{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%config InlineBackend.figure_format='svg'\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib.patches as mpatches\n",
"import numpy as np\n",
"import matplotlib as mpl\n",
"import xarray as xr\n",
"import seawater\n",
"import jmkfigure\n",
"# import colorcet as cc\n",
"\n",
"!mamba env export > environment.yml\n",
"\n",
"\n",
"def diffarray(a,b):\n",
" for bb in b:\n",
" a=a[abs(a-bb)>1.e-10]\n",
" return a\n",
"lon0=-125.6\n",
"lat0=48.4\n",
"def getSpice(pden,temp,sal):\n",
" \n",
" import seawater as sw\n",
"\n",
" beta = 7.7e-4*1000\n",
" alpha = 2.0e-4*1000\n",
" Sline=np.array([33.2,33.8])\n",
" Tline=np.array([7.75,6.6])\n",
" Sarray = np.arange(30,35,0.01)\n",
" m = (np.diff(Tline)/np.diff(Sline))\n",
" Tarray = m*(Sarray-Sline[0])+Tline[0]\n",
" Pdarray=sw.pden(Sarray,Tarray,100.+0.*Tarray,0.)\n",
" #plot(Pdarray)\n",
" S0 = np.interp(pden,Pdarray,Sarray)\n",
" T0 = m*(S0-Sline[0])+Tline[0]\n",
" dT = -(T0-temp)\n",
" dS = -(S0-sal)\n",
" tau = beta*(dS)+alpha*(dT)\n",
" return tau"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# LaPerouse 2013 data"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"\n",
"import glob\n",
"cruises = ['038', '058']\n",
"if False:\n",
" for cruise in cruises:\n",
" d = glob.glob(f'ctddata/2013-{cruise}-*.nc')\n",
" print(len(d))\n",
" big = xr.Dataset(coords=dict(z=np.arange(2000), index=np.arange(len(d))),\n",
" data_vars=dict(\n",
" temperature=(['z', 'index'], np.NaN*np.zeros((2000, len(d)))),\n",
" salinity=(['z', 'index'], np.NaN*np.zeros((2000, len(d)))),\n",
" O2=(['z', 'index'], np.NaN*np.zeros((2000, len(d)))),\n",
" lon=('index', np.zeros(len(d))),\n",
" lat=('index', np.zeros(len(d))),\n",
" time=('index', np.zeros(len(d), dtype='datetime64[ns]')))\n",
" )\n",
" \n",
" for n,fn in enumerate(d):\n",
" with xr.open_dataset(fn) as ds:\n",
" if ds.sizes['z'] > 20:\n",
" big['lon'][n] = ds.longitude\n",
" big['lat'][n] = ds.latitude\n",
" big['time'][n] = ds.time\n",
" N = np.min([ds.sizes['z'], 2000])\n",
" big['temperature'][:N, n] = ds.sea_water_temperature[:N]\n",
" big['salinity'][:N, n] = ds.sea_water_practical_salinity[:N]\n",
" big['O2'][:N, n] = ds.DOXMZZ01[:N]\n",
"\n",
" big['x0'] = (big['lon'] - lon0) * np.cos(lat0*np.pi/180)*111.32\n",
" big['y0'] = (big['lat']-lat0)*111.32\n",
" xy = big.x0 + 1j*big.y0\n",
" ang = np.arctan2( 80+9./8., 100.,)\n",
" xy = xy * np.exp(-1j * ang)\n",
" big['x'] = xy.real\n",
" big['y'] = xy.imag\n",
"\n",
" big['temperature'] = big.temperature.where(big.temperature<25)\n",
" big['salinity'] = big.salinity.where(big.salinity<40)\n",
" big['O2'] = big.O2.where(big.O2<1000)\n",
" big['pden'] = 0*big['temperature']\n",
" P = big['z'].values[:, np.newaxis]\n",
" big['pden'][:] = seawater.pden(big['salinity'][:], big['temperature'][:], P, 0)\n",
"\n",
" \n",
" big.to_netcdf('CtdGrid.nc')\n",
