def main(experiment_id, site, treatment, exp):
GDAY_SPIN = "gday -s -p "
GDAY = "gday -p "
# dir names
base_dir = os.path.dirname(os.getcwd())
param_dir = os.path.join(base_dir, "params")
met_dir = os.path.join(base_dir, "met_data")
run_dir = os.path.join(base_dir, "outputs")
shutil.copy(os.path.join(param_dir, "%s_%s_model_indust.cfg" % (experiment_id, site)),
os.path.join(param_dir, "%s_%s_model_indust_adj_%s.cfg" % (experiment_id, site, exp)))
itag = "%s_%s_model_indust_adj_%s" % (experiment_id, site, exp)
otag = "%s_%s_simulation_%s" % (experiment_id, site, exp)
mtag = "%s_met_data_%s_%s_co2.csv" % (site, treatment, exp)
out_fn = "D1GDAY%s%s%s.csv" % (site, treatment.upper(), exp.upper())
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "daily",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# translate output names, units and make a nice CSV compliment with
# experiment protocol
# add this directory to python search path so we can find the scripts!
sys.path.append(os.path.join(base_dir, "scripts"))
import translate_GDAY_output_to_EUCFACE_format as tr
tr.translate_output(out_fname, met_fname)
def main(site, treatment):
GDAY_SPIN = "./gday -s -p "
GDAY = "./gday -p "
# dir names
base_dir = os.path.dirname(os.getcwd())
param_dir = os.path.join(d, "params/Run1")
met_dir = os.path.join(d, "met_data")
run_dir = os.path.join(d, "outputs/Run1")
shutil.copy(os.path.join(param_dir, "%s_model_spunup.cfg" % (site)),
os.path.join(param_dir, "%s_model_transient.cfg" % (site)))
itag = "%s_model_transient" % (site)
otag = "%s_model_simulation_%s" % (site, treatment)
mtag = "%s_met_forcing_transient_%s.csv" % (site, treatment)
out_fn = "%s_transient_%s.csv" % (site, treatment.upper())
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "annual",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# add this directory to python search path so we can find the scripts!
sys.path.append(os.path.join(d, "code/scripts"))
import translate_GDAY_output_to_NCEAS_format as tr
def main(experiment_id,
site,
SPIN_UP=True,
POST_INDUST=True,
ELE_INITIALIZATION=True,
ELE_SPINUP=True,
ELE_EQUILIB=True):
GDAY_SPIN = "./gday -s -p "
GDAY = "./gday -p "
# dir names
base_param_name = "base_start_with_P"
base_param_dir = "/Users/%s/Documents/Research/Projects/eucface/Git/GDAY/params" % (
USER)
base_dir = os.path.dirname(os.getcwd())
param_dir = os.path.join(base_dir, "params")
met_dir = os.path.join(base_dir, "met_data")
run_dir = os.path.join(base_dir, "outputs")
if SPIN_UP == True:
# copy base files to make two new experiment files
shutil.copy(os.path.join(base_param_dir, base_param_name + ".cfg"),
os.path.join(param_dir, "%s_%s_model_spinup.cfg" % \
(experiment_id, site)))
# Run model to equilibrium assuming forest, growing C pools from
# effectively zero
itag = "%s_%s_model_spinup" % (experiment_id, site)
otag = "%s_%s_model_spunup" % (experiment_id, site)
mtag = "%s_met_data_amb_var_co2.csv" % (site)
out_fn = itag + "_equilib.out"
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# default C:N 25.
# Canopy height = 22 m average of 6 plots at UWS, site_description_stuff/EucFACE_Plot_Summary.doc
"activesoil": "0.001",
"activesoiln": "0.00004",
"activesoilp": "0.000002",
"age": "100.0",
"branch": "0.001",
"branchn": "0.00004",
"branchp": "0.000002",
"cstore": "0.0",
"nstore": "0.0",
"pstore": "0.0",
"inorgn": "0.0000", # 0.00004
"inorglabp": "0.0000", # 0.00004
"inorgsorbp": "0.0",
"inorgssorbp": "0.0",
"inorgoccp": "0.0",
"inorgparp": "0.054",
"metabsoil": "0.0",
"metabsoiln": "0.0",
"metabsoilp": "0.0",
"metabsurf": "0.0",
"metabsurfn": "0.0",
"metabsurfp": "0.0",
"passivesoil": "0.001",
"passivesoiln": "0.0004",
"passivesoilp": "0.000002",
"prev_sma": "1.0",
"root": "0.001",
"croot": "0.0", # don't simulate coarse roots
"crootn": "0.0", # don't simulate coarse roots
"crootp": "0.0", # don't simulate coarse roots
"rootn": "0.00004",
"rootp": "0.000002",
"sapwood": "0.001",
"shoot": "0.001",
"shootn": "0.00004",
"shootp": "0.000002",
"slowsoil": "0.001",
"slowsoiln": "0.00004",
"slowsoilp": "0.000002",
"stem": "0.001",
"stemn": "0.00004",
"stemp": "0.000002",
"stemnimm": "0.00004",
"stempimm": "0.000002",
"stemnmob": "0.0",
"stempmob": "0.0",
"structsoil": "0.001",
"structsoiln": "0.00004",
"structsoilp": "0.000002",
"structsurf": "0.001",
"structsurfn": "0.00004",
"structsurfp": "0.0000024",
# parameters
"resp_coeff": "0.2",
"alpha_j":
"0.308", # Taking the theoretical maximum (from Belinda) 0.385 x 0.8 (leaf absorptance) = 0.308
"intercep_frac": "0.15",
"max_intercep_lai": "3.0",
"latitude": "-33.61",
"albedo": "0.2",
"finesoil":
"0.2", # silt + clay fraction. Surface soil texture (upper 45 cm) for Clarenden sand: 80 +/- 8% sand, 9 +/- 5% silt, 11 +/- 3% clay
"slamax":
"5.1", # current unit: m2 kg-1; original unit: 43.7 +/- 1.5 cm2 g 1 dry mass
"sla":
"5.1", # current unit: m-2 kg-1; original unit: 43.7 +/- 1.5 cm2 g 1 dry mass
"slazero":
"5.1", # current unit: m-2 kg-1; original unit: 43.7+/- 1.5 cm2 g 1 dry mass
"lai_closed":
"0.5", # I am effectively turning this feature off by setting it so low
"c_alloc_fmax": "0.45", # 0.35
"c_alloc_fmin": "0.05", # 0.15
"c_alloc_rmax": "0.45", # 0.35
"c_alloc_rmin": "0.05", # 0.05
"c_alloc_bmax": "0.1", # 0.1
"c_alloc_bmin": "0.1", # 0.1
"c_alloc_cmax": "0.0", # turn off coarse roots!
"biochemical_p_constant": "150.0",
"fretrans": "0.5",
"fretransp": "0.5",
"rretrans": "0.0",
"bretrans": "0.0",
"wretrans": "0.7",
"cretrans": "0.0",
"crit_n_cost_of_p": "15.0",
"ncwnewz": "0.003", #New stem ring N:C at zero leaf N:C (mobile)
"ncwnew": "0.003", #New stem ring N:C at critical leaf N:C (mob)
"ncwimmz": "0.003", #Immobile stem N C at zero leaf N C
"ncwimm": "0.003", #Immobile stem N C at critical leaf N C
"ncbnewz": "0.003", #new branch N C at zero leaf N C
"ncbnew": "0.003", #new branch N C at critical leaf N C
"nccnewz": "0.003", #new coarse root N C at zero leaf N C
"nccnew": "0.003", #new coarse root N C at critical leaf N C
"ncrfac": "0.8",
"ncmaxfyoung": "0.04",
"ncmaxfold": "0.04",
"ncmaxr": "0.03",
"retransmob": "0.0",
"fdecay": "0.6", # 18 mth turnover * 1/30
"fdecaydry": "0.6", # 18 mth turnover * 1/30
"max_p_biochemical": "0.001",
"rdecay": "0.6",
"rdecaydry": "0.6",
"crdecay": "0.00", # turn off coarse roots!
"bdecay": "0.1", # no idea, assuming 50 years
"wdecay": "0.1", # no idea, assuming 50 years
"watdecaydry": "0.0",
"watdecaywet": "0.1",
"ligshoot":
"0.18", # Based on white et al. 2000 #"0.145", # assuming leaf and root same as DE word document
"ligroot":
"0.22", # Based on white et al. 2000 # assuming leaf and root same as DE word document
"rateuptake": "1.8",
"rateloss": "0.05", # was 0.1
"topsoil_depth":
"450.0", # Not needed as I have supplied the root zone water and topsoil water available
"rooting_depth":
"2500.0", # Not needed as I have supplied the root zone water and topsoil water available
"wcapac_root":
"300.0", # [mm] (FC-WP)*rooting_depth. But using 2.0 m, site_description_stuff/EucFACE_Plot_Summary.doc
"wcapac_topsoil":
"67.5", # [mm] (FC-WP)*rooting_depth. But using 0.45 m, site_description_stuff/EucFACE_Plot_Summary.doc
"ctheta_topsoil": "0.65", # Derive based on soil type loamy_sand
"ntheta_topsoil": "8.0", # Derive based on soil type loamy_sand
"ctheta_root":
"0.525", # Derive based on soil type sandy_clay_loam
"ntheta_root": "5.5", # Derive based on soil type sandy_clay_loam
"topsoil_type": "loamy_sand",
"rootsoil_type": "sandy_clay_loam",
"soil_order": "andisol",
"ks": "0.5",
"kp": "0.3",
"krp": "0.00001",
#"dz0v_dh": "0.1",
#"z0h_z0m": "1.0",
#"displace_ratio": "0.67",
"dz0v_dh":
"0.05", # Using Value from JULES for TREE PFTs as I don't know what is best. However I have used value from Jarvis, quoted in Jones 1992, pg. 67. Produces a value within the bounds of 3.5-1.1 mol m-2 s-1 Drake, 2010, GCB for canht=17
"displace_ratio":
"0.75", # From Jones, pg 67, following Jarvis et al. 1976
"z0h_z0m": "1.0",
"g1":
"3.8667", # 3.8667 Fit by Me to Teresa's data 7th Nov 2013; or 2.78 from stomatal model
#"jmaxna": "14.891", #
#"jmaxpa": "291.4305", #
#"jmaxnb": "99.497", #
#"jmaxpb": "99.949", # 88.56
#"vcmaxna": "10.453", # 6.426
#"vcmaxpa": "153.1748",
#"vcmaxnb": "74.522", # 60.526
#"vcmaxpb": "57.242", # 27.66
"jmaxna":
"49.930", # forcing intercept to zero; if use all species df, 49.743
"jmaxpa":
"933.90", # forcing intercept to zero; if use all species df, 842.46
"jmaxnb": "0.0", # forcing intercept to zero
"jmaxpb": "0.0", # forcing intercept to zero
"vcmaxna":
"27.707", # forcing intercept to zero; if use all species df, 27.627
"vcmaxpa":
"516.83", # forcing intercept to zero; if use all species df, 468.76
"vcmaxnb": "0.0", # forcing intercept to zero
"vcmaxpb": "0.0", # forcing intercept to zero
"measurement_temp":
"25.0", # parameters obtained at 22 not 25 degrees
"heighto": "4.826",
"htpower": "0.35",
"height0": "5.0",
"height1": "25.0",
"leafsap0": "4000.0", # "4000.0",
"leafsap1": "2700.0", # 2700
"branch0": "5.61",
"branch1": "0.346",
"croot0": "0.34",
"croot1": "0.84",
"targ_sens": "0.5",
"density": "800.0", # 480
"nf_min": "0.005",
"nf_crit": "0.015",
"sapturnover": "0.1",
"p_atm_deposition":
"0.000086", # 1/4 of value from Table 4, Olander et al. 2005; Earth Interactions.
"p_rate_par_weather":
"0.0001", # Calcualted so that weathering rate = atm deposition;
"passpcmin": "0.005",
"passpcmax": "0.05",
"psecmnp": "0.000022",
"pcbnew": "0.0003",
"pcbnewz": "0.0003",
"pccnew": "0.0003",
"pccnewz": "0.0003",
"pcmaxfold":
"0.002", # 0.0015 Table 3, Olander et al. 2005, Earth Interactions.
"pcmaxfyoung": "0.002",
"pcmaxr": "0.0006",
"pcrfac": "0.8",
"pcwimm": "0.00014",
"pcwimmz": "0.00014",
"pcwnew": "0.00014",
"pcwnewz": "0.00014",
"pf_crit": "0.002",
"pf_min": "0.0002",
"phmax": "7.6",
"phmin": "5.0",
"phtextmin": "0.000008",
"phtextmax": "0.00015",
"phtextslope": "0.00004",
"pmax": "0.002",
"pmin": "0.01",
"pmin0": "0.0",
"pmincrit": "2.0",
"prateloss": "0.05",
"prateuptake":
"3.6", # Fitted value to obtain balance between uptake N:P ratio and reasonable P labile pool
"slowpcmin": "0.005",
"slowpcmax": "0.011111",
"soilph": "4.5", # Olander et al., 2005, Earth Interactions.
