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@angus-g
Created October 15, 2018 02:19
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import scipy.io\n",
"import numpy as np\n",
"from netCDF4 import Dataset\n",
"\n",
"import seaborn as sns\n",
"import matplotlib\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib.cm as cm\n",
"import matplotlib.ticker as plticker\n",
"import matplotlib.gridspec as gridspec\n",
"import matplotlib.lines as plines\n",
"\n",
"import os.path"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"sns.set_style('whitegrid', {'grid.color': '.9',\n",
" 'legend.frameon': True})\n",
"\n",
"text_props = {'weight': 'bold',\n",
" 'horizontalalignment': 'left',\n",
" 'verticalalignment': 'center'}"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"plt.rcParams['figure.figsize']\n",
"plt.rcParams['figure.dpi'] = 100"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"base_path = os.path.expanduser('~/phd/data/spurious')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Lock Exchange"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"# load Petersen's data\n",
"lock_data = scipy.io.loadmat('data/m46_dam_break_131017.mat')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Figure 2\n",
"\n",
"Snapshot of lock exchange temperature at 6 hours and 17 hours"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 600x400 with 3 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = plt.figure()\n",
"\n",
"d = Dataset(os.path.join(base_path, 'lock_exchange_KH0.01_ADPPM_COZ.nc'), 'r')\n",
"cmap = cm.RdBu_r\n",
"\n",
"# 6-hour\n",
"ax = plt.subplot(211)\n",
"pcol = plt.pcolormesh(d.variables['xh'][:],\n",
" d.variables['zl'][:],\n",
" d.variables['temp'][11,:,0,:], linewidth=0, rasterized=True, cmap=cmap)\n",
"plt.axis('tight')\n",
"ax.invert_yaxis()\n",
"ax.xaxis.set_ticklabels([])\n",
"plt.ylabel('depth below surface (m)')\n",
"ax.text(2.0, 3.0, 'a)', color='white', **text_props)\n",
"\n",
"# 17-hour\n",
"ax = plt.subplot(212)\n",
"im = plt.pcolormesh(d.variables['xh'][:],\n",
" d.variables['zl'][:],\n",
" d.variables['temp'][-1,:,0,:], linewidth=0, rasterized=True, cmap=cmap)\n",
"#im.set_edgecolor('face')\n",
"plt.axis('tight')\n",
"plt.gca().invert_yaxis()\n",
"plt.xlabel('x (km)')\n",
"plt.ylabel('depth below surface (m)')\n",
"ax.text(2.0, 3.0, 'b)', color='white', **text_props)\n",
"\n",
"plt.tight_layout()\n",
"\n",
"# make some room for the colorbar and put it in\n",
"fig.subplots_adjust(right=0.82)\n",
"cbar_ax = fig.add_axes([0.85, 0.2, 0.05, 0.7])\n",
"fig.colorbar(im, cax=cbar_ax)\n",
"d.close()\n",
"\n",
"#plt.savefig('figures/lock_exchange_snapshot_0.01.pdf')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Figure 3\n",
"\n",
"Normalised RPE timeseries in the lowest viscosity experiment, and dRPE/dt at 17h for all models across all viscosities."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"# calculate RPE norm from energy\n",
"d = Dataset(os.path.join(base_path, 'lock_exchange/KH0.01_ADPPM_COZ/energy.nc'), 'r')\n",
"\n",
"lock_rpenorm = d.variables['RPE_postale'][:,0]\n",
"lock_rpeinit = d.variables['RPE_predyn'][:,0]\n",
"lock_rpenorm = (lock_rpenorm - lock_rpeinit[0]) / lock_rpeinit[0]\n",
"lock_time = d.variables['time'][:]\n",
"dt = lock_time[1] - lock_time[0]\n",
"\n",
"d.close()\n",
"\n",
"d = Dataset(os.path.join(base_path, 'lock_exchange/KH0.01_ADPPMH3_COZ/energy.nc'), 'r')\n",
"lock_rpenorm_h3 = d.variables['RPE_postale'][:,0]\n",
"lock_rpeinit_h3 = d.variables['RPE_predyn'][:,0]\n",