" #with xr.open_dataset('2013-058-0020.ctd.nc') as ds:\n",
" # ds\n",
" dat = np.loadtxt('Stations.txt', dtype={'names': ('geo', 'station', 'lat', 'lon', 'nomdepth', 'q'),\n",
" 'formats': ('S10', 'S10', 'f', 'f', 'f', 'f')})\n",
" with xr.open_dataset('CtdGrid.nc') as ds:\n",
" ds['station'] = ('index', [' '] * ds.sizes['index'])\n",
" ds['stadist'] = ('index', np.ones_like(ds['lon'])*1e6)\n",
" ds['stadepth'] = ('index', np.ones_like(ds['lon'])*1e6)\n",
" \n",
" for d in dat:\n",
" dist = ((ds.lon-d['lon']) * np.cos(45*np.pi/180))**2\n",
" dist += (ds.lat-d['lat'])**2\n",
" dist = np.sqrt(dist * 1.81 * 60 )\n",
" if (dist.values.min() < ds['stadist'][dist.values.argmin()] and \n",
" dist.values.min() < 1):\n",
" ds['station'][dist.values.argmin()] = d['station'].decode('utf8')\n",
" ds['stadist'][dist.values.argmin()] = dist.values.min()\n",
" ds['stadepth'][dist.values.argmin()] = d['nomdepth']\n",
" ds['spice'] = (('z', 'index'), getSpice(ds.pden.data, ds.temperature.data, ds.salinity.data))\n",
" \n",
" ds.to_netcdf(f'CtdGrid-{cruise}.nc')\n",
" print(f'Done CtdGrid-{cruise}.nc')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Plot cross sections LB and LC"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"image/svg+xml": [
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"def plot_prop(ax, ds, prop, clim, cmap='RdBu_r', cbarax=None, cblabel=''):\n",
" xvar = ds.x\n",
" pc = ax.pcolormesh(xvar, -ds.z, ds[prop], rasterized=True, cmap=cmap)\n",
" pc.set_clim(clim)\n",
" if cbarax is not None:\n",
" fig.colorbar(pc, cax=cbarax, orientation='horizontal', extend='both')\n",
" cbarax.set_title(cblabel, fontsize='small')\n",
" ax.set_ylim(-320, 0)\n",
" ax.set_facecolor('0.8')\n",
" c1 = ax.contour(xvar, -ds['z'], ds['pden']-1000., np.arange(23,27,1.), \n",
" colors='0.4', linewidths=0.7)\n",
" ax.clabel(c1,fontsize=7,fmt='%2.0f')\n",
" c2 = ax.contour(xvar, -ds['z'], ds['pden']-1000., diffarray(np.arange(23,27,0.2), \n",
" np.arange(23,27,1)),\n",
" colors='0.4',linewidths=0.4, zorder=10)\n",
" c3 = ax.contour(xvar, -ds['z'], ds['pden']-1000., [26.4], colors='m', linewidths=1.)\n",
"\n",
" # bottom?\n",
" ax.fill_between(xvar, -ds.stadepth, -1000, color='0.7')\n",
"\n",
"fig, axs = plt.subplots(4, 2, figsize=(7, 7), constrained_layout=True, sharey=True)\n",
"\n",
"axs[0, 0].set_xticklabels([])\n",
"axs[0, 1].set_xticklabels([])\n",
"axs[2, 0].set_xticklabels([])\n",
"axs[2, 1].set_xticklabels([])\n",
"\n",
"axs[0, 0].set_title('May 2013')\n",
"axs[0, 1].set_title('Sep 2013')\n",
"\n",
"axs[0, 0].set_ylabel('Depth [m]')\n",
"axs[2, 0].set_ylabel('Depth [m]')\n",
"axs[3, 0].set_xlabel('X [km]')\n",
"axs[1, 0].set_xlabel('X [km]')\n",
"\n",
"\n",
"clims = {'temperature': [5, 10], 'O2': [0, 300]}\n",
"cmaps = {'temperature': 'YlGnBu_r', 'O2': 'Spectral_r'}\n",
"ttl = {'temperature': '$T\\ \\mathrm{[^oC]}$', 'O2':'$O_2\\ \\mathrm{[\\mu mol\\ kg^{-1}]}$'}\n",
"\n",
