References:
-----------
* Medlyn et al. 2002, PCE, 25, 1167-1179.
"""
return k25 * np.exp((Ea * (Tk - 298.15)) / (298.15 * c.RGAS * Tk))
if __name__ == "__main__":
from get_days_met_forcing import get_met_data
#
## Met data ...
#
doy = 180.
(par, tair, vpd) = get_met_data(p.lat, p.lon, doy)
#par = np.mean(par.reshape(-1, 2), axis=1)
#par *= 1800.0/par.max() #* c.SEC_TO_HR
#tair = np.mean(tair.reshape(-1, 2), axis=1)
#tair = np.ones(len(par)) * 25.
# convert atmospheric CO2 from umol mol-1 --> Pa
co2 = 400.0 * p.patm * c.CO2_CONV
# Ratio of intercellular to ambient partial pressure of CO2
lambdax = p.lambda_max
# Convert Vcmax mol m-2 s-1
vm = 60. * c.UMOL_TO_MOL
def main():
lat = -23.575001
lon = 152.524994
doy = 180.0
#
## Met data ...
#
(par, tair, vpd) = get_met_data(lat, lon, doy)
wind = 2.5
pressure = 101325.0
Ca = 400.0
lat = 61.8474
lon = 24.2948
fpath = "/Users/mdekauwe/Downloads/"
fname = "Hyytiala_met_and_plant_data_drought_2003.csv"
fn = os.path.join(fpath, fname)
df = pd.read_csv(fn, skiprows=range(1, 2))
dox = int(doy) * 48
par = df.PPFD.iloc[dox:dox + 48].values
tair = df.Tair.iloc[dox:dox + 48].values
vpd = df.VPD.iloc[dox:dox + 48].values
wind = 2.5
pressure = 101325.0
Ca = 400.0
LAI = df.LAI[dox]
#
## Parameters
#
g0 = 1E-09
g1 = df.g1[0]
D0 = 1.5 # kpa
Vcmax25 = df.Vmax25[0]
#g0 = 0.001
#g1 = 2.0
#D0 = 1.5 # kpa
#Vcmax25 = 60.0
Jmax25 = Vcmax25 * 1.67
Rd25 = 2.0
Eaj = 30000.0
Eav = 60000.0
deltaSj = 650.0
deltaSv = 650.0
Hdv = 200000.0
Hdj = 200000.0
Q10 = 2.0
gamma = 0.0
leaf_width = 0.02
LAI = 1.5
# Cambell & Norman, 11.5, pg 178
# The solar absorptivities of leaves (-0.5) from Table 11.4 (Gates, 1980)
# with canopies (~0.8) from Table 11.2 reveals a surprising difference.
# The higher absorptivityof canopies arises because of multiple reflections
# among leaves in a canopy and depends on the architecture of the canopy.
SW_abs = 0.8 # use canopy absorptance of solar radiation
##
### Run Big-leaf
##
B = BigLeaf(g0,
g1,
D0,
gamma,
Vcmax25,
Jmax25,
Rd25,
Eaj,
Eav,
deltaSj,
deltaSv,
Hdv,
Hdj,
Q10,
leaf_width,
SW_abs,
gs_model="medlyn")
An_bl = np.zeros(48)
gsw_bl = np.zeros(48)
et_bl = np.zeros(48)
tcan_bl = np.zeros(48)
hod = 0
for i in range(len(par)):
(An_bl[i], gsw_bl[i], et_bl[i],
tcan_bl[i]) = B.main(tair[i], par[i], vpd[i], wind, pressure, Ca, doy,
hod, lat, lon, LAI)
hod += 1
##
### Run 2-leaf
##
T = TwoLeaf(g0,
g1,
D0,
gamma,
Vcmax25,
Jmax25,
Rd25,
Eaj,
Eav,
deltaSj,
deltaSv,
Hdv,
Hdj,
Q10,
leaf_width,
SW_abs,
gs_model="medlyn")
An_tl = np.zeros(48)
gsw_tl = np.zeros(48)