"sorpmx": "5.0",
"sorpaf": "1.0",
"structcp": "5500.0",
"structratp": "0.0",
# control
"adjust_rtslow": "false", # priming, off
"alloc_model": "allometric",
"assim_model": "mate",
"calc_sw_params": "true", #false=use fwp values, true=derive them
"deciduous_model": "false",
"disturbance": "false",
"exudation": "false",
"fixed_stem_nc": "true",
"fixed_stem_pc": "true",
"fixleafnc": "false",
"fixleafpc": "false",
"grazing": "false",
"gs_model": "medlyn",
"aci_relationship": "ellsworth",
"model_optroot": "false",
"modeljm": "1",
"ncycle": "true",
"pcycle": "false",
"nuptake_model": "1",
"puptake_model": "1",
"triose_p": "false",
"output_ascii": "true",
"passiveconst": "false",
"print_options": "end",
"ps_pathway": "c3",
"respiration_model": "fixed",
"strfloat": "0",
"strpfloat": "0",
"sw_stress_model": "1", # Sands and Landsberg
"use_eff_nc": "0",
"text_effect_p": "1",
"water_stress": "true",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY_SPIN + cfg_fname)
if POST_INDUST == True:
# copy spunup base files to make two new experiment files
shutil.copy(
os.path.join(param_dir,
"%s_%s_model_spunup.cfg" % (experiment_id, site)),
os.path.join(param_dir,
"%s_%s_model_spunup_adj.cfg" % (experiment_id, site)))
itag = "%s_%s_model_spunup_adj" % (experiment_id, site)
otag = "%s_%s_model_indust" % (experiment_id, site)
mtag = "%s_met_data_amb_var_co2.csv" % (site)
out_fn = "%s_amb_equilib.csv" % (site)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "end",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
if POST_INDUST == True:
# copy spunup base files to make two new experiment files
shutil.copy(
os.path.join(param_dir,
"%s_%s_model_spunup.cfg" % (experiment_id, site)),
os.path.join(param_dir,
"%s_%s_model_spunup_adj.cfg" % (experiment_id, site)))
itag = "%s_%s_model_spunup_adj" % (experiment_id, site)
otag = "%s_%s_model_indust" % (experiment_id, site)
mtag = "%s_met_data_amb_var_co2.csv" % (site)
out_fn = "%s_amb_equilib.csv" % (site)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "daily",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# elevated co2 initialization to store output
if ELE_INITIALIZATION == True:
# copy last cfg file and make new one
shutil.copy(
os.path.join(param_dir,
"%s_%s_model_indust.cfg" % (experiment_id, site)),
os.path.join(param_dir,
"%s_%s_model_indust_adj.cfg" % (experiment_id, site)))
itag = "%s_%s_model_indust_adj" % (experiment_id, site)
otag = "%s_%s_model_ele_initial" % (experiment_id, site)
mtag = "%s_met_data_%s_var_co2.csv" % (site, treatment)
out_fn = "%s_ele_initial.csv" % (site)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "daily",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# elevated co2 initialization to store cfg
if ELE_INITIALIZATION == True:
# copy last cfg file and make new one
shutil.copy(
os.path.join(param_dir,
"%s_%s_model_indust.cfg" % (experiment_id, site)),
os.path.join(param_dir,
"%s_%s_model_indust_adj.cfg" % (experiment_id, site)))
itag = "%s_%s_model_indust_adj" % (experiment_id, site)
otag = "%s_%s_model_ele_initial" % (experiment_id, site)
mtag = "%s_met_data_%s_var_co2.csv" % (site, treatment)
out_fn = "%s_ele_initial.csv" % (site)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "end",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# elevated CO2 during spin up to store cfg file
if ELE_SPINUP == True:
# copy last cfg file and make new one
shutil.copy(
os.path.join(param_dir, "%s_%s_model_ele_initial.cfg" %
(experiment_id, site)),
os.path.join(param_dir,
"%s_%s_model_ele_spinup.cfg" % (experiment_id, site)))
itag = "%s_%s_model_ele_spinup" % (experiment_id, site)
otag = "%s_%s_model_ele_spunup" % (experiment_id, site)
mtag = "%s_met_data_%s_var_co2.csv" % (site, treatment)
out_fn = "FACE_EUC_ele_spunup_%s%s.csv" % (site, treatment.upper())
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "end",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY_SPIN + cfg_fname)
# elevated co2 final equilibrium simulation
if ELE_EQUILIB == True:
# copy last cfg file and make new one
shutil.copy(
os.path.join(param_dir,
"%s_%s_model_ele_spunup.cfg" % (experiment_id, site)),
os.path.join(param_dir,
"%s_%s_model_ele_equil.cfg" % (experiment_id, site)))
itag = "%s_%s_model_ele_equil" % (experiment_id, site)
otag = "%s_%s_model_ele_final" % (experiment_id, site)
mtag = "%s_met_data_%s_var_co2.csv" % (site, treatment)
out_fn = "%s_ele_final_equilib.csv" % (site)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "daily",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
def main(experiment_id, latitude, albedo, topsoil_type,
rootsoil_type, finesoil, SPIN_UP=False, RUN_SIM=False):
GDAY_SPIN = "gday -s -p "
GDAY = "gday -p "
# dir names
base_param_name = "base_start"
base_dir = os.getcwd()
base_param_dir = "/Users/%s/src/c/gday/example/params" % (USER)
param_dir = os.path.join(base_dir, "params")
met_dir = os.path.join(base_dir, "gday_met_files")
run_dir = os.path.join(base_dir, "outputs")
if SPIN_UP == True:
# copy base files to make two new experiment files
shutil.copy(os.path.join(base_param_dir, base_param_name + ".cfg"),
os.path.join(param_dir, "%s_model_spinup.cfg" % \
(experiment_id)))
# Run model to equilibrium assuming forest, growing C pools from
# effectively zero
itag = "%s_model_spinup" % (experiment_id)
otag = "%s_model_spunup" % (experiment_id)
mtag = "%s.daily_spin.csv" % (experiment_id)
out_fn = itag + "_equilib.out"
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# state - default C:N 25.
"age": "0.0",
"canht": "20.0", # Made up
"activesoil": "0.001",
"activesoiln": "0.00004",
"age": "0.0",
"branch": "0.001",
"branchn": "0.00004",
"cstore": "0.001",
"inorgn": "0.00004",
"metabsoil": "0.0",
"metabsoiln": "0.0",
"metabsurf": "0.0",
"metabsurfn": "0.0",
"nstore": "0.00004",
"passivesoil": "0.001",
"passivesoiln": "0.0004",
"prev_sma": "-999.9",
"root": "0.001",
"root_depth": "-9999.9",
"rootn": "0.00004",
"sapwood": "0.001",
"shoot": "0.001",
"shootn": "0.00004",
"slowsoil": "0.001",
"slowsoiln": "0.00004",
"stem": "0.001",
"stemn": "0.00004",
"stemnimm": "0.00004",
"stemnmob": "0.0",
"structsoil": "0.001",
"structsoiln": "0.00004",
"structsurf": "0.001",
"structsurfn": "0.00004",
"croot": "0.0", # don't simulate coarse roots
"crootn": "0.0", # don't simulate coarse roots
# parameters
#"fix_lai": "3.0",
"latitude": "%f" % (latitude),
"albedo": "%f" % (albedo),
"finesoil": "%f" % (finesoil),
"intercep_frac": "0.15",
"max_intercep_lai": "3.0",
"slamax": "4.4", # made up [m2 kg-1 DW]
"sla": "4.4", # made up [m2 kg-1 DW]
"slazero": "4.4", # made up [m2 kg-1 DW]
"cfracts": "0.5",
"lai_closed": "0.5", # I am effectively turning this feature off by setting it so low
"c_alloc_fmax": "0.25",
"c_alloc_fmin": "0.25",
"c_alloc_rmax": "0.05",
"c_alloc_rmin": "0.05",
"c_alloc_bmax": "0.1",
"c_alloc_bmin": "0.1",
"c_alloc_cmax": "0.0", # turn off coarse roots!
#"c_alloc_fmax": "0.35",
#"c_alloc_fmin": "0.15",
#"c_alloc_rmax": "0.35",
#"c_alloc_rmin": "0.05",
#"c_alloc_bmax": "0.1",
#"c_alloc_bmin": "0.1",
#"c_alloc_cmax": "0.0", # turn off coarse roots!
"fretrans": "0.5",
"rretrans": "0.0",
"bretrans": "0.0",
"wretrans": "0.0",
"ncwnewz": "0.003",
"ncwnew": "0.003",
"ncwimmz": "0.003",
"ncwimm": "0.003",
"ncbnewz": "0.003",
"ncbnew": "0.003",
"ncrfac": "0.8",
"ncmaxfyoung": "0.04",
"ncmaxfold": "0.04",
"ncmaxr": "0.03",
"retransmob": "0.0",
"fdecay": "0.59988", # Protocol [years-1]
"fdecaydry": "0.59988", # Protocol
"rdecay": "0.33333", # Protocol
"rdecaydry": "0.33333", # Protocol
"bdecay": "0.02", # No data, assuming 50 years
"wdecay": "0.02",
"crdecay": "0.00", # turn off coarse roots!
"watdecaydry": "0.0",
"watdecaywet": "0.1",
"ligshoot": "0.24", # Based on White et al. 2000 for ENF
"ligroot": "0.22", # Based on White et al. 2000
"rateuptake": "1.9", # set somewhat (very) arbitarly to get an LAI ~ 4.
"rateloss": "0.3",
"topsoil_depth": "50.0",
"rooting_depth": "2000.0",
"topsoil_type": topsoil_type,
"rootsoil_type": rootsoil_type,
"ctheta_topsoil": "-999.9", # Derive based on soil type
"ntheta_topsoil": "-999.9", # Derive based on soil type
"ctheta_root": "-999.9", # Derive based on soil type
"ntheta_root": "-999.9", # Derive based on soil type
"measurement_temp": "25.0",
"dz0v_dh": "0.075", # However I have used value from Jarvis, quoted in Jones 1992, pg. 67. Produces a value within the bounds of 3.5-1.1 mol m-2 s-1 Drake, 2010, GCB for canht=17
"displace_ratio": "0.78",
"g1": "2.74",
#"jmax": "60.0",
#"vcmax": "30.0",
"jmaxna": "60.0",
"jmaxnb": "0.0",
"vcmaxna": "30.0",
"vcmaxnb": "0.0",
"measurement_temp": "25.0",
"heighto": "4.826",
"htpower": "0.35",
"height0": "5.0",
"height1": "30.0",
"leafsap0": "4000.0",
"leafsap1": "2700.0",
"branch0": "5.61",
"branch1": "0.346",
"croot0": "0.34",
"croot1": "0.84",
"targ_sens": "0.5",
"density": "480.0",
"sapturnover": "0.1",
"prescribed_leaf_NC": "0.03",
# control
"adjust_rtslow": "false", # priming, off
"alloc_model": "fixed",
"assim_model": "mate",
"calc_sw_params": "true", #false=use fwp values, true=derive them
"deciduous_model": "false",
"disturbance": "false",
"exudation": "false",
"fixed_stem_nc": "true",
"fixleafnc": "false",
"fixed_lai": "false",
"grazing": "false",
"gs_model": "medlyn",
"model_optroot": "false",
"modeljm": "1",
"ncycle": "false",
"nuptake_model": "1",
"passiveconst": "false",
"print_options": "end",
"ps_pathway": "c3",
"respiration_model": "fixed",
"strfloat": "0",
"sw_stress_model": "1", # Sands and Landsberg
"water_stress": "true",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY_SPIN + cfg_fname)
if RUN_SIM == True:
# dir names
param_dir = os.path.join(base_dir, "params")
met_dir = os.path.join(base_dir, "gday_met_files")
run_dir = os.path.join(base_dir, "outputs")
if SPIN_UP == True:
shutil.copy(os.path.join(param_dir, "%s_model_spunup.cfg" % (experiment_id)),
os.path.join(param_dir, "%s_model_spunup_adj.cfg" % (experiment_id)))
itag = "%s_model_spunup_adj" % (experiment_id)
otag = "%s_simulation" % (experiment_id)
mtag = "%s.daily_run.csv" % (experiment_id)
out_fn = "%s_simulation.csv" % (experiment_id)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "daily",
"sub_daily": "false",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
def main(experiment_id, site, SPIN_UP=True, POST_INDUST=True):
GDAY_SPIN = "gday -s -p "
GDAY = "gday -p "
# dir names
base_param_name = "base_start"
base_dir = os.path.dirname(os.getcwd())
# the base param file has been stored in the params directory, so this
# link isn't necessary
base_param_dir = "/Users/mdekauwe/src/c/gday/example/params"
param_dir = os.path.join(base_dir, "params")
met_dir = os.path.join(base_dir, "met_data")
run_dir = os.path.join(base_dir, "outputs")
if SPIN_UP == True:
# copy base files to make two new experiment files
shutil.copy(os.path.join(base_param_dir, base_param_name + ".cfg"),
os.path.join(param_dir, "%s_%s_model_spinup.cfg" % \
(experiment_id, site)))
# Run model to equilibrium assuming forest, growing C pools from
# effectively zero
itag = "%s_%s_model_spinup" % (experiment_id, site)
otag = "%s_%s_model_spunup" % (experiment_id, site)
mtag = "%s_met_data_equilibrium_50_yrs.csv" % (site)
out_fn = itag + "_equilib.out"
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# default C:N 25.
# Canopy height = 22 m average of 6 plots at UWS, site_description_stuff/EucFACE_Plot_Summary.doc
"activesoil": "0.001",
"activesoiln": "0.00004",
"age": "0.0",
"branch": "0.001",
"branchn": "0.00004",
"cstore": "0.0",
"nstore": "0.0",
"inorgn": "0.00004",
"metabsoil": "0.0",
"metabsoiln": "0.0",
"metabsurf": "0.0",
"metabsurfn": "0.0",
"passivesoil": "0.001",
"passivesoiln": "0.0004",
"prev_sma": "1.0",
"root": "0.001",
"croot": "0.0", # don't simulate coarse roots
"crootn": "0.0", # don't simulate coarse roots
"rootn": "0.00004",
"sapwood": "0.001",
"shoot": "0.001",
"shootn": "0.00004",
"slowsoil": "0.001",
"slowsoiln": "0.00004",
"stem": "0.001",
"stemn": "0.00004",
"stemnimm": "0.00004",
"stemnmob": "0.0",
"structsoil": "0.001",
"structsoiln": "0.00004",
"structsurf": "0.001",
"structsurfn": "0.00004",
# parameters
"alpha_j": "0.308", # Taking the theoretical maximum (from Belinda) 0.385 x 0.8 (leaf absorptance) = 0.308
"intercep_frac": "0.15",
"max_intercep_lai": "3.0",
"latitude": "-33.61",
"albedo": "0.2",
"finesoil": "0.2", # silt + clay fraction. Surface soil texture (upper 45 cm) for Clarenden sand: 80 +/- 8% sand, 9 +/- 5% silt, 11 +/- 3% clay
"slamax": "4.37", # 43.7 +/- 1.5 cm2 g 1 dry mass
"sla": "4.37", # 43.7 +/- 1.5 cm2 g 1 dry mass
"slazero": "4.37", # 43.7+/- 1.5 cm2 g 1 dry mass
"lai_closed": "0.5", # I am effectively turning this feature off by setting it so low
"c_alloc_fmax": "0.35",
"c_alloc_fmin": "0.15",
"c_alloc_rmax": "0.35",
"c_alloc_rmin": "0.05",
"c_alloc_bmax": "0.1",
"c_alloc_bmin": "0.1",
"c_alloc_cmax": "0.0", # turn off coarse roots!