"with xr.open_dataset('CtdGrid-038.nc') as jun, xr.open_dataset('CtdGrid-058.nc') as sep:\n",
" for j, ds0 in enumerate([jun, sep]):\n",
" for line, todo in enumerate([\"LC\", \"LB\"]):\n",
" ds = ds0.isel(index=(ds0.station.str[:2] == todo))\n",
" ds = ds.sortby(ds.lon)\n",
" for propn, prop in enumerate(['temperature', 'O2']):\n",
" ax = axs[line*2 + propn, j]\n",
" cax = ax.inset_axes([0.6, 0.2, 0.35, 0.07])\n",
" \n",
" plot_prop(ax, ds, prop, clims[prop], cmap=cmaps[prop], cbarax=cax, cblabel=ttl[prop])\n",
" if propn == 0:\n",
" ax.set_title(f'{todo} Line', loc='left', fontsize=10, fontstyle='italic')\n",
" \n",
" def forward(x):\n",
" return np.interp(x, ds.x, ds.lon)\n",
"\n",
" def inverse(x):\n",
" return np.interp(x, ds.lon, ds.x)\n",
" if propn == 1:\n",
" axis = ax.secondary_xaxis('top', functions=(forward, inverse))\n",
" axis.set_xticks(np.arange(-126, -125, 0.5), labels=['126 W', '125.5'])\n",
" axis.tick_params(axis='x', which='major', labelsize='small')\n",
"if False:\n",
" jmkfigure.jmkprint('LaPerouse2013CtdNoSpice', 'analyze.ipynb')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Figure(432x720)\n"
]
},
{
"data": {
"image/svg+xml": [
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"def plot_prop(ax, ds, prop, clim, cmap='RdBu_r', cbarax=None, cblabel=''):\n",
" xvar = ds.x\n",
" pc = ax.pcolormesh(xvar, -ds.z, ds[prop], rasterized=True, cmap=cmap)\n",
" pc.set_clim(clim)\n",
" if cbarax is not None:\n",
" cbar = fig.colorbar(pc, cax=cbarax, orientation='horizontal', extend='both')\n",
" cbar.ax.tick_params(axis='x', labelsize='small')\n",
" cbar.ax.set_title(cblabel, fontsize='small')\n",
" ax.set_ylim(-320, 0)\n",
" ax.set_facecolor('0.8')\n",
" c1 = ax.contour(xvar, -ds['z'], ds['pden']-1000., np.arange(23,27,1.), \n",
" colors='0.4', linewidths=0.7)\n",
" ax.clabel(c1,fontsize=7,fmt='%2.0f')\n",
" c2 = ax.contour(xvar, -ds['z'], ds['pden']-1000., diffarray(np.arange(23,27,0.2), \n",
" np.arange(23,27,1)),\n",
" colors='0.4',linewidths=0.4, zorder=10)\n",
" c3 = ax.contour(xvar, -ds['z'], ds['pden']-1000., [26.4], colors='m', linewidths=1.)\n",
"\n",
" # bottom?\n",
" try:\n",
" \n",
" ax.fill_between(xvar, -ds.stadepth, -1000, color='0.7', zorder=1)\n",
" except:\n",
" ax.fill_between(xvar, -ds.bottom, -1000, color='0.7', zorder=1)\n",
"\n",
"\n",
"import matplotlib.transforms as mtransforms\n",
"\n",
"fig, axs = plt.subplots(6, 2, figsize=(6, 10), constrained_layout=True, sharey=True)\n",
"\n",
"for i in [0, 1, 3, 4]:\n",
" axs[i, 0].set_xticklabels([])\n",
" axs[i, 1].set_xticklabels([])\n",
"\n",
"axs[0, 0].set_title('May 2013')\n",
"axs[0, 1].set_title('Sep 2013')\n",
"\n",
"axs[0, 0].set_ylabel('Depth [m]')\n",
"axs[3, 0].set_ylabel('Depth [m]')\n",
"axs[5, 0].set_xlabel('X [km]')\n",
"axs[2, 0].set_xlabel('X [km]')\n",
"\n",
"\n",
"clims = {'temperature': [6, 10], 'spice': [-0.2, 0.2], 'O2': [0, 300]}\n",
"cmaps = {'temperature': 'turbo', 'spice': 'RdBu_r', 'O2': 'Spectral_r'}\n",