et_tl = np.zeros(48)
tcan_tl = np.zeros(48)
hod = 0
for i in range(len(par)):
(An_tl[i], gsw_tl[i], et_tl[i],
tcan_tl[i]) = T.main(tair[i], par[i], vpd[i], wind, pressure, Ca, doy,
hod, lat, lon, LAI)
hod += 1
fig = plt.figure(figsize=(16, 4))
fig.subplots_adjust(hspace=0.1)
fig.subplots_adjust(wspace=0.2)
plt.rcParams['text.usetex'] = False
plt.rcParams['font.family'] = "sans-serif"
plt.rcParams['font.sans-serif'] = "Helvetica"
plt.rcParams['axes.labelsize'] = 14
plt.rcParams['font.size'] = 14
plt.rcParams['legend.fontsize'] = 10
plt.rcParams['xtick.labelsize'] = 14
plt.rcParams['ytick.labelsize'] = 14
almost_black = '#262626'
# change the tick colors also to the almost black
plt.rcParams['ytick.color'] = almost_black
plt.rcParams['xtick.color'] = almost_black
# change the text colors also to the almost black
plt.rcParams['text.color'] = almost_black
# Change the default axis colors from black to a slightly lighter black,
# and a little thinner (0.5 instead of 1)
plt.rcParams['axes.edgecolor'] = almost_black
plt.rcParams['axes.labelcolor'] = almost_black
ax1 = fig.add_subplot(131)
ax2 = fig.add_subplot(132)
ax3 = fig.add_subplot(133)
ax1.plot(np.arange(48) / 2., An_bl, label="Big leaf")
ax1.plot(np.arange(48) / 2., An_tl, label="Two leaf")
ax1.legend(numpoints=1, loc="best")
ax1.set_ylabel("$A_{\mathrm{n}}$ ($\mathrm{\mu}$mol m$^{-2}$ s$^{-1}$)")
ax2.plot(np.arange(48) / 2., et_bl * c.MOL_TO_MMOL, label="Big leaf")
ax2.plot(np.arange(48) / 2., et_tl * c.MOL_TO_MMOL, label="Two leaf")
ax2.set_ylabel("E (mmol m$^{-2}$ s$^{-1}$)")
ax2.set_xlabel("Hour of day")
ax3.plot(np.arange(48) / 2., tcan_bl, label="Tcanopy$_{1leaf}$")
ax3.plot(np.arange(48) / 2., tcan_tl, label="Tcanopy$_{2leaf}$")
ax3.plot(np.arange(48) / 2., tair, label="Tair")
ax3.set_ylabel("Temperature (deg C)")
ax3.legend(numpoints=1, loc="best")
ax1.locator_params(nbins=6, axis="y")
ax2.locator_params(nbins=6, axis="y")
plt.show()
fig.savefig("/Users/%s/Desktop/A_E_Tcan.pdf" % (os.getlogin()),
bbox_inches='tight',
pad_inches=0.1)
def main():
doy = 180.
#
## Met data ...
#
(par, tair, vpd) = get_met_data(p.lat, p.lon, doy)
# more realistic VPD
rh = 40.
esat = calc_esat(tair)
ea = rh / 100. * esat
vpd = (esat - ea) * c.PA_2_KPA
vpd = np.where(vpd < 0.05, 0.05, vpd)
#
## Fixed met stuff
#
wind = 2.5
pressure = 101325.0
Ca = 400.0
LAI = p.LAI
##
### Run Big-leaf
##
B = BigLeaf(p, gs_model="medlyn")
An_bl = np.zeros(48)
gsw_bl = np.zeros(48)
et_bl = np.zeros(48)
tcan_bl = np.zeros(48)
for i in range(len(par)):
hod = float(i) / 2. + 1800. / 3600. / 2.
