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Update, including the inclusion of creating a s-th-diagram (work in progress)

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Gabriel Wolf 2018-09-21 18:10:29 +01:00
parent a6fbce9822
commit 046e99856c
3 changed files with 222 additions and 18 deletions
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52
calc_ref_state.py
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@ -30,6 +30,7 @@ from get_data import get_data_woa2009 as read_data
# calculation modules # calculation modules
from mycalc_ocean import calc_rho_from_theta # calc of density from theta from mycalc_ocean import calc_rho_from_theta # calc of density from theta
from mycalc_ocean import calc_area_lat # calc horizontal area from mycalc_ocean import calc_area_lat # calc horizontal area
from gw_ocean_refstate import refstate_meandensity, refstate_sorted_stheta # calc. ref. states
# plotting modules / functions # plotting modules / functions
from myplot import myplot_2dmap # plot of lat-lon fields from myplot import myplot_2dmap # plot of lat-lon fields
from myplot import myplot_2d # plot of crossections fields from myplot import myplot_2d # plot of crossections fields
@ -44,18 +45,22 @@ from myplot_inputs import myplot_create_pn # create plotname
# variables : variables necessary for calculations # variables : variables necessary for calculations
# MANUAL DEFINED OUTPUTS MISSING # MANUAL DEFINED OUTPUTS MISSING
# ############################################################################################ # ############################################################################################
print '----------------------------------------------'
print 'Manual defined input data'
# information about input data # information about input data
print 'MANUAL DEFINED OUTPUTS MISSING' print ' *** MANUAL DEFINED OUTPUTS MISSING ***'
dim = ('lon','lat','z','time',) dim = ('lon','lat','z','time',)
variables = {'s':{},'theta':{},'grd':[],'valid':[]} variables = {'s':{},'theta':{},'grd':[],'valid':[]}
# plotting input # plotting input
plot_var = {'rho':[]} plot_var = {'rho':[]}
saveplot = input('Do you want to save the plots? Enter 1 for yes or 0 for no') saveplot = input(' Save plots? Enter 1 for YES or 0 for NO: ')
dir_plot = '/glusterfs/inspect/users/xg911182/Code/Python/plots_test/' dir_plot = '/glusterfs/inspect/users/xg911182/Code/Python/plots_test/'
lonlat_reg = [25.0, 25.0+360.0, -90.0, 90.0] # plotting range for 2dmap lonlat_reg = [25.0, 25.0+360.0, -90.0, 90.0] # plotting range for 2dmap
plot_2d = 1 # plot 2d fields (lat-lon) plot_2d = 1 # plot 2d fields (lat-lon)
plot_cs = 1 # plot crosssections plot_cs = 1 # plot crosssections
cs_plot = {'lon':[-47.5,172.5],'lat':[0]} # crosssections cs_plot = {'lon':[-47.5,172.5],'lat':[0]} # crosssections
print '----------------------------------------------'
# Input 1 #################################################################################### # Input 1 ####################################################################################
# Physical constants # Physical constants
# input : None # input : None
@ -174,20 +179,49 @@ print '----------------------------------------------'
# step e ##################################################################################### # step e #####################################################################################
# Calculate reference state # Calculate reference state
# input : dens, zlev, area_xyz # input : area_xyz, dens, _t, zlev, ztarget
# dens : output of step c # dens : output of step c
# i_t : MISSING - DONE LOCALLY HERE
# zlev : output of step a # zlev : output of step a
# area_xyz : output of step d # area_xyz : output of step d
# otput : pp_rhor # ztarget : target depth [m], 1d - DONE LOCALLY HERE
# pp_rhor : interpolant of reference density # otput : pp_rhor, pp_rhor_botup, pp_rhor_topdn
# pp_rhor : interpolant for ref. density (hor. av. rho)
# pp_rhor_botup : interpolant for ref. density (sorted in th-s-space, calc. bottom-up)
# pp_rhor_topdn : interpolant for ref. density (sorted in th-s-space, calc. top-down)
# ############################################################################################ # ############################################################################################
beg_time = time.time() i_t = 0
