def data(request):
"""
Run parcel simulation and return opened netdcf file
"""
# copy options from chem_conditions
p_dict = copy.deepcopy(parcel_dict)
# modify options from chem_conditions
p_dict['outfreq'] = p_dict['z_max'] / p_dict['w'] / p_dict['dt'] / 4
p_dict['outfile'] = "test_mass.nc"
p_dict['chem_dsl'] = True
p_dict['out_bin'] = \
'{"wradii": {"rght": 1e-4, "left": 1e-10, "drwt": "wet", "lnli": "lin", "nbin": 500, "moms": [0, 3]}, \
"dradii": {"rght": 1e-4, "left": 1e-10, "drwt": "dry", "lnli": "lin", "nbin": 500, "moms": [0, 3]}}'
# run parcel model
parcel(**p_dict)
data = netcdf.netcdf_file(p_dict['outfile'], "r")
# remove all netcdf files after all tests
def removing_files():
subprocess.call(["rm", p_dict['outfile']])
request.addfinalizer(removing_files)
return data
def data(request):
# copy options from chem_conditions ...
p_dict = copy.deepcopy(parcel_dict)
# ... and modify them for the current test
p_dict['outfile'] = "test_chem_kreidenweis.nc"
p_dict['chem_dsl'] = True
p_dict['chem_dsc'] = True
p_dict['chem_rct'] = True
p_dict['sd_conc'] = 1025
p_dict['outfreq'] = int(p_dict['z_max'] / p_dict['dt'] / 100) * 4
p_dict['out_bin'] = p_dict['out_bin'][:-1] + \
', "chem" : {"rght": 1e-4, "left": 1e-10, "drwt": "wet", "lnli": "log", "nbin": 100, "moms": ["H"]},\
"chemd" : {"rght": 1e-6, "left": 1e-10, "drwt": "dry", "lnli": "log", "nbin": 100, "moms": ["S_VI", "H2O2_a", "O3_a"]},\
"radii" : {"rght": 1e-4, "left": 1e-10, "drwt": "wet", "lnli": "log", "nbin": 100, "moms": [3]},\
"specd" : {"rght": 1e-6, "left": 1e-10, "drwt": "dry", "lnli": "log", "nbin": 100, "moms": [0, 1, 3]}}'
pp.pprint(p_dict)
# run parcel
parcel(**p_dict)
#simulation results
data = netcdf.netcdf_file(p_dict['outfile'], "r")
# removing all netcdf files after all tests
def removing_files():
subprocess.call(["rm", p_dict['outfile']])
request.addfinalizer(removing_files)
return data
def data(request):
# copy options from chem_conditions
p_dict = copy.deepcopy(parcel_dict)
# modify options from chem_conditions
p_dict['outfile'] = "test_init_spectrum.nc"
p_dict['chem_dsl'] = True
p_dict['chem_dsc'] = True
p_dict['z_max'] = .05
p_dict['dt'] = .1
p_dict['w'] = .5
p_dict['outfreq'] = 1
p_dict['sd_conc'] = 1024 * 44
p_dict['out_bin'] = '{"drad": {"rght": 1e-6, "left": 1e-10, "drwt": "dry", "lnli": "log", "nbin": 26, "moms": [0,3]}}'
# run parcel
parcel(**p_dict)
# simulation results
data = netcdf.netcdf_file(p_dict['outfile'], "r")
# removing all netcdf files after all tests
def removing_files():
subprocess.call(["rm", p_dict['outfile']])
request.addfinalizer(removing_files)
return data
def test_chem_off():
outfile_on = "test_on.nc"
pc.parcel(outfile=outfile_on,
chem_dsl=True,
chem_dsc=False,
chem_rct=False,
SO2_g=200e-12,
O3_g=50e-9,
H2O2_g=500e-12,
CO2_g=360e-6,
NH3_g=100e-12,
HNO3_g=100e-12)
nc_on = nc.netcdf_file(outfile_on)
outfile_off = "test_off.nc"
pc.parcel(outfile=outfile_off,
chem_dsl=False,
chem_dsc=False,
chem_rct=False)
nc_off = nc.netcdf_file(outfile_off)
assert (nc_on.SO2_g > 0)
assert (nc_off.SO2_g == 0)
assert ("SO2_g" in nc_on.variables)
assert ("SO2_a" in nc_on.variables)
assert ("SO2_g" not in nc_off.variables)
assert ("SO2_a" not in nc_off.variables)
subprocess.call(["rm", outfile_on])
subprocess.call(["rm", outfile_off])
def data(request):
# copy options from chem_conditions
p_dict = copy.deepcopy(parcel_dict)
# modify options from chem_conditions
p_dict['outfile'] = "test_chem_closed_rct.nc"
p_dict['chem_dsl'] = True
p_dict['chem_dsc'] = True
p_dict['chem_rct'] = True
p_dict['sd_conc'] = 1
p_dict['out_bin'] = p_dict['out_bin'][:-1] + \
', "chem" : {"rght": 1e-4, "left": 1e-9, "drwt": "wet", "lnli": "log", "nbin": 1,\
"moms": ["SO2_a", "S_VI", "H", "CO2_a", "NH3_a", "HNO3_a", "O3_a", "H2O2_a"]}}'
# run parcel
parcel(**p_dict)
# simulation results
data = netcdf.netcdf_file(p_dict['outfile'], "r")
# removing all netcdf files after all tests
def removing_files():
subprocess.call(["rm", p_dict['outfile']])
request.addfinalizer(removing_files)
return data
def data(request):
# initial values
RH_init = .99999
T_init = 280.
p_init = 100000.
r_init = common.eps * RH_init * common.p_vs(T_init) / (p_init - RH_init * common.p_vs(T_init))
# lists to store RH_max and N at the end of the simulation from each test run
RH_list = []
N_list = []
for dt in Dt_list:
print "\nt time step", dt
outfile_nc = "timesteptest_dt=" + str(dt) + ".nc"
parcel(dt=dt, outfreq = int(100/dt), outfile = outfile_nc,\
w = 1., T_0 = T_init, p_0 = p_init, r_0 = r_init, z_max = 200, \
mean_r = 5e-8, gstdev = 1.5, n_tot = 1e9, sd_conc = 1000, \
out_bin = '{"radii": {"rght": 1, "moms": [0], "drwt": "wet", "nbin": 1, "lnli": "lin", "left": 1e-06}}'
)
f_out = netcdf.netcdf_file(outfile_nc, "r")
RH_max = f_out.RH_max
N_end = f_out.variables["radii_m0"][-1,0] # concentration of drops > 1e-6 m
RH_list.append((RH_max - 1)*100) # [%]
N_list.append(N_end / 1e6) # [1/mg]
data = {"RH" : RH_list, "N" : N_list, "dt" : Dt_list}
# removing all netcdf files after all tests
def removing_files():
for file in glob.glob("timesteptest_dt*"):
subprocess.call(["rm", file])
request.addfinalizer(removing_files)
return data
def main(dt_list = [1e-3, 1.5e-3, 2e-3, 3e-3, 4e-3, 8e-3, 1e-2, 2e-2, 4e-2, 8e-2, 1e-1, 2e-1, 4e-1, 8e-1, 1.]):
# initial values
z_max = 200.
w = 1.