"fretrans": "0.5",
"rretrans": "0.0",
"bretrans": "0.0",
"wretrans": "0.0",
"cretrans": "0.0",
"ncwnewz": "0.003", #New stem ring N:C at zero leaf N:C (mobile)
"ncwnew": "0.003", #New stem ring N:C at critical leaf N:C (mob)
"ncwimmz": "0.003", #Immobile stem N C at zero leaf N C
"ncwimm": "0.003", #Immobile stem N C at critical leaf N C
"ncbnewz": "0.003", #new branch N C at zero leaf N C
"ncbnew": "0.003", #new branch N C at critical leaf N C
"nccnewz": "0.003", #new coarse root N C at zero leaf N C
"nccnew": "0.003", #new coarse root N C at critical leaf N C
"ncrfac": "0.8",
"ncmaxfyoung": "0.04",
"ncmaxfold": "0.04",
"ncmaxr": "0.03",
"retransmob": "0.0",
"fdecay": "0.6", # 18 mth turnover * 1/30
"fdecaydry": "0.6", # 18 mth turnover * 1/30
"rdecay": "0.6",
"rdecaydry": "0.6",
"crdecay": "0.00", # turn off coarse roots!
"bdecay": "0.02", # no idea, assuming 50 years
"wdecay": "0.02", # no idea, assuming 50 years
"watdecaydry": "0.0",
"watdecaywet": "0.1",
"ligshoot": "0.18", # Based on white et al. 2000 #"0.145", # assuming leaf and root same as DE word document
"ligroot": "0.22", # Based on white et al. 2000 # assuming leaf and root same as DE word document
"rateuptake": "4.0",
"rateloss": "0.1", # was 0.1
"topsoil_depth": "450.0", # Not needed as I have supplied the root zone water and topsoil water available
"rooting_depth": "2000.0", # Not needed as I have supplied the root zone water and topsoil water available
"wcapac_root": "300.0", # [mm] (FC-WP)*rooting_depth. But using 2.0 m, site_description_stuff/EucFACE_Plot_Summary.doc
"wcapac_topsoil": "67.5", # [mm] (FC-WP)*rooting_depth. But using 0.45 m, site_description_stuff/EucFACE_Plot_Summary.doc
"ctheta_topsoil": "0.65", # Derive based on soil type loamy_sand
"ntheta_topsoil": "8.0", # Derive based on soil type loamy_sand
"ctheta_root": "0.525", # Derive based on soil type sandy_clay_loam
"ntheta_root": "5.5", # Derive based on soil type sandy_clay_loam
"topsoil_type": "loamy_sand",
"rootsoil_type": "sandy_clay_loam",
#"dz0v_dh": "0.1",
#"z0h_z0m": "1.0",
#"displace_ratio": "0.67",
"dz0v_dh": "0.05", # Using Value from JULES for TREE PFTs as I don't know what is best. However I have used value from Jarvis, quoted in Jones 1992, pg. 67. Produces a value within the bounds of 3.5-1.1 mol m-2 s-1 Drake, 2010, GCB for canht=17
"displace_ratio": "0.75", # From Jones, pg 67, following Jarvis et al. 1976
"z0h_z0m": "1.0",
"g1": "3.8667", # Fit by Me to Teresa's data 7th Nov 2013
"jmaxna": "31.5", # "jmaxna": "133.35", # at 22 deg c
"jmaxnb": "0.0", # "jmaxnb": "0.0", # at 22 deg c
"vcmaxna": "15.6", # "vcmaxna": "66.04", # at 22 deg c
"vcmaxnb": "0.0", # "vcmaxnb": "0.0", # at 22 deg c
"measurement_temp": "22.0", # parameters obtained at 22 not 25 degrees
"heighto": "4.826",
"htpower": "0.35",
"height0": "5.0",
"height1": "25.0",
"leafsap0": "4000.0", #"4000.0",
"leafsap1": "2700.0", #2700
"branch0": "5.61",
"branch1": "0.346",
"croot0": "0.34",
"croot1": "0.84",
"targ_sens": "0.5",
"density": "480.0",
"nf_min": "0.005",
"nf_crit": "0.015",
"sapturnover": "0.1",
# control
"alloc_model": "allometric",
"assim_model": "mate",
"calc_sw_params": "true", #false=use fwp values, true=derive them
"deciduous_model": "false",
"disturbance": "false",
"fixed_stem_nc": "true",
"fixleafnc": "false",
"grazing": "false",
"model_optroot": "false",
"modeljm": "1",
"ncycle": "true",
"nuptake_model": "2",
"output_ascii": "true",
"passiveconst": "false",
"print_options": "end",
"ps_pathway": "c3",
"respiration_model": "fixed",
"strfloat": "0",
"trans_model": "1",
"use_eff_nc": "0",
"use_leuning": "0",
"water_stress": "true",
"sw_stress_model": "1", # Sands and Landsberg
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY_SPIN + cfg_fname)
if POST_INDUST == True:
# run for 260 odd years post industrial with increasing co2/ndep
# copy spunup base files to make two new experiment files
shutil.copy(os.path.join(param_dir, "%s_%s_model_spunup.cfg" % (experiment_id, site)),
os.path.join(param_dir, "%s_%s_model_spunup_adj.cfg" % (experiment_id, site)))
itag = "%s_%s_model_spunup_adj" % (experiment_id, site)
otag = "%s_%s_model_indust" % (experiment_id, site)
mtag = "%s_met_data_industrial_to_present_1750_2011.csv" % (site)
out_fn = itag + "_indust.out"
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
def ambient_sim(experiment_id, site, treatment, ascii=True):
GDAY_EXE = "../src/gday -p "
# --- FILE PATHS, DIR NAMES ETC --- #
#base_dir = os.getcwd()
param_dir = "params"
met_dir = "met_data"
run_dir = "outputs"
# --- CHANGE PARAM VALUES ON THE FLY --- #
itag = "%s_%s_model_youngforest_%s" % (experiment_id, site, treatment)
otag = "%s_%s_model_simulation_%s" % (experiment_id, site, treatment)
mtag = "%s_met_data_%s_co2.csv" % (site, treatment)
out_fn = "D1GDAY%s%s" + (".csv" if ascii else ".bin")
#import pdb; pdb.set_trace()
out_fn = out_fn % (site, treatment.upper())
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# state
"age": "12.0",
# control
"alloc_model": "allometric",
"assim_model": "mate",
"calc_sw_params": "True", #0 uses fwp values, 1= derive them
"deciduous_model": "false",
"fixed_stem_nc": "true",
"fixleafnc": "false",
"grazing": "false",
"model_optroot": "false",
"modeljm": "2",
"nuptake_model": "2",
"output_ascii": str(ascii),
"passiveconst": "false",
"print_options": "daily",
"ps_pathway": "c3",
"respiration_model": "fixed",
"strfloat": "0",
"trans_model": "1",
"use_eff_nc": "0",
"use_leuning": "0",
"water_stress": "true",
"sw_stress_model": "1", # Landsberg
}
ad.adjust_param_file(cfg_fname, replace_dict)
# --- RUN THE MODEL --- #
os.system(GDAY_EXE + cfg_fname)
# translate output to NCEAS style output
# add this directory to python search path so we can find the scripts!
sys.path.append("scripts")
import translate_GDAY_output_to_NCEAS_format as tr
if ascii:
tr.translate_output(out_fname, met_fname, binary=False)
else:
tr.translate_output(out_fname, met_fname, binary=True)
def main(experiment_id,
site,
SPIN_UP=True,
POST_INDUST=True,
SPIN_UP_SIMS=True):
GDAY_SPIN = "gday -s -p "
GDAY = "gday -p "
base_dir = os.path.dirname(os.getcwd())
# dir names
base_dir = "/Users/%s/src/c/gday/example/params" % (USER)
param_dir = "params"
met_dir = os.path.join(base_dir, "met_data")
run_dir = os.path.join(base_dir, "outputs")
if SPIN_UP == True:
# copy base files to make two new experiment files
shutil.copy(os.path.join(base_param_dir, base_param_name + ".cfg"),
os.path.join(param_dir, "%s_%s_model_spinup.cfg" % \
(experiment_id, site)))
# Run model to equilibrium assuming forest, growing C pools from effectively
# zero
itag = "%s_%s_model_spinup" % (experiment_id, site)
otag = "%s_%s_model_spunup" % (experiment_id, site)
mtag = "%s_met_data_equilibrium_50_yrs.csv" % (site)
out_fn = itag + "_equilib.out"
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# state - default C:N 25.
"age": "0.0",
"canht":
"17.0", # Canopy height increased from 16m in 2001 to 18m in 2004 at Duke
"activesoil": "0.001",
"activesoiln": "0.00004",
"age": "0.0",
"branch": "0.001",
"branchn": "0.00004",
"cstore": "0.001",
"inorgn": "0.00004",
"metabsoil": "0.0",
"metabsoiln": "0.0",
"metabsurf": "0.0",
"metabsurfn": "0.0",
"nstore": "0.00004",
"passivesoil": "0.001",
"passivesoiln": "0.0004",
"prev_sma": "-999.9",
"root": "0.001",
"root_depth": "-9999.9",
"rootn": "0.00004",
"sapwood": "0.001",
"shoot": "0.001",
"shootn": "0.00004",
"slowsoil": "0.001",
"slowsoiln": "0.00004",
"stem": "0.001",
"stemn": "0.00004",
"stemnimm": "0.00004",
"stemnmob": "0.0",
"structsoil": "0.001",
"structsoiln": "0.00004",
"structsurf": "0.001",
"structsurfn": "0.00004",
"croot": "0.0", # don't simulate coarse roots
"crootn": "0.0", # don't simulate coarse roots
# parameters
"latitude": "35.9",
"intercep_frac": "0.15",
"max_intercep_lai": "3.0",
"albedo": "0.123", # modis site avg
"finesoil":
"0.51", # set based on silt+clay fractions of topsoil 0.42+0.09=0.5
"slamax": "4.4", # Protocol [m2 kg-1 DW]
"sla": "4.4", # Protocol [m2 kg-1 DW]
"slazero": "4.4", # Protocol [m2 kg-1 DW]
"cfracts": "0.5",
"lai_closed":
"0.5", # I am effectively turning this feature off by setting it so low
#"c_alloc_fmax": "0.25",
#"c_alloc_fmin": "0.25",
#"c_alloc_rmax": "0.05",
#"c_alloc_rmin": "0.05",
#"c_alloc_bmax": "0.2",
#"c_alloc_bmin": "0.2",
#"c_alloc_fmax": "0.3",
#"c_alloc_fmin": "0.3",
#"c_alloc_rmax": "0.3",
#"c_alloc_rmin": "0.3",
#"c_alloc_bmax": "0.2",
#"c_alloc_bmin": "0.2",
#"c_alloc_cmax": "0.0", # turn off coarse roots!
"c_alloc_fmax": "0.35",
"c_alloc_fmin": "0.15",
"c_alloc_rmax": "0.35",
"c_alloc_rmin": "0.05",
"c_alloc_bmax": "0.1",
"c_alloc_bmin": "0.1",
"c_alloc_cmax": "0.0", # turn off coarse roots!
"fretrans": "0.5",
"rretrans": "0.0",
"bretrans": "0.0",
"wretrans": "0.0",
"ncwnewz": "0.003",
"ncwnew": "0.003",
"ncwimmz": "0.003",
"ncwimm": "0.003",
"ncbnewz": "0.003",
"ncbnew": "0.003",
"ncrfac": "0.8",
"ncmaxfyoung": "0.04",
"ncmaxfold": "0.04",
"ncmaxr": "0.03",
"retransmob": "0.0",
"fdecay": "0.59988", # Protocol [years-1]
"fdecaydry": "0.59988", # Protocol
"rdecay": "0.33333", # Protocol
"rdecaydry": "0.33333", # Protocol
"bdecay": "0.02", # No data, assuming 50 years
"wdecay": "0.02",
"crdecay": "0.00", # turn off coarse roots!
"watdecaydry": "0.0",
"watdecaywet": "0.1",
"ligshoot": "0.24", # Based on White et al. 2000 for ENF
"ligroot": "0.22", # Based on White et al. 2000
"rateuptake":
"2.2", # set somewhat (very) arbitarly to get an LAI ~ 4.
"rateloss": "0.5",
"wcapac_root":
"96.75", # [mm] (FC (m3/m-3)-WP (m3/m-3)) * rooting_depth (mm) using derived values and depth from protocol, 750 mm (FC=0.164 - WP=0.035)
"wcapac_topsoil":
"25.8", # [mm] (FC (m3/m-3)-WP (m3/m-3)) * rooting_depth (mm) using derived values and depth from protocol, assuming 200 mm top soil following Corbeels 2005a (FC=0.164 - WP=0.035)
"ctheta_topsoil": "0.5", # Derive based on soil type clay_loam
"ntheta_topsoil": "5.0", # Derive based on soil type clay_loam
"ctheta_root": "0.4", # Derive based on soil type clay
"ntheta_root": "3.0", # Derive based on soil type clay
"topsoil_type": "clay_loam",
"rootsoil_type": "clay",
"measurement_temp": "25.0",
"dz0v_dh":
"0.075", # However I have used value from Jarvis, quoted in Jones 1992, pg. 67. Produces a value within the bounds of 3.5-1.1 mol m-2 s-1 Drake, 2010, GCB for canht=17
"displace_ratio": "0.78",
"g1": "2.74",
#"jmaxna": "60.0", # Original values Belinda had, I think based on Crous 2008, fig 2. Although those values I think are measured at 28 and 30 deg, the assumption being here that this is the same as 25 deg!