"lock_rpenorm_h3 = (lock_rpenorm_h3 - lock_rpeinit_h3[0]) / lock_rpeinit_h3[0]\n",
"d.close()\n",
"\n",
"d = Dataset(os.path.join(base_path, 'lock_exchange/KH0.01_ADPPM_CORHO/energy.nc'), 'r')\n",
"lock_rpenorm_rho = d.variables['RPE_postale'][:,0]\n",
"lock_rpeinit_rho = d.variables['RPE_predyn'][:,0]\n",
"lock_rpenorm_rho = (lock_rpenorm_rho - lock_rpeinit_rho[0]) / lock_rpeinit_rho[0]\n",
"d.close()\n",
"\n",
"d = Dataset(os.path.join(base_path, 'adaptive/lock_exchange/KH0.01_ADPPMH3/energy.nc'), 'r')\n",
"lock_rpenorm_adapt = d.variables['RPE_postale'][:,0]\n",
"lock_rpeinit_adapt = d.variables['RPE_predyn'][:,0]\n",
"lock_rpenorm_adapt = (lock_rpenorm_adapt - lock_rpeinit_adapt[0]) / lock_rpeinit_adapt[0]\n",
"d.close()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"# calculate dRPE/dt for each viscosity\n",
"lock_kh = ['0.01', '0.1', '1', '10', '100', '200']\n",
"\n",
"lock_drpe = []\n",
"lock_drpe_h = []\n",
"lock_drpe_v = []\n",
"\n",
"lock_drpeh3 = []\n",
"lock_drpeh3_h = []\n",
"lock_drpeh3_v = []\n",
"\n",
"lock_drpel = []\n",
"lock_drpel_h = []\n",
"lock_drpel_v = []\n",
"\n",
"lock_drpe_rho = []\n",
"lock_drpe_rho_h = []\n",
"lock_drpe_rho_v = []\n",
"\n",
"lock_drpe_adapt = []\n",
"lock_drpe_adapt_h = []\n",
"lock_drpe_adapt_v = []\n",
"\n",
"sl = slice(-1)\n",
"\n",
"for kh in lock_kh:\n",
" d = Dataset(os.path.join(base_path, 'lock_exchange/KH{}_ADPPM_COZ/energy.nc'.format(kh)), 'r')\n",
" #lock_drpe.append(-(d.variables['RPE_postale'][-1,0] - d.variables['RPE_postale'][-2,0]) / dt)\n",
" #lock_drpe_h.append(-(d.variables['RPE_preale'][-1,0] - d.variables['RPE_predyn'][-1,0]) / dt)\n",
" #lock_drpe_v.append(-(d.variables['RPE_postale'][-1,0] - d.variables['RPE_preale'][-1,0]) / dt)\n",
" lock_drpe_h.append(-d.variables['RPE_dyndiff'][-1,0] / dt)\n",
" lock_drpe_v.append(-d.variables['RPE_alediff'][-1,0] / dt)\n",
" lock_drpe.append(lock_drpe_h[-1] + lock_drpe_v[-1])\n",
" d.close()\n",
" \n",
" d = Dataset(os.path.join(base_path, 'lock_exchange/KH{}_ADPPMH3_COZ/energy.nc'.format(kh)), 'r')\n",
" #lock_drpeh3.append(-(d.variables['RPE_dyndiff'][-1,0] + d.variables['RPE_alediff'][-1,0]) / dt)\n",
" lock_drpeh3_h.append(-d.variables['RPE_dyndiff'][-1,0] / dt)\n",
" lock_drpeh3_v.append(-d.variables['RPE_alediff'][-1,0] / dt)\n",
" lock_drpeh3.append(lock_drpeh3_h[-1] + lock_drpeh3_v[-1])\n",
" d.close()\n",
" \n",
" \"\"\"\n",
" d = Dataset(os.path.join(base_path, 'lock_exchange/KH{}_ADPLM_COZ/energy.nc'.format(kh)), 'r')\n",
" #lock_drpeh3.append(-(d.variables['RPE_dyndiff'][-1,0] + d.variables['RPE_alediff'][-1,0]) / dt)\n",
" lock_drpel_h.append(-d.variables['RPE_dyndiff'][sl,0].mean() / dt)\n",
" lock_drpel_v.append(-d.variables['RPE_alediff'][sl,0].mean() / dt)\n",
" lock_drpel.append(lock_drpel_h[-1] + lock_drpel_v[-1])\n",
" d.close()\n",
" \"\"\"\n",
" \n",
" d = Dataset(os.path.join(base_path, 'lock_exchange/KH{}_ADPPM_CORHO/energy.nc'.format(kh)), 'r')\n",
" #lock_drpe_rho.append(-(d.variables['RPE_postale'][-1,0] - d.variables['RPE_postale'][-2,0]) / dt)\n",
" #lock_drpe_rho_h.append(-(d.variables['RPE_preale'][-1,0] - d.variables['RPE_predyn'][-1,0]) / dt)\n",
" #lock_drpe_rho_v.append(-(d.variables['RPE_postale'][-1,0] - d.variables['RPE_preale'][-1,0]) / dt)\n",
" lock_drpe_rho_h.append(-d.variables['RPE_dyndiff'][sl,0].mean() / dt)\n",
" lock_drpe_rho_v.append(-d.variables['RPE_alediff'][sl,0].mean() / dt)\n",
" lock_drpe_rho.append(lock_drpe_rho_h[-1] + lock_drpe_rho_v[-1])\n",
" d.close()\n",
" \n",