RH_init = .99999
T_init = 280.
p_init = 100000.
r_init = common.eps * RH_init * common.p_vs(T_init) / (p_init - RH_init * common.p_vs(T_init))
# lists to store RH_max and N at the end of the simulation from each test run
RH_list = []
N_list = []
for dt in dt_list:
print("\nt time step", dt)
outfile_nc = "timesteptest_dt=" + str(dt) + ".nc"
parcel(dt=dt, outfreq = int(z_max/w/dt), outfile = outfile_nc,\
w = w, T_0 = T_init, p_0 = p_init, r_0 = r_init, z_max = z_max, \
mean_r = 5e-8, gstdev = 1.5, n_tot = 1e9, sd_conc = 1000, \
radii = 1e-6 * pow(10, -3 + np.arange(26) * .2)
)
f_out = netcdf.netcdf_file(outfile_nc, "r")
RH_max = f_out.RH_max
N_end = sum(f_out.variables["conc"][-1, -9:]) # concentration of drops > 1e-6 m
RH_list.append((RH_max - 1)*100) # [%]
N_list.append(N_end / 1e6) # [1/mg]
subprocess.call(["rm", outfile_nc])
data = {"RH" : RH_list, "N" : N_list, "dt" : dt_list}
timestep_plot(data)
def data(request):
# copy options from chem_conditions
p_dict = copy.deepcopy(parcel_dict)
# modify options from chem_conditions
p_dict['sd_conc'] = 1
p_dict['outfile'] = "test_chem_closed_dsc.nc"
p_dict['chem_dsl'] = True
p_dict['chem_dsc'] = True
p_dict['out_bin'] = p_dict['out_bin'][:-1] + \
', "radii" : {"rght": 1e-4, "left": 1e-9, "drwt": "wet", "lnli": "log", "nbin": 1, "moms": [3]}, \
"chem" : {"rght": 1e-4, "left": 1e-9, "drwt": "wet", "lnli": "log", "nbin": 1,\
"moms": ["O3_a", "H2O2_a", "H", "SO2_a", "S_VI", "CO2_a", "NH3_a", "HNO3_a"]}}'
pp.pprint(p_dict)
# run parcel
parcel(**p_dict)
# simulation results
data = netcdf.netcdf_file(p_dict['outfile'], "r")
# removing all netcdf files after all tests
def removing_files():
subprocess.call(["rm", p_dict['outfile']])
request.addfinalizer(removing_files)
return data
def main():
# copy options from chem_conditions ...
opts_dict = copy.deepcopy(parcel_dict)
# ... and modify them for the current test
opts_dict['outfile'] = "test_init_spectrum.nc"
opts_dict['chem_dsl'] = True
opts_dict['z_max'] = .05
opts_dict['dt'] = .1
opts_dict['w'] = .5
opts_dict['outfreq'] = 1
opts_dict['sd_conc'] = 1024 * 44
opts_dict['outfreq'] = 1
opts_dict[
'out_bin'] = '{"drad": {"rght": 1e-6, "left": 1e-10, "drwt": "dry", "lnli": "log", "nbin": 26, "moms": [0,3]}}'
# run parcel
parcel(**opts_dict)
# simulation results
data = netcdf.netcdf_file(opts_dict['outfile'], "r")
# doing plotting
plot_init_spectrum(data, outfolder="../outputs/")
# cleanup
subprocess.call(["rm", opts_dict['outfile']])
def data(request):
# copy options from chem_conditions
p_dict = copy.deepcopy(parcel_dict)
# modify options from chem_conditions
p_dict['outfile'] = "test_init_spectrum.nc"
p_dict['chem_dsl'] = True
p_dict['chem_dsc'] = True
p_dict['z_max'] = .05
p_dict['dt'] = .1
p_dict['w'] = .5
p_dict['outfreq'] = 1
p_dict['sd_conc'] = 1024 * 44
p_dict[
'out_bin'] = '{"drad": {"rght": 1e-6, "left": 1e-10, "drwt": "dry", "lnli": "log", "nbin": 26, "moms": [0,3]}}'
# run parcel
parcel(**p_dict)
# simulation results
data = netcdf.netcdf_file(p_dict['outfile'], "r")
# removing all netcdf files after all tests
def removing_files():
subprocess.call(["rm", p_dict['outfile']])
request.addfinalizer(removing_files)
return data
def data(request):
"""
Run parcel simulation and return opened netdcf file
"""
# copy options from chem_conditions
p_dict = copy.deepcopy(parcel_dict)
# modify options from chem_conditions
p_dict['outfreq'] = p_dict['z_max'] / p_dict['w'] / p_dict['dt'] / 4
p_dict['outfile'] = "test_mass.nc"
p_dict['chem_dsl'] = True
p_dict['out_bin'] = \
'{"wradii": {"rght": 1e-4, "left": 1e-10, "drwt": "wet", "lnli": "lin", "nbin": 500, "moms": [0, 3]}, \
"dradii": {"rght": 1e-4, "left": 1e-10, "drwt": "dry", "lnli": "lin", "nbin": 500, "moms": [0, 3]}}'
# run parcel model
parcel(**p_dict)
data = netcdf.netcdf_file(p_dict['outfile'], "r")
# remove all netcdf files after all tests
def removing_files():
subprocess.call(["rm", p_dict['outfile']])
request.addfinalizer(removing_files)
return data
def test_RH_gt1(tmpdir, kappa):
""" checking if RH at the end of simulation is close to 1
(i.e. cloud is created)
"""
str_f = str(tmpdir.join("test_pcl.nc"))
pc.parcel(outfile=str_f, outfreq=1, aerosol='{"ammonium_sulfate": {"kappa": ' + str(kappa) + ', "mean_r": [0.02e-6], "gstdev": [1.4], "n_tot": [60.0e6]}}')
f_out = netcdf.netcdf_file(str_f, "r")
assert f_out.variables["RH"][-1] >= .99
def data(request):
parcel(outfile="file_test.nc")
fnc = netcdf.netcdf_file("file_test.nc")
def removing_files():
fnc.close()
subprocess.call(["rm", "file_test.nc"])
request.addfinalizer(removing_files)
return fnc
def main(dt=1):
# running parcel model for different ways to solve for pressure ...
outfile = "thesis_plot.nc"
parcel(dt=dt, outfreq=10, outfile=outfile)
fnc = netcdf.netcdf_file(outfile)
thesis_profiles(fnc)
fnc.close()
subprocess.call(["rm", outfile])
def main(dt=1):
# running parcel model for different ways to solve for pressure ...
outfile = "onesim_plot.nc"
parcel(dt=dt, outfreq = 10, outfile=outfile)
fnc = netcdf.netcdf_file(outfile)
plot_profiles(fnc)
fnc.close()
subprocess.call(["rm", outfile])
def test_RH_gt1(tmpdir, kappa):
""" checking if RH at the end of simulation is close to 1
(i.e. cloud is created)
"""
str_f = str(tmpdir.join("test_pcl.nc"))
pc.parcel(outfile=str_f, outfreq=1, kappa=kappa)
f_out = netcdf.netcdf_file(str_f, "r")
assert f_out.variables["RH"][-1] >= .99
def main(dt=0.1):
# running parcel model for different ways to solve for pressure ...
fnc = {}
for pprof in pprof_list:
outfile = "test_" + pprof + ".nc"
parcel(dt=dt, outfreq=100, pprof=pprof, outfile=outfile)
fnc[pprof] = netcdf.netcdf_file(outfile)
plot_pressure_opt(fnc)
subprocess.call(["rm", outfile])
def test_smax(tmpdir, outfreq):
str_f = str(tmpdir.join("test_pcl.nc"))
print(str_f)
pc.parcel(outfile=str_f, outfreq=outfreq)
f_out = netcdf.netcdf_file(str_f, "r")
if outfreq == 1:
assert f_out.variables["RH"][:].max() == f_out.RH_max
else:
assert f_out.variables["RH"][:].max() <= f_out.RH_max
def main(dt=0.1):
# running parcel model for different ways to solve for pressure ...
fnc = {}
for pprof in pprof_list:
outfile = "test_" + pprof + ".nc"
parcel(dt=dt, outfreq = 100, pprof = pprof, outfile=outfile)
fnc[pprof] = netcdf.netcdf_file(outfile)
plot_pressure_opt(fnc)
subprocess.call(["rm", outfile])
def data(request):
parcel(outfile="file_test.nc")
fnc = netcdf.netcdf_file("file_test.nc")
def removing_files():
fnc.close()
subprocess.call(["rm", "file_test.nc"])
request.addfinalizer(removing_files)
return fnc
def main():
# running parcel
outfile = "test_spectrum.nc"
parcel(dt = .5, sd_conc = 1024, outfreq = 40, outfile=outfile,\
out_bin = ["wradii:1e-9/1e-4/26/log/wet/0", "dradii:1e-9/1e-6/26/log/dry/0"])
data = netcdf.netcdf_file(outfile, "r")
# doing plotting
plot_spectrum(data, outfolder="../outputs/")
# cleanup
subprocess.call(["rm", outfile])
def main():
# initial condition
RH_init = .95
T_init = 285.2
p_init = 95000.