#"jmaxnb": "0.0", # Original values Belinda had, I think based on Crous 2008, fig 2. Although those values I think are measured at 28 and 30 deg, the assumption being here that this is the same as 25 deg!
#"vcmaxna": "30.61",# Original values Belinda had, I think based on Crous 2008, fig 2. Although those values I think are measured at 28 and 30 deg, the assumption being here that this is the same as 25 deg!
#"vcmaxnb": "0.0", # Original values Belinda had, I think based on Crous 2008, fig 2. Although those values I think are measured at 28 and 30 deg, the assumption being here that this is the same as 25 deg!
"vcmaxna": "22.29",
"vcmaxnb": "8.45",
"jv_slope": "1.86",
"jv_intercept": "0.0",
"sapturnover": "0.1",
"heighto": "4.826",
"htpower": "0.35",
"height0": "5.0",
"height1": "20.0",
"leafsap0": "8000.0",
"leafsap1": "3060.0", # Duke protocol
"branch0": "5.61",
"branch1": "0.346",
"targ_sens": "0.5",
"density": "420.0",
# control
"adjust_rtslow": "false", # priming, off
"alloc_model": "allometric",
"assim_model": "mate",
"calc_sw_params": "false", #false=use fwp values, true=derive them
"deciduous_model": "false",
"disturbance": "false",
"exudation": "false",
"fixed_stem_nc": "true",
"fixleafnc": "false",
"grazing": "false",
"gs_model": "medlyn",
"model_optroot": "false",
"modeljm": "2",
"ncycle": "true",
"nuptake_model": "2",
"passiveconst": "false",
"print_options": "end",
"ps_pathway": "c3",
"respiration_model": "fixed",
"strfloat": "0",
"sw_stress_model": "1", # Sands and Landsberg
"trans_model": "1",
"use_eff_nc": "0",
"use_leuning": "0",
"water_stress": "true",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY_SPIN + cfg_fname)
if POST_INDUST == True:
# run for 200 odd years post industrial with increasing co2/ndep
# we are swapping forest params for grass params now
# copy spunup base files to make two new experiment files
shutil.copy(
os.path.join(param_dir,
"%s_%s_model_spunup.cfg" % (experiment_id, site)),
os.path.join(param_dir,
"%s_%s_model_spunup_adj.cfg" % (experiment_id, site)))
itag = "%s_%s_model_spunup_adj" % (experiment_id, site)
otag = "%s_%s_model_indust" % (experiment_id, site)
mtag = "%s_met_data_industrial_to_present_1850_1983.csv" % (site)
out_fn = itag + "_indust.out"
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# git stuff
#"git_hash": str(git_revision),
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# state - default C:N 25.
"age": "0.0",
"branch": "0.0",
"branchn": "0.0",
"canht": "0.79", # Taken default C3grass value from JULES
"cstore": "0.001",
"nstore": "0.00004",
"croot": "0.0", # don't simulate coarse roots
"crootn": "0.0", # don't simulate coarse roots
"root": "0.001",
"rootn": "0.00004",
"sapwood": "0.0",
"shoot": "0.001",
"shootn": "0.00004",
"stem": "0.0",
"stemn": "0.0",
"stemnimm": "0.0",
"stemnmob": "0.0",
"nepsum": "0.0",
"nppsum": "0.0",
# parameters
"ligshoot": "0.09", # Smith et al. 2000, GRASS
"ligroot": "0.22", # Smith et al. 2000
"age": "1.0",
"slamax": "6.0",
"sla": "6.0",
"slazero": "6.0",
"cfracts": "0.5",
"lai_closed":
"0.5", # I am effectively turning this feature off by setting it so low
"c_alloc_fmax": "0.8",
"c_alloc_fmin": "0.2",
"c_alloc_rmax": "0.8",
"c_alloc_rmin": "0.2",
"c_alloc_bmax": "0.0",
"c_alloc_bmin": "0.0",
"c_alloc_cmax": "0.0", # turn off coarse roots!
"fretrans": "0.4",
"rretrans": "0.0",
"bretrans": "0.0",
"wretrans": "0.0",
"ncwnewz": "0.0",
"ncwnew": "0.0",
"ncwimmz": "0.0",
"ncwimm": "0.0",
"ncbnewz": "0.0",
"ncbnew": "0.0",
"ncrfac": "0.7",
"ncmaxfyoung": "0.035",
"ncmaxfold": "0.035",
"ncmaxr": "0.0287",
"retransmob": "0.0",
"fdecay": "1.0",
"fdecaydry": "1.0",
"rdecay": "1.0",
"rdecaydry": "1.0",
"bdecay": "0.0",
"wdecay": "0.0",
"watdecaydry": "0.0",
"watdecaywet": "0.1",
"crdecay": "0.00", # turn off coarse roots!
"dz0v_dh": "0.10", # Taken default C3grass value from JULES
"displace_ratio": "0.64", #Jones 1992, pg. 67.
"z0h_z0m":
"1.0", # Assume z0m = z0h, probably a big assumption [as z0h often < z0m.], see comment in code!!
"jmaxna": "62.0", # assuming j = v * 2
"jmaxnb": "0.0", # assuming no intercept
"vcmaxna":
"31.0", # C3 grasses - CLM4 tech doc, table 8.2, Oleson et al 2010, page 176
"vcmaxnb": "0.0", # assuming no intercept
# control
"adjust_rtslow": "false", # priming, off
"alloc_model": "grasses",
"assim_model": "mate",
"calc_sw_params": "false", #false=use fwp values, true=derive them
"deciduous_model": "false",
"disturbance": "false",
"exudation": "false",
"fixed_stem_nc": "true",
"fixleafnc": "false",
"grazing": "false",
"gs_model": "medlyn",
"model_optroot": "false",
"modeljm": "1",
"nuptake_model": "2",
"ncycle": "true",
"passiveconst": "false",
"print_options": "end",
"ps_pathway": "c3",
"respiration_model": "fixed",
"strfloat": "0",
"sw_stress_model": "1", # Sands and Landsberg
"trans_model": "1",
"use_eff_nc": "0",
"use_leuning": "0",
"water_stress": "true",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
def ambient_sim(experiment_id, site, treatment, ascii=True):
GDAY_EXE = "../src/gday -p "
# --- FILE PATHS, DIR NAMES ETC --- #
#base_dir = os.getcwd()
param_dir = "params"
met_dir = "met_data"
run_dir = "outputs"
# --- CHANGE PARAM VALUES ON THE FLY --- #
itag = "%s_%s_model_youngforest_%s" % (experiment_id, site, treatment)
otag = "%s_%s_model_simulation_%s" % (experiment_id, site, treatment)
mtag = "%s_met_data_%s_co2.csv" % (site, treatment)
out_fn = "D1GDAY%s%s" + (".csv" if ascii else ".bin")
#import pdb; pdb.set_trace()
out_fn = out_fn % (site, treatment.upper())
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# state
"age": "12.0",
# control
"alloc_model": "allometric",
"assim_model": "mate",
"calc_sw_params": "True", #0 uses fwp values, 1= derive them
"deciduous_model": "false",
"fixed_stem_nc": "true",
"fixleafnc": "false",
"grazing": "false",
"model_optroot": "false",
"modeljm": "2",
"nuptake_model": "2",
"output_ascii" : str(ascii),
"passiveconst": "false",
"print_options": "daily",
"ps_pathway": "c3",
"respiration_model": "fixed",
"strfloat": "0",
"trans_model": "1",
"use_eff_nc": "0",
"use_leuning": "0",
"water_stress": "true",
"sw_stress_model": "1", # Landsberg
}
ad.adjust_param_file(cfg_fname, replace_dict)
# --- RUN THE MODEL --- #
os.system(GDAY_EXE + cfg_fname)
# translate output to NCEAS style output
# add this directory to python search path so we can find the scripts!
sys.path.append("scripts")
import translate_GDAY_output_to_NCEAS_format as tr
if ascii:
tr.translate_output(out_fname, met_fname, binary=False)
else:
tr.translate_output(out_fname, met_fname, binary=True)
def main(experiment_id, latitude, longitude, treatment, scheme):
GDAY = "canopy_scaling -p "
# dir names
base_param_name = "base_start"
base_dir = os.path.dirname(os.getcwd())
base_param_dir = "../../params"
param_dir = os.path.join(base_dir, "params")
met_dir = os.path.join(base_dir, "met_data")
run_dir = os.path.join(base_dir, "outputs")
# copy base files to make two new experiment files
shutil.copy(os.path.join(base_param_dir, base_param_name + ".cfg"),
os.path.join(param_dir, "%s_model_run.cfg" % \
(experiment_id)))
if scheme == "mate":
sub_daily = "false"
alpha_j = 0.26
else:
sub_daily = "true"
alpha_j = 0.308
itag = "%s_model_run" % (experiment_id)
otag = "%s_simulation" % (experiment_id)
mtag = "%s_%s.csv" % (scheme, treatment)
out_fn = "%s_simulation.csv" % (experiment_id)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
"fix_lai": "1.2",
#"alpha_j": "0.30588",
"alpha_j": "%f" % (alpha_j),
"max_intercep_lai": "3.0",
"latitude": "%f" % (latitude),
"longitude": "%f" % (longitude),
"slamax": "4.37", # 43.7 +/- 1.5 cm2 g 1 dry mass
"sla": "4.37", # 43.7 +/- 1.5 cm2 g 1 dry mass
"slazero": "4.37", # 43.7+/- 1.5 cm2 g 1 dry mass
"lai_cover": "0.5",
"kn": "0.3",
"g1": "3.8667", # Fit by Me to Teresa's data 7th Nov 2013
"jmax": "55.0", # 2.0 * vcmax
"vcmax": "110.0", # CABLE EBF
"jmaxna": "110.0",
"jmaxnb": "0.0",
"vcmaxna": "55.0",
"vcmaxnb": "0.0",
"measurement_temp": "25.0",
"prescribed_leaf_NC": "0.03",
# control
"assim_model": "mate",
"fixed_lai": "true",
"gs_model": "medlyn",
"modeljm": "1",
"ncycle": "false",
"ps_pathway": "c3",
"respiration_model": "fixed",
"sub_daily": "%s" % (sub_daily),
"sw_stress_model": "1", # Sands and Landsberg
"water_stress": "false",
}
ad.adjust_param_file(cfg_fname, replace_dict)
ofname = " > outputs/%s_%s.csv" % (scheme, treatment)
#print(cfg_fname)
#os.system(GDAY + cfg_fname + ofname)
os.system(GDAY + cfg_fname)
def main(experiment_id, site, SPIN_UP=True, POST_INDUST=True, ELE_INITIALIZATION=True, ELE_SPINUP=True, ELE_EQUILIB=True):
GDAY_SPIN = "./gday -s -p "
GDAY = "./gday -p "
# dir names
base_param_name = "base_start_with_P"
base_param_dir = "/Users/%s/Documents/Research/Projects/Temperature_acclimation/Git/GDAY/params" % (USER)
base_dir = os.path.dirname(os.getcwd())
param_dir = os.path.join(base_dir, "params")
met_dir = os.path.join(base_dir, "met_data")
run_dir = os.path.join(base_dir, "outputs")
if SPIN_UP == True:
# copy base files to make two new experiment files
shutil.copy(os.path.join(base_param_dir, base_param_name + ".cfg"),
os.path.join(param_dir, "%s_%s_model_spinup.cfg" % \
(experiment_id, site)))
# Run model to equilibrium assuming forest, growing C pools from
# effectively zero
itag = "%s_%s_model_spinup" % (experiment_id, site)
otag = "%s_%s_model_spunup" % (experiment_id, site)
mtag = "%s_met_data_amb_var_co2.csv" % (site)
out_fn = itag + "_equilib.out"
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# default C:N 25.
# Canopy height = 22 m average of 6 plots at UWS, site_description_stuff/EucFACE_Plot_Summary.doc
"activesoil": "0.001",
"activesoiln": "0.00004",
"activesoilp": "0.000002",
"age": "100.0",
"branch": "0.001",
"branchn": "0.00004",
"branchp": "0.000002",
"cstore": "0.0",
"nstore": "0.0",
"pstore": "0.0",
"inorgn": "0.0000", # 0.00004
"inorglabp": "0.0000", # 0.00004
"inorgsorbp": "0.0",
"inorgssorbp": "0.0",
"inorgoccp": "0.0",
"inorgparp": "0.054",
"metabsoil": "0.0",
"metabsoiln": "0.0",
"metabsoilp": "0.0",
"metabsurf": "0.0",
"metabsurfn": "0.0",
"metabsurfp": "0.0",
"passivesoil": "0.001",
"passivesoiln": "0.0004",
"passivesoilp": "0.000002",
"prev_sma": "1.0",
"root": "0.001",
"croot": "0.0", # don't simulate coarse roots
"crootn": "0.0", # don't simulate coarse roots
"crootp": "0.0", # don't simulate coarse roots
"rootn": "0.00004",
"rootp": "0.000002",
"sapwood": "0.001",
"shoot": "0.001",
"shootn": "0.00004",
"shootp": "0.000002",
"slowsoil": "0.001",
"slowsoiln": "0.00004",
"slowsoilp": "0.000002",
"stem": "0.001",
"stemn": "0.00004",
"stemp": "0.000002",
"stemnimm": "0.00004",
"stempimm": "0.000002",
"stemnmob": "0.0",
"stempmob": "0.0",
"structsoil": "0.001",
"structsoiln": "0.00004",
"structsoilp": "0.000002",
"structsurf": "0.001",
"structsurfn": "0.00004",
"structsurfp": "0.0000024",
# parameters
"resp_coeff": "0.2",
"alpha_j": "0.308", # Taking the theoretical maximum (from Belinda) 0.385 x 0.8 (leaf absorptance) = 0.308
"intercep_frac": "0.15",
"max_intercep_lai": "3.0",
"latitude": "-33.61",
"albedo": "0.2",
"finesoil": "0.2", # silt + clay fraction. Surface soil texture (upper 45 cm) for Clarenden sand: 80 +/- 8% sand, 9 +/- 5% silt, 11 +/- 3% clay
"slamax": "5.1", # current unit: m2 kg-1; original unit: 43.7 +/- 1.5 cm2 g 1 dry mass
"sla": "5.1", # current unit: m-2 kg-1; original unit: 43.7 +/- 1.5 cm2 g 1 dry mass
"slazero": "5.1", # current unit: m-2 kg-1; original unit: 43.7+/- 1.5 cm2 g 1 dry mass
"lai_closed": "0.5", # I am effectively turning this feature off by setting it so low
"c_alloc_fmax": "0.45", # 0.35
"c_alloc_fmin": "0.05", # 0.15
"c_alloc_rmax": "0.45", # 0.35
"c_alloc_rmin": "0.05", # 0.05
"c_alloc_bmax": "0.1", # 0.1
"c_alloc_bmin": "0.1", # 0.1
"c_alloc_cmax": "0.0", # turn off coarse roots!