"ttl = {'temperature': r'$\\theta\\ \\mathrm{[^oC]}$','spice': '$\\gamma \\ \\mathrm{[kg\\,m^{-3}]}$', 'O2':'$O_2\\ \\mathrm{[\\mu mol\\ kg^{-1}]}$'}\n",
"\n",
"with xr.open_dataset('CtdGrid-038.nc') as jun, xr.open_dataset('CtdGrid-058.nc') as sep:\n",
" nnn = 0\n",
" for j, ds0 in enumerate([jun, sep]):\n",
" \n",
" for line, todo in enumerate([\"LC\", \"LB\"]):\n",
" ds = ds0.isel(index=(ds0.station.str[:2] == todo))\n",
" ds = ds.sortby(ds.lon)\n",
" for propn, prop in enumerate(['temperature', 'spice', 'O2']):\n",
" nnn += 1\n",
" ax = axs[line*3 + propn, j]\n",
" cax = ax.inset_axes([0.6, 0.2, 0.35, 0.07], transform=ax.transAxes)\n",
" \n",
" plot_prop(ax, ds, prop, clims[prop], cmap=cmaps[prop], cbarax=cax, cblabel=ttl[prop])\n",
" axla = f'{chr(ord(\"a\") + nnn-1)})'\n",
" ax.text(0, 1.07, axla, transform = ax.transAxes)\n",
" if propn == 0:\n",
" title = f' {todo} Line'\n",
" ax.set_title(title, loc='left', fontsize=10, fontstyle='italic')\n",
" \n",
" def forward(x):\n",
" return np.interp(x, ds.x, ds.lon)\n",
"\n",
" def inverse(x):\n",
" return np.interp(x, ds.lon, ds.x)\n",
" if propn == 1:\n",
"\n",
" if line == 0:\n",
" trans = mtransforms.blended_transform_factory(ax.transData, ax.transAxes)\n",
" ax.text(5, 1.08, 'La Perouse Bank', transform=trans, fontsize='small', \n",
" ha='center', style='italic')\n",
"\n",
" else:\n",
" trans = mtransforms.blended_transform_factory(ax.transData, ax.transAxes)\n",
" ax.plot([0, 33], [1.04, 1.04], transform=trans, clip_on=False, lw=3)\n",
" ax.text(33/2, 1.08, 'Eddy', transform=trans, fontsize='small', \n",
" ha='center', style='italic')\n",
" ax.text(50, 1.08, 'VICC', transform=trans, fontsize='small', \n",
" ha='center', style='italic')\n",
" ax.plot([38, 55], [1.04, 1.04], transform=trans, clip_on=False, lw=3)\n",
" \n",
"\n",
" if propn == 2:\n",
" axis = ax.secondary_xaxis('top', functions=(forward, inverse))\n",
" axis.set_xticks(np.arange(-126, -125, 0.5), labels=['126 W', '125.5'])\n",
" axis.tick_params(axis='x', which='major', labelsize='small')\n",
"if True:\n",
" jmkfigure.jmkprint('LaPerouse2013Ctd', 'analyze.ipynb')"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Dimensions: (depths: 200, x: 120)\n",
"Coordinates:\n",
" * x (x) float64 -60.0 -59.16 -58.32 -57.48 ... 37.48 38.32 39.16 40.0\n",
" * depths (depths) float64 0.0 1.0 2.0 3.0 4.0 ... 196.0 197.0 198.0 199.0\n",
"Data variables:\n",
" temp (depths, x) float64 ...\n",
" spice (depths, x) float64 ...\n",
" O2 (depths, x) float64 ...\n",
" pden (depths, x) float64 ...\n",
" salinity (depths, x) float64 ...\n",
" bottom (x) float64 ...\n",
" lon (x) float64 ...\n",
" lat (x) float64 ...\n",
" y (x) float64 ...\n",
" xold (x) float64 ...\n",
"\n",
"Dimensions: (depths: 200, x: 120)\n",
"Coordinates:\n",
" * x (x) float64 -60.0 -59.16 -58.32 -57.48 ... 37.48 38.32 39.16 40.0\n",