r_init = fn.rh_to_rv(RH_init, T_init, p_init)
# calculate rhod for initial gas mixing ratio
rhod_init = fn.rhod_calc(T_init, p_init, r_init)
# initial condition for trace geses
SO2_g_init = fn.mole_frac_to_mix_ratio(200e-12, p_init, cm.M_SO2, T_init, rhod_init)
O3_g_init = fn.mole_frac_to_mix_ratio(50e-9, p_init, cm.M_O3, T_init, rhod_init)
H2O2_g_init = fn.mole_frac_to_mix_ratio(500e-12, p_init, cm.M_H2O2, T_init, rhod_init)
CO2_g_init = fn.mole_frac_to_mix_ratio(360e-6, p_init, cm.M_CO2, T_init, rhod_init)
NH3_g_init = fn.mole_frac_to_mix_ratio(100e-12, p_init, cm.M_NH3, T_init, rhod_init)
HNO3_g_init = fn.mole_frac_to_mix_ratio(100e-12, p_init, cm.M_HNO3, T_init, rhod_init)
# output
z_max = 20. #200.
dt = .05
outfreq = int(z_max / dt / 100)
w = 1.
sd_conc = 2048
# turn on chemistry
chem_dsl = True
chem_dsc = True
chem_rct = True
# define output for moments and chemistry
out_bin_chem = '{"plt_rw": {"rght": 1, "left": 0, "drwt": "wet", "lnli": "lin", "nbin": 1, "moms": [0, 1, 3]},\
"plt_rd": {"rght": 1, "left": 0, "drwt": "dry", "lnli": "lin", "nbin": 1, "moms": [0, 1, 3]},\
"plt_ch": {"rght": 1, "left": 0, "drwt": "dry", "lnli": "lin", "nbin": 1,\
"moms": ["O3_a", "H2O2_a", "H", "SO2_a", "S_VI", "CO2_a", "NH3_a", "HNO3_a"]}}'
out_bin = '{"plt_rw": {"rght": 1, "left": 0, "drwt": "wet", "lnli": "lin", "nbin": 1, "moms": [0, 1, 3]},\
"plt_rd": {"rght": 1, "left": 0, "drwt": "dry", "lnli": "lin", "nbin": 1, "moms": [0, 1, 3]}}'
# run parcel model
parcel(dt = dt, z_max = z_max, w = w, outfreq = outfreq,\
T_0 = T_init, p_0 = p_init, r_0 = r_init,\
SO2_g = SO2_g_init, O3_g = O3_g_init, H2O2_g = H2O2_g_init,\
CO2_g = CO2_g_init, NH3_g = NH3_g_init, HNO3_g = HNO3_g_init,\
outfile="test_plot_chem_closed.nc",\
sd_conc = sd_conc,\
chem_dsl = chem_dsl, chem_dsc = chem_dsc, chem_rct = chem_rct, \
out_bin = out_bin_chem)
data = netcdf.netcdf_file("test_plot_chem.nc", "r")
plot_chem(data, output_folder = "../outputs", output_title = "/test_plot_chem_")
netcdf.close()
subprocess.call(["rm", "test_plot_chem.nc"])
def data(request):
# initial condition
RH_init = .999999
T_init = 300.
p_init = 100000.
r_init = cm.eps * RH_init * cm.p_vs(T_init) / (p_init - RH_init * cm.p_vs(T_init))
# calculate rhod for gas init cond
th_0 = T_init * (cm.p_1000 / p_init)**(cm.R_d / cm.c_pd)
rhod_init = cm.rhod(p_init, th_0, r_init)
# init cond for trace gases
SO2_g_init = fn.mole_frac_to_mix_ratio(200e-12, p_init, cm.M_SO2, T_init, rhod_init)
O3_g_init = fn.mole_frac_to_mix_ratio(50e-9, p_init, cm.M_O3, T_init, rhod_init)
H2O2_g_init = fn.mole_frac_to_mix_ratio(500e-12, p_init, cm.M_H2O2, T_init, rhod_init)
CO2_g_init = fn.mole_frac_to_mix_ratio(360e-6, p_init, cm.M_CO2, T_init, rhod_init)
NH3_g_init = fn.mole_frac_to_mix_ratio(100e-12, p_init, cm.M_NH3, T_init, rhod_init)
HNO3_g_init = fn.mole_frac_to_mix_ratio(100e-12, p_init, cm.M_HNO3, T_init, rhod_init)
# aerosol size distribution
mean_r = .08e-6 / 2
gstdev = 2.
n_tot = 566.e6
# output
sd_conc = 1
outfreq = 50
z_max = 300.
outfile = "test_chem_henry.nc"
dt = 0.1
wait = 100
parcel(dt = dt, z_max = z_max, outfreq = outfreq, wait=wait,\
T_0 = T_init, p_0 = p_init, r_0 = r_init,\
SO2_g = SO2_g_init, O3_g = O3_g_init, H2O2_g = H2O2_g_init,\
CO2_g = CO2_g_init, NH3_g = NH3_g_init, HNO3_g = HNO3_g_init,\
outfile = outfile,\
chem_dsl = True, chem_dsc = True, chem_rct = False,\
aerosol = \
'{"test": {"kappa": 0.5, "mean_r": [' + str(mean_r) + '], "gstdev": [' + str(gstdev) + '], "n_tot": [' + str(n_tot) + ']}}',\
sd_conc = sd_conc,\
out_bin = \
'{"radii": {"rght": 1.0, "left": 0.0, "drwt": "wet", "lnli": "lin", "nbin": 1, "moms": [0, 3]},\
"chem" : {"rght": 1.0, "left": 0.0, "drwt": "wet", "lnli": "lin", "nbin": 1,\
"moms": ["O3_a", "H2O2_a", "SO2_a", "CO2_a", "NH3_a", "HNO3_a", "H"]}}')
data = netcdf.netcdf_file("test_chem_henry.nc", "r")
# removing all netcdf files after all tests
def removing_files():
subprocess.call(["rm", "test_chem_henry.nc"])
request.addfinalizer(removing_files)
return data
def data(request):
data = {}
data["dt"] = request.param
for pprof in Pprof_list:
filename = "profopttest_" + pprof + str(request.param) + ".nc"
parcel(dt=request.param, outfreq = 100, pprof = pprof, outfile=filename)
data[pprof] = netcdf.netcdf_file(filename)
# removing all netcdf files after all tests
def removing_files():
for file in glob.glob("profopttest_pprof*"):
subprocess.call(["rm", file])
request.addfinalizer(removing_files)
return data
def main():
RH_init = .99999
T_init = 300.
p_init = 100000.
r_init = cm.eps * RH_init * cm.p_vs(T_init) / (p_init -
RH_init * cm.p_vs(T_init))
# calculate rhod for initial gas mixing ratio
th_0 = T_init * (cm.p_1000 / p_init)**(cm.R_d / cm.c_pd)
rhod_init = cm.rhod(p_init, th_0, r_init)
SO2_g_init = fn.mole_frac_to_mix_ratio(200e-12, p_init, cm.M_SO2, T_init,
rhod_init)
O3_g_init = fn.mole_frac_to_mix_ratio(50e-9, p_init, cm.M_O3, T_init,
rhod_init)
H2O2_g_init = fn.mole_frac_to_mix_ratio(500e-12, p_init, cm.M_H2O2, T_init,
rhod_init)
CO2_g_init = fn.mole_frac_to_mix_ratio(360e-6, p_init, cm.M_CO2, T_init,
rhod_init)
NH3_g_init = fn.mole_frac_to_mix_ratio(100e-12, p_init, cm.M_NH3, T_init,
rhod_init)
HNO3_g_init = fn.mole_frac_to_mix_ratio(100e-12, p_init, cm.M_HNO3, T_init,
rhod_init)
outfreq = 50
z_max = 50.