" d = Dataset(os.path.join(base_path, 'adaptive/lock_exchange/KH{}_ADPPMH3/energy.nc'.format(kh)), 'r')\n",
" dyndiff = d.variables['RPE_preale'][:] - d.variables['RPE_predyn'][:]\n",
" lock_drpe_adapt_h.append(-dyndiff[sl,0].mean() / dt)\n",
" lock_drpe_adapt_v.append(-d.variables['RPE_alediff'][sl,0].mean() / dt)\n",
" lock_drpe_adapt.append(lock_drpe_adapt_h[-1] + lock_drpe_adapt_v[-1])\n",
" d.close()\n",
" \n",
"lock_re = [0.4956 * 0.5e3 / float(kh) for kh in lock_kh]"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 400x500 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = plt.figure(figsize=(4.0, 5.0))\n",
"\n",
"# normalised RPE\n",
"ax = plt.subplot(211)\n",
"\n",
"plt.plot(lock_data['time'][0] / 3600, lock_data['rpeNorm'][:,0], label='MPAS-O')\n",
"plt.plot(lock_data['mitgcm_delta_x_500_time_days'][:,0], lock_data['mitgcm_delta_x_500_drpe_dt'][0], label='MITGCM')\n",
"plt.plot(lock_time / 3600, -lock_rpenorm, label='MOM6')\n",
"plt.plot(lock_time / 3600, -lock_rpenorm_adapt, label='MOM6 adapt.')\n",
"#plt.plot(lock_time / 3600, -lock_rpenorm_h3, label='MOM6 PPM:H3')\n",
"#plt.plot(lock_time / 3600, -lock_rpenorm_rho, '--', color=ax.lines[-1]._color, label='MOM6 rho')\n",
"plt.plot(lock_data['mom_delta_x_500_time_days'][:,0], lock_data['mom_delta_x_500_drpe_dt'][0], label='MOM5')\n",
"\n",
"#plt.plot([0, 17], [0, 0], '--', label='GOLD')\n",
"\n",
"plt.xlabel('time (hours)')\n",
"plt.ylabel('normalised RPE')\n",
"plt.ticklabel_format(style='sci', axis='y', scilimits=(0, 0))\n",
"\n",
"leg = plt.legend(loc='upper left', fontsize=8)\n",
"leg.get_frame().set_linewidth(0)\n",
"\n",
"ax.set_xlim(0, 17)\n",
"ax.set_ylim(-1e-5, 7.9e-5)\n",
"ax.text(8.5, 7.3e-5, 'a)', **text_props)\n",
"\n",
"# dRPE/dt\n",
"ax = plt.subplot(212)\n",
"# MPAS-O z-star\n",
"plt.loglog(lock_data['gridRe'][0], lock_data['meanDrpeDt'][0,6:12], marker='*')\n",
"plt.loglog(lock_data['mitgcm_dx_500_nu_changes_Re'][0], lock_data['mitgcm_dx_500_nu_changes_drpe_dt'], marker='*')\n",
"plt.loglog(lock_re, lock_drpe, marker='*')\n",
"plt.loglog(lock_re, lock_drpeh3, '^', color=ax.lines[-1]._color)\n",
"plt.loglog(lock_re, lock_drpe_adapt, 's', color=ax.lines[-1]._color)\n",
"\n",
"#plt.loglog(lock_re, lock_drpel, 's')\n",
"#plt.loglog(lock_re, lock_drpe_rho, '--o', color=ax.lines[-1]._color)\n",
"\n",
"# show grid Re = 2 line\n",
"plt.plot((2, 2), (1e-4, 1e-2), 'k--')\n",
"\n",
"plt.xlabel('grid Reynolds number')\n",
"plt.ylabel('dRPE/dt (W/m²)')\n",
"plt.grid(True, which='minor', axis='y')\n",
"#ax.set_ylim(2e-5, 1e-2)\n",
"\n",
"leg = plt.legend(['MPAS-O', 'MITGCM', 'MOM6', 'MOM6 PPM:H3', 'MOM6 adapt'], loc='lower right', fontsize=8, ncol=2)\n",
"leg.get_frame().set_linewidth(0)\n",
"#leg = plt.legend(['MPAS-O', 'MITGCM', 'MOM6', 'MOM6 PPM:H3', 'MOM6 rho'],\n",
"# loc='upper left', bbox_to_anchor=(1.01,1.0), frameon=False, fontsize=8)\n",
"ax.text(3e2, 7e-3, 'b)', **text_props)\n",
"\n",
"plt.tight_layout()\n",
"plt.savefig(os.path.expanduser('~/phd/writing/thesis/figures/lock_exchange_rpe_both.pdf'), bbox_inches='tight')"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[1.917987817638574e-05,\n",
" 1.8486858093373103e-05,\n",
" 2.1204589333960978e-05,\n",
" 1.8608500310674202e-05,\n",
" 1.1893048671000415e-05,\n",
" 8.931150717097234e-06]"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"lock_drpe_adapt"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Figure 4\n",
"\n",
"Split dRPE/dt at 17h for MOM6 only"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 400x250 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(4, 2.5))\n",