"biochemical_p_constant": "150.0",
"fretrans": "0.5",
"fretransp": "0.5",
"rretrans": "0.0",
"bretrans": "0.0",
"wretrans": "0.7",
"cretrans": "0.0",
"crit_n_cost_of_p": "15.0",
"ncwnewz": "0.003", #New stem ring N:C at zero leaf N:C (mobile)
"ncwnew": "0.003", #New stem ring N:C at critical leaf N:C (mob)
"ncwimmz": "0.003", #Immobile stem N C at zero leaf N C
"ncwimm": "0.003", #Immobile stem N C at critical leaf N C
"ncbnewz": "0.003", #new branch N C at zero leaf N C
"ncbnew": "0.003", #new branch N C at critical leaf N C
"nccnewz": "0.003", #new coarse root N C at zero leaf N C
"nccnew": "0.003", #new coarse root N C at critical leaf N C
"ncrfac": "0.8",
"ncmaxfyoung": "0.04",
"ncmaxfold": "0.04",
"ncmaxr": "0.03",
"retransmob": "0.0",
"fdecay": "0.6", # 18 mth turnover * 1/30
"fdecaydry": "0.6", # 18 mth turnover * 1/30
"max_p_biochemical": "0.001",
"rdecay": "0.6",
"rdecaydry": "0.6",
"crdecay": "0.00", # turn off coarse roots!
"bdecay": "0.1", # no idea, assuming 50 years
"wdecay": "0.1", # no idea, assuming 50 years
"watdecaydry": "0.0",
"watdecaywet": "0.1",
"ligshoot": "0.18", # Based on white et al. 2000 #"0.145", # assuming leaf and root same as DE word document
"ligroot": "0.22", # Based on white et al. 2000 # assuming leaf and root same as DE word document
"rateuptake": "1.8",
"rateloss": "0.05", # was 0.1
"topsoil_depth": "450.0", # Not needed as I have supplied the root zone water and topsoil water available
"rooting_depth": "2500.0", # Not needed as I have supplied the root zone water and topsoil water available
"wcapac_root": "300.0", # [mm] (FC-WP)*rooting_depth. But using 2.0 m, site_description_stuff/EucFACE_Plot_Summary.doc
"wcapac_topsoil": "67.5", # [mm] (FC-WP)*rooting_depth. But using 0.45 m, site_description_stuff/EucFACE_Plot_Summary.doc
"ctheta_topsoil": "0.65", # Derive based on soil type loamy_sand
"ntheta_topsoil": "8.0", # Derive based on soil type loamy_sand
"ctheta_root": "0.525", # Derive based on soil type sandy_clay_loam
"ntheta_root": "5.5", # Derive based on soil type sandy_clay_loam
"topsoil_type": "loamy_sand",
"rootsoil_type": "sandy_clay_loam",
"soil_order": "andisol",
"ks": "0.5",
"kp": "0.3",
"krp": "0.00001",
#"dz0v_dh": "0.1",
#"z0h_z0m": "1.0",
#"displace_ratio": "0.67",
"dz0v_dh": "0.05", # Using Value from JULES for TREE PFTs as I don't know what is best. However I have used value from Jarvis, quoted in Jones 1992, pg. 67. Produces a value within the bounds of 3.5-1.1 mol m-2 s-1 Drake, 2010, GCB for canht=17
"displace_ratio": "0.75", # From Jones, pg 67, following Jarvis et al. 1976
"z0h_z0m": "1.0",
"g1": "3.8667", # 3.8667 Fit by Me to Teresa's data 7th Nov 2013; or 2.78 from stomatal model
#"jmaxna": "14.891", #
#"jmaxpa": "291.4305", #
#"jmaxnb": "99.497", #
#"jmaxpb": "99.949", # 88.56
#"vcmaxna": "10.453", # 6.426
#"vcmaxpa": "153.1748",
#"vcmaxnb": "74.522", # 60.526
#"vcmaxpb": "57.242", # 27.66
"jmaxna": "49.930", # forcing intercept to zero; if use all species df, 49.743
"jmaxpa": "933.90", # forcing intercept to zero; if use all species df, 842.46
"jmaxnb": "0.0", # forcing intercept to zero
"jmaxpb": "0.0", # forcing intercept to zero
"vcmaxna": "27.707", # forcing intercept to zero; if use all species df, 27.627
"vcmaxpa": "516.83", # forcing intercept to zero; if use all species df, 468.76
"vcmaxnb": "0.0", # forcing intercept to zero
"vcmaxpb": "0.0", # forcing intercept to zero
"measurement_temp": "25.0", # parameters obtained at 22 not 25 degrees
"heighto": "4.826",
"htpower": "0.35",
"height0": "5.0",
"height1": "25.0",
"leafsap0": "4000.0", # "4000.0",
"leafsap1": "2700.0", # 2700
"branch0": "5.61",
"branch1": "0.346",
"croot0": "0.34",
"croot1": "0.84",
"targ_sens": "0.5",
"density": "800.0", # 480
"nf_min": "0.005",
"nf_crit": "0.015",
"sapturnover": "0.1",
"p_atm_deposition": "0.000086", # 1/4 of value from Table 4, Olander et al. 2005; Earth Interactions.
"p_rate_par_weather": "0.0001", # Calcualted so that weathering rate = atm deposition;
"passpcmin": "0.005",
"passpcmax": "0.05",
"psecmnp": "0.000022",
"pcbnew": "0.0003",
"pcbnewz": "0.0003",
"pccnew": "0.0003",
"pccnewz": "0.0003",
"pcmaxfold": "0.002", # 0.0015 Table 3, Olander et al. 2005, Earth Interactions.
"pcmaxfyoung": "0.002",
"pcmaxr": "0.0006",
"pcrfac": "0.8",
"pcwimm": "0.00014",
"pcwimmz": "0.00014",
"pcwnew": "0.00014",
"pcwnewz": "0.00014",
"pf_crit": "0.002",
"pf_min": "0.0002",
"phmax": "7.6",
"phmin": "5.0",
"phtextmin": "0.000008",
"phtextmax": "0.00015",
"phtextslope": "0.00004",
"pmax": "0.002",
"pmin": "0.01",
"pmin0": "0.0",
"pmincrit": "2.0",
"prateloss": "0.05",
"prateuptake": "3.6", # Fitted value to obtain balance between uptake N:P ratio and reasonable P labile pool
"slowpcmin": "0.005",
"slowpcmax": "0.011111",
"soilph": "4.5", # Olander et al., 2005, Earth Interactions.
"sorpmx": "5.0",
"sorpaf": "1.0",
"structcp": "5500.0",
"structratp": "0.0",
# control
"adjust_rtslow": "false", # priming, off
"alloc_model": "allometric",
"assim_model": "mate",
"calc_sw_params": "true", #false=use fwp values, true=derive them
"deciduous_model": "false",
"disturbance": "false",
"exudation": "false",
"fixed_stem_nc": "true",
"fixed_stem_pc": "true",
"fixleafnc": "false",
"fixleafpc": "false",
"grazing": "false",
"gs_model": "medlyn",
"aci_relationship": "ellsworth",
"model_optroot": "false",
"modeljm": "1",
"ncycle": "true",
"pcycle": "false",
"nuptake_model": "1",
"puptake_model": "1",
"triose_p": "false",
"output_ascii": "true",
"passiveconst": "false",
"print_options": "end",
"ps_pathway": "c3",
"respiration_model": "fixed",
"strfloat": "0",
"strpfloat": "0",
"sw_stress_model": "1", # Sands and Landsberg
"use_eff_nc": "0",
"text_effect_p": "1",
"water_stress": "true",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY_SPIN + cfg_fname)
if POST_INDUST == True:
# copy spunup base files to make two new experiment files
shutil.copy(os.path.join(param_dir, "%s_%s_model_spunup.cfg" % (experiment_id, site)),
os.path.join(param_dir, "%s_%s_model_spunup_adj.cfg" % (experiment_id, site)))
itag = "%s_%s_model_spunup_adj" % (experiment_id, site)
otag = "%s_%s_model_indust" % (experiment_id, site)
mtag = "%s_met_data_amb_var_co2.csv" % (site)
out_fn = "%s_amb_equilib.csv" % (site)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "end",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
if POST_INDUST == True:
# copy spunup base files to make two new experiment files
shutil.copy(os.path.join(param_dir, "%s_%s_model_spunup.cfg" % (experiment_id, site)),
os.path.join(param_dir, "%s_%s_model_spunup_adj.cfg" % (experiment_id, site)))
itag = "%s_%s_model_spunup_adj" % (experiment_id, site)
otag = "%s_%s_model_indust" % (experiment_id, site)
mtag = "%s_met_data_amb_var_co2.csv" % (site)
out_fn = "%s_amb_equilib.csv" % (site)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "daily",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# elevated co2 initialization to store output
if ELE_INITIALIZATION == True:
# copy last cfg file and make new one
shutil.copy(os.path.join(param_dir, "%s_%s_model_indust.cfg" % (experiment_id, site)),
os.path.join(param_dir, "%s_%s_model_indust_adj.cfg" % (experiment_id, site)))
itag = "%s_%s_model_indust_adj" % (experiment_id, site)
otag = "%s_%s_model_ele_initial" % (experiment_id, site)
mtag = "%s_met_data_%s_var_co2.csv" % (site, treatment)
out_fn = "%s_ele_initial.csv" % (site)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "daily",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# elevated co2 initialization to store cfg
if ELE_INITIALIZATION == True:
# copy last cfg file and make new one
shutil.copy(os.path.join(param_dir, "%s_%s_model_indust.cfg" % (experiment_id, site)),
os.path.join(param_dir, "%s_%s_model_indust_adj.cfg" % (experiment_id, site)))
itag = "%s_%s_model_indust_adj" % (experiment_id, site)
otag = "%s_%s_model_ele_initial" % (experiment_id, site)
mtag = "%s_met_data_%s_var_co2.csv" % (site, treatment)
out_fn = "%s_ele_initial.csv" % (site)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "end",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# elevated CO2 during spin up to store cfg file
if ELE_SPINUP == True:
# copy last cfg file and make new one
shutil.copy(os.path.join(param_dir, "%s_%s_model_ele_initial.cfg" % (experiment_id, site)),
os.path.join(param_dir, "%s_%s_model_ele_spinup.cfg" % (experiment_id, site)))
itag = "%s_%s_model_ele_spinup" % (experiment_id, site)
otag = "%s_%s_model_ele_spunup" % (experiment_id, site)
mtag = "%s_met_data_%s_var_co2.csv" % (site, treatment)
out_fn = "FACE_EUC_ele_spunup_%s%s.csv" % (site, treatment.upper())
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "end",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY_SPIN + cfg_fname)
# elevated co2 final equilibrium simulation
if ELE_EQUILIB == True:
# copy last cfg file and make new one
shutil.copy(os.path.join(param_dir, "%s_%s_model_ele_spunup.cfg" % (experiment_id, site)),
os.path.join(param_dir, "%s_%s_model_ele_equil.cfg" % (experiment_id, site)))
itag = "%s_%s_model_ele_equil" % (experiment_id, site)
otag = "%s_%s_model_ele_final" % (experiment_id, site)
mtag = "%s_met_data_%s_var_co2.csv" % (site, treatment)
out_fn = "%s_ele_final_equilib.csv" % (site)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "daily",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
def main(site, SPIN_UP=True):
GDAY_SPIN = "./gday -s -p "
GDAY = "./gday -p "
# dir names
base_param_name = "base_start_with_P"
base_dir = os.path.dirname(os.getcwd())
base_param_dir = os.path.join(d, "code/example/params")
param_dir = os.path.join(d, "params/Run1")
run_dir = os.path.join(d, "outputs/Run1")
if SPIN_UP == True:
# copy base files to make two new experiment files
shutil.copy(os.path.join(base_param_dir, base_param_name + ".cfg"),
os.path.join(param_dir, "%s_model_spinup.cfg" % \
(site)))
# Run model to equilibrium assuming forest, growing C pools from effectively
# zero
itag = "%s_model_spinup" % (site)
otag = "%s_model_spunup" % (site)
# mtag = "%s_met_forcing_transient_co2_amb.csv" % (site)
out_fn = itag + "_equilib.csv"