outfile = "test_chem_henry.nc"
dt = 0.1
wait = 1000
sd_conc = 1
# run parcel run!
parcel(dt = dt, z_max = z_max, outfreq = outfreq, wait=wait,\
T_0 = T_init, p_0 = p_init, r_0 = r_init, sd_conc=sd_conc,\
SO2_g = SO2_g_init, O3_g = O3_g_init, H2O2_g = H2O2_g_init,\
CO2_g = CO2_g_init, NH3_g = NH3_g_init, HNO3_g = HNO3_g_init,\
outfile = outfile,\
chem_dsl = True, chem_dsc = False, chem_rct = False,\
out_bin = \
'{"radii": {"rght": 1, "left": 0, "drwt": "wet", "lnli": "lin", "nbin": 1, "moms": [0, 3]},\
"chem" : {"rght": 1, "left": 0, "drwt": "wet", "lnli": "lin", "nbin": 1,\
"moms": ["O3_a", "H2O2_a", "SO2_a", "CO2_a", "NH3_a", "HNO3_a", "H"]}}' )
data = netcdf.netcdf_file(outfile, "r")
#plot
plot_henry(data, output_folder="../outputs")
#cleanup
data.close()
subprocess.call(["rm", "test_chem_henry.nc"])
def data(request):
"""
run parcel simulations with different initial sd_conc
return data with values of sd_conc and initial dry mass of the aerosol
"""
# copy options from chem_conditions
p_dict = copy.deepcopy(parcel_dict)
# ... and modify them for the current test
p_dict['chem_dsl'] = True
p_dict['z_max'] = .05
p_dict['outfreq'] = 1
p_dict[
'out_bin'] = '{"drad": {"rght": 1e-6, "left": 1e-10, "drwt": "dry", "lnli": "log", "nbin": 26, "moms": [3]}}'
# lists to store sd_conc at the total dry mass at t=0 of each test run
out_sd_conc = []
out_m3_dry = []
for sd_conc in sd_conc_list:
print("sd_conc = ", sd_conc)
p_dict['outfile'] = "convergence_test_sd_conc=" + str(sd_conc) + ".nc"
p_dict['sd_conc'] = sd_conc
# run parcel simulation
parcel(**p_dict)
# read data
f_out = netcdf.netcdf_file(p_dict['outfile'], "r")
mom3_init = f_out.variables["drad_m3"][0, :]
rhod_init = f_out.variables["rhod"][0]
chem_rho = getattr(f_out, "chem_rho")
# initial dry mass of aerosol [kg/kg dry air]
ini = mom3_init.sum() * 4. / 3 * math.pi * chem_rho
out_sd_conc.append(sd_conc)
out_m3_dry.append(ini)
data = {"sd_conc": out_sd_conc, "dry_mass": out_m3_dry}
# removing all netcdf files after all tests
def removing_files():
for file in glob.glob("convergence_test_sd_conc*"):
subprocess.call(["rm", file])
request.addfinalizer(removing_files)
return data
def data(request):
data = {}
data["dt"] = request.param
for pprof in Pprof_list:
filename = "profopttest_" + pprof + str(request.param) + ".nc"
parcel(dt=request.param, outfreq=100, pprof=pprof, outfile=filename)
data[pprof] = netcdf.netcdf_file(filename)
# removing all netcdf files after all tests
def removing_files():
for file in glob.glob("profopttest_pprof*"):
subprocess.call(["rm", file])
request.addfinalizer(removing_files)
return data
def data(request):
"""
run parcel simulations with different initial sd_conc
return data with values of sd_conc and initial dry mass of the aerosol
"""
# copy options from chem_conditions
p_dict = copy.deepcopy(parcel_dict)
# ... and modify them for the current test
p_dict['chem_dsl'] = True
p_dict['z_max'] = .05
p_dict['outfreq'] = 1
p_dict['out_bin'] = '{"drad": {"rght": 1e-6, "left": 1e-10, "drwt": "dry", "lnli": "log", "nbin": 26, "moms": [3]}}'
# lists to store sd_conc at the total dry mass at t=0 of each test run
out_sd_conc = []
out_m3_dry = []
for sd_conc in sd_conc_list:
print "sd_conc = ", sd_conc
p_dict['outfile'] = "convergence_test_sd_conc=" + str(sd_conc) + ".nc"
p_dict['sd_conc'] = sd_conc
# run parcel simulation
parcel(**p_dict)
# read data
f_out = netcdf.netcdf_file(p_dict['outfile'], "r")
mom3_init = f_out.variables["drad_m3"][0,:]
rhod_init = f_out.variables["rhod"][0]
chem_rho = getattr(f_out, "chem_rho")
# initial dry mass of aerosol [kg/kg dry air]
ini = mom3_init.sum() * 4./3 * math.pi * chem_rho
out_sd_conc.append(sd_conc)
out_m3_dry.append(ini)
data = {"sd_conc" : out_sd_conc, "dry_mass" : out_m3_dry}
# removing all netcdf files after all tests
def removing_files():
for file in glob.glob("convergence_test_sd_conc*"):
subprocess.call(["rm", file])
request.addfinalizer(removing_files)
return data
def main():
outfile = "test_spectrum.nc"
out_bin = '{"wradii": {"rght": 1e-4, "left": 1e-9, "drwt": "wet", "lnli": "log", "nbin": 26, "moms": [0]},\
"dradii": {"rght": 1e-6, "left": 1e-9, "drwt": "dry", "lnli": "log", "nbin": 26, "moms": [0]}}'
# run parcel run!
parcel(dt = .5, sd_conc = 1024, outfreq = 40, outfile = outfile, out_bin = out_bin)
data = netcdf.netcdf_file(outfile, "r")
# plotting
plot_spectrum(data, outfolder="../outputs/")
# cleanup
subprocess.call(["rm", outfile])
def test_cmdline(tmpdir, arg):
# calling from Python
file = str(tmpdir.join("test.nc"))
pc.parcel(outfile=file, **arg)
# renaming the output file
subprocess.call(["mv", file, str(tmpdir.join("test_pyt.nc"))])
# calling via subprocess
# creating a list with all provided arguments
list_arg = ["python", "parcel.py", "--outfile="+file]
for key, value in arg.items():
list_arg.append("--" + key + "=" + str(value))
subprocess.check_call(list_arg)
# comparing if the output is the same
subprocess.check_call(["diff", file, str(tmpdir.join("test_pyt.nc"))])
def test_chem_closed():
"""
Checking if the total mass of SO_2, O_3 and H2O2 in the closed chemical system
with only dissocoation present remains constant
"""
#TODO - the same for dissociation
#TODO - think of a similar test for reactions
SO2_g_init = 200e-12
O3_g_init = 50e-9
H2O2_g_init = 500e-12
outfreq = 20
z_max = 200.
outfile = "test_chem_closed.nc"
dt = .01
# run parcel
parcel(dt = dt, z_max = z_max, outfreq = outfreq,\
SO2_g_0 = SO2_g_init, O3_g_0 = O3_g_init, H2O2_g_0 = H2O2_g_init,\
chem_sys = 'closed', outfile = outfile,\
chem_dsl = True, chem_dsc = False, chem_rct = False,\
out_bin = '{"chem": {"rght": 1, "moms": ["O3_a", "H2O2_a", "SO2_a"], "drwt": "wet", "nbin": 1, "lnli": "lin", "left": 0}}',)
f = netcdf.netcdf_file(outfile, "r")
Mass = [cm.M_SO2, cm.M_O3, cm.M_H2O2]
chem_list = ["SO2", "O3", "H2O2"]
eps = [4e-9, 4e-11, 2e-4]
#TODO why so big?
# convert aqueous phase within droplets to gase phase (mole fraction)
def aq_to_g(chem_aq, rhod, T, M, p):
return chem_aq * rhod * cm.R * T / M / p
for chem in chem_list :
ini = f.variables[chem+"_g"][0]
#final gas phase = current gas phase + mass dissolved into droplets
end = f.variables[chem+"_g"][-1] + \
aq_to_g(f.variables[chem+"_a"][-1], f.variables["rhod"][-1], f.variables["T"][-1],\
Mass[chem_list.index(chem)], f.variables["p"][-1])
assert np.isclose(end, ini, atol=0, rtol=eps[chem_list.index(chem)])
# cleanup
subprocess.call(["rm", outfile])
def test_cmdline(tmpdir, arg):
# calling from Python
file = str(tmpdir.join("test.nc"))
pc.parcel(outfile=file, **arg)
# renaming the output file
subprocess.call(["mv", file, str(tmpdir.join("test_pyt.nc"))])
# calling via subprocess
# creating a list with all provided arguments
list_arg = ["python", "parcel.py", "--outfile=" + file]
for key, value in arg.items():
list_arg.append("--" + key + "=" + str(value))
subprocess.check_call(list_arg)
# comparing if the output is the same
# this test might fail if libcloudph++ was compiled with -Ofast flag (should work with -O3)
subprocess.check_call(["diff", file, str(tmpdir.join("test_pyt.nc"))])
def main():
RH_init = .99999
T_init = 300.
p_init = 100000.