"\n",
"ax = plt.gca()\n",
"ax.set_axisbelow(True)\n",
"ax.minorticks_on()\n",
"\n",
"plt.axhline(0, color='k', linewidth=1.0)\n",
"plt.semilogx(lock_re, lock_drpe_h, '*', label='horiz. z-star')\n",
"plt.semilogx(lock_re, lock_drpe_v, '*', label='vert. z-star')\n",
"ax.set_prop_cycle(None)\n",
"plt.semilogx(lock_re, lock_drpe_adapt_h, 's', label='horiz. adaptive')\n",
"plt.semilogx(lock_re, lock_drpe_adapt_v, 's', label='vert. adaptive')\n",
"\n",
"plt.ticklabel_format(style='sci', axis='y', scilimits=(0, 0))\n",
"plt.grid(True, which='both', axis='y')\n",
" \n",
"plt.ylabel('dRPE/dt (W/m²)')\n",
"plt.xlabel('grid Reynolds number')\n",
"\n",
"leg = plt.legend(loc='lower right', ncol=2, fontsize=8)\n",
"leg.get_frame().set_linewidth(0)\n",
"\n",
"plt.tight_layout()\n",
"plt.savefig(os.path.expanduser('~/phd/writing/thesis/figures/lock_exchange_drpe_split.pdf'))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Internal waves"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"wave_data = scipy.io.loadmat('data/m52_igw_m52a-x.mat')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Figure 5\n",
"\n",
"Snapshots from internal waves test case"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/usr/lib/python3.7/site-packages/matplotlib/figure.py:2299: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n",
" warnings.warn(\"This figure includes Axes that are not compatible \"\n"
]
},
{
"ename": "ValueError",
"evalue": "negative dimensions are not allowed",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-14-07d06d298faf>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 110\u001b[0m \u001b[0;31m# save to disk and fix up the bounding box to actually include the entire figure\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 111\u001b[0m plt.savefig(os.path.expanduser('~/phd/writing/thesis/figures/internal_waves_snapshot_all_{}.pdf').format(kh),\n\u001b[0;32m--> 112\u001b[0;31m bbox_inches='tight')\n\u001b[0m",
"\u001b[0;32m/usr/lib/python3.7/site-packages/matplotlib/pyplot.py\u001b[0m in \u001b[0;36msavefig\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 693\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0msavefig\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 694\u001b[0m \u001b[0mfig\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgcf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 695\u001b[0;31m \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msavefig\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 696\u001b[0m \u001b[0mfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw_idle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# need this if 'transparent=True' to reset colors\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 697\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/lib/python3.7/site-packages/matplotlib/figure.py\u001b[0m in \u001b[0;36msavefig\u001b[0;34m(self, fname, **kwargs)\u001b[0m\n\u001b[1;32m 2060\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_frameon\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mframeon\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2061\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2062\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprint_figure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2063\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2064\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mframeon\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/usr/lib/python3.7/site-packages/matplotlib/image.py\u001b[0m