(An, gsw, et, Tcan) = B.main(p, tair[i], par[i], vpd[i], wind,
pressure, Ca, doy, hod, LAI)
An_bl[i] = An
et_bl[i] = et
tcan_bl[i] = Tcan
##
### Run 2-leaf
##
T = TwoLeaf(p, gs_model="medlyn")
An_tl = np.zeros(48)
et_tl = np.zeros(48)
tcan_tl = np.zeros(48)
hod = 0
for i in range(len(par)):
(An, et, Tcan, apar, lai_leaf) = T.main(p, tair[i], par[i], vpd[i],
wind, pressure, Ca, doy,
hod / 2., LAI)
sun_frac = lai_leaf[c.SUNLIT] / np.sum(lai_leaf)
sha_frac = lai_leaf[c.SHADED] / np.sum(lai_leaf)
An_tl[i] = np.sum(An)
et_tl[i] = np.sum(et)
tcan_tl[i] = (Tcan[c.SUNLIT] * sun_frac) + (Tcan[c.SHADED] * sha_frac)
hod += 1
fig = plt.figure(figsize=(16, 4))
fig.subplots_adjust(hspace=0.1)
fig.subplots_adjust(wspace=0.2)
plt.rcParams['text.usetex'] = False
plt.rcParams['font.family'] = "sans-serif"
plt.rcParams['font.sans-serif'] = "Helvetica"
plt.rcParams['axes.labelsize'] = 14
plt.rcParams['font.size'] = 14
plt.rcParams['legend.fontsize'] = 10
plt.rcParams['xtick.labelsize'] = 14
plt.rcParams['ytick.labelsize'] = 14
almost_black = '#262626'
# change the tick colors also to the almost black
plt.rcParams['ytick.color'] = almost_black
plt.rcParams['xtick.color'] = almost_black
# change the text colors also to the almost black
plt.rcParams['text.color'] = almost_black
# Change the default axis colors from black to a slightly lighter black,
# and a little thinner (0.5 instead of 1)
plt.rcParams['axes.edgecolor'] = almost_black
plt.rcParams['axes.labelcolor'] = almost_black
ax1 = fig.add_subplot(131)
ax2 = fig.add_subplot(132)
ax3 = fig.add_subplot(133)
ax1.plot(np.arange(48) / 2., An_bl, label="Big leaf")
ax1.plot(np.arange(48) / 2., An_tl, label="Two leaf")
ax1.legend(numpoints=1, loc="best")
ax1.set_ylabel("$A_{\mathrm{n}}$ ($\mathrm{\mu}$mol m$^{-2}$ s$^{-1}$)")
ax2.plot(np.arange(48) / 2., et_bl * c.MOL_TO_MMOL, label="Big leaf")
ax2.plot(np.arange(48) / 2., et_tl * c.MOL_TO_MMOL, label="Two leaf")
ax2.set_ylabel("E (mmol m$^{-2}$ s$^{-1}$)")
ax2.set_xlabel("Hour of day")
ax3.plot(np.arange(48) / 2., tcan_bl, label="Tcanopy$_{1leaf}$")
ax3.plot(np.arange(48) / 2., tcan_tl, label="Tcanopy$_{2leaf}$")
ax3.plot(np.arange(48) / 2., tair, label="Tair")
ax3.set_ylabel("Temperature (deg C)")
ax3.legend(numpoints=1, loc="best")
ax1.locator_params(nbins=6, axis="y")
ax2.locator_params(nbins=6, axis="y")
plt.show()
fig.savefig("/Users/%s/Desktop/A_E_Tcan.pdf" % (os.getlogin()),
bbox_inches='tight',
pad_inches=0.1)
#scalex[c.SHADED] = lai * (1.0 - exp(-kn)) / kn - scalex[c.SUNLIT]
return scalex
if __name__ == "__main__":
from get_days_met_forcing import get_met_data
lat = -23.575001
lon = 152.524994
doy = 180.0
#
## Met data ...
#
(par, tair, vpd) = get_met_data(lat, lon, doy)
wind = 2.5
pressure = 101325.0
Ca = 400.0
#
## Parameters
#
g0 = 0.001
g1 = 4.0
D0 = 1.5 # kpa
Vcmax25 = 60.0
Jmax25 = Vcmax25 * 1.67
Rd25 = 2.0
Eaj = 30000.0
Eav = 60000.0
def main():
lat = -23.575001
lon = 152.524994
doy = 180.0
#
## Met data ...
#
(par, tair, vpd) = get_met_data(lat, lon, doy)
wind = 2.5
pressure = 101325.0
Ca = 400.0
# more realistic VPD
rh = 40.
esat = calc_esat(tair)
ea = rh / 100. * esat
vpd = (esat - ea) * c.PA_2_KPA
vpd = np.where(vpd < 0.05, 0.05, vpd)
#plt.plot(vpd)
#plt.show()
#sys.exit()
## Parameters
#
g0 = 0.001
g1 = 1.5635 # Puechabon
D0 = 1.5 # kpa
Vcmax25 = 60.0
Jmax25 = Vcmax25 * 1.67
Rd25 = 2.0
Eaj = 30000.0
Eav = 60000.0
deltaSj = 650.0
deltaSv = 650.0
Hdv = 200000.0
Hdj = 200000.0
Q10 = 2.0
gamma = 0.0
leaf_width = 0.02
LAI = 3.