r_init = cm.eps * RH_init * cm.p_vs(T_init) / (p_init - RH_init * cm.p_vs(T_init))
# calculate rhod for initial gas mixing ratio
th_0 = T_init * (cm.p_1000 / p_init)**(cm.R_d / cm.c_pd)
rhod_init = cm.rhod(p_init, th_0, r_init)
SO2_g_init = fn.mole_frac_to_mix_ratio(200e-12, p_init, cm.M_SO2, T_init, rhod_init)
O3_g_init = fn.mole_frac_to_mix_ratio(50e-9, p_init, cm.M_O3, T_init, rhod_init)
H2O2_g_init = fn.mole_frac_to_mix_ratio(500e-12, p_init, cm.M_H2O2, T_init, rhod_init)
CO2_g_init = fn.mole_frac_to_mix_ratio(360e-6, p_init, cm.M_CO2, T_init, rhod_init)
NH3_g_init = fn.mole_frac_to_mix_ratio(100e-12, p_init, cm.M_NH3, T_init, rhod_init)
HNO3_g_init = fn.mole_frac_to_mix_ratio(100e-12, p_init, cm.M_HNO3, T_init, rhod_init)
outfreq = 50
z_max = 50.
outfile = "test_chem_henry.nc"
dt = 0.1
wait = 1000
sd_conc = 1
# run parcel run!
parcel(dt = dt, z_max = z_max, outfreq = outfreq, wait=wait,\
T_0 = T_init, p_0 = p_init, r_0 = r_init, sd_conc=sd_conc,\
SO2_g = SO2_g_init, O3_g = O3_g_init, H2O2_g = H2O2_g_init,\
CO2_g = CO2_g_init, NH3_g = NH3_g_init, HNO3_g = HNO3_g_init,\
outfile = outfile,\
chem_dsl = True, chem_dsc = False, chem_rct = False,\
out_bin = \
'{"radii": {"rght": 1, "left": 0, "drwt": "wet", "lnli": "lin", "nbin": 1, "moms": [0, 3]},\
"chem" : {"rght": 1, "left": 0, "drwt": "wet", "lnli": "lin", "nbin": 1,\
"moms": ["O3_a", "H2O2_a", "SO2_a", "CO2_a", "NH3_a", "HNO3_a", "H"]}}')
data = netcdf.netcdf_file(outfile,"r")
#plot
plot_henry(data, output_folder = "../outputs")
#cleanup
data.close()
subprocess.call(["rm", "test_chem_henry.nc"])
def main():
# copy options from chem_conditions ...
p_dict = copy.deepcopy(parcel_dict)
# ... and modify them for the current test
p_dict['outfile'] = "Kreidenweis.nc"
p_dict['chem_dsl'] = True
p_dict['chem_dsc'] = True
p_dict['chem_rct'] = True
p_dict['sd_conc'] = 1025
p_dict['outfreq'] = int(p_dict['z_max'] / p_dict['dt'] / 100) * 4
p_dict['out_bin'] = '{\
"chem" : {"rght": 1e-4, "left": 1e-10, "drwt": "wet", "lnli": "log", "nbin": 100, "moms": ["H"]},\
"chemd" : {"rght": 1e-6, "left": 1e-10, "drwt": "dry", "lnli": "log", "nbin": 100, "moms": ["S_VI"]},\
"radii" : {"rght": 1e-4, "left": 1e-10, "drwt": "wet", "lnli": "log", "nbin": 100, "moms": [0, 1, 3]},\
"specd": {"rght": 1e-6, "left": 1e-10, "drwt": "dry", "lnli": "log", "nbin": 100, "moms": [0, 1, 3]},\
"plt_rw": {"rght": 1, "left": 0, "drwt": "wet", "lnli": "lin", "nbin": 1, "moms": [0, 1, 3]},\
"plt_rd": {"rght": 1, "left": 0, "drwt": "dry", "lnli": "lin", "nbin": 1, "moms": [0, 1, 3]},\
"plt_ch": {"rght": 1, "left": 0, "drwt": "dry", "lnli": "lin", "nbin": 1,\
"moms": ["O3_a", "H2O2_a", "H", "OH", "SO2_a", "S_VI", "CO2_a", "NH3_a", "HNO3_a"]}}'
# run parcel
parcel(**p_dict)
# simulation results
data = netcdf.netcdf_file(p_dict['outfile'], "r")
# do the plotting
plot_fig1(data,
output_folder="../outputs",
output_title="/Kreidenweis_fig1")
plot_fig2(data,
output_folder="../outputs",
output_title="/Kreidenweis_fig2")
plot_fig3(data,
output_folder="../outputs",
output_title="/Kreidenweis_fig3")
# cleanup
subprocess.call(["rm", p_dict['outfile']])
def main(dt_list=[1e-3, 1.5e-3, 2e-3, 3e-3, 4e-3, 8e-3, 1e-2, 2e-2, 4e-2, 8e-2, 1e-1, 2e-1, 4e-1, 8e-1, 1.0]):
# initial values
z_max = 200.0
w = 1.0
RH_init = 0.99999
T_init = 280.0
p_init = 100000.0
r_init = common.eps * RH_init * common.p_vs(T_init) / (p_init - RH_init * common.p_vs(T_init))
# lists to store RH_max and N at the end of the simulation from each test run
RH_list = []
N_list = []
for dt in dt_list:
print "\nt time step", dt
outfile_nc = "timesteptest_dt=" + str(dt) + ".nc"
parcel(
dt=dt,
outfreq=int(z_max / w / dt),
outfile=outfile_nc,
w=w,
T_0=T_init,
p_0=p_init,
r_0=r_init,
z_max=z_max,
mean_r=5e-8,
gstdev=1.5,
n_tot=1e9,
sd_conc=1000,
radii=1e-6 * pow(10, -3 + np.arange(26) * 0.2),
)
f_out = netcdf.netcdf_file(outfile_nc, "r")
RH_max = f_out.RH_max
N_end = sum(f_out.variables["conc"][-1, -9:]) # concentration of drops > 1e-6 m
RH_list.append((RH_max - 1) * 100) # [%]
N_list.append(N_end / 1e6) # [1/mg]
subprocess.call(["rm", outfile_nc])
data = {"RH": RH_list, "N": N_list, "dt": dt_list}
timestep_plot(data)
def test_chem_off():
outfile_on = "test_on.nc"
pc.parcel(outfile=outfile_on, chem_dsl = True, chem_dsc = True, chem_rct = True,
SO2_g_0 = 200e-12, O3_g_0 = 50e-9, H2O2_g_0 = 500e-12
)
nc_on = nc.netcdf_file(outfile_on)
outfile_off = "test_off.nc"
pc.parcel(outfile=outfile_off, chem_dsl = False, chem_dsc = False, chem_rct = False)
nc_off = nc.netcdf_file(outfile_off)
assert(nc_on.SO2_g_0 > 0)
assert(nc_off.SO2_g_0 == 0)
assert(nc_on.variables.has_key("SO2_g"))
assert(nc_on.variables.has_key("SO2_a"))
assert(not nc_off.variables.has_key("SO2_g"))
assert(not nc_off.variables.has_key("SO2_a"))
subprocess.call(["rm", outfile_on])
subprocess.call(["rm", outfile_off])
def data(request):
p_dict = {}
p_dict['outfile'] = "test_moms.nc"
p_dict['sd_conc'] = 1000
p_dict['large_tail'] = True
p_dict['outfreq'] = 1000
p_dict['dt'] = 1.
p_dict['w'] = 0.5
p_dict['z_max'] = 500.
p_dict['RH_0'] = 0.9999
p_dict['T_0'] = 273.15 + 10
p_dict['p_0'] = 90000.
p_dict['wait'] = 0
# initial aerosol: 1-mode ammonium sulfate lognormal
p_dict[
'aerosol'] = '{"ammonium_sulfate": {"kappa": 0.61, "mean_r": [0.02e-6], "gstdev": [1.4], "n_tot": [100e6]}}'
# output for size distribution moments
p_dict['out_bin'] = '{\
"dry_moms": {"rght": 1e-6, "left": 1e-9, "drwt": "dry", "lnli": "log", "nbin": 1, "moms": [0,1,2,3,4,5,6]},\
"dry_dstr": {"rght": 1e-6, "left": 1e-9, "drwt": "dry", "lnli": "log", "nbin": 50, "moms": [0]},\
"wet_moms": {"rght": 1e-4, "left": 1e-6, "drwt": "wet", "lnli": "log", "nbin": 1, "moms": [0,1,2,3,4,5,6]},\
"wet_dstr": {"rght": 1e-4, "left": 1e-6, "drwt": "wet", "lnli": "log", "nbin": 50, "moms": [0]}\
}'
# run parcel
parcel(**p_dict)
#simulation results
data = netcdf.netcdf_file(p_dict['outfile'], "r")
# removing all netcdf files after all tests
def removing_files():
subprocess.call(["rm", p_dict['outfile']])
request.addfinalizer(removing_files)
return data
def data(request):
"""
Run parcel simulation and return opened netdcf file
"""
outfile = "test_spectrum.nc"
