Rl)
34. downward shortwave radiation (Rs)
35. downward net longwave radiation (Rnl)
2020 / Author S. Biri
"""
logging.basicConfig(filename='flux_calc.log',
format='%(asctime)s %(message)s',level=logging.INFO)
......@@ -135,6 +140,7 @@ def AirSeaFluxCode(spd, T, SST, lat=None, hum=None, P=None,
np.nanmedian(qsea), np.nanmedian(qair))
if (np.all(np.isnan(qsea)) or np.all(np.isnan(qair))):
print("qsea and qair cannot be nan")
# tlapse = gamma_moist(SST, T, qair/1000) lapse rate can be computed like this
dt = Ta - sst
dq = qair - qsea
# first guesses
......@@ -289,7 +295,7 @@ def AirSeaFluxCode(spd, T, SST, lat=None, hum=None, P=None,
elif (tol[0] == 'all'):
new = np.array([np.copy(u10n), np.copy(t10n), np.copy(q10n),
np.copy(tau), np.copy(sensible), np.copy(latent)])
d = np.fabs(new-old)
d = np.abs(new-old)
if (tol[0] == 'flux'):
ind = np.where((d[0, :] > tol[1])+(d[1, :] > tol[2]) +
(d[2, :] > tol[3]))
......@@ -305,6 +311,7 @@ def AirSeaFluxCode(spd, T, SST, lat=None, hum=None, P=None,
else:
ii = True
itera[ind] = -1
# itera = np.where(itera > n, -1, itera)
logging.info('method %s | # of iterations:%s', meth, it)
logging.info('method %s | # of points that did not converge :%s', meth,
ind[0].size)
......
Documentation.pdf
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data_Mxtr.nc deleted 100644 → 0
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data_all.nc 0 → 100644
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data_mod.nc deleted 100644 → 0
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data_trp.nc deleted 100644 → 0
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data_xtr.nc deleted 100644 → 0
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era5_r360x180.nc 0 → 100644
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File added
flux_subs.py
View file @ b8115ade
......@@ -32,7 +32,7 @@ def cdn_calc(u10n, Ta, Tp, lat, meth="S80"):
np.where((u10n <= 25) & (u10n >= 11),
(0.49+0.065*u10n)*0.001, 1.14*0.001))
elif (meth == "S88" or meth == "UA" or meth == "ERA5" or meth == "C30" or
meth == "C35" or meth == "C40"):
meth == "C35" or meth == "C40" or meth == "Beljaars"):
cdn = cdn_from_roughness(u10n, Ta, None, lat, meth)
elif (meth == "YT96"):
# for u<3 same as S80
......@@ -101,7 +101,7 @@ def cdn_from_roughness(u10n, Ta, Tp, lat, meth="S88"):
a = 0.011*np.ones(Ta.shape)
a = np.where(u10n > 22, 0.0016*22-0.0035, 0.0016*u10n-0.0035)
zo = a*np.power(usr, 2)/g+0.11*visc_air(Ta)/usr # surface roughness
elif (meth == "ERA5"):
elif ((meth == "ERA5" or meth == "Beljaars")):
# eq. (3.26) p.38 over sea IFS Documentation cy46r1
zo = 0.018*np.power(usr, 2)/g+0.11*visc_air(Ta)/usr
else:
......@@ -209,7 +209,7 @@ def ctcqn_calc(zol, cdn, u10n, zo, Ta, meth="S80"):
# 5e-5/np.power(rr, 0.6)) # moisture roughness as in C30
cqn = kappa**2/np.log(10/zo)/np.log(10/zoq)
ctn = kappa**2/np.log(10/zo)/np.log(10/zot)
elif (meth == "ERA5"):
elif (meth == "ERA5" or meth == "Beljaars"):
# eq. (3.26) p.38 over sea IFS Documentation cy46r1
usr = np.sqrt(cdn*np.power(u10n, 2))
zot = 0.40*visc_air(Ta)/usr
......@@ -274,8 +274,8 @@ def get_stabco(meth="S80"):
"""
alpha, beta, gamma = 0, 0, 0
if (meth == "S80" or meth == "S88" or meth == "LY04" or
meth == "UA" or meth == "ERA5" or meth == "C30" or meth == "C35" or
meth == "C40"):
meth == "UA" or meth == "ERA5" or meth == "C30" or
meth == "C35" or meth == "C40" or meth == "Beljaars"):
alpha, beta, gamma = 16, 0.25, 5 # Smith 1980, from Dyer (1974)
elif (meth == "LP82"):
alpha, beta, gamma = 16, 0.25, 7
......@@ -308,6 +308,8 @@ def psim_calc(zol, meth="S80"):
psim = psim_era5(zol)
elif (meth == "C30" or meth == "C35" or meth == "C40"):
psim = psiu_26(zol, meth)
elif (meth == "Beljaars"): # Beljaars (1997) eq. 16, 17
psim = np.where(zol < 0, psim_conv(zol, meth), psi_Bel(zol))
else:
psim = np.where(zol < 0, psim_conv(zol, meth),
psim_stab(zol, meth))