" * depths (depths) float64 0.0 1.0 2.0 3.0 4.0 ... 196.0 197.0 198.0 199.0\n",
"Data variables:\n",
" temp (depths, x) float64 ...\n",
" spice (depths, x) float64 ...\n",
" O2 (depths, x) float64 ...\n",
" pden (depths, x) float64 ...\n",
" salinity (depths, x) float64 ...\n",
" bottom (x) float64 ...\n",
" lon (x) float64 ...\n",
" lat (x) float64 ...\n",
" y (x) float64 ...\n",
" xold (x) float64 ...\n",
"Figure(720x720)\n"
]
},
{
"data": {
"image/svg+xml": [
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# As above, except with MVP surveys\n",
"import matplotlib.transforms as mtransforms\n",
"\n",
"fig, axs = plt.subplots(6, 3, figsize=(10, 10), constrained_layout=True, sharey=True)\n",
"\n",
"def annotate_eddy(ax):\n",
" trans = mtransforms.blended_transform_factory(ax.transData, ax.transAxes)\n",
" ax.plot([0, 33], [1.04, 1.04], transform=trans, clip_on=False, lw=3)\n",
" ax.text(33/2, 1.08, 'Eddy', transform=trans, fontsize='small', \n",
" ha='center', style='italic')\n",
" ax.text(50, 1.08, 'VICC', transform=trans, fontsize='small', \n",
" ha='center', style='italic')\n",
" ax.plot([38, 55], [1.04, 1.04], transform=trans, clip_on=False, lw=3)\n",
"\n",
"def add_latlon(ax, ds):\n",
" def forward(x):\n",
" return np.interp(x, ds.x, ds.lon)\n",
"\n",
" def inverse(x):\n",
" return np.interp(x, ds.lon, ds.x)\n",
"\n",
" axis = ax.secondary_xaxis('top', functions=(forward, inverse))\n",
" axis.set_xticks(np.arange(-126, -125, 0.5), labels=['126 W', '125.5'])\n",
" axis.tick_params(axis='x', which='major', labelsize='small')\n",
"\n",
"\n",
"\n",
"for i in [0, 1, 3, 4]:\n",
" for j in range(3):\n",
" axs[i, j].set_xticklabels([])\n",
"\n",
"axs[0, 0].set_title('Jun 2013')\n",
"axs[0, 2].set_title('Sep 2013')\n",
"\n",
"axs[0, 0].set_ylabel('DEPTH [m]')\n",
"axs[3, 0].set_ylabel('DEPTH [m]')\n",
"axs[5, 0].set_xlabel('X [km]')\n",
"axs[2, 0].set_xlabel('X [km]')\n",
"\n",
"\n",
"clims = {'temperature': [6, 10], 'spice': [-0.2, 0.2], 'O2': [0, 300]}\n",
"cmaps = {'temperature': 'turbo', 'spice': 'RdBu_r', 'O2': 'Spectral_r'}\n",
"ttl = {'temperature': r'$\\theta\\ \\mathrm{[^oC]}$','spice': '$\\gamma \\ \\mathrm{[kg\\,m^{-3}]}$', 'O2':'$O_2\\ \\mathrm{[\\mu mol\\ kg^{-1}]}$'}\n",
"\n",
"with xr.open_dataset('CtdGrid-038.nc') as jun, xr.open_dataset('CtdGrid-058.nc') as sep:\n",
" for j, ds0 in enumerate([jun, sep]):\n",
" j = j + 1 if (j==1) else j\n",
" for line, todo in enumerate([\"LC\", \"LB\"]):\n",
" ds = ds0.isel(index=(ds0.station.str[:2] == todo))\n",
" ds = ds.sortby(ds.lon)\n",
" for propn, prop in enumerate(['temperature', 'spice', 'O2']):\n",
" ax = axs[line*3 + propn, j]\n",
" cax = ax.inset_axes([0.6, 0.2, 0.35, 0.07])\n",
" \n",
" plot_prop(ax, ds, prop, clims[prop], cmap=cmaps[prop], cbarax=cax, cblabel=ttl[prop])\n",
" if propn == 0 and j == 0:\n",
" ax.set_title(f'{todo} Line', loc='left', fontsize=10, fontstyle='italic')\n",
" if propn == 1:\n",
" if line == 0:\n",