# running parcel model ...
parcel(dt = .5, sd_conc = 1024, outfreq = 40, outfile=outfile, chem_dsl = True, out_bin = \
'{"linwradii": {"rght": 0.0001, "left": 1e-09, "drwt": "wet", "lnli": "lin", "nbin": 26, "moms": [0, 1, 3]}, \
"lindradii": {"rght": 1e-06, "left": 1e-09, "drwt": "dry", "lnli": "lin", "nbin": 26, "moms": [0, 1, 3]}, \
"wradii": {"rght": 0.0001, "left": 1e-09, "drwt": "wet", "lnli": "log", "nbin": 26, "moms": [0, 1, 3]}, \
"dradii": {"rght": 1e-06, "left": 1e-09, "drwt": "dry", "lnli": "log", "nbin": 26, "moms": [0, 1, 3]}}'\
)
data = netcdf.netcdf_file(outfile, "r")
# removing all netcdf files after all tests
def removing_files():
subprocess.call(["rm", outfile])
request.addfinalizer(removing_files)
return data
def data(request):
"""
Run parcel simulation and return opened netdcf file
"""
outfile = "test_spectrum.nc"
# running parcel model ...
parcel(dt = .5, sd_conc = 1024, outfreq = 40, outfile=outfile, chem_dsl = True, out_bin = \
'{"linwradii": {"rght": 0.0001, "left": 1e-09, "drwt": "wet", "lnli": "lin", "nbin": 26, "moms": [0, 1, 3]}, \
"lindradii": {"rght": 1e-06, "left": 1e-09, "drwt": "dry", "lnli": "lin", "nbin": 26, "moms": [0, 1, 3]}, \
"wradii": {"rght": 0.0001, "left": 1e-09, "drwt": "wet", "lnli": "log", "nbin": 26, "moms": [0, 1, 3]}, \
"dradii": {"rght": 1e-06, "left": 1e-09, "drwt": "dry", "lnli": "log", "nbin": 26, "moms": [0, 1, 3]}}'\
)
data = netcdf.netcdf_file(outfile, "r")
# removing all netcdf files after all tests
def removing_files():
subprocess.call(["rm", outfile])
request.addfinalizer(removing_files)
return data
def main():
# copy options from chem_conditions ...
p_dict = copy.deepcopy(parcel_dict)
# ... and modify them for the current test
p_dict['outfile'] = "Kreidenweis.nc"
p_dict['chem_dsl'] = True
p_dict['chem_dsc'] = True
p_dict['chem_rct'] = True
p_dict['sd_conc'] = 1025
p_dict['outfreq'] = int(p_dict['z_max'] / p_dict['dt'] / 100) * 4
p_dict['out_bin'] = '{\
"chem" : {"rght": 1e-4, "left": 1e-10, "drwt": "wet", "lnli": "log", "nbin": 100, "moms": ["H"]},\
"chemd" : {"rght": 1e-6, "left": 1e-10, "drwt": "dry", "lnli": "log", "nbin": 100, "moms": ["S_VI"]},\
"radii" : {"rght": 1e-4, "left": 1e-10, "drwt": "wet", "lnli": "log", "nbin": 100, "moms": [3]},\
"specd": {"rght": 1e-6, "left": 1e-10, "drwt": "dry", "lnli": "log", "nbin": 100, "moms": [0, 1, 3]},\
"plt_rw": {"rght": 1, "left": 0, "drwt": "wet", "lnli": "lin", "nbin": 1, "moms": [0, 1, 3]},\
"plt_rd": {"rght": 1, "left": 0, "drwt": "dry", "lnli": "lin", "nbin": 1, "moms": [0, 1, 3]},\
"plt_ch": {"rght": 1, "left": 0, "drwt": "dry", "lnli": "lin", "nbin": 1,\
"moms": ["O3_a", "H2O2_a", "H", "OH", "SO2_a", "S_VI", "CO2_a", "NH3_a", "HNO3_a"]}}'
# run parcel
parcel(**p_dict)
# simulation results
data = netcdf.netcdf_file(p_dict['outfile'], "r")
# do the plotting
plot_fig1(data, output_folder = "../outputs", output_title = "/Kreidenweis_fig1")
plot_fig2(data, output_folder = "../outputs", output_title = "/Kreidenweis_fig2")
plot_fig3(data, output_folder = "../outputs", output_title = "/Kreidenweis_fig3")
# cleanup
subprocess.call(["rm", p_dict['outfile']])
def data(request):
# initial values
RH_init = .99999
T_init = 280.
p_init = 100000.
r_init = common.eps * RH_init * common.p_vs(T_init) / (
p_init - RH_init * common.p_vs(T_init))
# lists to store RH_max and N at the end of the simulation from each test run
RH_list = []
N_list = []
for dt in Dt_list:
print("\nt time step", dt)
outfile_nc = "timesteptest_dt=" + str(dt) + ".nc"
parcel(dt=dt, outfreq = int(100/dt), outfile = outfile_nc,\
w = 1., T_0 = T_init, p_0 = p_init, r_0 = r_init, z_max = 200, \
sd_conc = 1000, \
aerosol = '{"ammonium_sulfate": {"kappa": 0.61, "mean_r": [5e-8], "gstdev": [1.5], "n_tot": [1e9]}}',
out_bin = '{"radii": {"rght": 1, "moms": [0], "drwt": "wet", "nbin": 1, "lnli": "lin", "left": 1e-06}}'
)
f_out = netcdf.netcdf_file(outfile_nc, "r")
RH_max = f_out.RH_max
N_end = f_out.variables["radii_m0"][
-1, 0] # concentration of drops > 1e-6 m
RH_list.append((RH_max - 1) * 100) # [%]
N_list.append(N_end / 1e6) # [1/mg]
data = {"RH": RH_list, "N": N_list, "dt": Dt_list}
# removing all netcdf files after all tests
def removing_files():
for file in glob.glob("timesteptest_dt*"):
subprocess.call(["rm", file])
request.addfinalizer(removing_files)
return data
def data(request):
p_dict = {}
p_dict['outfile'] = "test_moms.nc"
p_dict['sd_conc'] = 1000
p_dict['large_tail'] = True
p_dict['outfreq'] = 1000
p_dict['dt'] = 1.
p_dict['w'] = 0.5
p_dict['z_max'] = 500.
p_dict['RH_0'] = 0.9999
p_dict['T_0'] = 273.15 + 10
p_dict['p_0'] = 90000.
p_dict['wait'] = 0
# initial aerosol: 1-mode ammonium sulfate lognormal
p_dict['aerosol'] = '{"ammonium_sulfate": {"kappa": 0.61, "mean_r": [0.02e-6], "gstdev": [1.4], "n_tot": [100e6]}}'
# output for size distribution moments
p_dict['out_bin'] = '{\
"dry_moms": {"rght": 1e-6, "left": 1e-9, "drwt": "dry", "lnli": "log", "nbin": 1, "moms": [0,1,2,3,4,5,6]},\
"dry_dstr": {"rght": 1e-6, "left": 1e-9, "drwt": "dry", "lnli": "log", "nbin": 50, "moms": [0]},\
"wet_moms": {"rght": 1e-4, "left": 1e-6, "drwt": "wet", "lnli": "log", "nbin": 1, "moms": [0,1,2,3,4,5,6]},\
"wet_dstr": {"rght": 1e-4, "left": 1e-6, "drwt": "wet", "lnli": "log", "nbin": 50, "moms": [0]}\
}'
# run parcel
parcel(**p_dict)
#simulation results
data = netcdf.netcdf_file(p_dict['outfile'], "r")
# removing all netcdf files after all tests
def removing_files():
subprocess.call(["rm", p_dict['outfile']])
request.addfinalizer(removing_files)
return data
def data(request):
# copy options from chem_conditions
p_dict = copy.deepcopy(parcel_dict)
# modify options from chem_conditions
p_dict['outfile'] = "test_chem_closed_dsl.nc"
p_dict['chem_dsl'] = True
pp.pprint(p_dict)
# run parcel
parcel(**p_dict)
# simulation results
data = netcdf.netcdf_file(p_dict['outfile'], "r")
# removing all netcdf files after all tests
def removing_files():
subprocess.call(["rm", p_dict['outfile']])
#request.addfinalizer(removing_files)
return data
def data(request):
# copy options from chem_conditions
p_dict = copy.deepcopy(parcel_dict)
# modify options from chem_conditions
p_dict['outfile'] = "test_chem_closed_dsl.nc"
p_dict['chem_dsl'] = True
pp.pprint(p_dict)
# run parcel
parcel(**p_dict)
# simulation results
data = netcdf.netcdf_file(p_dict['outfile'], "r")
# removing all netcdf files after all tests
def removing_files():
subprocess.call(["rm", p_dict['outfile']])
#request.addfinalizer(removing_files)
return data
def data(request):
