nmax = int((1300. * 86400.) / dt) # total duration of run
# create model instance
model = TwoLevel(sp, dt)
print 'pole/equator temp diff = ', model.thetaref.max() - model.thetaref.min()
# vort, div initial conditions
psipert = np.zeros((2, model.nlat, model.nlon), np.float)
psipert[1, :, :] = 5.e6 * np.sin(
(model.lons - np.pi))**12 * np.sin(2. * model.lats)**12
psipert = np.where(model.lons[np.newaxis, :, :] > 0., 0, psipert)
psipert[1, :, :] += np.random.normal(scale=1.e6, size=(sp.nlats, sp.nlons))
ug = np.zeros((2, model.nlat, model.nlon), np.float)
vg = np.zeros((2, model.nlat, model.nlon), np.float)
ug[1, :, :] = model.umax * np.sin(2. * model.lats)**model.jetexp
vrtspec, divspec = sp.getvrtdivspec(ug, vg)
vrtspec = vrtspec + model.lap * sp.grdtospec(psipert)
thetaspec = model.nlbalance(vrtspec)
divspec = np.zeros(thetaspec.shape, thetaspec.dtype)
# create netcdf file.
nc = Dataset(output_file, 'w', format='NETCDF4_CLASSIC')
nc.rsphere = rsphere
nc.gridtype = gridtype
nc.ntrunc = ntrunc
nc.dt = dt
atts = [
'grav', 'omega', 'cp', 'rgas', 'p0', 'ptop', 'delth', 'efold', 'ndiss',
'tdrag', 'tdiab', 'umax', 'jetexp'
]
for att in atts:
nobsall = len(oblatsall)
print '# %s obs to assimilate (out of %s) with ob err stdev = %s' % (nobs,nobsall,oberrstdev)
print '# covlocal_scale=%s km, covinflate1=%s covinflate2=%s' %\
(covlocal_scale/1000., covinflate1, covinflate2)
thetaobsall = np.empty((nassim,nobsall),np.float)
utruth = np.empty((nassim,2,nlats,nlons),np.float)
vtruth = np.empty((nassim,2,nlats,nlons),np.float)
wtruth = np.empty((nassim,nlats,nlons),np.float)
thetatruth = np.empty((nassim,nlats,nlons),np.float)
oberrvar = np.empty(nobs,np.float); oberrvar[:] = oberrstdev**2
obtimes = np.empty((nassim),np.float)
for n in range(nassim):
# flip latitude direction so lats are increasing (needed for interpolation)
vrtspec_tmp,divspec_tmp =\
spin.getvrtdivspec(nct.variables['u'][n],nct.variables['v'][n])
w = models[0].dp*spin.spectogrd(divspec_tmp[1]-divspec_tmp[0])
obtimes[n] = nct.variables['t'][n]
thetaobsall[n] =\
bilintrp(nct.variables['theta'][n,::-1,:],lons,lats[::-1],oblonsall,oblatsall)
if samegrid:
utruth[n] = nct.variables['u'][n]
vtruth[n] = nct.variables['v'][n]
thetatruth[n] = nct.variables['theta'][n]
wtruth[n] = w
else:
utruth[n], vtruth[n] =\
regriduv(spin,spout,nct.variables['u'][n],nct.variables['v'][n])
thetatruth[n] = regrid(spin,spout,nct.variables['theta'][n],levs=1)
wtruth[n] = regrid(spin,spout,w,levs=1)
nct.close()
varspect[indxn[n]] += 2.*norm[n]*vrtmag
varspect[indxn[n]] += 2.*norm[n]*divmag
return varspect
f = Dataset('/Volumes/Drobo/truth_twolevel_t63_12h.nc')
lats = f.variables['lat'][:]; lons = f.variables['lon'][:]
u = f.variables['u']; v = f.variables['v']
ntimes, nlevs, nlats, nlons = u.shape
print nlons, nlats, f.ntrunc, f.rsphere
sp = Spharmt(nlons,nlats,int(f.ntrunc),f.rsphere,gridtype='gaussian')
kenorm = (-0.25*sp.invlap).astype(np.float)
kespecmean = None
nout = 0
for ntime in range(ntimes):
print ntime
vrtspec, divspec = sp.getvrtdivspec(u[ntime,1,...],v[ntime,1,...])