# define target depth
n_target = grd.Nz+9
ztarget = np.zeros(n_target)
ztarget[0:10] = np.arange(0,10)
ztarget[10:] = grd.z[1:]
beg_time = time.time()
print '' print ''
print '----------------------------------------------' print '----------------------------------------------'
print 'Insert code to calculate reference state' print 'Calculate reference state for mean density'
# Define input data
mask = data['rho']['valid'][:,:,:,i_t]
# calculation of reference profiles
pp_rhor = refstate_meandensity(data['rho']['val'][:,:,:,i_t]*mask,grd,area_xyz*mask)
end_time = time.time()
beg_time2 = time.time()
print 'Calculate sorted density reference state'
# Define input data
rho = data['rho']['val']
s = data['s']['val']
th = data['theta']['val']
mask = data['rho']['valid']*data['s']['valid']*data['theta']['valid']
# calculation of reference profiles
pp_rhor_botup, pp_rhor_topdn = refstate_sorted_stheta(th,s,rho,mask,ztarget,grd)
input('Stop here')
# Deallocation
del th, s, rho
print '----------------------------------------------' print '----------------------------------------------'
end_time = time.time() end_time2 = time.time()
print 'Elapsed time to calculate reference state: '+ '{:.2f}'.format(end_time-beg_time)+'s' print 'Elapsed time to calculate reference state: '
print '-> mean density (hor. averaged): '+ '{:.2f}'.format(end_time-beg_time)+'s'
print '-> sorted density in S-Theta diagram: '+ '{:.2f}'.format(end_time2-beg_time2)+'s'
print '----------------------------------------------' print '----------------------------------------------'
# step f ##################################################################################### # step f #####################################################################################

75
gw_ocean_refstate.py
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@ -1,5 +1,5 @@
def refstate_meandensity(rho_in,grd,area_xyz_in): def refstate_meandensity(rho_in,grd,area_xyz_in):
# def refstate_meandensity(rho,zlev,area_xyz) ############################################ # refstate_meandensity(rho,zlev,area_xyz) ################################################
# written by : Gabriel Wolf, g.a.wolf@reading.ac.uk # written by : Gabriel Wolf, g.a.wolf@reading.ac.uk
# adapted from get_refstate_meandensity.m of Remi Tailleux (10.04.2013) # adapted from get_refstate_meandensity.m of Remi Tailleux (10.04.2013)
# last modified : 20.09.2018 # last modified : 20.09.2018
@ -25,3 +25,76 @@ def refstate_meandensity(rho_in,grd,area_xyz_in):
pp_rhor = interpolate.PchipInterpolator(grd.z, rhor, axis=0) pp_rhor = interpolate.PchipInterpolator(grd.z, rhor, axis=0)
# return interpolant for reference state # return interpolant for reference state
return pp_rhor return pp_rhor
def refstate_sorted_stheta(th,s,rho,mask,ztarget,grd,sbin=[0.0,43.0,0.002],\
thbin=[-2.6,30.0,0.005]):
# refstate_sorted_stheta(th,s,rho,mask,ztarget,grd) ######################################
# written by : Gabriel Wolf, g.a.wolf@reading.ac.uk
# adapted from get_refstate_sorted.m of Remi Tailleux (10.04.2013)
# last modified : 20.09.2018
# Content/Description ####################################################################
# Reference : method based on Tailleux (2013), -> https://doi.org/10.1017/jfm.2013.509
# : summary of this framework in Saenz et al. (2015):
# -> https://doi.org/10.1175/JPO-D-14-0105.1
# Usage : from gw_ocean_refstate import refstate_sorted_stheta
# Input : grd, mask, rho, s, sbin, thbin, th, ztarget
# grd : Input grid [python class]
# mask : valid points [boolean], 3d
# rho : density [kg m**-3], 3d
# s : salinity [psu], 3d
# s_bin : bin range for s to construct s-th-diagram [min,max,delta]
# th : potential temperature [deg C], 3d
# th_bin : bin range for th to construct s-th-diagram [min,max,delta]
# ztarget : target height level [m], 1d
# Output :pp_rhor_botup, pp_rhor_topdn
# pp_rhor_botup : interpolant for density reference state (calc. from bottom up)
# pp_rhor_topdn : interpolant for density reference state (calc. from bottom up)
# ########################################################################################
# Load modules
import numpy as np
from scipy import interpolate # for interpolation
from mycalc_ocean import volume_census_levitus # to create s-th-pdf with vol info
# Allocation
n_target = len(ztarget)
s[mask==False] = np.nan
th[mask==False] = np.nan
rho[mask==False] = np.nan
# Compute the pdf of the salinity/theta data ---------------------------------------------
print ' *** MISSING: computation of the pdf salinity/theta data ***'
pdf_vol_lev, vol_tot_ocean = volume_census_levitus(th, s, grd, thbin, sbin)
# Define properties of the binned temperature/salinity data ------------------------------
#n_sbin, n_thbin =
print ' *** MISSING: property definition of binned temperature/salinity data ***'
# define target pressure from target depths ----------------------------------------------
print ' *** MISSING: define target pressure from target depths ***'
# compute bounding salinity curves -------------------------------------------------------
print ' *** MISSING: compute bounding salinity curves ***'
# Seek the global min. and max. of density by bringing all parcels at the surface and at
# the bottom and the oceans ----------------------------------------------------------
print ' *** MISSING: density profiles ***'
# Compute potential density reference to target pressure at surface ----------------------
print ' *** MISSING: pot. density at surface ***'
# Compute potential density referenced to last target pressure ---------------------------
print ' *** MISSING: pot. density for last target pressure ***'
# Compute global density minimum and maximum ---------------------------------------------
print ' *** MISSING: min. and max. of global density ***'
# Compute upper and lower salinity curves in theta/salt space ----------------------------
print ' *** MISSING: upper and lower salinity curves in th-s space ***'
# Compute the topography statistics ------------------------------------------------------
print ' *** MISSING: topography statistics ***'
# New attempt to compute the top-down profile --------------------------------------------
print ' *** MISSING: rhor top-down profile ***'
print(' Computing top-dwon profile for reference density')
# Allocation
rhor_topdn = np.zeros(n_target)
# New attempt at computing bottom-up profile ---------------------------------------------
print ' *** MISSING: rhor bottom-up profile ***'
print(' Computing bottom-up profile for reference density')
# Allocation
rhor_botup = np.zeros(n_target)
# Assign interpolants for the two possible reference states ------------------------------
pp_rhor_botup = interpolate.PchipInterpolator(ztarget, rhor_botup, axis=0)
pp_rhor_topdn = interpolate.PchipInterpolator(ztarget, rhor_topdn, axis=0)
# return interpolant for the two reference states ----------------------------------------
#return pp_rhor_botup, pp_rhor_topdn
return pdf_vol_lev, vol_tot_ocean

113
mycalc_ocean.py
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@ -2,17 +2,19 @@
# calc_rho_from_theta # calc_rho_from_theta
# calc_theta_from_temp # calc_theta_from_temp
# gsw_g # gsw_g
# volume_census_levitus
def calc_area_lat(grd,r_earth,calc_old=0): def calc_area_lat(grd,r_earth,calc_old=0):