" trans = mtransforms.blended_transform_factory(ax.transData, ax.transAxes)\n",
" ax.text(5, 1.08, 'La Perouse Bank', transform=trans, fontsize='small', \n",
" ha='center', style='italic')\n",
" else:\n",
" annotate_eddy(ax)\n",
" if propn == 2:\n",
" add_latlon(ax, ds)\n",
" \n",
"for ind_km, dx in enumerate([42, 0]):\n",
" with xr.open_dataset('../analysis/mvp/LinesSpice%fkmNew2.nc'%dx) as ds:\n",
" print(ds)\n",
" ds['z'] = ds.depths\n",
" ds['temperature'] = ds.temp\n",
" # transform O2 sat to O2 concentration. \n",
" for nn, td in enumerate(['temperature', 'spice', 'O2']):\n",
" ax = axs[nn + ind_km * 3, 1]\n",
" plot_prop(ax, ds, prop=td, clim=clims[td],cmap=cmaps[td])\n",
" if ind_km == 1 and nn == 1:\n",
" annotate_eddy(ax)\n",
" if nn == 2:\n",
" add_latlon(ax, ds)\n",
"\n",
"\n",
"axs[0, 1].set_title('Aug 2013')\n",
"\n",
"if True:\n",
" jmkfigure.jmkprint('LaPerouse2013Ctd', 'analyze.ipynb')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Plot T-S for La Perouse"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"beta = 7.7e-4*1000\n",
"alpha = 2.0e-4*1000\n",
"\n",
"Sline = np.array([33.2,33.8])*beta\n",
"Tline = np.array([7.75,6.6])*alpha\n",
"# extend:\n",
"m = np.diff(Tline)/np.diff(Sline)\n",
"Ss = np.array([20,35])\n",
"Tt = (Ss-Sline[0])*m+Tline[0]\n",
"tt = np.arange(3,14,0.2)\n",
"ss = np.arange(32,35.1,0.02)\n",
"TT,SS = np.meshgrid(tt,ss)\n",
"pden = seawater.pden(SS,TT,SS*0+0.,0.)\n",
"#spice = getSpice(pden, TT, SS)\n",
"spice = getSpice(pden, TT, SS)\n"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Levels [22. 23. 24. 25. 26. 27.]\n"
]
},
{
"data": {
"image/svg+xml": [
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# %matplotlib qt\n",
"fig, ax = plt.subplots(figsize=(3.5, 3.5), constrained_layout=True)\n",
"col = ['C0', 'C1']\n",
"tit = ['Jun', 'Sep']\n",
"with xr.open_dataset('CtdGrid-038.nc') as jun, xr.open_dataset('CtdGrid-058.nc') as sep:\n",
" for j, ds0 in enumerate([jun, sep]):\n",
" for line, todo in enumerate([\"LB\"]):\n",
" ds = ds0.isel(index=(ds0.station.str[:2] == todo))\n",
" ds = ds.sortby(ds.lon)\n",
" #dsal = j * -0.0\n",
" ax.plot(ds.salinity.values.flat, ds.temperature.values.flat, '.', color=col[j], \n",
" markersize=1, label=tit[j], rasterized=True)\n",
"leg = ax.legend(loc='upper right')\n",
"for handle in leg.legendHandles:\n",
" handle.set_markersize(6.0)\n",
"ax.set_xlim([32, 34.7])\n",
"ax.set_ylim([3,12])\n",
"cs=ax.contour(ss,tt,pden.T-1000.,np.arange(22,28,1.),colors='0.4', zorder=-10)\n",
"print(\"Levels\", cs.levels)\n",
"ax.clabel(cs, fontsize='small', manual=[(33.5, 9), (34.6, 7.8), (32.7, 10.5)])\n",
"ax.contour(ss,tt,pden.T-1000.,np.setdiff1d(np.arange(22.,28.,0.2), np.arange(22.,28.,0.2)[::5]),\n",
" colors='0.6', linewidths=0.4, zorder=-10)\n",
"ax.contour(ss,tt,pden.T-1000., [26.4], colors='m', zorder=-10)\n",
"csspice = ax.contour(ss, tt, spice.T, [-0.2, -0.1, 0.0, 0.1, 0.2], cmap='RdBu_r', vmin=-0.2, vmax=0.2 , zorder=-10)\n",
