def write_text():
with open("./experimetal_settings.log", "w") as f:
f.write("# Experimental Settings\n")
f.write("# " + pm.version() + "\n")
f.write("# " + pm.CaMa_ver() + "\n")
f.write("#======================================================\n")
# Experimental Settings
f.write("# Experiment Name: " + pm.experiment() + "\n")
f.write("# Experiment Mode: " + "%d" % (pm.mode()) + "\n")
# Runoff data
f.write("# Runoff Data: " + pm.input(pm.mode()) + "\n")
# Time domain for analysis
f.write("# Start Date: %04d-%02d-%02d\n" % (pm.starttime()))
f.write("# End Date: %04d-%02d-%02d\n" % (pm.endtime()))
# Calibration
f.write("# Model Calibration: " + calibration(pm.calibrate()) + "\n")
# Assimilation Settings
f.write("# Assimilation Mode: " + assimlation_mode(pm.conflag()) +
"\n")
f.write("# Assimilation Domain: \n")
f.write("# \tWest : %5.2f\n" % (pm.assimW()))
f.write("# \tSouth: %5.2f\n" % (pm.assimS()))
f.write("# \tEest : %5.2f\n" % (pm.assimE()))
f.write("# \tNorth: %5.2f\n" % (pm.assimN()))
f.write("# Assimilation Settings: \n")
f.write("# \tPatch Size : " + patch_character(pm.patch_size()) + "\n")
f.write("# \tPatch Id : " + pm.patch_name() + " " + pm.patch_id() +
"\n")
f.write("# \tInflation Method : " + inflation_para(pm.rho()) + "\n")
f.write("# Assimilation Statistics: \n")
f.write("# \tMean : " + stat_name(pm.conflag(), pm.calibrate())[0] +
"\n")
f.write("# \tStandrad Deviation : " +
stat_name(pm.conflag(), pm.calibrate())[1] + "\n")
return 0
def cal_monthly_mean(start_year,end_year,months=24):
# calc monthly mean value for two years
runname=pm.runname(pm.mode())
true_run=pm.true_run(pm.mode())
if runname=="ELSE_KIM2009":
nx,ny=360,180
prefix="Roff____"
suffix=".one"
if runname=="E2O":
nx,ny=1440,720
prefix="Roff__"
suffix="%03d.one"%(true_run)
if runname=="ERA20CM":
nx,ny=360,180
prefix="Roff__"
suffix="%03d.one"%(true_run)
#os.system("rm -Rf ./CaMa_in/ELSE_GPCC/mean_month/*")
mkdir("./CaMa_in/"+runname+"/mean_month")
#os.system("rm -Rf ./CaMa_in/ELSE_KIM2009/mean_month/*")
threshold=0.1
start_dt=datetime.date(start_year,1,1)
end_dt=datetime.date(end_year,12,31)
for month in np.arange(months):
ynow=int(start_year+int(month/12))
ychar="%04d"%(ynow)
mchar="%02d"%((month%12)+1)
#print ychar, mchar
roff_mon=np.zeros([ny,nx],np.float32)#.reshape([180,360])
count=np.zeros([ny,nx],np.float32)#.reshape([180,360])
for day in np.arange(month*30,(month+1)*30):
day_num=day-month*30
running_dt=start_dt+datetime.timedelta(days=day)
yyyy='%04d' % (running_dt.year)
mm='%02d' % (running_dt.month)
dd='%02d' % (running_dt.day)
roff=np.fromfile("./CaMa_in/"+runname+"/Roff/"+prefix+str(yyyy)+str(mm)+str(dd)+suffix,np.float32).reshape([ny,nx])
roff_mon=roff_mon+roff*(roff>threshold)
count=count+(roff>threshold)
roff_mean=roff_mon/(count+1e-20)
roff_mean=roff_mean.astype(np.float32)
roff_mean=roff_mean+threshold
roff_mean.tofile("./CaMa_in/"+runname+"/mean_month/mean_"+ychar+mchar+".bin")
def cal_monthly_mean_ens(ens_num): #start_year,end_year,ens_num,months=24):
# calc monthly mean value for two years
start_year=pm.spinup_end_year()
end_year,end_month,end_date=pm.starttime()
#start_year=pm.start_year() #inputlist[0]
#end_year=pm.end_year() #inputlist[1]