# def calc_area_lat(grd,r_earth) ######################################################### # def calc_area_lat(grd,r_earth) #########################################################
# written by : Gabriel Wolf, g.a.wolf@reading.ac.uk # written by : Gabriel Wolf, g.a.wolf@reading.ac.uk
# adapted from get_area_latitude.m of Remi Tailleux (09/2018) # adapted from get_area_latitude.m of Remi Tailleux (09/2018)
# last modified : 19.09.2018 # last modified : 20.09.2018
# Content/Description #################################################################### # Content/Description ####################################################################
# Usage : from mycalc_ocean import calc_area_lat
# Input : grd, r_earth # Input : grd, r_earth
# grd : Input grid [python class] # grd : Input grid [python class]
# r_earth : earth radius [m] # r_earth : earth radius [m]
# Output : area_lat # Output : area_lat
# area_lat : hor. area for 3d grid [m**2] # area_xyz : hor. area for 3d grid [m**2]
# ######################################################################################## # ########################################################################################
# import modules # import modules
import numpy as np import numpy as np
@ -20,10 +22,10 @@ def calc_area_lat(grd,r_earth,calc_old=0):
deg_to_rad = np.pi/180.0 deg_to_rad = np.pi/180.0
lat_radians = grd.lat*deg_to_rad lat_radians = grd.lat*deg_to_rad
if calc_old == 1: if calc_old == 1:
print '*** old version of area calculation ***' print ' *** old version of area calculation ***'
# compute length of longitudinal and latitudinal elements # compute length of longitudinal and latitudinal elements
print '*** area calculation not valid for non-equidistant input lon-grid ***' print ' *** area calculation not valid for non-equidistant input lon-grid ***'
print '*** area calculation not valid for non-equidistant input lat-grid ***' print ' *** area calculation not valid for non-equidistant input lat-grid ***'
dx = r_earth*deg_to_rad*(grd.Nlon/360.0) dx = r_earth*deg_to_rad*(grd.Nlon/360.0)
dy = r_earth*deg_to_rad*abs(grd.lat[1]-grd.lat[0]) dy = r_earth*deg_to_rad*abs(grd.lat[1]-grd.lat[0])
# calculate area # calculate area
@ -166,7 +168,7 @@ def calc_theta_from_temp(s,temp,p,pr):
if s.shape != pr.shape: if s.shape != pr.shape:
raise ValueError('**** Data shape of salinity and reference pressure do not agree ****') raise ValueError('**** Data shape of salinity and reference pressure do not agree ****')
# Calculate first estimate for potential temperature # Calculate first estimate for potential temperature
print 'Is this above statemtent true? First estimate?' print ' Is this above statemtent true? First estimate?'
n0 = 0 n0 = 0
n2 = 2 n2 = 2
# Allocate values # Allocate values
@ -175,7 +177,7 @@ def calc_theta_from_temp(s,temp,p,pr):
p1 = p p1 = p
pr1 = pr pr1 = pr
# First estimate for pot. temp. # First estimate for pot. temp.
print 'Where is this equation coming from?' print ' Where is this equation coming from?'
theta = t1 + (p1-pr1)*( 8.65483913395442e-6 - \ theta = t1 + (p1-pr1)*( 8.65483913395442e-6 - \
s1*1.41636299744881e-6 - \ s1*1.41636299744881e-6 - \
(p1+pr1) * 7.38286467135737e-9 + \ (p1+pr1) * 7.38286467135737e-9 + \
@ -189,7 +191,7 @@ def calc_theta_from_temp(s,temp,p,pr):
# NOTE: nloops = 1 gives theta with a maximum error of ... # NOTE: nloops = 1 gives theta with a maximum error of ...
# nloops = 2 gives theta with a maximum error of ... # nloops = 2 gives theta with a maximum error of ...
n = 0 n = 0
print 'Where are the equations in this while loop coming from?' print ' Where are the equations in this while loop coming from?'
while n <= nloops: while n <= nloops:
n = n+1 n = n+1
theta_old = theta; theta_old = theta;
@ -429,3 +431,98 @@ def gsw_g(Ns,Nt,Np,s,temp,p):
(681.370187043564 - 133.5392811916956*z)*z)))) (681.370187043564 - 133.5392811916956*z)*z))))
result = (g03 + g08)*1e-16 result = (g03 + g08)*1e-16
return result return result
def volume_census_levitus(th, s, grd, thbin, sbin):