kespec = getvarspectrum(vrtspec,divspec,kenorm,sp.order,sp.degree,sp.ntrunc)
if kespecmean is None:
kespecmean = kespec
else:
kespecmean += kespec
nout += 1
kespecmean = kespecmean/nout
plt.loglog(np.arange(f.ntrunc+1),kespec,linewidth=2,\
label='t63')
f.close()
f = Dataset('truth_twolevel_t32_12h_tst.nc')
u = f.variables['u']; v = f.variables['v']
ntimes, nlevs, nlats, nlons = u.shape
print nlons, nlats, f.ntrunc, f.rsphere
nobs, nobsall, oberrstdev)
print '# covlocal_scale=%s km, covinflate=%s obshr_interval=%s' %\
(covlocal_scale/1000., covinflate, obshr_interval)
thetaobsall = np.empty((nassim, nobsall), np.float)
utruth = np.empty((nassim, 2, nlats, nlons), np.float)
vtruth = np.empty((nassim, 2, nlats, nlons), np.float)
wtruth = np.empty((nassim, nlats, nlons), np.float)
thetatruth = np.empty((nassim, nlats, nlons), np.float)
oberrvar = np.empty(nobs, np.float)
oberrvar[:] = oberrstdev**2
obtimes = np.empty((nassim), np.float)
for n in range(nassim):
# flip latitude direction so lats are increasing (needed for interpolation)
theta = nct.variables['theta'][n, ::-1, :]
vrtspec_tmp,divspec_tmp =\
spin.getvrtdivspec(nct.variables['u'][n,...],nct.variables['v'][n,...])
w = models[0].dp * spin.spectogrd(divspec_tmp[1] - divspec_tmp[0])
obtimes[n] = nct.variables['t'][n]
thetaobsall[n] = bilintrp(theta, lons, lats[::-1], oblonsall, oblatsall)
if samegrid:
utruth[n] = nct.variables['u'][n]
vtruth[n] = nct.variables['v'][n]
wtruth[n] = w
thetatruth[n] = nct.variables['theta'][n]
else:
utruth[n], vtruth[n] =\
regriduv(spin,spout,nct.variables['u'][n],nct.variables['v'][n])
thetatruth[n] = regrid(spin, spout, nct.variables['theta'][n], levs=1)
wtruth[n] = regrid(spin, spout, w, levs=1)
nct.close()
else:
nobsall = len(oblatsall)
print "# %s obs to assimilate (out of %s) with ob err stdev = %s" % (nobs, nobsall, oberrstdev)
print "# covlocal_scale=%s km, covinflate1=%s covinflate2=%s" % (covlocal_scale / 1000.0, covinflate1, covinflate2)
thetaobsall = np.empty((nassim, nobsall), np.float)
utruth = np.empty((nassim, 2, nlats, nlons), np.float)
vtruth = np.empty((nassim, 2, nlats, nlons), np.float)
wtruth = np.empty((nassim, nlats, nlons), np.float)
thetatruth = np.empty((nassim, nlats, nlons), np.float)
oberrvar = np.empty(nobs, np.float)
oberrvar[:] = oberrstdev ** 2
obtimes = np.empty((nassim), np.float)
for n in range(nassim):
# flip latitude direction so lats are increasing (needed for interpolation)
vrtspec_tmp, divspec_tmp = spin.getvrtdivspec(nct.variables["u"][n], nct.variables["v"][n])
w = models[0].dp * spin.spectogrd(divspec_tmp[1] - divspec_tmp[0])
obtimes[n] = nct.variables["t"][n]
thetaobsall[n] = bilintrp(nct.variables["theta"][n, ::-1, :], lons, lats[::-1], oblonsall, oblatsall)
if samegrid:
utruth[n] = nct.variables["u"][n]
vtruth[n] = nct.variables["v"][n]
thetatruth[n] = nct.variables["theta"][n]
wtruth[n] = w
else:
utruth[n], vtruth[n] = regriduv(spin, spout, nct.variables["u"][n], nct.variables["v"][n])
thetatruth[n] = regrid(spin, spout, nct.variables["theta"][n], levs=1)
wtruth[n] = regrid(spin, spout, w, levs=1)
nct.close()
# create initial ensemble by randomly sampling climatology
# create spherical harmonic instance.
rsphere = 6.37122e6 # earth radius
sp = Spharmt(nlons,nlats,ntrunc,rsphere,gridtype=gridtype)