"ax.clabel(csspice, fmt=r'$\\gamma$ = %1.1f', manual=[(34.5, 4.7), (33.5, 5), (34.3, 6.7)], \n",
" inline_spacing=1, fontsize='small')\n",
"ax.set_facecolor('0.9')\n",
"ax.set_xlabel(r'$S\\ \\mathrm{[psu]}$')\n",
"ax.set_ylabel(r'$\\theta \\ \\mathrm{[^oC]}$')\n",
"ax.set_title('La Perouse, LB Line, 2013', loc='left', fontsize='medium')\n",
"ax.add_patch(\n",
" mpatches.Rectangle(\n",
" (32.24,6),\n",
" 34-32.24,\n",
" 9.5-6,\n",
" fill=False # remove background\n",
" ) ) \n",
"ax.set_aspect(0.3)\n",
"if False:\n",
" jmkfigure.jmkprint('LaPerouse2013TS', 'analyze.ipynb', dpi=300)\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Levels [22. 23. 24. 25. 26. 27.]\n",
"Figure(1400x700)\n"
]
}
],
"source": [
"\n",
"fig, axs = plt.subplots(1, 2, figsize=(7, 3.5), sharex=True,\n",
" constrained_layout=True)\n",
"col = ['C0', 'C1']\n",
"tit = ['Jun', 'Sep']\n",
"\n",
"with xr.open_dataset('CtdGrid-038.nc') as jun, xr.open_dataset('CtdGrid-058.nc') as sep:\n",
" for j, ds0 in enumerate([jun, sep]):\n",
" for line, todo in enumerate([\"LB\"]):\n",
" ds = ds0.isel(index=(ds0.station.str[:2] == todo))\n",
" ds = ds.sortby(ds.lon)\n",
" #dsal = j * -0.0\n",
" ax = axs[0]\n",
" ax.plot(ds.salinity.values.flat, ds.temperature.values.flat, '.', color=col[j], \n",
" markersize=1, label=tit[j], rasterized=True)\n",
" ax = axs[1]\n",
" ax.plot(ds.salinity.values.flat, ds.O2.values.flat, '.', color=col[j], \n",
" markersize=1, label=tit[j], rasterized=True)\n",
"ax = axs[0]\n",
"leg = ax.legend(loc='upper right')\n",
"for handle in leg.legendHandles:\n",
" handle.set_markersize(6.0)\n",
"ax.set_xlim([32, 34.7])\n",
"ax.set_ylim([3,12])\n",
"cs=ax.contour(ss,tt,pden.T-1000.,np.arange(22,28,1.),colors='0.4', zorder=-10)\n",
"print(\"Levels\", cs.levels)\n",
"ax.clabel(cs, fontsize='small', manual=[(33.5, 9), (34.6, 7.8), (32.7, 10.5)])\n",
"ax.contour(ss,tt,pden.T-1000.,np.setdiff1d(np.arange(22.,28.,0.2), np.arange(22.,28.,0.2)[::5]),\n",
" colors='0.6', linewidths=0.4, zorder=-10)\n",
"ax.contour(ss,tt,pden.T-1000., [26.4], colors='m', zorder=-10)\n",
"csspice = ax.contour(ss, tt, spice.T, [-0.2, -0.1, 0.0, 0.1, 0.2], cmap='RdBu_r', vmin=-0.2, vmax=0.2 , zorder=-10)\n",
"ax.clabel(csspice, fmt=r'$\\gamma$ = %1.1f', manual=[(34.5, 4.7), (33.5, 5), (34.3, 6.7)], \n",
" inline_spacing=1, fontsize='small')\n",
"ax.set_facecolor('0.9')\n",
"ax.set_xlabel(r'$S\\ \\mathrm{[psu]}$')\n",
"ax.set_ylabel(r'$\\theta \\ \\mathrm{[^oC]}$')\n",
"ax.set_title('a) La Perouse, LB Line, 2013', loc='left', fontsize='medium')\n",
"ax.add_patch(\n",
" mpatches.Rectangle(\n",
" (32.24,6),\n",
" 34-32.24,\n",
" 9.5-6,\n",
" fill=False # remove background\n",
" ) ) \n",
"axs[0].set_aspect(0.3)\n",
"#axs[1].set_ylim([1027, 1026])\n",
"axs[1].set_xlabel('S [psu]')\n",
"axs[1].set_ylim([0, 310])\n",
"axs[1].set_ylabel('$O_2\\ \\mathrm{[\\mu mol\\ kg^{-1}]}$')\n",