# copy options from chem_conditions ...
p_dict = copy.deepcopy(parcel_dict)
# ... and modify them for the current test
p_dict['outfile'] = "test_chem_kreidenweis.nc"
p_dict['chem_dsl'] = True
p_dict['chem_dsc'] = True
p_dict['chem_rct'] = True
p_dict['sd_conc'] = 1024
p_dict['outfreq'] = 10 / (p_dict['dt'] * p_dict['w'])
p_dict['out_bin'] = p_dict['out_bin'][:-1] + \
', "chem" : {"rght": 1e-4, "left": 1e-6, "drwt": "wet", "lnli": "log", "nbin": 100, "moms": ["H"]},\
"radii" : {"rght": 1e-4, "left": 1e-6, "drwt": "wet", "lnli": "log", "nbin": 100, "moms": [3]},\
"acti" : {"rght": 1e-3, "left": 1e-6, "drwt": "wet", "lnli": "log", "nbin": 1, "moms": [0,3]},\
"chemd" : {"rght": 1e-6, "left": 1e-8, "drwt": "dry", "lnli": "log", "nbin": 100, "moms": ["S_VI", "H2O2_a", "O3_a"]},\
"specd" : {"rght": 1e-6, "left": 1e-8, "drwt": "dry", "lnli": "log", "nbin": 100, "moms": [0, 1, 3]}}'
pp.pprint(p_dict)
# run parcel
parcel(**p_dict)
#simulation results
data = netcdf.netcdf_file(p_dict['outfile'], "r")
# removing all netcdf files after all tests
def removing_files():
subprocess.call(["rm", p_dict['outfile']])
request.addfinalizer(removing_files)
return data
def data(request):
SO2_g_init = 200e-12
O3_g_init = 50e-9
H2O2_g_init = 500e-12
outfreq = 20
z_max = 200.
outfile = "test_chem_dsl.nc"
# running parcel model for open chem system and only for dissolving chem species into droplets
parcel(dt = .5, z_max = z_max, outfreq = outfreq, SO2_g_0 = SO2_g_init, O3_g_0 = O3_g_init, H2O2_g_0 = H2O2_g_init,\
chem_sys = 'open', outfile = outfile,\
chem_dsl = True, chem_dsc = False, chem_rct = False,\
out_bin = \
'{"radii": {"rght": 1, "left": 0, "drwt": "wet", "lnli": "lin", "nbin": 1, "moms": [3]},\
"chem" : {"rght": 1, "left": 0, "drwt": "wet", "lnli": "lin", "nbin": 1, "moms": ["O3_a", "H2O2_a", "SO2_a"]}}')
data = netcdf.netcdf_file(outfile, "r")
# removing all netcdf files after all tests
def removing_files():
subprocess.call(["rm", outfile])
request.addfinalizer(removing_files)
return data
def data(request):
# initial condition
SO2_g_init = 200e-12
O3_g_init = 50e-9
H2O2_g_init = 500e-12
outfreq = 1000
z_max = 250.
dt = .01
w = 1.
# turn on chemistry
chem_dsl = True
chem_dsc = True
chem_rct = True
chem_spn = 10
# define output for moments and chemistry
out_bin_chem = '{"radii": {"rght": 1, "moms": [0, 1, 3], "drwt": "wet", "nbin": 1, "lnli": "lin", "left": 0}, "chem": {"rght": 1, "moms": ["O3_a", "H2O2_a", "SO2_a", "H", "OH", "HSO3_a", "SO3_a", "HSO4_a", "SO4_a", "S_VI"], "drwt": "wet", "nbin": 1, "lnli": "lin", "left": 0}, "radiidry": {"rght": 1, "moms": [0, 1, 3], "drwt": "dry", "nbin": 1, "lnli": "lin", "left": 0}}'
out_bin = '{"radii": {"rght": 1, "moms": [0, 1, 3], "drwt": "wet", "nbin": 1, "lnli": "lin", "left": 0}, "radiidry": {"rght": 1, "moms": [0, 1, 3], "drwt": "dry", "nbin": 1, "lnli": "lin", "left": 0}}'
# running parcel model for open / closed chem system ...
parcel(dt = dt, z_max = z_max, w = w, outfreq = outfreq,\
SO2_g_0 = SO2_g_init, O3_g_0 = O3_g_init, H2O2_g_0 = H2O2_g_init,\
chem_sys = 'open', outfile="test_chem_open.nc",\
chem_dsl = chem_dsl, chem_dsc = chem_dsc, chem_rct = chem_rct, chem_spn = chem_spn, \
out_bin = out_bin_chem)
parcel(dt = dt, z_max = z_max, w = w, outfreq = outfreq,\
SO2_g_0 = SO2_g_init, O3_g_0 = O3_g_init, H2O2_g_0 = H2O2_g_init,\
chem_sys = 'closed', outfile="test_chem_closed.nc",\
chem_dsl = chem_dsl, chem_dsc = chem_dsc, chem_rct = chem_rct, chem_spn = chem_spn, \
out_bin = out_bin_chem)
parcel(dt = dt, z_max = z_max, w = w, outfreq = outfreq, SO2_g_0=0, O3_g_0=0, H2O2_g_0=0,\
outfile="test_chem_off.nc", out_bin = out_bin)
# TODO - why do I have to repeat this import here?
from scipy.io import netcdf
data = {'open' : netcdf.netcdf_file("test_chem_open.nc", "r"),\
'closed' : netcdf.netcdf_file("test_chem_closed.nc", "r"),\
'off' : netcdf.netcdf_file("test_chem_off.nc", "r")}
def removing_files():
for name, netcdf in data.iteritems():
subprocess.call(["rm", "test_chem_" + name + ".nc"])
request.addfinalizer(removing_files)
return data
def main():
# initial condition
SO2_g_init = 200e-12
O3_g_init = 50e-9
H2O2_g_init = 500e-12
outfreq = 1000
z_max = 250.
dt = .01
w = 1.
# turn on chemistry
chem_dsl = True
chem_dsc = True
chem_rct = True
chem_spn = 10
# define output for moments and chemistry
out_bin_chem = ["radii:0/1/1/lin/wet/0,1,3", "radiidry:0/1/1/lin/dry/0,1,3",\
"chem:0/1/1/lin/wet/O3_a,H2O2_a,SO2_a,H,OH,HSO3_a,SO3_a,HSO4_a,SO4_a,S_VI"]
out_bin = ["radii:0/1/1/lin/wet/0,1,3", "radiidry:0/1/1/lin/dry/0,1,3"]
# running parcel model for open / closed chem system ...
parcel(dt = dt, z_max = z_max, w = w, outfreq = outfreq,\
SO2_g_0 = SO2_g_init, O3_g_0 = O3_g_init, H2O2_g_0 = H2O2_g_init,\
chem_sys = 'open', outfile="test_chem_open.nc",\
chem_dsl = chem_dsl, chem_dsc = chem_dsc, chem_rct = chem_rct, chem_spn = chem_spn, \
out_bin = out_bin_chem)
parcel(dt = dt, z_max = z_max, w = w, outfreq = outfreq,\
SO2_g_0 = SO2_g_init, O3_g_0 = O3_g_init, H2O2_g_0 = H2O2_g_init,\
chem_sys = 'closed', outfile="test_chem_closed.nc",\
chem_dsl = chem_dsl, chem_dsc = chem_dsc, chem_rct = chem_rct, chem_spn = chem_spn, \
out_bin = out_bin_chem)
parcel(dt = dt, z_max = z_max, w = w, outfreq = outfreq, SO2_g_0=0, O3_g_0=0, H2O2_g_0=0,\
outfile="test_chem_off.nc", out_bin = out_bin)
