def READ_BBIO_DIURNALCYCLE(DATA_DIR, nx, ny, \
MONTH, DAY, YYYY, HOUR,\
CO2_DIR='CO2_200508//BBIO_DIURNALCYCLE', \
flnmpref='nep', tracer=2,category='CO2-SRCE'):
# 3/4 only 2x25 for now...
ext2d=bp.get_name_ext_2d()
extres=bp.get_res_ext()
DOY=tm.day_of_year(YYYY, MONTH,DAY)
# if (DOY>59 and mod(YYYY,4)==0):
# DOY=DOY+1for ireg in self.regs:
SDOY=r'%3.3d' % DOY
FILENAME = DATA_DIR.strip()+'/'+CO2_DIR+'/'+flnmpref.strip()+'.'+ext2d.strip()+'.'+extres.strip()+"."+SDOY
# print 'read data from ', FILENAME
tau0=tm.get_tau(1985,MONTH,DAY, HOUR)
tau0=tau0/(3600.0)
data, dunit, ios=bp.read_bpch2(FILENAME, category, tracer,tau0, \
nx, ny, 1)
if (ios==0):
data=squeeze(data)
return data,dunit
else:
print('error in read data ', ios)
print(FILENAME)
return None, ""
def READ_BBIO_DAILYAVERAGE(DATA_DIR, nx, ny, \
MONTH, DAY, YYYY, \
CO2_DIR='CO2_200508/BBIO_DAILYAVG', \
flnmpref='/CO2.daily', tracer=3,category='CO2-SRCE'):
# 3/4 only 2x25 for now...
ext2d=bp.get_name_ext_2d()
extres=bp.get_res_ext()
DOY=tm.day_of_year(YYYY, MONTH,DAY)
if (DOY>59 and mod(YYYY,4)>0):
DOY=DOY+1
SDOY=r'%3.3d' % DOY
FILENAME = DATA_DIR.strip()+'/'+CO2_DIR+'/'+flnmpref.strip()+'.'+ext2d.strip()+'.'+extres.strip()+"."+SDOY
# print 'read data from ', FILENAME
tau0=tm.get_tau(2000,MONTH,DAY)
tau0=tau0/(3600.0)
data, dunit, ios=bp.read_bpch2(FILENAME, category, tracer,tau0, \
nx, ny, 1)
if (ios==0):
data=squeeze(data)
return data,dunit
else:
print('error in read data ', ios)
print(FILENAME)
return None, ""
def READ_MONTH_BIOBRN_CO2(DATA_DIR, nx, ny, \
MONTH, YYYY,\
LBBSEA=True, \
CO2_DIR='biomass_200110', \
flnmpref='bioburn', tracer=4,\
category='BIOBSRCE'):
EMFACTCO2CO = 12.068
MONTHDATES = [31, 28, 31, 30,31, 30, 31, 31,30, 31, 30, 31]
# 3/4 only 2x25 for now...
ext2d=bp.get_name_ext_2d()
extres=bp.get_res_ext()
SYYYY=r'%4.4d' % YYYY
TIME=MONTHDATES[MONTH-1] * 86400.0
if (LBBSEA):
FILENAME = DATA_DIR.strip()+'/'+CO2_DIR+'/'+flnmpref.strip()+'.seasonal.'+ext2d.strip()+'.'+extres.strip()
# print 'read data from ', FILENAME
tau0=tm.get_tau(1985,MONTH,1)
tau0=tau0/(3600.0)
else:
FILENAME = DATA_DIR.strip()+'/'+CO2_DIR+'/'+'bioburn'+'.interannual.'+ext2d.strip()+'.'+extres.strip()
# print 'read data from ', FILENAME
tau0=tm.get_tau(YYYY,MONTH,1)
tau0=tau0/(3600.0)
data, dunit, ios=bp.read_bpch2(FILENAME, category, tracer,tau0, \
nx, ny, 1)
if (ios==0):
data=array(data)
# Convert from [molec CO/cm2/month] to [molec CO2/cm2/month
factor=EMFACTCO2CO/TIME
data=factor*data
data=squeeze(data)
dunit='molec/cm2/s'
return data,dunit
else:
print('error in read data ', ios)
print(FILENAME)
return None, ""
def READ_ANNUAL_BIONET_CO2(DATA_DIR, nx, ny, CO2_DIR='CO2_200508', flnmpref='//net_terr_exch_CO2', tracer=5,category='CO2-SRCE'):