......@@ -334,6 +336,8 @@ def psit_calc(zol, meth="S80"):
psi_era5(zol))
elif (meth == "C30" or meth == "C35" or meth == "C40"):
psit = psit_26(zol)
elif (meth == "Beljaars"): # Beljaars (1997) eq. 16, 17
psit = np.where(zol < 0, psi_conv(zol, meth), psi_Bel(zol))
else:
psit = np.where(zol < 0, psi_conv(zol, meth),
psi_stab(zol, meth))
......@@ -341,6 +345,26 @@ def psit_calc(zol, meth="S80"):
# ---------------------------------------------------------------------
def psi_Bel(zol):
""" Calculates momentum/heat stability function
Parameters
----------
zol : float
height over MO length
meth : str
parameterisation method
Returns
-------
psit : float
"""
a, b, c, d = 0.7, 0.75, 5, 0.35
psi = -(a*zol+b*(zol-c/d)*np.exp(-d*zol)+b*c/d)
return psi
# ---------------------------------------------------------------------
def psi_era5(zol):
""" Calculates heat stability function for stable conditions
for method ERA5
......@@ -578,8 +602,11 @@ def get_skin(sst, qsea, rho, Rl, Rs, Rnl, cp, lv, tkt, usr, tsr, qsr, lat):
Returns
-------
dter : float
cool-skin temperature depression
dqer : float
cool-skin humidity depression
tkt : float
cool skin thickness
"""
# coded following Saunders (1967) with lambda = 6
g = gc(lat, None)
......@@ -717,7 +744,7 @@ def get_L(L, lat, usr, tsr, qsr, t10n, tv10n, qair, h_in, T, Ta, th, tv, sst,
(np.log((h_in[0]+zo)/zot) -
psit_calc((h_in[0]+zo)/monob, meth) +
psit_calc(zot/monob, meth))))
monob = h_in[0]/zol
monob = h_in[0]/zol
return tsrv, monob
#------------------------------------------------------------------------------
......
get_init.py
View file @ b8115ade
......@@ -73,6 +73,7 @@ def get_init(spd, T, SST, lat, P, Rl, Rs, cskin, gust, L, tol, meth, qmeth):
MO length switch
"""
# check if input is correct (type, size, value) and set defaults
if ((type(spd) != np.ndarray) or (type(T) != np.ndarray) or
(type(SST) != np.ndarray)):
sys.exit("input type of spd, T and SST should be numpy.ndarray")
......@@ -82,11 +83,11 @@ def get_init(spd, T, SST, lat, P, Rl, Rs, cskin, gust, L, tol, meth, qmeth):
sys.exit("input dtype of spd, T and SST should be float")
# if input values are nan break
if meth not in ["S80", "S88", "LP82", "YT96", "UA", "LY04", "C30", "C35",
"C40","ERA5"]:
"C40", "ERA5", "Beljaars"]:
sys.exit("unknown method")
if qmeth not in ["HylandWexler", "Hardy", "Preining", "Wexler", "CIMO",
"GoffGratch", "MagnusTetens", "Buck", "Buck2", "WMO",
"WMO2000", "Sonntag", "Bolton", "IAPWS", "MurphyKoop"]:
if qmeth not in ["HylandWexler", "Hardy", "Preining", "Wexler",
"GoffGratch", "WMO", "MagnusTetens", "Buck", "Buck2",
"WMO2018", "Sonntag", "Bolton", "IAPWS", "MurphyKoop"]:
sys.exit("unknown q-method")
if (np.all(np.isnan(spd)) or np.all(np.isnan(T)) or np.all(np.isnan(SST))):
sys.exit("input wind, T or SST is empty")
......@@ -107,11 +108,13 @@ def get_init(spd, T, SST, lat, P, Rl, Rs, cskin, gust, L, tol, meth, qmeth):
meth == "LY04")):
cskin = 0
elif ((cskin == None) and (meth == "C30" or meth == "C35" or meth == "C40"
or meth == "ERA5")):
or meth == "ERA5" or meth == "Beljaars")):
cskin = 1
if (np.all(gust == None) and (meth == "C30" or meth == "C35" or meth == "C40")):
if (np.all(gust == None) and (meth == "C30" or meth == "C35" or
meth == "C40")):
gust = [1, 1.2, 600]
elif (np.all(gust == None) and (meth == "UA" or meth == "ERA5")):
elif (np.all(gust == None) and (meth == "UA" or meth == "ERA5" or
meth == "Beljaars")):
gust = [1, 1, 1000]
elif np.all(gust == None):
gust = [1, 1.2, 800]
......@@ -124,7 +127,7 @@ def get_init(spd, T, SST, lat, P, Rl, Rs, cskin, gust, L, tol, meth, qmeth):
if ((L == None) and (meth == "S80" or meth == "S88" or meth == "LP82"
or meth == "YT96" or meth == "LY04" or
meth == "UA" or meth == "C30" or meth == "C35"
or meth == "C40")):
or meth == "C40" or meth == "Beljaars")):
L = "S80"
elif ((L == None) and (meth == "ERA5")):
L = "ERA5"
......