# volume_census_levitus(th,s,grd,thbin,sbin) #############################################
# written by : Gabriel Wolf, g.a.wolf@reading.ac.uk
# adapted from volume_census_levitus.m of Remi Tailleux (08.03.2013)
# last modified : 20.09.2018
# Content/Description ####################################################################
# Usage : from mycalc_ocean import volume_census_levitus
# Input : grd, s, sbin, th, thbin
# grd : Input grid [python class]
# s : salinity [psu], 3d
# sbin : bin range for s to construct s-th-diagram [min,max,delta]
# th : potential temperature [deg C], 3d
# thbin : bin range for th to construct s-th-diagram [min,max,delta]
# Output : pdf_vol_lev, vol_ocean_lev
# pdf_vol_lev :
# vol_ocean_lev :
# ########################################################################################
# Load modules
import numpy as np
from myconstants import r_earth
from mydata_classes import Grid # class containing grid information
from scipy.interpolate import interpn # interpolation in 3d
# error checking
if grd.symlon == 0:
raise ValueError('*** Input grid must span full longitude grid ***')
# Compute the number of points in each categories
n_sbin = np.ceil((sbin[1]-sbin[0])/sbin[2])
n_thbin = np.ceil((thbin[1]-thbin[0])/thbin[2])
# Allocate pdf_vol_lev (pdf in s-th-space)
pdf_vol_lev = np.zeros([n_sbin, n_thbin])
# Define a finer mesh associated with known volume elements that are used
res_xfine = 0.25
res_yfine = 0.25
res_zfine = 10.0
if grd.lon[1]-grd.lon[0] > res_xfine:
lon_fine = np.arange(res_xfine/2.0,360,res_xfine)
else:
lon_fine = grd.lon
if grd.lat[1]-grd.lat[0] > res_yfine:
lat_fine = np.arange(-90.0+res_yfine/2.0,90.0,res_yfine)
else:
lat_fine = grd.lat
z_max = max(grd.z)+max(grd.z)%(10**np.floor(np.log10(max(grd.z))))
n_z = np.ceil(z_max/res_zfine)
n_z_sub = n_z/10.0
z_range = z_max/n_z_sub
vol_tot_ocean = 0.0
print(' Vertical levels: '+ str(int(n_z)) + ', splitted into ' +\
str(int(n_z_sub)) + ' subdomains')
# Compute the volume associted with each elements as a function of l
print ' *** MISSING: make volume z-dependent ***'
grd_fine = Grid(0,lat_fine,0.0,[],1,len(lat_fine),[],[],[],[],[],[])
grd_fine.symlon = 1
vol_fine_lat = np.squeeze(calc_area_lat(grd_fine,r_earth))*res_zfine
# Split vertical domains into smaller subdomains
for i_subdom in range(0,int(n_z_sub)):
print ' Subdomain ' + str(int(i_subdom+1)) + ' of ' + str(int(n_z_sub))
# create meshgrid for interpolation
z_beg = res_zfine/2.0 + i_subdom * z_range
z_end = res_zfine/2.0 + (i_subdom+1) * z_range - 1
z_fine = np.arange(z_beg,z_end,res_zfine)
yfine_xyz, xfine_xyz, zfine_xyz = np.meshgrid(lat_fine, lon_fine, z_fine)
# interpolate s and th onto finer grid
reshape_form = [len(lon_fine),len(lat_fine),len(z_fine)]
xyz_fine_pt = np.array([np.reshape(xfine_xyz,[np.prod(reshape_form)]),\
np.reshape(yfine_xyz,[np.prod(reshape_form)]),\
np.reshape(zfine_xyz,[np.prod(reshape_form)])]).T
s_fine = np.reshape(interpn((grd.lon,grd.lat,grd.z), s, xyz_fine_pt, \
bounds_error=False, fill_value=None),reshape_form)
th_fine = np.reshape(interpn((grd.lon,grd.lat,grd.z), th, xyz_fine_pt, \
bounds_error=False, fill_value=None),reshape_form)
del xyz_fine_pt
print ' replace this np.nan stuff'
s_fine[s_fine<sbin[0]] = np.nan
s_fine[s_fine>sbin[1]] = np.nan
th_fine[th_fine<thbin[0]] = np.nan
th_fine[th_fine>thbin[1]] = np.nan
# associate s-bin and th-bin integers to s_fine and th_fine
i_s = np.ceil((s_fine-sbin[0])/sbin[2])
i_th = np.ceil((th_fine-thbin[0])/thbin[2])
# write associated ocean volume into s- and th-bins
for i_xf in range(0,reshape_form[0]):
for i_yf in range(0,reshape_form[1]):
for i_zf in range(0,reshape_form[2]):
i_sd = i_s[i_xf,i_yf,i_zf]
i_thd = i_th[i_xf,i_yf,i_zf]
if (i_sd == i_sd) and (i_thd == i_thd):
pdf_vol_lev[i_sd,i_thd] = pdf_vol_lev[i_sd,i_thd] + \
vol_fine_lat[i_yf]
vol_tot_ocean = vol_tot_ocean + vol_fine_lat[i_yf]
del grd_fine
# Return
return pdf_vol_lev, vol_tot_ocean