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
# met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
# "met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# state - default C:N 25.
"shoot": "11.0", # assuming total 10 g plant, 2 in leaf
"shootn": "0.3", # 0.0008 C:N = 25
"shootp": "0.01", # 0.00003 C:P = 680
"stem": "1700.0", # assuming total 10 g plant, 6 in stem
"stemn": "0.2", # 0.0003 C:N = 200
"stemp": "0.0005", # 0.000018 C:P = 3333.33
"root": "3.0", # assuming total 10 g plant, 2 in root
"rootn": "0.07", # 0.00056 Root CN = leaf * 0.7
"rootp": "0.002", # 0.000021 Root CP = leaf * 0.7
"activesoil": "11.0", # guess
"activesoiln": "0.7", # C:N = 15
"activesoilp": "0.01", # C:P = 800
"slowsoil": "170.0", # guess
"slowsoiln": "8.0", # C:N = 20
"slowsoilp": "0.08", # C:P = 2000
"passivesoil": "180.0", # analytical
"passivesoiln": "18.0", # C:N = 10
"passivesoilp": "0.9", # C:P = 200
"metabsoil": "0.00", #
"metabsoiln": "0.0", # C:N = 10 <-> 25
"metabsoilp": "0.0", # C:P = 80 <-> 150
"metabsurf": "0.00", #
"metabsurfn": "0.0", # C:N = 10 <-> 25
"metabsurfp": "0.0", # C:P = 80 <-> 150
"structsoil": "0.00", #
"structsoiln": "0.00000", # C:N = 150
"structsoilp": "0.000000", # C:P = 500
"structsurf": "0.00", #
"structsurfn": "0.00000", # C:N = 150
"structsurfp": "0.000000", # C:P = 500
"inorgn": "0.016", # annual input = 0.01 t/ha, monthly rate
"inorgavlp": "0.0005", # annual input = 0.0004 t/ha, monthly rate
"inorgssorbp": "0.00009", #
"inorgoccp": "1.2", #
"inorgparp": "0.00003", # annual input = 0.0004 t/ha, monthly rate
"canht": "30.0", #
"sapwood": "0.01", # initialize value, needed it for initialize alloc_stuffs
# parameters
"co2_in": "350.0", # spin-up value
"I0": "3000.0", # spin-up value, annual rate, unit MJ/m2/yr
"ndep_in": "0.005", # spin-up value, annual rate, unit t/ha/yr
"nfix_in": "0.005", # spin-up value, annual rate, unit t/ha/yr
"pdep_in": "0.0004", # spin-up value, annual rate, unit t/ha/yr
"tsoil_in": "15.0", # spin-up value
"k1": "0.01", # rate from inorgavlp to inorgssorbp, adjustable
"k2": "0.01", # rate from inorgssorbp to inorgavlp, adjustable
"k3": "0.05", # rate from inorgssorbp to inorgoccp, adjustable
"finesoil": "0.5", # match against analytical
"sla": "5.0", # match against analytical
"cfracts": "0.45", # match against analytical
"c_alloc_fmax": "0.2", # allocation to leaf, fixed
"c_alloc_fmin": "0.2", # allocation to leaf, fixed
"c_alloc_rmax": "0.2", # allocation to root, fixed
"c_alloc_rmin": "0.2", # allocation to root, fixed
"fdecay": "0.5", # /yr
"rdecay": "1.5", # /yr
"wdecay": "0.01", # /yr
"sapturnover": "0.1", # /yr
"fretransn": "0.5", # match against analytical
"fretransp": "0.6", # match against analytical
"rretrans": "0.0", #
"wretrans": "0.0", #
"structcn": "200.0", # Commins and MCM uses 150
"structcp": "3333.33", # Literature suggests 500:62500
"metabcnmax": "25.0", #
"metabcnmin": "10.0", #
"metabcpmax": "150.0", #
"metabcpmin": "80.0", #
"ligshoot": "0.2", # match against analytical
"ligroot": "0.16", # match against analytical
"height0": "5.0",
"height1": "30.0",
"heighto": "4.826",
"htpower": "0.35",
"density": "420.0",
"leafsap0": "8000.0",
"leafsap1": "3060.0",
"targ_sens": "0.5",
"actncmax": "0.066667", # C:N = 15
"actncmin": "0.066667", # C:N = 15
"actpcmax": "0.00125", # C:P = 800
"actpcmin": "0.00125", # C:P = 800
"slowncmax": "0.05", # C:N = 20
"slowncmin": "0.05", # C:N = 20
"slowpcmin": "0.0005", # C:P = 2000
"slowpcmax": "0.0005", # C:P = 2000
"passncmax": "0.1", # C:N = 10
"passncmin": "0.1", # C:N = 10
"passpcmin": "0.005", # C:P = 200
"passpcmax": "0.005", # C:P = 200
"lue0": "2.8", # 2.8 for GPP, 1.4 for NPP
"cue": "0.5", #
"ncmaxf": "0.05", # 0.05
"ncwnewz": "0.005", # C:N = 200, match analytical
"ncrfac": "0.7", # match against analytical
"nref": "0.04", # N saturation threshold for photosynthesis
"pcmaxf": "0.005", #
"pcwnewz": "0.0003", # C:P = 3333.33 match analytical
"pcrfac": "0.7", # match against analytical
"rateuptake": "0.96884", # 0.96884
"rateloss": "0.05", # match against analytical
"prateuptake": "1.9", # 0.82395
"prateloss": "0.05", # match against analytical
"p_rate_par_weather": "1.0", # Assumes all p_atm_dep into parent pool transfers into inorgavlp
"nuptakez": "0.01", #
"puptakez": "0.0004", #
"passivesoilz": "26.8", # 26.8 match against analytical
"passivesoilnz": "2.68", # 2.68 match against analytical
"passivesoilpz": "0.134", # 0.134 match against analytical
"num_years": "1", # no need to change
"kr": "3.0", # 0.5 t/ha in Dewar and McMurtrie 1996; the value of root carbon at which 50% of available N is taken up
"krp": "3.0", # 0.00001; can set krp equals kr for consistency
"a0rhizo": "0.05",
"a1rhizo": "0.6",
"root_exu_CUE": "-999.99",
"prime_y": "0.0",
"prime_z": "0.0",
"nmin0": "0.0", # for variable som NC depend on inorgN
"nmincrit": "2.0", # for variable som NC depend on inorgN
"pmin0": "0.0", # for variable som PC depend on inorgavlp
"pmincrit": "2.0", # for variable som PC depend on inorgavlp
# control
"adjust_rtslow": "false", # goes together with exudation
"alloc_model": "fixed", # fixed and variable allocation pattern
"diagnosis": "false",
"exudation": "false",
"fixed_stem_nc": "false",
"fixed_stem_pc": "false",
"fixleafnc": "false",
"fixleafpc": "false",
"ncycle": "true",
"pcycle": "true",
"nuptake_model": "0",
"puptake_model": "0",
"print_options": "end", # during spin up, set to end
"passiveconst": "false",
"respiration_model": "fixed",
"som_nc_calc": "fixed",
"som_pc_calc": "fixed",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY_SPIN + cfg_fname)
# add this directory to python search path so we can find the scripts!
sys.path.append(os.path.join(d, "code/scripts"))
import translate_GDAY_output_to_NCEAS_format as tr
def main(experiment_id, latitude, albedo, topsoil_type,
rootsoil_type, finesoil, SPIN_UP=False, RUN_SIM=False):
gday_exe = "@PATHTOGDAY@"
GDAY_SPIN = gday_exe + " -s -p "
GDAY = gday_exe + " -p "
# dir names
base_param_name = "base_start"
base_dir = os.getcwd()
base_param_dir = "@PATH_PARAMS@"
param_dir = "@RUNDIR@"
met_dir = "@SITE_MET@"
run_dir = "@RUNDIR@"
if SPIN_UP == True:
# copy base files to make two new experiment files
shutil.copy(os.path.join(base_param_dir, base_param_name + ".cfg"),
os.path.join(param_dir, "%s_model_spinup.cfg" % \
(experiment_id)))
# Run model to equilibrium assuming forest, growing C pools from
# effectively zero
itag = "%s_model_spinup" % (experiment_id)
otag = "%s_model_spunup" % (experiment_id)
mtag = "%s.daily_spin.csv" % (experiment_id)
out_fn = itag + "_equilib.out"
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# state - default C:N 25.
"age": "0.0",
"canht": "20.0", # Made up
"activesoil": "0.001",
"activesoiln": "0.00004",
"age": "0.0",
"branch": "0.001",
"branchn": "0.00004",
"cstore": "0.001",
"inorgn": "0.00004",
"metabsoil": "0.0",
"metabsoiln": "0.0",
"metabsurf": "0.0",
"metabsurfn": "0.0",
"nstore": "0.00004",
"passivesoil": "0.001",
"passivesoiln": "0.0004",
"prev_sma": "-999.9",
"root": "0.001",
"root_depth": "-9999.9",
"rootn": "0.00004",
"sapwood": "0.001",
"shoot": "0.001",
"shootn": "0.00004",
"slowsoil": "0.001",
"slowsoiln": "0.00004",
"stem": "0.001",
"stemn": "0.00004",
"stemnimm": "0.00004",
"stemnmob": "0.0",
"structsoil": "0.001",
"structsoiln": "0.00004",
"structsurf": "0.001",
"structsurfn": "0.00004",
"croot": "0.0", # don't simulate coarse roots
"crootn": "0.0", # don't simulate coarse roots
# parameters
#"fix_lai": "3.0",
"latitude": "%f" % (latitude),
"albedo": "%f" % (albedo),
"finesoil": "%f" % (finesoil),
"intercep_frac": "0.15",
"max_intercep_lai": "3.0",
"slamax": "4.4", # made up [m2 kg-1 DW]
"sla": "4.4", # made up [m2 kg-1 DW]
"slazero": "4.4", # made up [m2 kg-1 DW]
"cfracts": "0.5",
"lai_closed": "0.5", # I am effectively turning this feature off by setting it so low
"c_alloc_fmax": "0.25",
"c_alloc_fmin": "0.25",
"c_alloc_rmax": "0.05",
"c_alloc_rmin": "0.05",
"c_alloc_bmax": "0.1",
"c_alloc_bmin": "0.1",
"c_alloc_cmax": "0.0", # turn off coarse roots!
#"c_alloc_fmax": "0.35",
#"c_alloc_fmin": "0.15",
#"c_alloc_rmax": "0.35",
#"c_alloc_rmin": "0.05",
#"c_alloc_bmax": "0.1",
#"c_alloc_bmin": "0.1",
#"c_alloc_cmax": "0.0", # turn off coarse roots!
"fretrans": "0.5",
"rretrans": "0.0",
"bretrans": "0.0",
"wretrans": "0.0",
"ncwnewz": "0.003",
"ncwnew": "0.003",
"ncwimmz": "0.003",
"ncwimm": "0.003",
"ncbnewz": "0.003",
"ncbnew": "0.003",
"ncrfac": "0.8",
"ncmaxfyoung": "0.04",
"ncmaxfold": "0.04",
"ncmaxr": "0.03",
"retransmob": "0.0",
"fdecay": "0.59988", # Protocol [years-1]
"fdecaydry": "0.59988", # Protocol
"rdecay": "0.33333", # Protocol
"rdecaydry": "0.33333", # Protocol
"bdecay": "0.02", # No data, assuming 50 years
"wdecay": "0.02",
"crdecay": "0.00", # turn off coarse roots!
"watdecaydry": "0.0",
"watdecaywet": "0.1",
"ligshoot": "0.24", # Based on White et al. 2000 for ENF
"ligroot": "0.22", # Based on White et al. 2000
"rateuptake": "1.9", # set somewhat (very) arbitarly to get an LAI ~ 4.
"rateloss": "0.3",
"topsoil_depth": "50.0",
"rooting_depth": "2000.0",
"topsoil_type": topsoil_type,
"rootsoil_type": rootsoil_type,
"ctheta_topsoil": "-999.9", # Derive based on soil type
"ntheta_topsoil": "-999.9", # Derive based on soil type
"ctheta_root": "-999.9", # Derive based on soil type
"ntheta_root": "-999.9", # Derive based on soil type
"measurement_temp": "25.0",
"dz0v_dh": "0.075", # However I have used value from Jarvis, quoted in Jones 1992, pg. 67. Produces a value within the bounds of 3.5-1.1 mol m-2 s-1 Drake, 2010, GCB for canht=17
"displace_ratio": "0.78",
"g1": "2.74",
#"jmax": "60.0",
#"vcmax": "30.0",
"jmaxna": "60.0",
"jmaxnb": "0.0",
"vcmaxna": "30.0",
"vcmaxnb": "0.0",
"measurement_temp": "25.0",
"heighto": "4.826",
"htpower": "0.35",
"height0": "5.0",
"height1": "30.0",
"leafsap0": "4000.0",
"leafsap1": "2700.0",
"branch0": "5.61",
"branch1": "0.346",
"croot0": "0.34",
"croot1": "0.84",
"targ_sens": "0.5",
"density": "480.0",
"sapturnover": "0.1",
"prescribed_leaf_NC": "0.03",
# control
"adjust_rtslow": "false", # priming, off
"alloc_model": "fixed",
"assim_model": "mate",
"calc_sw_params": "true", #false=use fwp values, true=derive them
"deciduous_model": "false",
"disturbance": "false",
"exudation": "false",
"fixed_stem_nc": "true",
"fixleafnc": "false",
"fixed_lai": "false",
"grazing": "false",
"gs_model": "medlyn",
"model_optroot": "false",
"modeljm": "1",
"ncycle": "false",
"nuptake_model": "1",
"passiveconst": "false",
"print_options": "end",
"ps_pathway": "c3",
"respiration_model": "fixed",
"strfloat": "0",
"sw_stress_model": "1", # Sands and Landsberg
"water_stress": "true",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY_SPIN + cfg_fname)
if RUN_SIM == True:
# dir names
param_dir = os.path.join("@RUNDIR@")
met_dir = os.path.join("@SITE_MET@")
run_dir = os.path.join("@RUNDIR@")
if SPIN_UP == True:
shutil.copy(os.path.join(param_dir, "%s_model_spunup.cfg" % (experiment_id)),
os.path.join(param_dir, "%s_model_spunup_adj.cfg" % (experiment_id)))
itag = "%s_model_spunup_adj" % (experiment_id)
otag = "%s_simulation" % (experiment_id)
mtag = "%s.daily_run.csv" % (experiment_id)
out_fn = "%s_simulation.csv" % (experiment_id)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, "gday_out.csv")
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "daily",
"sub_daily": "false",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
def main(experiment_id,
site,
SPIN_UP=True,
POST_INDUST=True,
OBS_DRY=True,
OBS_WET=True,
PRD_DRY_NOP=True,
PRD_WET_NOP=True,
PRD_DRY_MDP=True,
PRD_WET_MDP=True,
PRD_DRY_HIP=True,
PRD_WET_HIP=True):
GDAY_SPIN = "./gday -s -p "
GDAY = "./gday -p "
# dir names
base_param_name = "base_start_with_P"
base_param_dir = "/Users/%s/Documents/Research/Projects/EucFACE_Modeling/GDAY-EucFACE/GDAY/params" % (
USER)
base_dir = os.path.dirname(os.getcwd())
param_dir = os.path.join(base_dir, "params")
met_dir = os.path.join(base_dir, "met_data")
run_dir = os.path.join(base_dir, "outputs")
if SPIN_UP == True:
# copy base files to make two new experiment files
shutil.copy(os.path.join(base_param_dir, base_param_name + ".cfg"),
os.path.join(param_dir, "%s_%s_model_spinup.cfg" % \
(experiment_id, site)))
# Run model to equilibrium assuming forest, growing C pools from
# effectively zero
itag = "%s_%s_model_spinup" % (experiment_id, site)
otag = "%s_%s_model_spunup" % (experiment_id, site)
mtag = "%s_met_spinup_daily_50yrs.csv" % (site)
out_fn = itag + "_equilib.out"
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# default C:N 25.