hum_subs.py
View file @ b8115ade
......@@ -24,19 +24,16 @@ def VaporPressure(temp, P, phase, meth):
'ice' : Calculate vapor pressure over ice
meth : str
formula to be used
MartiMauersberger : vaporpressure formula from Marti Mauersberger
Hardy : vaporpressure formula from Hardy (1998)
MagnusTetens : vaporpressure formula from Magnus Tetens
GoffGratch : vaporpressure formula from Goff Gratch
Buck_original : vaporpressure formula from Buck (original)
Buck_manual : vaporpressure formula from the Buck manual
CIMO : vaporpressure formula recommended by CIMO
Vaisala : vaporpressure formula from Vaisala
WMO_Goff : vaporpressure formula from WMO, which should have been Goff
WMO2000 : vaporpressure formula from WMO (2000) containing a typo
Buck : vaporpressure formula from Buck (1981)
Buck2 : vaporpressure formula from the Buck (2012)
WMO : vaporpressure formula from WMO (1988)
WMO2018 : vaporpressure formula from WMO (2018)
Wexler : vaporpressure formula from Wexler (1976)
Sonntag : vaporpressure formula from Sonntag (1994)
Bolton : vaporpressure formula from Bolton (1980)
Fukuta : vaporpressure formula from Fukuta (2003)
HylandWexler : vaporpressure formula from Hyland and Wexler (1983)
IAPWS : vaporpressure formula from IAPWS (2002)
Preining : vaporpressure formula from Preining (2002)
......@@ -111,12 +108,6 @@ def VaporPressure(temp, P, phase, meth):
1.3816e-7*(np.power(10, 11.344*(1-T/Ts))-1) +
8.1328e-3*(np.power(10, -3.49149*(Ts/T-1))-1) +
np.log10(ews))
if (meth == 'CIMO'):
"""Source: Annex 4B, Guide to Meteorological Instruments and
Methods of Observation, WMO Publication No 8, 7th edition, Geneva,
2008. (CIMO Guide)"""
Psat = (6.112*np.exp(17.62*temp/(243.12+temp)) *
(1.0016+3.15e-6*P-0.074/P))
if (meth == 'MagnusTetens'):
"""Source: Murray, F. W., On the computation of \
saturation vapor pressure, J. Appl. Meteorol., \
......@@ -134,7 +125,7 @@ def VaporPressure(temp, P, phase, meth):
if (meth == 'Buck2'):
"""Bucks vapor pressure formulation based on Tetens formula.
Source: Buck Research, Model CR-1A Hygrometer Operating Manual,
Sep 2001"""
May 2012"""
Psat = (6.1121*np.exp((18.678-(temp)/234.5)*(temp)/(257.14+temp)) *
(1+1e-4*(7.2+P*(0.0320)+5.9e-6*np.power(T, 2))))
if (meth == 'WMO'):
......@@ -147,18 +138,12 @@ def VaporPressure(temp, P, phase, meth):
Ts = 273.16 # triple point temperature in K
Psat = np.power(10, 10.79574*(1-Ts/T)-5.028*np.log10(T/Ts) +
1.50475e-4*(1-np.power(10, -8.2969*(T/Ts-1))) +
0.42873e-3*(np.power(10, -4.76955*(1-Ts/T))-1) +
0.78614)
if (meth == 'WMO2000'):
"""WMO formulation, which is very similar to Goff & Gratch.