in \u001b[0;36m_draw_list_compositing_images\u001b[0;34m(renderer, parent, artists, suppress_composite)\u001b[0m\n\u001b[1;32m 139\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mnot_composite\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mhas_images\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 140\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0ma\u001b[0m \u001b[0;32min\u001b[0m \u001b[0martists\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 141\u001b[0;31m \u001b[0ma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 142\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 143\u001b[0m \u001b[0;31m# Composite any adjacent images together\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/lib/python3.7/site-packages/matplotlib/artist.py\u001b[0m in \u001b[0;36mdraw_wrapper\u001b[0;34m(artist, renderer, *args, **kwargs)\u001b[0m\n\u001b[1;32m 58\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstop_filter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0martist\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_agg_filter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 59\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0martist\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_rasterized\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 60\u001b[0;31m \u001b[0mrenderer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstop_rasterizing\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 61\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 62\u001b[0m \u001b[0mdraw_wrapper\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_supports_rasterization\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/lib/python3.7/site-packages/matplotlib/backends/backend_mixed.py\u001b[0m in \u001b[0;36mstop_rasterizing\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 128\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 129\u001b[0m \u001b[0mheight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_height\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdpi\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 130\u001b[0;31m \u001b[0mbuffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbounds\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_raster_renderer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtostring_rgba_minimized\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 131\u001b[0m \u001b[0ml\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mb\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mw\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mh\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbounds\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 132\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mw\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m0\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mh\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/lib/python3.7/site-packages/matplotlib/backends/backend_agg.py\u001b[0m in \u001b[0;36mtostring_rgba_minimized\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 142\u001b[0m [extents[0] + extents[2], self.height - extents[1]]]\n\u001b[1;32m 143\u001b[0m \u001b[0mregion\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy_from_bbox\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbbox\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 