# Cambell & Norman, 11.5, pg 178
# The solar absorptivities of leaves (-0.5) from Table 11.4 (Gates, 1980)
# with canopies (~0.8) from Table 11.2 reveals a surprising difference.
# The higher absorptivityof canopies arises because of multiple reflections
# among leaves in a canopy and depends on the architecture of the canopy.
SW_abs = 0.8 # use canopy absorptance of solar radiation
##
### Run Big-leaf
##
B = BigLeaf(g0,
g1,
D0,
gamma,
Vcmax25,
Jmax25,
Rd25,
Eaj,
Eav,
deltaSj,
deltaSv,
Hdv,
Hdj,
Q10,
leaf_width,
SW_abs,
gs_model="medlyn")
An_bl = np.zeros(48)
gsw_bl = np.zeros(48)
et_bl = np.zeros(48)
tcan_bl = np.zeros(48)
hod = 0
for i in range(len(par)):
(An_bl[i], gsw_bl[i], et_bl[i],
tcan_bl[i]) = B.main(tair[i], par[i], vpd[i], wind, pressure, Ca, doy,
hod, lat, lon, LAI)
hod += 1
##
### Run 2-leaf
##
T = TwoLeaf(g0,
g1,
D0,
gamma,
Vcmax25,
Jmax25,
Rd25,
Eaj,
Eav,
deltaSj,
deltaSv,
Hdv,
Hdj,
Q10,
leaf_width,
SW_abs,
gs_model="medlyn")
An_tl = np.zeros(48)
gsw_tl = np.zeros(48)
et_tl = np.zeros(48)
tcan_tl = np.zeros(48)
hod = 0
for i in range(len(par)):
(An_tl[i], gsw_tl[i], et_tl[i],
tcan_tl[i]) = T.main(tair[i], par[i], vpd[i], wind, pressure, Ca, doy,
hod, lat, lon, LAI)
hod += 1
##
### Run 2-leaf opt
##
T = TwoLeafOpt(g0,
g1,
D0,
gamma,
Vcmax25,
Jmax25,
Rd25,
Eaj,
Eav,
deltaSj,
deltaSv,
Hdv,
Hdj,
Q10,
leaf_width,
SW_abs,
gs_model="medlyn")
An_tlo = np.zeros(48)
gsw_tlo = np.zeros(48)
et_tlo = np.zeros(48)
tcan_tlo = np.zeros(48)
hod = 0
for i in range(len(par)):
(An_tlo[i], gsw_tlo[i], et_tlo[i],
tcan_tlo[i]) = T.main(tair[i], par[i], vpd[i], wind, pressure, Ca,
doy, hod, lat, lon, LAI)
hod += 1
##
### Run 2-leaf Manon
##
Ao = np.zeros(48)
gso = np.zeros(48)
Eo = np.zeros(48)
Aob = np.zeros(48)
gsob = np.zeros(48)
Eob = np.zeros(48)
hod = 0
for i in range(len(par)):
cos_zenith = calculate_solar_geometry(doy, hod, lat, lon)
zenith_angle = np.rad2deg(np.arccos(cos_zenith))
elevation = 90.0 - zenith_angle
if elevation > 0.0 and par[i] > 50.0:
p = declared_params()
p.PPFD = par[i]
p.sw_rad_day = par[i] * c.PAR_2_SW
p.LAI = LAI
p.coszen = cos_zenith
p.VPD = vpd[i]
p.precip = 0
p.Tair = tair[i]
p.Vmax25 = Vcmax25
p.g1 = g1
p.CO2 = Ca / 1000 * 101.325
p.JV = 1.67
p.Rlref = Rd25
p.Ej = Eaj
p.Ev = Eav
p.deltaSv = deltaSv
p.deltaSj = deltaSj
p.max_leaf_width = leaf_width
p.gamstar25 = 4.33 # 42.75 / 101.25 umol m-2 s-1
p.Kc25 = 41.0264925 # 404.9 umol m-2 s-1
p.Ko25 = 28208.88 # 278.4 mmol mol-1
p.O2 = 21.27825 # 210 *1000. / 101.25 210 mmol mol-1
p.alpha = 0.3
p.albedo = 0.2
p.Egamstar = 37830.0
p.Ec = 79430.0
p.Eo = 36380.0
p.P50 = 2.02 # Puechabon
p.P88 = 4.17
p.kmax = 0.862457122856143
_, _, fscale2can = absorbed_radiation_2_leaves(p)
p = p.append(pd.Series([np.nansum(fscale2can)], index=['fscale']))
Eo[i], gso[i], Ao[i], __, __ = solve_std(p, p.fc, photo='Farquhar')
#"""
try:
fstom_opt_psi, Eo[i], gso[i], Ao[i], _, _ = profit_psi(
p, photo='Farquhar', res='med', case=2)
p = p.append(
pd.Series([fstom_opt_psi], index=['fstom_opt_psi']))
except (ValueError, AttributeError):
(Eo[i], gso[i], Ao[i]) = (0., 0., 0.)