Source : WMO technical regulations, WMO-NO 49, Vol I, General
Meteorological Standards and Recommended Practices, App. A,
Corrigendum Aug 2000."""
Ts = 273.16 # triple point temperature in K
Psat = np.power(10, 10.79574*(1-Ts/T)-5.028*np.log10(T/Ts) +
1.50475e-4*(1-np.power(10, -8.2969*(T/Ts-1))) +
0.42873e-3*(np.power(10, -4.76955*(1.-Ts/T))-1) +
0.42873e-3*(np.power(10, 4.76955*(1-Ts/T))-1) + # in eq. 13 is -4.76955; in aerobulk is like this
0.78614)
if (meth == 'WMO2018'):
"""WMO 2018 edition. Annex 4.B, eq. 4.B.1, 4.B.2, 4.B.5 """
Psat = 6.112*np.exp(17.62*temp/(243.12+temp))*(1.0016+3.15e-6*P -
0.074/P)
if (meth == 'Sonntag'):
"""Source: Sonntag, D., Advancements in the field of hygrometry,
Meteorol. Z., N. F., 3, 51-66, 1994."""
......@@ -413,3 +398,38 @@ def get_hum(hum, T, sst, P, qmeth):
qsea = qsat_sea(sst, P, qmeth)/1000 # surface water q (g/kg)
return qair, qsea
#------------------------------------------------------------------------------
def gamma_moist(sst, t, q):
"""
Computes the moist adiabatic lapse-rate
Parameters
----------
sst : float
sea surface temperature [K]
t : float
air temperature [K]
q : float
specific humidity of air [kg/kg]
Returns
-------
gamma : float
lapse rate [K/m]
"""
if (np.nanmin(sst) < 200): # if sst in Celsius convert to Kelvin
sst = sst+CtoK
if (np.nanmin(t) < 200): # if sst in Celsius convert to Kelvin
t = t+CtoK
t = np.maximum(t, 180)
q = np.maximum(q, 1e-6)
w = q/(1-q) # mixing ratio w = q/(1-q)
iRT = 1/(287.05*t)
# latent heat of vaporization of water as a function of temperature
lv = (2.501-0.00237*(sst-CtoK))*1e6
gamma = 9.8*(1+lv*w*iRT)/(1005+np.power(lv, 2)*w*(287.05/461.495)*iRT/t)
return gamma
#------------------------------------------------------------------------------
run_ASFC.py 0 → 100644
View file @ b8115ade
"""
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
and statistics in stats.txt
@author: sbiri
"""
#%% import packages
import matplotlib.pyplot as plt
import netCDF4 as nc
import numpy as np
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 run_ASFC(inF, outF, gustIn, cskinIn, tolIn, meth):
if (inF == "data_all.nc"):
#%% load data_all
fid=nc.Dataset('data_all.nc')
date = np.array(fid.variables["date"])
lon = np.array(fid.variables["lon"])
lat = np.array(fid.variables["lat"])
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"])
hu = np.array(fid.variables["spd"].getncattr("height"))
ht = np.array(fid.variables["t"].getncattr("height"))
hin = np.array([hu, ht, ht])
del hu, ht
fid.close()
del fid
#%% 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)
#%% save NetCDF4
fid = nc.Dataset(outF,'w', format='NETCDF4')
fid.createDimension('lon', len(lon))
fid.createDimension('lat', len(lat))
fid.createDimension('time', None)
longitude = fid.createVariable('lon', 'f4', 'lon')
latitude = fid.createVariable('lat', 'f4', 'lat')
Date = fid.createVariable('Date', 'i4', 'time')
tau = fid.createVariable('tau', 'f4', 'time')
sensible = fid.createVariable('shf', 'f4', 'time')
latent = fid.createVariable('lhf', 'f4', 'time')
monob = fid.createVariable('MO', 'f4', 'time')
cd = fid.createVariable('cd', 'f4', 'time')
cdn = fid.createVariable('cdn', 'f4', 'time')
ct = fid.createVariable('ct', 'f4', 'time')
ctn = fid.createVariable('ctn', 'f4', 'time')
cq = fid.createVariable('cq', 'f4', 'time')
cqn = fid.createVariable('cqn', 'f4', 'time')
tsrv = fid.createVariable('tsrv', 'f4', 'time')
tsr = fid.createVariable('tsr', 'f4', 'time')
qsr = fid.createVariable('qsr', 'f4', 'time')
usr = fid.createVariable('usr', 'f4', 'time')