144\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mregion\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mextents\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 145\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 146\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mdraw_path\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpath\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtransform\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrgbFace\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mValueError\u001b[0m: negative dimensions are not allowed"
]
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 600x400 with 6 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = plt.figure()\n",
"\n",
"# viscosity and timestep to take snapshots at\n",
"kh = '15'\n",
"t = -1\n",
"cmap = cm.RdBu_r\n",
"\n",
"# open datasets\n",
"#di = Dataset('/home/users/AngusGibson/phd/spurious/config/internal_waves/input.nc', 'r')\n",
"#d = Dataset('/scratch/mizuchi1/angus/spurious/internal_waves/internal_waves_KH{}/prog.nc'.format(kh), 'r')\n",
"#d_tilde = Dataset('/scratch/mizuchi1/angus/spurious/internal_waves/internal_waves_T30d_KH{}/prog.nc'.format(kh), 'r')\n",
"#d_rho = Dataset('/scratch/mizuchi1/angus/spurious/internal_waves/internal_waves_rho_KH{}/prog.nc'.format(kh), 'r')\n",
"\n",
"di = Dataset(os.path.join(base_path, 'internal_waves_input.nc'), 'r')\n",
"d = Dataset(os.path.join(base_path, 'internal_waves_KH{}_ADPPM_COZ.nc'.format(kh)), 'r')\n",
"d_til = Dataset(os.path.join(base_path, 'internal_waves_KH{}_ADPPM_COZT_lay.nc'.format(kh)), 'r')\n",
"d_rho = Dataset(os.path.join(base_path, 'internal_waves_KH{}_ADPPM_CORHO.nc'.format(kh)), 'r')\n",
"d_adapt = Dataset(os.path.join(base_path, 'adaptive/internal_waves/KH{}_ADPPM/prog.nc'.format(kh)), 'r')\n",
"#d_adapt = Dataset(os.path.join(base_path, 'adaptive/internal_waves/KH{}_ADPPM/energy.nc'.format(kh)), 'r')\n",
"\n",
"#\n",
"# a. Initial condition\n",
"#\n",
"ax = plt.subplot(231)\n",
"plt.pcolormesh(di.variables['x'][:],\n",
" di.variables['z'][:],\n",
" di.variables['temp'][:,0,:], vmin=10, vmax=20, linewidth=0, rasterized=True, cmap=cmap)\n",
"plt.axis('tight')\n",
"ax.invert_yaxis()\n",
"plt.ylabel('depth (m)')\n",
"ax.get_xaxis().set_visible(False)\n",
"ax.text(15, 75, 'a)', color='white', **text_props)\n",
"\n",
"#\n",
"# b. z-star snapshot\n",
"#\n",
"ax = plt.subplot(232)\n",
"plt.pcolormesh(d.variables['xh'][:],\n",
" -d.variables['e'][t,:,0,:],\n",
" d.variables['temp'][t,:,0,:], vmin=10, vmax=20, linewidth=0, rasterized=True, cmap=cmap)\n",
"for k in range(20):\n",
" plt.plot(d.variables['xh'][:], -d.variables['e'][t,k,0,:], 'k', linewidth=0.5)\n",
"plt.axis('tight')\n",
"ax.get_yaxis().set_visible(False)\n",
"ax.get_xaxis().set_visible(False)\n",
"ax.set_ylim(0, 500)\n",
"ax.invert_yaxis()\n",
"ax.text(15, 65, 'b)', color='white', **text_props)\n",
"\n",
"#\n",
"# c. z-tilde snapshot\n",
"#\n",
"ax = plt.subplot(233)\n",
"plt.pcolormesh(d_til.variables['xh'][:],\n",
" -d_til.variables['e'][t,:,0,:],\n",
" d_til.variables['temp'][t,:,0,:], linewidth=0, rasterized=True, vmin=10, vmax=20, cmap=cmap)\n",
"for k in range(20):\n",
" plt.plot(d.variables['xh'][:], -d_til.variables['e'][t,k,0,:], 'k', linewidth=0.5)\n",
"plt.axis('tight')\n",
"ax.invert_yaxis()\n",
"plt.ylabel('depth (m)')\n",
"plt.xlabel('x (km)')\n",
"ax.text(15, 65, 'c)', color='white', **text_props)\n",
"\n",
"#\n",
"# d. rho snapshot\n",
"#\n",
"ax = plt.subplot(234)\n",
"im = plt.pcolormesh(d_rho.variables['xh'][:],\n",
" -d_rho.variables['e'][t,:,0,:],\n",