# Canopy height = 22 m average of 6 plots at UWS, site_description_stuff/EucFACE_Plot_Summary.doc
"activesoil": "0.001",
"activesoiln": "0.00004",
"activesoilp": "0.000002",
"age": "90.0", # EucFACE parameter file
"branch": "0.001",
"branchn": "0.00004",
"branchp": "0.000002",
"cstore": "0.0",
"nstore": "0.0",
"pstore": "0.0",
"inorgn": "0.0000", # 0.00004
"inorglabp": "0.0000", # 0.00004
"inorgsorbp": "0.0",
"inorgssorbp": "0.0",
"inorgoccp": "0.0",
"inorgparp": "0.0",
"fertilizerp": "0.0", # Fertilizer P pool
"metabsoil": "0.0",
"metabsoiln": "0.0",
"metabsoilp": "0.0",
"metabsurf": "0.0",
"metabsurfn": "0.0",
"metabsurfp": "0.0",
"passivesoil": "0.001",
"passivesoiln": "0.0004",
"passivesoilp": "0.000002",
"prev_sma": "1.0",
"root": "0.001",
"croot": "0.0", # don't simulate coarse roots
"crootn": "0.0", # don't simulate coarse roots
"crootp": "0.0", # don't simulate coarse roots
"rootn": "0.00004",
"rootp": "0.000002",
"sapwood": "0.001",
"shoot": "0.001",
"shootn": "0.00004",
"shootp": "0.000002",
"slowsoil": "0.001",
"slowsoiln": "0.00004",
"slowsoilp": "0.000002",
"stem": "0.001",
"stemn": "0.00004",
"stemp": "0.000002",
"stemnimm": "0.00004",
"stempimm": "0.000002",
"stemnmob": "0.0",
"stempmob": "0.0",
"structsoil": "0.001",
"structsoiln": "0.00004",
"structsoilp": "0.000002",
"structsurf": "0.001",
"structsurfn": "0.00004",
"structsurfp": "0.0000024",
# parameters
"resp_coeff":
"0.9", # controlling the rate of respiration and CUE. to be used when vary respiration flag is on.
"alpha_j":
"0.308", # Taking the theoretical maximum (from Belinda) 0.385 x 0.8 (leaf absorptance) = 0.308
"intercep_frac": "0.15",
"max_intercep_lai": "3.0",
"latitude": "-33.61", # EucFACE parameter file
"albedo": "0.2",
"slamax": "6.34", # EucFACE parameter file
"sla": "5.57", # EucFACE parameter file
"slazero": "5.57", # EucFACE parameter file
"lai_closed":
"0.5", # I am effectively turning this feature off by setting it so low
"c_alloc_fmax": "0.48", # EucFACE parameter file
"c_alloc_fmin": "0.40", # EucFACE parameter file
"c_alloc_rmax": "0.26", # EucFACE parameter file
"c_alloc_rmin": "0.16", # EucFACE parameter file
"c_alloc_bmax": "0.05", # guess
"c_alloc_bmin": "0.05", # guess
"c_alloc_cmax": "0.0", # turn off coarse roots!
"cue": "0.35", # cue
"fretransn": "0.31", # EucFACE parameter file
"fretransp": "0.53", # EucFACE parameter file
"rretrans": "0.3", # EucFACE parameter file
"bretrans": "0.7", # EucFACE parameter file
"wretrans": "0.82", # EucFACE parameter file
"retransmob": "0.82", # EucFACE parameter file
"cretrans": "0.0",
"ncwnewz": "0.008", #New stem ring N:C at zero leaf N:C (mobile)
"ncwnew": "0.008", #New stem ring N:C at critical leaf N:C (mob)
"ncwimmz": "0.008", #Immobile stem N C at zero leaf N C
"ncwimm": "0.008", #Immobile stem N C at critical leaf N C
"ncbnewz": "0.008", #new branch N C at zero leaf N C
"ncbnew": "0.008", #new branch N C at critical leaf N C
"nccnewz": "0.008", #new coarse root N C at zero leaf N C
"nccnew": "0.008", #new coarse root N C at critical leaf N C
"ncrfac": "0.8",
"ncmaxfyoung": "0.5",
"ncmaxfold": "0.05",
"ncmaxr": "0.05",
"fdecay": "1.1", # foliage decay rate, guess parameter
"fdecaydry": "1.1", # foliage decay rate, guess parameter
"rdecay": "0.9", # EucFACE parameter file
"rdecaydry": "0.9", # as above
"crdecay": "0.00", # turn off coarse roots!
"bdecay": "0.1", # no idea, assuming 25 years
"wdecay": "0.02", # no idea, assuming 25 years
"watdecaydry": "0.0",
"watdecaywet": "0.1",
"ligshoot": "0.15", # EucFACE parameter file
"ligroot": "0.2", # Same as Medlyn 2016
"rateuptake": "0.6",
"rateloss": "0.02", # guess value
"topsoil_depth": "450.0",
"rooting_depth": "11000.0",
"topsoil_type": "loamy_sand",
"rootsoil_type": "sandy_clay_loam",
"fractup_soil":
"0.5", # fraction of transpiration from up of the soil
"kn": "0.1", # extinction coefficient for top canopy N
"kp": "0.1", # extinction coefficient for top canopy P
"krp": "0.00001",
"dz0v_dh":
"0.05", # Using Value from JULES for TREE PFTs as I don't know what is best. However I have used value from Jarvis, quoted in Jones 1992, pg. 67. Produces a value within the bounds of 3.5-1.1 mol m-2 s-1 Drake, 2010, GCB for canht=17
"displace_ratio":
"0.75", # From Jones, pg 67, following Jarvis et al. 1976
"z0h_z0m": "1.0",
# root exudation
"a0rhizo": "0.01",
"a1rhizo": "0.6",
"prime_km": "0.3",
"g1": "4.35", # EucFACE parameter: 3.04 +- 1.31
"jmaxna":
"49.930", # forcing intercept to zero; if use all species df, 49.743
"jmaxpa":
"933.90", # forcing intercept to zero; if use all species df, 842.46
"jmaxnb": "0.0", # forcing intercept to zero
"jmaxpb": "0.0", # forcing intercept to zero
"vcmaxna":
"27.707", # forcing intercept to zero; if use all species df, 27.627
"vcmaxpa":
"516.83", # forcing intercept to zero; if use all species df, 468.76
"vcmaxnb": "0.0", # forcing intercept to zero
"vcmaxpb": "0.0", # forcing intercept to zero
"jmax": "162.91", # EucFACE parameter file
"vcmax": "92.85", # EucFACE parameter file
"measurement_temp":
"25.0", # parameters obtained at 22 not 25 degrees
"heighto": "4.826",
"htpower": "0.35",
"height0": "5.0",
"height1": "25.0",
"leafsap0": "4000.0", # "4000.0",
"leafsap1": "2700.0", # 2700
"branch0": "5.61",
"branch1": "0.346",
"croot0": "0.34",
"croot1": "0.84",
"targ_sens": "0.5",
"density": "492.0", # EucFACE parameter file
"nf_min": "0.005",
"sapturnover": "0.1", # guess value for EucFACE
"p_rate_par_weather": "0.00004", #
"p_rate_release_fertilizer":
"1.0", # 10 - 15 month release rate for slow-release fertilizer
"rate_sorb_ssorb": "0.01", # fitted value, reasonable for EucFACE
"rate_ssorb_occ": "0.048", # fitted value, reasonable for EucFACE
# sorption calculation
"smax":
"0.01", # convert to unit in t ha-1, Yang et al., 2016, GRL, Table S2
"ks":
"0.006", # convert to unit in t ha-1, Yang et al., 2016, GRL, Table S2
# biochemical P mineralization
"biochemical_p_constant": "150.0",
"max_p_biochemical": "0.001",
"crit_n_cost_of_p": "15.0",
"actncmax": "0.1",
"actncmin": "0.006",
"slowncmax": "0.006",
"slowncmin": "0.0025",
"passncmax": "0.0025",
"passncmin": "0.001",
"actpcmax": "0.01", # empirical
"actpcmin": "0.005", # empirical
"slowpcmax": "0.05", # empirical
"slowpcmin": "0.005", # empirical
"passpcmax": "0.0051", # empirical
"passpcmin": "0.0051", # empirical
"pcbnew": "0.00013", # same as sapwood
"pcbnewz": "0.00013", # same as sapwood
"pccnew": "0.00013", # same as sapwood
"pccnewz": "0.00013", # same as sapwood
"pcmaxfold": "0.01", # EucFACE parameter file
"pcmaxfyoung": "0.05", # EucFACE parameter file
"pcmaxr": "0.06", # EucFACE parameter file
"pcrfac": "0.8",
"pcwimm": "0.00013", # EucFACE parameter file
"pcwimmz": "0.00013", # EucFACE parameter file
"pcwnew": "0.00013", # EucFACE parameter file
"pcwnewz": "0.00013", # EucFACE parameter file
"pf_min": "0.0002",
# for calculate_p_ssorb_to_sorb function
"finesoil": "0.2", # EucFACE parameter file
"phmin": "5.0",
"phmax": "14.0",
"soilph": "5.52", # EucFACE parameter file
"phtextmin": "0.000008",
"phtextmax": "0.00015",
"phtextslope": "0.00004",
"psecmnp": "0.000022",
# to determine soil SOM PC ratios
"pmin0": "0.0", # set to zero for now
"pmincrit": "2.0",
"prateloss": "0.05", # set it to be the same as N rate loss
"prateuptake":
"0.9", # Fitted value to obtain balance between uptake N:P ratio and reasonable P labile pool
"puptakez": "0.002", # EucFACE value
"structcp": "5500.0",
"structratp": "0.0",
# control
"adjust_rtslow": "true", # priming, off
"alloc_model": "fixed",
"assim_model": "mate",
"calc_sw_params": "true", #false=use fwp values, true=derive them
"deciduous_model": "false",
"disturbance": "false",
"exudation":
"true", # note that exudation not implemented in hourly model.