# 3/4 only 2x25 for now...
ext2d=bp.get_name_ext_2d()
extres=bp.get_res_ext()
FILENAME = DATA_DIR.strip()+'/'+CO2_DIR+'/'+flnmpref.strip()+'.'+ext2d.strip()+'.'+extres.strip()+".txt"
# print 'read data from ', FILENAME
tau0=tm.get_tau(1985,1,1)
data, dunit, ios=bp.read_bpch2(FILENAME, category, tracer,tau0, \
nx, ny, 1)
if (ios==0):
data=squeeze(data)
return data,dunit
else:
print('error in read data ', ios)
print(FILENAME)
return None, ""
print('step range:',list(range(gcdf.nstep_start, nstep)))
#gcdf.restart_file
pre_year = 1985
pre_restart_name = ' '
#>>/ps/loop0/over each step
for istep in range(gcdf.nstep_start, nstep): # run through the emission time period
npbf = em_npb[istep]
pbflnm = em_ch4flnm[istep]
yyyy_st = em_yyyy_st[istep]
doy_st = em_doy_st[istep]
yyyy, mm, dd = tm.doy_to_time_array(doy_st, yyyy_st)
##c/tau_st in seconds since 1985.1.1.0.0
tau_st = tm.get_tau(yyyy,mm, dd)
# print('-'*10+'starting year, month, day:', yyyy, mm, dd)
istep_end = min(istep+lag_window, len(em_doy_st)-1)
# print('-'*10+'istep_start, istep_end:' istep, istep_end)
if (sub_sous):
nsub_sous = gcdf.n_sous_loop
# sub emission sources loop
else:
nsub_sous = 1
if (sub_tracers):
nsub_run = gcdf.n_tracer_loop
def gen_prior(self, timestep, ntime, yyyy0, mm0, dd0, hh0=0, mi0=0, sec0=0, \
update_state=True, errset=None, do_debug=False):
"""
construct a prior surface flux used for a time period starting with yyyy0, mm0, dd0
"""
tau0=tm.get_tau(yyyy0, mm0, dd0, hh0, mi0, sec0)
self.ntime=ntime
self.timestep=timestep
self.prior=zeros([self.nreg, self.ntime], float)
self.err=zeros([self.nreg, self.ntime], float)
for itime in range(self.ntime):
tau1=tau0+timestep
self.tau0.append(tau0)
self.tau1.append(tau1)
tau=0.5*(tau0+tau1)
date_new=tm.tai85_to_utc(tau0)
yyyy, mm, dd, hh, mi, sec=tm.utc_to_time_array(date_new)
# print yyyy, mm, dd, hh
doy=tm.day_of_year(yyyy, mm, dd)
self.yyyy.append(yyyy)
self.doy.append(doy)
stt=EMISSCO2(yyyy,mm, dd, hh, do_debug=False)
stv=self.map_to_st(stt)
# for test only
# if (itime in [0, 2, 4,6,8]):
# stv[3]=1.80*stv[3]
# stv[5]=1.80*stv[5]
# stv=1.8*stv
self.prior[:,itime]=stv
if (itime==1 and do_debug):
subplot(3,1,1)
gpl.plot_map(stt, self.lon, self.lat, use_pcolor=1)
subplot(3,1,2)
stt2=self.st_to_map(stv)
gpl.plot_map(stt2, self.lon, self.lat, use_pcolor=1)
subplot(3,1,3)
gpl.plot_map(self.reg_map, self.lon, self.lat, use_pcolor=1)
show()
if (errset==None):
# err_fact=sqrt(365.0*24*3600.0/self.timestep)
err_factor=5.0
self.err[1:,itime]=err_factor*self.def_err[1:]
self.err[0, itime]=self.def_err[0]*stv[0]
# if (itime==0):
# print self.err[:,0]
# print self.prior[:,0]
elif (size(errset)==1):
self.err[:,itime]=errset*stv[:]
else:
self.err[:,itime]=errset[:]
tau0=tau1
self.construct_err_cov()
if (update_state):
self.st=array(self.prior)
def gen_transcom_coef(flnm, flux_name,\
yyyy,\
inv_step,\
inv_path=gcdf.inv_path,\
modelname='GEOS4', \
category='CO2-SRCE', ntracer=1, \
do_debug=True, \
test_month=0):
print flnm
ext1 = bpy.get_name_ext_2d()
ext1 = ext1.strip()
model_res = bpy.get_res_ext()
model_res = model_res.strip()
# model information
gc_lon = cmgrd.get_model_lon(model_res=model_res)
ix = size(gc_lon)
gc_lat = cmgrd.get_model_lat(model_res=model_res)
iy = size(gc_lat)
reg_m = rco2_f.read_region_map()