psim = fid.createVariable('psim', 'f4', 'time')
psit = fid.createVariable('psit', 'f4', 'time')
psiq = fid.createVariable('psiq', 'f4', 'time')
u10n = fid.createVariable('u10n', 'f4', 'time')
t10n = fid.createVariable('t10n', 'f4', 'time')
tv10n = fid.createVariable('tv10n', 'f4', 'time')
q10n = fid.createVariable('q10n', 'f4', 'time')
zo = fid.createVariable('zo', 'f4', 'time')
zot = fid.createVariable('zot', 'f4', 'time')
zoq = fid.createVariable('zoq', 'f4', 'time')
urefs = fid.createVariable('uref', 'f4', 'time')
trefs = fid.createVariable('tref', 'f4', 'time')
qrefs = fid.createVariable('qref', 'f4', 'time')
itera = fid.createVariable('iter', 'i4', 'time')
dter = fid.createVariable('dter', 'f4', 'time')
dqer = fid.createVariable('dqer', 'f4', 'time')
qair = fid.createVariable('qair', 'f4', 'time')
qsea = fid.createVariable('qsea', 'f4', 'time')
Rl = fid.createVariable('Rl', 'f4', 'time')
Rs = fid.createVariable('Rs', 'f4', 'time')
Rnl = fid.createVariable('Rnl', 'f4', 'time')
longitude[:] = lon
latitude[:] = lat
Date[:] = date
tau[:] = res[0]
sensible[:] = res[1]
latent[:] = res[2]
monob[:] = res[3]
cd[:] = res[4]
cdn[:] = res[5]
ct[:] = res[6]
ctn[:] = res[7]
cq[:] = res[8]
cqn[:] = res[9]
tsrv[:] = res[10]
tsr[:] = res[11]
qsr[:] = res[12]
usr[:] = res[13]
psim[:] = res[14]
psit[:] = res[15]
psiq[:] = res[16]
u10n[:] = res[17]
t10n[:] = res[18]
tv10n[:] = res[19]
q10n[:] = res[20]
zo[:] = res[21]
zot[:] = res[22]
zoq[:] = res[23]
urefs[:] = res[24]
trefs[:] = res[25]
qrefs[:] = res[26]
itera[:] = res[27]
dter[:] = res[28]
dqer[:] = res[29]
qair[:] = res[30]
qsea[:] = res[31]
Rl = res[32]
Rs = res[33]
Rnl = res[34]
longitude.long_name = 'Longitude'
longitude.units = 'degrees East'
latitude.long_name = 'Latitude'
latitude.units = 'degrees North'
Date.long_name = "calendar date"
Date.units = "YYYYMMDD UTC"
tau.long_name = 'Wind stress'
tau.units = 'N/m^2'
sensible.long_name = 'Sensible heat fluxe'
sensible.units = 'W/m^2'
latent.long_name = 'Latent heat flux'
latent.units = 'W/m^2'
monob.long_name = 'Monin-Obukhov length'
monob.units = 'm'
cd.long_name = 'Drag coefficient'
cd.units = ''
cdn.long_name = 'Neutral Drag coefficient'
cdn.units = ''
ct.long_name = 'Heat exchange coefficient'
ct.units = ''
ctn.long_name = 'Neutral Heat exchange coefficient'
ctn.units = ''
cq.long_name = 'Moisture exchange coefficient'
cq.units = ''
cqn.long_name = 'Neutral Moisture exchange coefficient'
cqn.units = ''
tsrv.long_name = 'star virtual temperature'
tsrv.units = 'degrees Celsius'
tsr.long_name = 'star temperature'
tsr.units = 'degrees Celsius'
qsr.long_name = 'star specific humidity'
qsr.units = 'gr/kgr'
usr.long_name = 'friction velocity'
usr.units = 'm/s'
psim.long_name = 'Momentum stability function'
psit.long_name = 'Heat stability function'
u10n.long_name = '10m neutral wind speed'
u10n.units = 'm/s'
t10n.long_name = '10m neutral temperature'
t10n.units = 'degrees Celsius'
tv10n.long_name = '10m neutral virtual temperature'
tv10n.units = 'degrees Celsius'
q10n.long_name = '10m neutral specific humidity'
q10n.units = 'gr/kgr'
zo.long_name = 'momentum roughness length'
zo.units = 'm'
zot.long_name = 'temperature roughness length'
zot.units = 'm'
zoq.long_name = 'moisture roughness length'
zoq.units = 'm'
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 = 'gr/kgr'
qair.long_name = 'specific humidity of air'
qair.units = 'gr/kgr'
qsea.long_name = 'specific humidity over water'
qsea.units = 'gr/kgr'
itera.long_name = 'number of iterations'