#ens_num=inputlist[2]
months=24 #inputlist[3]
#threshold=inputlist[4]
runname=pm.runname(pm.mode())
if runname=="E2O":
nx=1440
ny=720
threshold=0.1
else:
nx=360
ny=180
threshold=1.0e-8
#os.system("rm -Rf ./CaMa_in/ELSE_GPCC/mean_month/*")
mkdir("./CaMa_in/"+runname+"/mean_month")
#os.system("rm -Rf ./CaMa_in/ELSE_KIM2009/mean_month/*")
#threshold=0.1
start_dt=datetime.date(start_year,1,1)
end_dt=datetime.date(end_year,12,31)
ens_char="%03d"%(ens_num)
for month in np.arange(months):
ynow=int(start_year+int(month/12))
ychar="%04d"%(ynow)
mchar="%02d"%((month%12)+1)
#print ychar, mchar
roff_mon=np.zeros([ny,nx],np.float32)#.reshape([180,360])
count=np.zeros([ny,nx],np.float32)#.reshape([180,360])
for day in np.arange(month*30,(month+1)*30):
day_num=day-month*30
running_dt=start_dt+datetime.timedelta(days=day)
yyyy='%04d' % (running_dt.year)
mm='%02d' % (running_dt.month)
dd='%02d' % (running_dt.day)
roff=np.fromfile(pm.DA_dir()+"/inp/"+runname+"/Roff/Roff__"+str(yyyy)+str(mm)+str(dd)+ens_char+".one",np.float32).reshape([ny,nx])
roff_mon=roff_mon+roff*(roff>threshold)
count=count+(roff>threshold)
roff_mean=roff_mon/(count+1e-20)
roff_mean=roff_mean.astype(np.float32)
roff_mean=roff_mean+threshold
roff_mean.tofile("./CaMa_in/"+runname+"/mean_month/mean_"+ychar+mchar+ens_char+".bin")
def make_anomaly_data(mode=pm.mode()):
# make directory for mean sfcelv
mkdir("./assim_out/mean_sfcelv/")
# copy the anomaly files
if mode == 1:
# for mean
iname = pm.DA_dir() + "/dat/mean_sfcelv_E2O_" + pm.mapname(
) + "_1980-2014.bin"
oname = "./assim_out/mean_sfcelv/mean_sfcelv.bin"
os.system("cp " + iname + " " + oname)
# for std
iname = pm.DA_dir() + "/dat/std_sfcelv_E2O_" + pm.mapname(
) + "_1980-2014.bin"
oname = "./assim_out/mean_sfcelv/std_sfcelv.bin"
os.system("cp " + iname + " " + oname)
if mode == 2:
# for mean
iname = pm.DA_dir() + "/dat/mean_sfcelv_E2O_" + pm.mapname(
) + "_1980-2014.bin"
oname = "./assim_out/mean_sfcelv/mean_sfcelv.bin"
os.system("cp " + iname + " " + oname)
# for std
iname = pm.DA_dir() + "/dat/std_sfcelv_E2O_" + pm.mapname(
) + "_1980-2014.bin"
oname = "./assim_out/mean_sfcelv/std_sfcelv.bin"
os.system("cp " + iname + " " + oname)
if mode == 3:
# for mean
iname = pm.DA_dir() + "/dat/mean_sfcelv_VIC_BC_" + pm.mapname(
) + "_1979-2013.bin"
oname = "./assim_out/mean_sfcelv/mean_sfcelv.bin"
os.system("cp " + iname + " " + oname)
# for std
iname = pm.DA_dir() + "/dat/std_sfcelv_VIC_BC_" + pm.mapname(
) + "_1979-2013.bin"
oname = "./assim_out/mean_sfcelv/std_sfcelv.bin"
os.system("cp " + iname + " " + oname)
return 0
def save_statistic():
# copy mean and std of simulated WSE
# for anomaly and normalized assimilations
mkdir("./assim_out/mean_sfcelv/")
# if pm.input()=="E2O":
# iname = pm.DA_dir()+"/dat/mean_sfcelv_"+pm.input()+"_"+pm.mapname()+"_2000-2010"+ens_char+".bin
# oname = "./assim_out/mean_sfcelv/meansfcelv"+ens+".bin"
# os.system("cp -r "+pm.DA_dir()+"/dat/mean_sfcelv_"+pm.input()+"_"+pm.mapname()+"_2000-2014.bin ./assim_out/mean_sfcelv/mean_sfcelv.bin")
# os.system("cp -r "+pm.DA_dir()+"/dat/std_sfcelv_"+pm.input()+"_"+pm.mapname()+"_2000-2014.bin ./assim_out/mean_sfcelv/std_sfcelv.bin")
# print ("cp -r "+pm.DA_dir()+"/dat/mean_sfcelv_"+pm.input()+"_"+pm.mapname()+"_2000-2014.bin ./assim_out/mean_sfcelv/mean_sfcelv.bin")
# if pm.input()=="VIC_BC":
# os.system("cp -r "+pm.DA_dir()+"/dat/mean_sfcelv_"+pm.input()+"_"+pm.mapname()+"_1979-2013.bin ./assim_out/mean_sfcelv/mean_sfcelv.bin")
# os.system("cp -r "+pm.DA_dir()+"/dat/std_sfcelv_"+pm.input()+"_"+pm.mapname()+"_1979-2013.bin ./assim_out/mean_sfcelv/std_sfcelv.bin")
# print ("cp -r "+pm.DA_dir()+"/dat/mean_sfcelv_"+pm.input()+"_"+pm.mapname()+"_1979-2013.bin ./assim_out/mean_sfcelv/mean_sfcelv.bin")
# #===========
# # mean
# inputlist=[]
# for ens in np.arange(1,pm.ens_mem(pm.mode())+1):
# ens_char="%03d"%(ens)
# if pm.input()=="E2O":
# iname = pm.DA_dir()+"/dat/mean_"+pm.stat_name()+"_"+ens_char+".bin"
# # iname = pm.DA_dir()+"/dat/mean_sfcelv_E2O_"+pm.mapname()+"_2000-2010_"+ens_char+".bin"
# # iname = pm.DA_dir()+"/dat/mean_sfcelv_cal_E2O_"+pm.mapname()+"_2000-2010_"+ens_char+".bin"
# oname = "./assim_out/mean_sfcelv/meansfcelvC"+ens_char+".bin"
# if pm.input()=="VIC_BC":
# iname = pm.DA_dir()+"/dat/mean_"+pm.stat_name()+"_"+ens_char+".bin"
# # iname = pm.DA_dir()+"/dat/mean_sfcelv_VIC_BC_"+pm.mapname()+"_2000-2010_"+ens_char+".bin"
# # iname = pm.DA_dir()+"/dat/mean_sfcelv_cal_VIC_BC_"+pm.mapname()+"_2000-2010_"+ens_char+".bin"
# oname = "./assim_out/mean_sfcelv/meansfcelvC"+ens_char+".bin"
# inputlist.append([iname,oname])
#===========
# mean
inputlist = []
for ens in np.arange(1, pm.ens_mem(pm.mode()) + 1):
ens_char = "%03d" % (ens)
iname = pm.DA_dir() + "/dat/mean_" + pm.stat_name(
) + "_" + ens_char + ".bin"
oname = "./assim_out/mean_sfcelv/meansfcelvC" + ens_char + ".bin"
inputlist.append([iname, oname])
# do parallel
p = Pool(pm.para_nums())
p.map(copy_stat, inputlist)
p.terminate()
# #===========
# # std
# inputlist=[]
# for ens in np.arange(1,pm.ens_mem(pm.mode())+1):
# ens_char="%03d"%(ens)
# if pm.input()=="E2O":
# iname = pm.DA_dir()+"/dat/std_"+pm.stat_name()+"_"+ens_char+".bin"
# # iname = pm.DA_dir()+"/dat/std_sfcelv_E2O_"+pm.mapname()+"_2000-2010_"+ens_char+".bin"
# # iname = pm.DA_dir()+"/dat/std_sfcelv_cal_E2O_"+pm.mapname()+"_2000-2010_"+ens_char+".bin"
# oname = "./assim_out/mean_sfcelv/stdsfcelvC"+ens_char+".bin"
# if pm.input()=="VIC_BC":
# iname = pm.DA_dir()+"/dat/std_"+pm.stat_name()+"_"+ens_char+".bin"
# # iname = pm.DA_dir()+"/dat/std_sfcelv_VIC_BC_"+pm.mapname()+"_2000-2010_"+ens_char+".bin"
# # iname = pm.DA_dir()+"/dat/std_sfcelv_cal_VIC_BC_"+pm.mapname()+"_2000-2010_"+ens_char+".bin"
# oname = "./assim_out/mean_sfcelv/stdsfcelvC"+ens_char+".bin"
# inputlist.append([iname,oname])
#===========
# std
inputlist = []
for ens in np.arange(1, pm.ens_mem(pm.mode()) + 1):
ens_char = "%03d" % (ens)
iname = pm.DA_dir() + "/dat/std_" + pm.stat_name(
) + "_" + ens_char + ".bin"
oname = "./assim_out/mean_sfcelv/stdsfcelvC" + ens_char + ".bin"
inputlist.append([iname, oname])
# do parallel
p = Pool(pm.para_nums()) #*cpu_nums())
p.map(copy_stat, inputlist)
p.terminate()
return 0
def prepare_input():
"create a soft link to runoff data set"
if os.path.islink("./CaMa_in/"+pm.runname(pm.mode())):
os.system("rm -r ./CaMa_in/"+pm.runname(pm.mode()))
os.system("ln -sf "+pm.runoff_dir()+" ./CaMa_in/")
return 0