"fixed_stem_nc": "true",
"fixed_stem_pc": "true",
"fixleafnc": "false",
"fixleafpc": "false",
"grazing": "false",
"gs_model": "medlyn",
"aci_relationship": "walker",
"model_optroot": "false",
"modeljm": "1",
"ncycle": "true",
"pcycle": "true",
"nuptake_model": "1",
"puptake_model": "1",
"triose_p": "false",
"output_ascii": "true",
"passiveconst": "false",
"print_options": "end",
"ps_pathway": "c3",
"respiration_model": "vary",
"strfloat": "0",
"strpfloat": "0",
"sw_stress_model": "1",
"use_eff_nc": "0",
"text_effect_p": "1",
"water_stress": "true",
"water_balance": "BUCKET",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY_SPIN + cfg_fname)
if POST_INDUST == True:
# copy spunup base files to make two new experiment files
shutil.copy(
os.path.join(param_dir,
"%s_%s_model_spunup.cfg" % (experiment_id, site)),
os.path.join(param_dir,
"%s_%s_model_spunup_adj.cfg" % (experiment_id, site)))
itag = "%s_%s_model_spunup_adj" % (experiment_id, site)
otag = "%s_%s_model_indust" % (experiment_id, site)
mtag = "%s_met_historic_daily_1750_2011.csv" % (site)
out_fn = "%s_amb_equilib.csv" % (site)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "end",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
if POST_INDUST == True:
# copy spunup base files to make two new experiment files
shutil.copy(
os.path.join(param_dir,
"%s_%s_model_spunup.cfg" % (experiment_id, site)),
os.path.join(param_dir,
"%s_%s_model_spunup_adj.cfg" % (experiment_id, site)))
itag = "%s_%s_model_spunup_adj" % (experiment_id, site)
otag = "%s_%s_model_indust" % (experiment_id, site)
mtag = "%s_met_historic_daily_1750_2011.csv" % (site)
out_fn = "%s_amb_equilib.csv" % (site)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "daily",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# translate output to EucFACE requested output
#tr.translate_output(out_fname, met_fname)
# observed (2011-2019) under dry condition: store output
if OBS_DRY == True:
# copy last cfg file and make new one
shutil.copy(
os.path.join(param_dir,
"%s_%s_model_indust.cfg" % (experiment_id, site)),
os.path.join(param_dir,
"%s_%s_model_indust_adj.cfg" % (experiment_id, site)))
itag = "%s_%s_model_indust_adj" % (experiment_id, site)
otag = "%s_%s_model_DRY_%s_2012_2019" % (experiment_id, site,
CO2_treatment)
mtag = "%s_met_DRY_%s_daily_2012_2019.csv" % (site, CO2_treatment)
out_fn = "%s_simulated_DRY_%s_2012_2019.csv" % (site, CO2_treatment)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "daily",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# translate output to EucFACE requested output
#tr.translate_output(out_fname, met_fname)
# observed (2011-2019) under dry condition: store cfg
if OBS_DRY == True:
# copy last cfg file and make new one
shutil.copy(
os.path.join(param_dir,
"%s_%s_model_indust.cfg" % (experiment_id, site)),
os.path.join(param_dir,
"%s_%s_model_indust_adj.cfg" % (experiment_id, site)))
itag = "%s_%s_model_indust_adj" % (experiment_id, site)
otag = "%s_%s_model_DRY_%s_2012_2019" % (experiment_id, site,
CO2_treatment)
mtag = "%s_met_DRY_%s_daily_2012_2019.csv" % (site, CO2_treatment)
out_fn = "%s_simulated_DRY_%s_2012_2019.csv" % (site, CO2_treatment)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "end",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# predicted (2020-2069) under DRY and NOP condition: store output
if PRD_DRY_NOP == True:
# copy last cfg file and make new one
shutil.copy(
os.path.join(
param_dir, "%s_%s_model_DRY_%s_2012_2019.cfg" %
(experiment_id, site, CO2_treatment)),
os.path.join(
param_dir, "%s_%s_model_DRY_%s_2012_2019_adj.cfg" %
(experiment_id, site, CO2_treatment)))
itag = "%s_%s_model_DRY_%s_2012_2019_adj" % (experiment_id, site,
CO2_treatment)
otag = "%s_%s_model_DRY_%s_NOP_2020_2069" % (experiment_id, site,
CO2_treatment)
mtag = "%s_met_DRY_%s_NOP_daily_2020_2069.csv" % (site, CO2_treatment)
out_fn = "%s_simulated_DRY_%s_NOP_2020_2069.csv" % (site,
CO2_treatment)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "daily",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# translate output to EucFACE requested output
#tr.translate_output(out_fname, met_fname)
# predicted (2020-2069) under DRY and NOP condition: store cfg
if PRD_DRY_NOP == True:
# copy last cfg file and make new one
shutil.copy(
os.path.join(
param_dir, "%s_%s_model_DRY_%s_2012_2019.cfg" %
(experiment_id, site, CO2_treatment)),
os.path.join(
param_dir, "%s_%s_model_DRY_%s_2012_2019_adj.cfg" %
(experiment_id, site, CO2_treatment)))
itag = "%s_%s_model_DRY_%s_2012_2019_adj" % (experiment_id, site,
CO2_treatment)
otag = "%s_%s_model_DRY_%s_NOP_2020_2069" % (experiment_id, site,
CO2_treatment)
mtag = "%s_met_DRY_%s_NOP_daily_2020_2069.csv" % (site, CO2_treatment)
out_fn = "%s_simulated_DRY_%s_NOP_2020_2069.csv" % (site,
CO2_treatment)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "end",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# predicted (2020-2069) under DRY and MDP condition: store output
if PRD_DRY_MDP == True:
# copy last cfg file and make new one
shutil.copy(
os.path.join(
param_dir, "%s_%s_model_DRY_%s_2012_2019.cfg" %
(experiment_id, site, CO2_treatment)),
os.path.join(
param_dir, "%s_%s_model_DRY_%s_2012_2019_adj.cfg" %
(experiment_id, site, CO2_treatment)))
itag = "%s_%s_model_DRY_%s_2012_2019_adj" % (experiment_id, site,
CO2_treatment)
otag = "%s_%s_model_DRY_%s_MDP_2020_2069" % (experiment_id, site,
CO2_treatment)
mtag = "%s_met_DRY_%s_MDP_daily_2020_2069.csv" % (site, CO2_treatment)
out_fn = "%s_simulated_DRY_%s_MDP_2020_2069.csv" % (site,
CO2_treatment)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "daily",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# translate output to EucFACE requested output
#tr.translate_output(out_fname, met_fname)
# predicted (2020-2069) under DRY and MDP condition: store cfg
if PRD_DRY_MDP == True:
# copy last cfg file and make new one
shutil.copy(
os.path.join(
param_dir, "%s_%s_model_DRY_%s_2012_2019.cfg" %
(experiment_id, site, CO2_treatment)),
os.path.join(
param_dir, "%s_%s_model_DRY_%s_2012_2019_adj.cfg" %
(experiment_id, site, CO2_treatment)))
itag = "%s_%s_model_DRY_%s_2012_2019_adj" % (experiment_id, site,
CO2_treatment)
otag = "%s_%s_model_DRY_%s_MDP_2020_2069" % (experiment_id, site,
CO2_treatment)
mtag = "%s_met_DRY_%s_MDP_daily_2020_2069.csv" % (site, CO2_treatment)
out_fn = "%s_simulated_DRY_%s_MDP_2020_2069.csv" % (site,
CO2_treatment)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "end",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# predicted (2020-2069) under DRY and HIP condition: store output
if PRD_DRY_HIP == True:
# copy last cfg file and make new one
shutil.copy(
os.path.join(
param_dir, "%s_%s_model_DRY_%s_2012_2019.cfg" %
(experiment_id, site, CO2_treatment)),
os.path.join(
param_dir, "%s_%s_model_DRY_%s_2012_2019_adj.cfg" %
(experiment_id, site, CO2_treatment)))
itag = "%s_%s_model_DRY_%s_2012_2019_adj" % (experiment_id, site,
CO2_treatment)
otag = "%s_%s_model_DRY_%s_HIP_2020_2069" % (experiment_id, site,
CO2_treatment)
mtag = "%s_met_DRY_%s_HIP_daily_2020_2069.csv" % (site, CO2_treatment)
out_fn = "%s_simulated_DRY_%s_HIP_2020_2069.csv" % (site,
CO2_treatment)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "daily",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# translate output to EucFACE requested output
#tr.translate_output(out_fname, met_fname)
# predicted (2020-2069) under DRY and MDP condition: store cfg
if PRD_DRY_HIP == True:
# copy last cfg file and make new one
shutil.copy(
os.path.join(
param_dir, "%s_%s_model_DRY_%s_2012_2019.cfg" %
(experiment_id, site, CO2_treatment)),
os.path.join(
param_dir, "%s_%s_model_DRY_%s_2012_2019_adj.cfg" %
(experiment_id, site, CO2_treatment)))
itag = "%s_%s_model_DRY_%s_2012_2019_adj" % (experiment_id, site,
CO2_treatment)
otag = "%s_%s_model_DRY_%s_HIP_2020_2069" % (experiment_id, site,
CO2_treatment)
mtag = "%s_met_DRY_%s_HIP_daily_2020_2069.csv" % (site, CO2_treatment)
out_fn = "%s_simulated_DRY_%s_HIP_2020_2069.csv" % (site,
CO2_treatment)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "end",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# observed (2012-2019) under wet condition: store output
if OBS_WET == True:
# copy last cfg file and make new one
shutil.copy(
os.path.join(param_dir,
"%s_%s_model_indust.cfg" % (experiment_id, site)),
os.path.join(param_dir,
"%s_%s_model_indust_adj.cfg" % (experiment_id, site)))
itag = "%s_%s_model_indust_adj" % (experiment_id, site)
otag = "%s_%s_model_WET_%s_2012_2019" % (experiment_id, site,
CO2_treatment)
mtag = "%s_met_WET_%s_daily_2012_2019.csv" % (site, CO2_treatment)
out_fn = "%s_simulated_WET_%s_2012_2019.csv" % (site, CO2_treatment)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "daily",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# translate output to EucFACE requested output
#tr.translate_output(out_fname, met_fname)
# observed (2012-2019) under wet condition: store cfg
if OBS_WET == True:
# copy last cfg file and make new one
shutil.copy(
os.path.join(param_dir,
"%s_%s_model_indust.cfg" % (experiment_id, site)),
os.path.join(param_dir,
"%s_%s_model_indust_adj.cfg" % (experiment_id, site)))
itag = "%s_%s_model_indust_adj" % (experiment_id, site)
otag = "%s_%s_model_WET_%s_2012_2019" % (experiment_id, site,
CO2_treatment)
mtag = "%s_met_WET_%s_daily_2012_2019.csv" % (site, CO2_treatment)
out_fn = "%s_simulated_WET_%s_2012_2019.csv" % (site, CO2_treatment)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "end",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# predicted (2020-2069) under WET and NOP condition: store output
if PRD_WET_NOP == True:
# copy last cfg file and make new one
shutil.copy(
os.path.join(
param_dir, "%s_%s_model_WET_%s_2012_2019.cfg" %
(experiment_id, site, CO2_treatment)),
os.path.join(
param_dir, "%s_%s_model_WET_%s_2012_2019_adj.cfg" %
(experiment_id, site, CO2_treatment)))
itag = "%s_%s_model_WET_%s_2012_2019_adj" % (experiment_id, site,
CO2_treatment)
otag = "%s_%s_model_WET_%s_NOP_2020_2069" % (experiment_id, site,
CO2_treatment)
mtag = "%s_met_WET_%s_NOP_daily_2020_2069.csv" % (site, CO2_treatment)
out_fn = "%s_simulated_WET_%s_NOP_2020_2069.csv" % (site,
CO2_treatment)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "daily",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# translate output to EucFACE requested output
#tr.translate_output(out_fname, met_fname)
# predicted (2020-2069) under WET and NOP condition: store cfg
if PRD_WET_NOP == True:
# copy last cfg file and make new one
shutil.copy(
os.path.join(
param_dir, "%s_%s_model_WET_%s_2012_2019.cfg" %
(experiment_id, site, CO2_treatment)),
os.path.join(
param_dir, "%s_%s_model_WET_%s_2012_2019_adj.cfg" %
(experiment_id, site, CO2_treatment)))
itag = "%s_%s_model_WET_%s_2012_2019_adj" % (experiment_id, site,
CO2_treatment)
otag = "%s_%s_model_WET_%s_NOP_2020_2069" % (experiment_id, site,
CO2_treatment)
mtag = "%s_met_WET_%s_NOP_daily_2020_2069.csv" % (site, CO2_treatment)
out_fn = "%s_simulated_WET_%s_NOP_2020_2069.csv" % (site,
CO2_treatment)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "end",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# predicted (2020-2069) under WET and MDP condition: store output
if PRD_WET_MDP == True:
# copy last cfg file and make new one
shutil.copy(
os.path.join(
param_dir, "%s_%s_model_WET_%s_2012_2019.cfg" %
(experiment_id, site, CO2_treatment)),
os.path.join(
param_dir, "%s_%s_model_WET_%s_2012_2019_adj.cfg" %
(experiment_id, site, CO2_treatment)))
itag = "%s_%s_model_WET_%s_2012_2019_adj" % (experiment_id, site,
CO2_treatment)
otag = "%s_%s_model_WET_%s_MDP_2020_2069" % (experiment_id, site,
CO2_treatment)
mtag = "%s_met_WET_%s_MDP_daily_2020_2069.csv" % (site, CO2_treatment)
out_fn = "%s_simulated_WET_%s_MDP_2020_2069.csv" % (site,
CO2_treatment)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "daily",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# translate output to EucFACE requested output
#tr.translate_output(out_fname, met_fname)
# predicted (2020-2069) under WET and MDP condition: store cfg
if PRD_WET_MDP == True:
# copy last cfg file and make new one
shutil.copy(
os.path.join(
param_dir, "%s_%s_model_WET_%s_2012_2019.cfg" %
(experiment_id, site, CO2_treatment)),
os.path.join(
param_dir, "%s_%s_model_WET_%s_2012_2019_adj.cfg" %
(experiment_id, site, CO2_treatment)))
itag = "%s_%s_model_WET_%s_2012_2019_adj" % (experiment_id, site,
CO2_treatment)
otag = "%s_%s_model_WET_%s_MDP_2020_2069" % (experiment_id, site,
CO2_treatment)
mtag = "%s_met_WET_%s_MDP_daily_2020_2069.csv" % (site, CO2_treatment)
out_fn = "%s_simulated_WET_%s_MDP_2020_2069.csv" % (site,
CO2_treatment)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "end",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# predicted (2020-2069) under WET and HIP condition: store output
if PRD_WET_HIP == True:
# copy last cfg file and make new one
shutil.copy(
os.path.join(
param_dir, "%s_%s_model_WET_%s_2012_2019.cfg" %
(experiment_id, site, CO2_treatment)),
os.path.join(
param_dir, "%s_%s_model_WET_%s_2012_2019_adj.cfg" %
(experiment_id, site, CO2_treatment)))
itag = "%s_%s_model_WET_%s_2012_2019_adj" % (experiment_id, site,
CO2_treatment)
otag = "%s_%s_model_WET_%s_HIP_2020_2069" % (experiment_id, site,
CO2_treatment)
mtag = "%s_met_WET_%s_HIP_daily_2020_2069.csv" % (site, CO2_treatment)
out_fn = "%s_simulated_WET_%s_HIP_2020_2069.csv" % (site,
CO2_treatment)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "daily",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
# translate output to EucFACE requested output
#tr.translate_output(out_fname, met_fname)
# predicted (2020-2069) under WET and MDP condition: store cfg
if PRD_WET_HIP == True:
# copy last cfg file and make new one
shutil.copy(
os.path.join(
param_dir, "%s_%s_model_WET_%s_2012_2019.cfg" %
(experiment_id, site, CO2_treatment)),
os.path.join(
param_dir, "%s_%s_model_WET_%s_2012_2019_adj.cfg" %
(experiment_id, site, CO2_treatment)))
itag = "%s_%s_model_WET_%s_2012_2019_adj" % (experiment_id, site,
CO2_treatment)
otag = "%s_%s_model_WET_%s_HIP_2020_2069" % (experiment_id, site,
CO2_treatment)
mtag = "%s_met_WET_%s_HIP_daily_2020_2069.csv" % (site, CO2_treatment)
out_fn = "%s_simulated_WET_%s_HIP_2020_2069.csv" % (site,
CO2_treatment)
out_param_fname = os.path.join(param_dir, otag + ".cfg")
cfg_fname = os.path.join(param_dir, itag + ".cfg")
met_fname = os.path.join(met_dir, mtag)
out_fname = os.path.join(run_dir, out_fn)
replace_dict = {
# files
"out_param_fname": "%s" % (out_param_fname),
"cfg_fname": "%s" % (cfg_fname),
"met_fname": "%s" % (met_fname),
"out_fname": "%s" % (out_fname),
# control
"print_options": "end",
}
ad.adjust_param_file(cfg_fname, replace_dict)
os.system(GDAY + cfg_fname)