fid.close()
#%% delete variables
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 t, rh, date, p, sw, spd, hin
elif (inF == 'era5_r360x180.nc'):
#%% load era5_r360x180.nc
fid = nc.Dataset(inF)
lon = np.array(fid.variables["lon"])
lat = np.array(fid.variables["lat"])
T = np.array(fid.variables["t2m"])
tim = np.array(fid.variables["time"])
Td = np.array(fid.variables["d2m"])
sst = np.array(fid.variables["sst"])
sst = np.where(sst < -100, np.nan, sst)
p = np.array(fid.variables["msl"])/100 # to set hPa
lw = np.array(fid.variables["strd"])/60/60
sw = np.array(fid.variables["ssrd"])/60/60
u = np.array(fid.variables["u10"])
v = np.array(fid.variables["v10"])
lsm = np.array(fid.variables["lsm"])
fid.close()
spd = np.sqrt(np.power(u, 2)+np.power(v, 2))
del u, v, fid
lsm = np.where(lsm > 0, np.nan, 1) # reverse 0 on land 1 over ocean
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))
# reshape input and run code
for x in range(len(tim)):
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,
hum=['Td', Td.reshape(len(tim), len(lon)*len(lat))[x, :]],
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, qmeth='WMO',
meth=meth, n=30, L="ERA5")
res[x, :, :] = a.T
del a
#%% save NetCDF4
fid = nc.Dataset(outF,'w', format='NETCDF4')
fid.createDimension('lon', len(lon))
fid.createDimension('lat', len(lat))
fid.createDimension('time', None)
longitude = fid.createVariable('lon', 'f4', 'lon')
latitude = fid.createVariable('lat', 'f4', 'lat')
Date = fid.createVariable('Date', 'i4', 'time')
tau = fid.createVariable('tau', 'f4', ('time','lat','lon'))
sensible = fid.createVariable('shf', 'f4', ('time','lat','lon'))
latent = fid.createVariable('lhf', 'f4', ('time','lat','lon'))
monob = fid.createVariable('MO', 'f4', ('time','lat','lon'))
cd = fid.createVariable('cd', 'f4', ('time','lat','lon'))
cdn = fid.createVariable('cdn', 'f4', ('time','lat','lon'))
ct = fid.createVariable('ct', 'f4', ('time','lat','lon'))
ctn = fid.createVariable('ctn', 'f4', ('time','lat','lon'))
cq = fid.createVariable('cq', 'f4', ('time','lat','lon'))
cqn = fid.createVariable('cqn', 'f4', ('time','lat','lon'))
tsrv = fid.createVariable('tsrv', 'f4', ('time','lat','lon'))
tsr = fid.createVariable('tsr', 'f4', ('time','lat','lon'))
qsr = fid.createVariable('qsr', 'f4', ('time','lat','lon'))
usr = fid.createVariable('usr', 'f4', ('time','lat','lon'))
psim = fid.createVariable('psim', 'f4', ('time','lat','lon'))
psit = fid.createVariable('psit', 'f4', ('time','lat','lon'))
psiq = fid.createVariable('psiq', 'f4', ('time','lat','lon'))
u10n = fid.createVariable('u10n', 'f4', ('time','lat','lon'))
t10n = fid.createVariable('t10n', 'f4', ('time','lat','lon'))
tv10n = fid.createVariable('tv10n', 'f4', ('time','lat','lon'))
q10n = fid.createVariable('q10n', 'f4', ('time','lat','lon'))
zo = fid.createVariable('zo', 'f4', ('time','lat','lon'))
zot = fid.createVariable('zot', 'f4', ('time','lat','lon'))
zoq = fid.createVariable('zoq', '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'))
itera = fid.createVariable('iter', 'i4', ('time','lat','lon'))
dter = fid.createVariable('dter', 'f4', ('time','lat','lon'))
dqer = fid.createVariable('dqer', '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'))
Rs = fid.createVariable('Rs', 'f4', ('time','lat','lon'))
Rnl = fid.createVariable('Rnl', 'f4', ('time','lat','lon'))
longitude[:] = lon
latitude[:] = lat
Date[:] = tim
tau[:] = res[:, :, 0].reshape((len(tim), len(lat), len(lon)))*lsm
sensible[:] = res[:, :, 1].reshape((len(tim), len(lat), len(lon)))*lsm