# TODO - why do I have to repeat this import here?
from scipy.io import netcdf
data = {'open' : netcdf.netcdf_file("test_chem_open.nc", "r"),\
'closed' : netcdf.netcdf_file("test_chem_closed.nc", "r"),\
'off' : netcdf.netcdf_file("test_chem_off.nc", "r")}
plot_chem(data, output_folder = "../outputs")
for name, netcdf in data.iteritems():
netcdf.close()
subprocess.call(["rm", "test_chem_" + name + ".nc"])
def test_supersat(tmpdir):
""" checking if parcel rises an exception when RH_init>0 """
str_f = str(tmpdir.join("test_pcl.nc"))
with pytest.raises(Exception) as excinfo:
pc.parcel(outfile=str_f, r_0=.1)
def test_supersat(tmpdir):
""" checking if parcel rises an exception when RH_init>0 """
str_f = str(tmpdir.join("test_pcl.nc"))
with pytest.raises(Exception) as excinfo:
pc.parcel(outfile=str_f, r_0=.1)
def test_args(tmpdir, arg):
"""checking if parcel rises exceptions when arguments don't make sense """
str_f = str(tmpdir.join("test_pcl.nc"))
with pytest.raises(Exception) as excinfo:
pc.parcel(outfile=str_f, **arg)
def data(request):
# copy options from chem_conditions ...
p_dict = copy.deepcopy(parcel_dict)
# ... and modify them for the current test
p_dict['outfile'] = "test_chem_kreidenweis.nc"
p_dict['chem_dsl'] = True
p_dict['chem_dsc'] = True
p_dict['chem_rct'] = True
p_dict['outfreq'] = 10 / (p_dict['dt'] * p_dict['w'])
p_dict['out_bin'] = p_dict['out_bin'][:-1] + \
', "chem" : {"rght": 1e-4, "left": 1e-6, "drwt": "wet", "lnli": "log", "nbin": 100, "moms": ["H"]},\
"radii" : {"rght": 1e-4, "left": 1e-6, "drwt": "wet", "lnli": "log", "nbin": 100, "moms": [3]},\
"acti" : {"rght": 1e-3, "left": 1e-6, "drwt": "wet", "lnli": "log", "nbin": 1, "moms": [0]},\
"chemd" : {"rght": 1e-6, "left": 1e-8, "drwt": "dry", "lnli": "log", "nbin": 100, "moms": ["S_VI" ]}}'
# create empty lists for storing simulation results
sd_list = []
pow_list = []
RH_max_list = []
N_drop_list = []
pH_list = []
tot_S_list = []
# run parcel test for super-droplet numbers between 1 and 1024
for pw in range(11):
sd_num = pow(2, pw)
p_dict['sd_conc'] = sd_num
pp.pprint(p_dict)
# run parcel
parcel(**p_dict)
# save the simulation results ...
tmp_data = netcdf.netcdf_file(p_dict['outfile'], "r")
# ... do the initial analysis ...
p = tmp_data.variables["p"][-1]
T = tmp_data.variables["T"][-1]
rhod = tmp_data.variables["rhod"][-1]
r3 = tmp_data.variables["radii_m3"][-1, :]
n_H = tmp_data.variables["chem_H"][-1, :] / cm.M_H
# water weighted average pH at the end of the simulation:
nom = 0
for it, val in enumerate(r3):
if val > 0:
nom += (n_H[it] / (4. / 3 * math.pi * val * 1e3)) * val
den = np.sum(r3[:]) # to liters
pH = -1 * np.log10(nom / den)
# total sulfate formation:
s6_ini = tmp_data.variables["chemd_S_VI"][0, :]
s6_end = tmp_data.variables["chemd_S_VI"][-1, :]
sulf_ppt = fn.mix_ratio_to_mole_frac(
(np.sum(s6_end) - np.sum(s6_ini)), p, cm.M_H2SO4, T, rhod) * 1e12
# number of droplets at RH = max:
n_tot = tmp_data.variables["acti_m0"][12, 0] * rhod * 1e-6
# ^^ TODO - think of something better
# maximum supersaturation:
RH_max = (tmp_data.RH_max - 1) * 100
# ... save the results ...
sd_list.append(sd_num)
pow_list.append(pw)
RH_max_list.append(RH_max)
N_drop_list.append(n_tot)
pH_list.append(pH)
tot_S_list.append(sulf_ppt)
# ... and remove the simulation data files
subprocess.call(["rm", p_dict['outfile']])
# pack all the data into a dictionary
data = {}
data['number of super-droplets'] = sd_list
data['power of two'] = pow_list
data['cloud droplet conc. at CB'] = N_drop_list
data['maximum supersaturation'] = RH_max_list
data['water weighted average pH'] = pH_list
data['total sulfate production'] = tot_S_list
return data
def data(request):
# initial condition
RH_init = .999999
T_init = 300.
p_init = 100000.
r_init = cm.eps * RH_init * cm.p_vs(T_init) / (p_init -
RH_init * cm.p_vs(T_init))
# calculate rhod for gas init cond
th_0 = T_init * (cm.p_1000 / p_init)**(cm.R_d / cm.c_pd)
rhod_init = cm.rhod(p_init, th_0, r_init)
# init cond for trace gases
SO2_g_init = fn.mole_frac_to_mix_ratio(200e-12, p_init, cm.M_SO2, T_init,
rhod_init)
O3_g_init = fn.mole_frac_to_mix_ratio(50e-9, p_init, cm.M_O3, T_init,
rhod_init)
H2O2_g_init = fn.mole_frac_to_mix_ratio(500e-12, p_init, cm.M_H2O2, T_init,
rhod_init)
CO2_g_init = fn.mole_frac_to_mix_ratio(360e-6, p_init, cm.M_CO2, T_init,
rhod_init)
NH3_g_init = fn.mole_frac_to_mix_ratio(100e-12, p_init, cm.M_NH3, T_init,
rhod_init)
HNO3_g_init = fn.mole_frac_to_mix_ratio(100e-12, p_init, cm.M_HNO3, T_init,
rhod_init)
# aerosol size distribution
mean_r = .08e-6 / 2
gstdev = 2.
n_tot = 566.e6
# output
sd_conc = 1
outfreq = 50
z_max = 300.
outfile = "test_chem_henry.nc"
dt = 0.1
wait = 100
parcel(dt = dt, z_max = z_max, outfreq = outfreq, wait=wait,\
T_0 = T_init, p_0 = p_init, r_0 = r_init,\
SO2_g = SO2_g_init, O3_g = O3_g_init, H2O2_g = H2O2_g_init,\
CO2_g = CO2_g_init, NH3_g = NH3_g_init, HNO3_g = HNO3_g_init,\
outfile = outfile,\
chem_dsl = True, chem_dsc = True, chem_rct = False,\
aerosol = \
'{"test": {"kappa": 0.5, "mean_r": [' + str(mean_r) + '], "gstdev": [' + str(gstdev) + '], "n_tot": [' + str(n_tot) + ']}}',\
sd_conc = sd_conc,\
out_bin = \
'{"radii": {"rght": 1.0, "left": 0.0, "drwt": "wet", "lnli": "lin", "nbin": 1, "moms": [0, 3]},\
"chem" : {"rght": 1.0, "left": 0.0, "drwt": "wet", "lnli": "lin", "nbin": 1,\
"moms": ["O3_a", "H2O2_a", "SO2_a", "CO2_a", "NH3_a", "HNO3_a", "H"]}}' )
data = netcdf.netcdf_file("test_chem_henry.nc", "r")
# removing all netcdf files after all tests
def removing_files():
subprocess.call(["rm", "test_chem_henry.nc"])
request.addfinalizer(removing_files)
return data
def test_args(tmpdir, arg):
"""checking if parcel rises exceptions when arguments don't make sense """
str_f = str(tmpdir.join("test_pcl.nc"))
with pytest.raises(Exception) as excinfo:
pc.parcel(outfile=str_f, **arg)
# lgrngn-specific parameters
sd_conc = 44
def lognormal(lnr):
mean_r = .08e-6 / 2
stdev = 2
n_tot = 566e6
return n_tot * exp(-pow(
(lnr - log(mean_r)), 2) / 2 / pow(log(stdev), 2)) / log(stdev) / sqrt(
2 * pi)
kappa = .61 #TODO - check
# rho = 1.8 # TODO
chem_gas = {
chem_species_t.SO2: 200e-12,
chem_species_t.O3: 50e-9,
chem_species_t.H2O2: 500e-12
}
# running all three
for rhs in [
rhs_blk_2m(dt),
rhs_lgrngn(dt, sd_conc, {kappa: lognormal}, chem_gas)
]:
parcel(p_d, th_d, r_v, w, dt, nt, rhs)
print p_d, arr_t([th_dry2std(th_d[0], r_v[0])]), r_v