#"""
hod += 1
fig = plt.figure(figsize=(16, 4))
fig.subplots_adjust(hspace=0.1)
fig.subplots_adjust(wspace=0.2)
plt.rcParams['text.usetex'] = False
plt.rcParams['font.family'] = "sans-serif"
plt.rcParams['font.sans-serif'] = "Helvetica"
plt.rcParams['axes.labelsize'] = 14
plt.rcParams['font.size'] = 14
plt.rcParams['legend.fontsize'] = 10
plt.rcParams['xtick.labelsize'] = 14
plt.rcParams['ytick.labelsize'] = 14
almost_black = '#262626'
# change the tick colors also to the almost black
plt.rcParams['ytick.color'] = almost_black
plt.rcParams['xtick.color'] = almost_black
# change the text colors also to the almost black
plt.rcParams['text.color'] = almost_black
# Change the default axis colors from black to a slightly lighter black,
# and a little thinner (0.5 instead of 1)
plt.rcParams['axes.edgecolor'] = almost_black
plt.rcParams['axes.labelcolor'] = almost_black
ax1 = fig.add_subplot(131)
ax2 = fig.add_subplot(132)
ax3 = fig.add_subplot(133)
#ax1.plot(np.arange(48)/2., An_bl, label="Big leaf")
ax1.plot(np.arange(48) / 2., An_tl, label="Two leaf")
ax1.plot(np.arange(48) / 2., An_tlo, label="Two leaf Opt")
ax1.plot(np.arange(48) / 2., Ao, label="Two leaf Manon")
ax1.legend(numpoints=1, loc="best")
ax1.set_ylabel("$A_{\mathrm{n}}$ ($\mathrm{\mu}$mol m$^{-2}$ s$^{-1}$)")
#ax2.plot(np.arange(48)/2., et_bl * c.MOL_TO_MMOL, label="Big leaf")
ax2.plot(np.arange(48) / 2., et_tl * c.MOL_TO_MMOL, label="Two leaf")
ax2.plot(np.arange(48) / 2., et_tlo * c.MOL_TO_MMOL, label="Two leaf opt")
ax2.plot(np.arange(48) / 2., Eo, label="Two leaf Manon")
ax2.set_ylabel("E (mmol m$^{-2}$ s$^{-1}$)")
ax2.set_xlabel("Hour of day")
#ax3.plot(np.arange(48)/2., tcan_bl, label="Tcanopy$_{1leaf}$")
ax3.plot(np.arange(48) / 2., tcan_tl, label="Tcanopy$_{2leaf}$")
ax3.plot(np.arange(48) / 2., tair, label="Tair")
ax3.set_ylabel("Temperature (deg C)")
ax3.legend(numpoints=1, loc="best")
ax1.locator_params(nbins=6, axis="y")
ax2.locator_params(nbins=6, axis="y")
plt.show()
fig.savefig("/Users/%s/Desktop/A_E_Tcan.pdf" % (os.getlogin()),
bbox_inches='tight',
pad_inches=0.1)