latent[:] = res[:, :, 2].reshape((len(tim), len(lat), len(lon)))*lsm
monob[:] = res[:, :, 3].reshape((len(tim), len(lat), len(lon)))*lsm
cd[:] = res[:, :, 4].reshape((len(tim), len(lat), len(lon)))*lsm
cdn[:] = res[:, :, 5].reshape((len(tim), len(lat), len(lon)))*lsm
ct[:] = res[:, :, 6].reshape((len(tim), len(lat), len(lon)))*lsm
ctn[:] = res[:, :, 7].reshape((len(tim), len(lat), len(lon)))*lsm
cq[:] = res[:, :, 8].reshape((len(tim), len(lat), len(lon)))*lsm
cqn[:] = res[:, :, 9].reshape((len(tim), len(lat), len(lon)))*lsm
tsrv[:] = res[:, :, 10].reshape((len(tim), len(lat), len(lon)))*lsm
tsr[:] = res[:, :, 11].reshape((len(tim), len(lat), len(lon)))*lsm
qsr[:] = res[:, :, 12].reshape((len(tim), len(lat), len(lon)))*lsm
usr[:] = res[:, :, 13].reshape((len(tim), len(lat), len(lon)))*lsm
psim[:] = res[:, :, 14].reshape((len(tim), len(lat), len(lon)))*lsm
psit[:] = res[:, :, 15].reshape((len(tim), len(lat), len(lon)))*lsm
psiq[:] = res[:, :, 16].reshape((len(tim), len(lat), len(lon)))*lsm
u10n[:] = res[:, :, 17].reshape((len(tim), len(lat), len(lon)))*lsm
t10n[:] = res[:, :, 18].reshape((len(tim), len(lat), len(lon)))*lsm
tv10n[:] = res[:, :, 19].reshape((len(tim), len(lat), len(lon)))*lsm
q10n[:] = res[:, :, 20].reshape((len(tim), len(lat), len(lon)))*lsm
zo[:] = res[:, :, 21].reshape((len(tim), len(lat), len(lon)))*lsm
zot[:] = res[:, :, 22].reshape((len(tim), len(lat), len(lon)))*lsm
zoq[:] = res[:, :, 23].reshape((len(tim), len(lat), len(lon)))*lsm
urefs[:] = res[:, :, 24].reshape((len(tim), len(lat), len(lon)))*lsm
trefs[:] = res[:, :, 25].reshape((len(tim), len(lat), len(lon)))*lsm
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)))
longitude.long_name = 'Longitude'
longitude.units = 'degrees East'
latitude.long_name = 'Latitude'
latitude.units = 'degrees North'
Date.long_name = "calendar date"
Date.units = "YYYYMMDD UTC"
tau.long_name = 'Wind stress'
tau.units = 'N/m^2'
sensible.long_name = 'Sensible heat fluxe'
sensible.units = 'W/m^2'
latent.long_name = 'Latent heat flux'
latent.units = 'W/m^2'
monob.long_name = 'Monin-Obukhov length'
monob.units = 'm'
cd.long_name = 'Drag coefficient'
cd.units = ''
cdn.long_name = 'Neutral Drag coefficient'
cdn.units = ''
ct.long_name = 'Heat exchange coefficient'
ct.units = ''
ctn.long_name = 'Neutral Heat exchange coefficient'
ctn.units = ''
cq.long_name = 'Moisture exchange coefficient'
cq.units = ''
cqn.long_name = 'Neutral Moisture exchange coefficient'
cqn.units = ''
tsrv.long_name = 'star virtual temperature'
tsrv.units = 'degrees Celsius'
tsr.long_name = 'star temperature'
tsr.units = 'degrees Celsius'
qsr.long_name = 'star specific humidity'
qsr.units = 'gr/kgr'
usr.long_name = 'friction velocity'
usr.units = 'm/s'
psim.long_name = 'Momentum stability function'
psit.long_name = 'Heat stability function'
u10n.long_name = '10m neutral wind speed'
u10n.units = 'm/s'
t10n.long_name = '10m neutral temperature'
t10n.units = 'degrees Celsius'
tv10n.long_name = '10m neutral virtual temperature'
tv10n.units = 'degrees Celsius'
q10n.long_name = '10m neutral specific humidity'
q10n.units = 'gr/kgr'
zo.long_name = 'momentum roughness length'
zo.units = 'm'
zot.long_name = 'temperature roughness length'
zot.units = 'm'
zoq.long_name = 'moisture roughness length'
zoq.units = 'm'
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 = 'gr/kgr'
qair.long_name = 'specific humidity of air'
qair.units = 'gr/kgr'
qsea.long_name = 'specific humidity over water'
qsea.units = 'gr/kgr'
itera.long_name = 'number of iterations'
fid.close()
