#for nrun in arange(len(runs)):
#for nrun in [0,]:
for nrun in [
1,
]:
run = runs[nrun]
# for ntau in arange(len(mytau)):
for ntau in [
4,
]:
close('all')
tau = mytau[ntau]
r = 'taux%04d_rb0110_%s' % (tau * 10000, run)
b = bump_channel.BumpChannel(base_dir, r)
sol = MITgcmdata.poisson.solver(b) # conjugate gradient solver
T = b.rdmds('Ttave')
Tw = b.cgrid_to_ugrid(T) # on the U grid
Ts = b.cgrid_to_vgrid(T) # on the V grid
V = b.rdmds('Vveltave')
U = b.rdmds('Uveltave')
P = b.rdmds('Phhytave')
Ug = -(b.f[newaxis, :, newaxis]**-1) * b.ddy_cgrid_to_vgrid(P)
Vg = (b.f[newaxis, :, newaxis]**-1) * b.ddx_cgrid_to_ugrid(P)
Ua = U - Ug
Va = V - Vg
UT = b.rdmds('UTtave')
from pylab import *
import bump_channel
import mycolors
import os
base_dir = os.path.join(os.environ['D'], 'DATASTORE.RPA', 'projects',
'drag_strat')
b_bump = bump_channel.BumpChannel(base_dir, 'taux2000_rb0110_bump')
b_long = bump_channel.BumpChannel(base_dir, 'taux2000_rb0110_bumplong')
# k indices
kr = r_[0, 4, 8, 12, 15, 17:b_bump.Nz:2]
t**s = ['ridge', 'long']
for b in [b_bump, b_long]:
b.load_default_fields()
b.VTwave = (b.Vwave * b.cgrid_to_vgrid(b.Twave)).mean(axis=2)
b.WTwave = (b.Wwave * b.cgrid_to_wgrid(b.Twave)).mean(axis=2)
b.VTg = b.VpTpbar + b.VTwave
b.WTg = b.WpTpbar + b.WTwave
deltaTheta = 8.
Qfac = b.rho0 * 3994
for b in [b_bump, b_long]:
b.D = -2 * b.integrate_vertical(
b.zc[:, newaxis] * b.Tbar) / b.integrate_vertical(b.Tbar)[-2]
b.Kg = -b.integrate_vertical(b.VTg) * b.Ly / (b.D * deltaTheta)
b.Hek = Qfac * b.Lx * b.integrate_vertical(b.Tbar * b.Vbar)
b.Hg = Qfac * b.Lx * b.integrate_vertical(b.VTg)
from pylab import *
import os
import bump_channel
import mycolors
rcParams['figure.figsize'] = [6, 3.5]
rcParams['legend.fontsize'] = 7
rcParams['font.size'] = 8
base_dir = os.path.join(os.environ['D'], 'DATASTORE.RPA', 'projects',
'drag_strat')
b = bump_channel.BumpChannel(base_dir, 'taux2000_rb0110_bump')
#b = bump_channel.BumpChannel(base_dir, 'taux2000_rb0110_flat')
T = b.rdmds('Ttave')
Tw = b.cgrid_to_ugrid(T) # on the U grid
Ts = b.cgrid_to_vgrid(T) # on the V grid
V = b.rdmds('Vveltave')
U = b.rdmds('Uveltave')
UT = b.rdmds('UTtave')
VT = b.rdmds('VTtave')
# vertically integrated fluxes
THETA = b.average_vertical(T)
THETAw = b.cgrid_to_ugrid(THETA)
THETAs = b.cgrid_to_ugrid(THETA)
# full time-mean flux
divTflux_m = b.ddx_ugrid_to_cgrid(UT) + b.ddy_vgrid_to_cgrid(VT)
# eddy flux
from pylab import *
import os
import bump_channel
run_name = 'taux2000_rb0110_bump'
base_dir = os.path.join(os.environ['D'], 'projects', 'drag_strat')
b = bump_channel.BumpChannel(base_dir, run_name)
outdir = '/Volumes/scratch/tmp/output_for_paraview/' + run_name
T = b.rdmds('Ttave')
V = b.rdmds('Vveltave')
U = b.rdmds('Uveltave')
W = b.rdmds('Wveltave')
P = b.rdmds('Phhytave')
UT = b.rdmds('UTtave')
VT = b.rdmds('VTtave')
WT = b.rdmds('WTtave')
Tdif = b.rdmds('Tdiftave')
Tbar = T.mean(axis=2)[:, :, newaxis]
Vbar = V.mean(axis=2)[:, :, newaxis]
Ubar = U.mean(axis=2)[:, :, newaxis]
Wbar = W.mean(axis=2)[:, :, newaxis]
Panom = P - P[:, :, 0][:, :, newaxis]
# terms in heat budget
dx_UT = b.ddx_ugrid_to_cgrid(UT)
dy_VT = b.ddy_vgrid_to_cgrid(VT)
dz_WT = b.ddz_wgrid_to_cgrid(WT)
res = dict()
for k in [
'D', 'D05', 'APE', 'PEtoKE', 'EPEtoEKE', 'PEtoIE', 'KEdiss', 'EKEdiss',
'EKEbot', 'EKE'
]:
res[k] = zeros(N)
for n in arange(N):
tau0 = tau[n]
if tau0 == 0:
suf = 'flatshort'
else:
suf = 'flat'
b = bump_channel.BumpChannel(base_dir,
'taux%04d_rb0110_%s' % (tau0 * 10000, suf))
b.load_default_fields()
U2 = b.rdmds('UUtave')
V2 = b.rdmds('VVtave')
EKE = 0.5 * (U2 - b.U**2 + V2 - b.V**2).mean(axis=2)
# thermocline depth
D = -2 * b.integrate_vertical(
b.zc[:, newaxis] *
(b.Tbar - b.Tbar[-1])) / b.integrate_vertical(b.Tbar)
res['D'][n] = D[-2]
# depth of 0.5 degree isotherm
res['D05'][n] = -interp(0.5, b.Tbar[::-1, -2], b.zc[::-1])
# available potential energy
from pylab import *
import bump_channel
#import mycolors
import os
base_dir = os.path.join(os.environ['D'], 'DATASTORE.RPA', 'projects',
'drag_strat')
b_bump = bump_channel.BumpChannel(base_dir, 'taux2000_rb0110_bump')
b_flat = bump_channel.BumpChannel(base_dir, 'taux2000_rb0110_flat')
for B in [b_bump]: #,b_flat]:
c = B.get_APEcomputer()
Ep = c.calc_PE()
Eb = c.calc_BPE()
Ea = c.calc_APE()
# Stu's QG approximation
bmean = c.b.mean(axis=1).mean(axis=1)
N2 = B.ddz_cgrid_centered(bmean)
Ea_QG = sum(c.vol * 0.5 * (c.b - bmean[:, newaxis, newaxis])**2 /
N2[:, newaxis, newaxis])
bbar = tile(c.b.mean(axis=2)[:, :, newaxis], [1, 1, B.Nx])
bbar_z = B.ddz_cgrid_centered(bbar)
bwave = c.b - bbar
print('%040s: %4.2f PJ' % ('Total Potential Energy', Ep / 1e15))
print('%040s: %4.2f PJ' % ('Background Potential Energy', Eb / 1e15))
print('%040s: %4.2f PJ' % ('Available Potential Energy', Ea / 1e15))
print('%040s: %4.2f PJ' %