"axs[1].set_facecolor('0.9')\n",
"axs[1].set_title('b) LB Line: $O_2$ versus S', loc='left', fontsize='medium')\n",
"\n",
"if True:\n",
" jmkfigure.jmkprint('LaPerouse2013TS', 'analyze.ipynb', dpi=300)\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Levels [22. 23. 24. 25. 26. 27.]\n"
]
}
],
"source": [
"\n",
"fig, axs = plt.subplots(1, 2, figsize=(7, 3.5), sharex=True,\n",
" constrained_layout=True)\n",
"col = ['C0', 'C1']\n",
"tit = ['Jun', 'Sep']\n",
"\n",
"with xr.open_dataset('CtdGrid-038.nc') as jun, xr.open_dataset('CtdGrid-058.nc') as sep:\n",
" for j, ds0 in enumerate([jun, sep]):\n",
" for line, todo in enumerate([\"LD\"]):\n",
" ds = ds0.isel(index=(ds0.station.str[:2] == todo))\n",
" ds = ds.sortby(ds.lon)\n",
" #dsal = j * -0.0\n",
" ax = axs[0]\n",
" ax.plot(ds.salinity.values.flat, ds.temperature.values.flat, '.', color=col[j], \n",
" markersize=1, label=tit[j], rasterized=True)\n",
" ax = axs[1]\n",
" ax.plot(ds.salinity.values.flat, ds.O2.values.flat, '.', color=col[j], \n",
" markersize=1, label=tit[j], rasterized=True)\n",
"ax = axs[0]\n",
"leg = ax.legend(loc='upper right')\n",
"for handle in leg.legendHandles:\n",
" handle.set_markersize(6.0)\n",
"ax.set_xlim([32, 34.7])\n",
"ax.set_ylim([3,12])\n",
"cs=ax.contour(ss,tt,pden.T-1000.,np.arange(22,28,1.),colors='0.4', zorder=-10)\n",
"print(\"Levels\", cs.levels)\n",
"ax.clabel(cs, fontsize='small', manual=[(33.5, 9), (34.6, 7.8), (32.7, 10.5)])\n",
"ax.contour(ss,tt,pden.T-1000.,np.setdiff1d(np.arange(22.,28.,0.2), np.arange(22.,28.,0.2)[::5]),\n",
" colors='0.6', linewidths=0.4, zorder=-10)\n",
"ax.contour(ss,tt,pden.T-1000., [26.4], colors='m', zorder=-10)\n",
"csspice = ax.contour(ss, tt, spice.T, [-0.2, -0.1, 0.0, 0.1, 0.2], cmap='RdBu_r', vmin=-0.2, vmax=0.2 , zorder=-10)\n",
"ax.clabel(csspice, fmt=r'$\\gamma$ = %1.1f', manual=[(34.5, 4.7), (33.5, 5), (34.3, 6.7)], \n",
" inline_spacing=1, fontsize='small')\n",
"ax.set_facecolor('0.9')\n",
"ax.set_xlabel(r'$S\\ \\mathrm{[psu]}$')\n",
"ax.set_ylabel(r'$\\theta \\ \\mathrm{[^oC]}$')\n",
"ax.set_title('a) La Perouse, LC Line, 2013', loc='left', fontsize='medium')\n",
"ax.add_patch(\n",
" mpatches.Rectangle(\n",
" (32.24,6),\n",
" 34-32.24,\n",
" 9.5-6,\n",
" fill=False # remove background\n",
" ) ) \n",
"axs[0].set_aspect(0.3)\n",
"#axs[1].set_ylim([1027, 1026])\n",
"axs[1].set_xlabel('S [psu]')\n",
"axs[1].set_ylim([0, 310])\n",
"axs[1].set_ylabel('$O_2\\ \\mathrm{[\\mu mol\\ kg^{-1}]}$')\n",
"axs[1].set_facecolor('0.9')\n",
"axs[1].set_title('b) LC Line: $O_2$ versus S', loc='left', fontsize='medium')\n",
"\n",
"if False:\n",
" jmkfigure.jmkprint('LaPerouse2013TS', 'analyze.ipynb', dpi=300)\n",
" "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"interpreter": {
"hash": "a22c6a21cf8049bc1143f75d2b2eea08954f990d7bcd9c8c915fb92eb006f7ed"
},
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
}
},
"nbformat": 4,
"nbformat_minor": 4
}