# create model instance using default parameters.
model = TwoLevel(sp,dt)
# vort, div initial conditions
psipert = np.zeros((2,model.nlat,model.nlon),np.float)
psipert[1,:,:] = 5.e6*np.sin((model.lons-np.pi))**12*np.sin(2.*model.lats)**12
psipert = np.where(model.lons[np.newaxis,:,:] > 0., 0, psipert)
psipert[1,:,:] += np.random.normal(scale=1.e6,size=(sp.nlats,sp.nlons))
ug = np.zeros((2,model.nlat,model.nlon),np.float)
vg = np.zeros((2,model.nlat,model.nlon),np.float)
ug[1,:,:] = model.umax*np.sin(2.*model.lats)**model.jetexp
vrtspec, divspec = sp.getvrtdivspec(ug,vg)
vrtspec = vrtspec + model.lap*sp.grdtospec(psipert)
thetaspec = model.nlbalance(vrtspec)
divspec = np.zeros(thetaspec.shape, thetaspec.dtype)
# animate potential temperature
fig = plt.figure(figsize=(16,8))
vrtspec, divspec, thetaspec = model.rk4step(vrtspec, divspec, thetaspec)
thetamean = (model.theta*model.globalmeanwts).sum()
varplot = 'theta'
#varplot = 'w'
#varplot = 'u'
if varplot == 'theta':
data = model.theta - thetamean
vmax = 50; vmin = -vmax
print '# %s obs to assimilate (out of %s) with ob err stdev = %s' % (nobs,nobsall,oberrstdev)
print '# covlocal_scale=%s km, covinflate=%s obshr_interval=%s' %\
(covlocal_scale/1000., covinflate, obshr_interval)
thetaobsall = np.empty((nassim,nobsall),np.float)
utruth = np.empty((nassim,2,nlats,nlons),np.float)
vtruth = np.empty((nassim,2,nlats,nlons),np.float)
wtruth = np.empty((nassim,nlats,nlons),np.float)
thetatruth = np.empty((nassim,nlats,nlons),np.float)
oberrvar = np.empty(nobs,np.float); oberrvar[:] = oberrstdev**2
obtimes = np.empty((nassim),np.float)
for n in range(nassim):
# flip latitude direction so lats are increasing (needed for interpolation)
theta = nct.variables['theta'][n,::-1,:]
vrtspec_tmp,divspec_tmp =\
spin.getvrtdivspec(nct.variables['u'][n,...],nct.variables['v'][n,...])
w = models[0].dp*spin.spectogrd(divspec_tmp[1]-divspec_tmp[0])
obtimes[n] = nct.variables['t'][n]
thetaobsall[n] = bilintrp(theta,lons,lats[::-1],oblonsall,oblatsall)
if samegrid:
utruth[n] = nct.variables['u'][n]
vtruth[n] = nct.variables['v'][n]
wtruth[n] = w
thetatruth[n] = nct.variables['theta'][n]
else:
utruth[n], vtruth[n] =\
regriduv(spin,spout,nct.variables['u'][n],nct.variables['v'][n])
thetatruth[n] = regrid(spin,spout,nct.variables['theta'][n],levs=1)
wtruth[n] = regrid(spin,spout,w,levs=1)
nct.close()
f = Dataset('/Volumes/Drobo/truth_twolevel_t63_12h.nc')
lats = f.variables['lat'][:]
lons = f.variables['lon'][:]
u = f.variables['u']
v = f.variables['v']
ntimes, nlevs, nlats, nlons = u.shape
print nlons, nlats, f.ntrunc, f.rsphere
sp = Spharmt(nlons, nlats, int(f.ntrunc), f.rsphere, gridtype='gaussian')
kenorm = (-0.25 * sp.invlap).astype(np.float)
kespecmean = None
nout = 0
for ntime in range(ntimes):
print ntime
vrtspec, divspec = sp.getvrtdivspec(u[ntime, 1, ...], v[ntime, 1, ...])
kespec = getvarspectrum(vrtspec, divspec, kenorm, sp.order, sp.degree,
sp.ntrunc)
if kespecmean is None:
kespecmean = kespec
else:
kespecmean += kespec
nout += 1
kespecmean = kespecmean / nout
plt.loglog(np.arange(f.ntrunc+1),kespec,linewidth=2,\
label='t63')
f.close()
f = Dataset('truth_twolevel_t32_12h_tst.nc')
u = f.variables['u']
v = f.variables['v']