#%% delete variables
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 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")
gustIn = input("Give gustiness option (to use default press enter): \n")
if (gustIn == ''):
gustIn = None
else:
gustIn = np.asarray(eval(gustIn), dtype=float)
cskinIn = input("Give cool skin option (to use default press enter): \n")
if (cskinIn == ''):
cskinIn = None
else:
cskinIn = int(cskinIn)
tolIn = input("Give tolerance option (to use default press enter): \n")
if (tolIn == ''):
tolIn = None
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]
outF = input("Give path and output file name: \n")
if (outF == ''):
outF = inF[:-3]+"_"+meth+".nc"
else:
outF = outF
print("\n run_ASFC.py, started for method "+meth)
res, lon, lat = run_ASFC(inF, outF, gustIn, cskinIn, tolIn, meth)
print("run_ASFC.py took ", np.round((time.perf_counter()-start_time)/60, 2),
"minutes to run")
#%% generate flux plots
if (inF == 'era5_r360x180.nc'):
cm = plt.cm.get_cmap('RdYlBu')
ttl = ["tau (Nm$^{-2}$)", "shf (Wm$^{-2}$)", "lhf (Wm$^{-2}$)"]
for i in range(3):
plt.figure()
plt.contourf(lon, lat,
np.nanmean(res[:, :, i], axis=0).reshape(len(lat),
len(lon)),
100, cmap=cm)
plt.colorbar()
plt.tight_layout()
plt.xlabel("Longitude")
plt.ylabel("Latitude")
plt.title(meth+', '+ttl[i])
plt.savefig('./'+ttl[i][:3]+'_'+meth+'.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')
#%% generate txt file with statistic
if ((cskinIn == None) and (meth == "S80" or meth == "S88" or meth == "LP82"
or meth == "YT96" or meth == "UA" or
meth == "LY04")):
cskinIn = 0
elif ((cskinIn == None) and (meth == "C30" or meth == "C35" or meth == "C40"
or meth == "ERA5" 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")):
gustIn = [1, 1, 1000]
elif np.all(gustIn == None):
gustIn = [1, 1.2, 800]
elif ((np.size(gustIn) < 3) and (gustIn == 0)):
gust = [0, 0, 0]
if (tolIn == None):
tolIn = ['flux', 0.01, 1, 1]
print("Input summary", file=open('./stats.txt', 'a'))
print('input file name: {}, \n method: {}, \n gustiness: {}, \n cskin: {},'
' \n tolerance: {}'.format(inF, meth, gustIn, cskinIn, tolIn),
file=open('./stats.txt', 'a'))
ttl = np.asarray(["tau ", "shf ", "lhf ", "L ", "cd ", "cdn ",
"ct ", "ctn ", "cq ", "cqn ", "tsrv ", "tsr ",
"qsr ", "usr ", "psim ", "psit ", "psiq ", "u10n ",
"t10n ", "tv10n", "q10n ", "zo ", "zot ", "zoq ",
"urefs", "trefs", "qrefs", "itera", "dter ", "dqer ",
"qair ", "qsea ", "Rl ", "Rs ", "Rnl "])
header = ["var", "mean", "median", "min", "max", "5%", "95%"]
n = np.shape(res)
stats = np.copy(ttl)
if (inF == 'era5_r360x180.nc'):
stats = np.c_[stats, np.nanmean(res.reshape(n[0]*n[1], n[2]), axis=0)]
stats = np.c_[stats, np.nanmedian(res.reshape(n[0]*n[1], n[2]), axis=0)]
stats = np.c_[stats, np.nanmin(res.reshape(n[0]*n[1], n[2]), axis=0)]
stats = np.c_[stats, np.nanmax(res.reshape(n[0]*n[1], n[2]), axis=0)]
stats = np.c_[stats, np.nanpercentile(res.reshape(n[0]*n[1], n[2]), 5,
axis=0)]
stats = np.c_[stats, np.nanpercentile(res.reshape(n[0]*n[1], n[2]), 95,
axis=0)]
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'))
elif (inF == "data_all.nc"):
stats = np.c_[stats, np.nanmean(res, axis=1)]
stats = np.c_[stats, np.nanmedian(res, axis=1)]
stats = np.c_[stats, np.nanmin(res, axis=1)]
stats = np.c_[stats, np.nanmax(res, axis=1)]
stats = np.c_[stats, np.nanpercentile(res, 5, axis=1)]
stats = np.c_[stats, np.nanpercentile(res, 95, axis=1)]
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'))
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