reg_m = squeeze(reg_m)
nreg = max(reg_m.flat) + 1
coef_m = zeros(shape(reg_m), float)
sstep = r'%2.2d' % (inv_step)
resflnm = inv_path + "std_oco_assim_res" + "." + sstep + ".nc"
print resflnm
varnames = ['whole_x', 'whole_x0', 'dx', 'sum_xtm']
x, x0, dx, xtm = ofb.ncf_read(resflnm, varnames)
coef_a = x - x0
if (test_month > 0):
stest_month = r'%2.2d' % (test_month - 1)
resflnm = inv_path + "/" + "std_oco_assim_res" + "." + stest_month + ".nc"
print resflnm
x_t, x0_t, dx_t, xtm_t = ofb.ncf_read(resflnm, varnames)
coef_t = x_t - x0_t
nx = nreg - 1
nst = (yyyy - 2004) * 12 * nx
for imm in range(1, 13):
# read biomass_burning in regular grid box
# covert to ktC /y
coef_cut = coef_a[nst:nst + nx]
coef_m[:, :] = 0
if (imm <= test_month):
coef_cut = coef_t[nst:nst + nx]
for ireg in range(1, nreg):
sel_cells = where(reg_m == ireg)
coef_m[sel_cells] = coef_cut[ireg - 1]
tau0 = tm.get_tau(yyyy, imm, 1)
tau0 = tau0 / 3600.0
if (imm < 12):
tau1 = tm.get_tau(yyyy, imm + 1, 1)
else:
tau1 = tm.get_tau(yyyy + 1, 1, 1)
tau1 = tau1 / 3600.0
sdate = r'%4.4d%2.2d' % (yyyy, imm)
full_flnm = flux_name + "." + sdate
funit = wfbp.open_flux_bpch2_file(full_flnm, title='flux')
unit = 'unitless'
wfbp.write_flux_record(funit, coef_m, \
gc_lon, gc_lat,\
tau0, tau1,\
ntracer, \
modelname,\
category,\
unit, \
do_debug=False)
wfbp.close_flux_bpch2_file(funit)
nst = nst + nx
def gen_transcom_coef(flux_name,\
yyyy,\
coef_a,\
inv_step,\
inv_path=gcdf.inv_path,\
modelname='GEOS5', \
category='CO2-SRCE', ntracer=1, \
do_debug=True, \
test_month=0):
# print flnm
ext1 = bpy.get_name_ext_2d()
ext1 = ext1.strip()
model_res = bpy.get_res_ext()
model_res = model_res.strip()
# model information
gc_lon = cmgrd.get_model_lon(model_res=model_res)
ix = size(gc_lon)
gc_lat = cmgrd.get_model_lat(model_res=model_res)
iy = size(gc_lat)
reg_m = rco2_f.read_region_map('2006D001')
reg_m = squeeze(reg_m)
nreg = max(reg_m.flat) + 1
coef_m = zeros(shape(reg_m), float)
# nx=nreg # -1
# nst=(yyyy-2003)*12*nx
nst = 0
idoy = 1
nstep = inv_step
print 'nstep, nreg', nstep, nreg
inc_doy = 8
for istep in range(0, nstep):
# read biomass_burning in regular grid box
# covert to ktC /y
coef_cut = coef_a[nst:nst + nreg]
coef_m[:, :] = 0
sdoy = r'%4.4dD%3.3d' % (yyyy, idoy)
reg_flux = rco2_f.read_reg_flux_map(sdoy)
print shape(reg_flux)
for ireg in range(nreg):
coef_m[:, :] = coef_m[:, :] + coef_cut[ireg] * reg_flux[:, :, ireg]
yyyy, mm, dd = tm.doy_to_time_array(idoy, yyyy)
tau0 = tm.get_tau(yyyy, mm, dd)
tau0 = tau0 / 3600.0
idoy = idoy + inc_doy
yyyy, mm, dd = tm.doy_to_time_array(idoy, yyyy)
tau1 = tm.get_tau(yyyy, mm, dd)
tau1 = tau1 / 3600.0
full_flnm = flux_name + sdoy
funit = wfbp.open_flux_bpch2_file(full_flnm, title='flux')
unit = 'kg/s'
print '--------sum--------'
print 'step:', istep
print 'max, min adjustment (GtC/a):', ocu.kg_s_to_GtC_Y * max(
coef_m.flat), ocu.kg_s_to_GtC_Y * min(coef_m.flat)
print 'total adjustment (GtC/a):', ocu.kg_s_to_GtC_Y * sum(coef_m)
print 'max, min adjustment (kg/s):', max(coef_m.flat), min(coef_m.flat)
print 'total adjustment (kg/s):', sum(coef_m)
print '--------end--------'
wfbp.write_flux_record(funit, coef_m, \
gc_lon, gc_lat,\
tau0, tau1,\
ntracer, \
modelname,\
category,\
unit, \
do_debug=False)
wfbp.close_flux_bpch2_file(funit)
nst = nst + nreg