" d_rho.variables['temp'][t,:,0,:], linewidth=0, rasterized=True, vmin=10, vmax=20, cmap=cmap)\n",
"for k in range(20):\n",
" plt.plot(d.variables['xh'][:], -d_rho.variables['e'][t,k,0,:], 'k', linewidth=0.5)\n",
"plt.axis('tight')\n",
"ax.invert_yaxis()\n",
"plt.xlabel('x (km)')\n",
"plt.ylabel('depth (m)')\n",
"ax.get_yaxis().set_visible(False)\n",
"ax.text(15, 65, 'd)', color='white', **text_props)\n",
"\n",
"#\n",
"# e. adaptive snapshot\n",
"#\n",
"ax = plt.subplot(235)\n",
"im = plt.pcolormesh(d_adapt.variables['xh'][:],\n",
" -d_adapt.variables['e'][t,:,0,:],\n",
" d_adapt.variables['temp'][t,:,0,:], linewidth=0, rasterized=True, vmin=10, vmax=20, cmap=cmap)\n",
"for k in range(20):\n",
" plt.plot(d.variables['xh'][:], -d_adapt.variables['e'][t,k,0,:], 'k', linewidth=0.5)\n",
"plt.axis('tight')\n",
"ax.invert_yaxis()\n",
"plt.xlabel('x (km)')\n",
"plt.ylabel('depth (m)')\n",
"ax.get_yaxis().set_visible(False)\n",
"ax.text(15, 65, 'e)', color='white', **text_props)\n",
"\n",
"# put a colourbar off to the side\n",
"cbar_ax = fig.add_axes([1.0, 0.2, 0.04, 0.7])\n",
"fig.colorbar(im, cax=cbar_ax)\n",
"\n",
"# reduce spacing between subplots\n",
"plt.tight_layout()\n",
"\n",
"# clean up\n",
"di.close()\n",
"d.close()\n",
"d_til.close()\n",
"d_rho.close()\n",
"\n",
"# save to disk and fix up the bounding box to actually include the entire figure\n",
"plt.savefig(os.path.expanduser('~/phd/writing/thesis/figures/internal_waves_snapshot_all_{}.pdf').format(kh),\n",
" bbox_inches='tight')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Figure 6\n",
"\n",
"dRPE/dt for all models averaged from 10-100 days and dRPE/dt split for MOM6"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"# calculate drpe and gridRe\n",
"\n",
"wave_kh = ['0.01', '1', '15', '150']\n",
"wave_dt = 1800.0\n",
"\n",
"wave_re = []\n",
"wave_re_rho = []\n",
"wave_re_til = []\n",
"wave_re_til_lay = []\n",
"wave_re_adapt = []\n",
"\n",
"wave_drpe = []\n",
"wave_drpe_h = []\n",
"wave_drpe_v = []\n",
"\n",
"wave_drpe_rho = []\n",
"wave_drpe_rho_h = []\n",
"wave_drpe_rho_v = []\n",
"\n",
"wave_drpe_til = []\n",
"wave_drpe_til_h = []\n",
"wave_drpe_til_v = []\n",
"\n",
"wave_drpe_til_lay = []\n",
"wave_drpe_til_lay_h = []\n",
"wave_drpe_til_lay_v = []\n",
"\n",
"wave_drpe_adapt = []\n",
"wave_drpe_adapt_h = []\n",
"wave_drpe_adapt_v = []\n",
"\n",
"for kh in wave_kh:\n",
" # calculate gridRe for Z\n",
" d = Dataset(os.path.join(base_path, 'internal_waves/KH{}_ADPPM_COZ_REPPMH4/ocean.stats.nc'.format(kh)), 'r')\n",
" vel = np.sqrt(2.0 * np.mean(d.variables['KE'][240:,:] / d.variables['Mass_lay'][240:,:]))\n",
" wave_re.append(vel * 5e3 / float(kh))\n",
" d.close()\n",
" \n",
" d = Dataset(os.path.join(base_path, 'internal_waves/KH{}_ADPPM_COZ_REPPMH4/energy.nc'.format(kh)), 'r')\n",
" dt = d.variables['time'][1] - d.variables['time'][0]\n",
" \n",
" #wave_drpe.append(-np.diff(d.variables['RPE_postale'][480:,0]).mean() / dt)\n",
" #wave_drpe.append(-(d.variables['RPE_postale'][-1,0] - d.variables['RPE_postale'][480,0])\n",
" # / (dt * d.variables['RPE_postale'][480:,0].size))\n",
" #wave_drpe_h.append(-np.mean((d.variables['RPE_preale'][480:,0] - d.variables['RPE_predyn'][480:,0]) / dt))\n",
" #wave_drpe_v.append(-np.mean((d.variables['RPE_postale'][480:,0] - d.variables['RPE_preale'][480:,0]) / dt))\n",
" wave_drpe_h.append(-np.mean(d.variables['RPE_dyndiff'][480:,0] / dt))\n",
" wave_drpe_v.append(-np.mean(d.variables['RPE_alediff'][480:,0] / dt))\n",
" wave_drpe.append(wave_drpe_h[-1] + wave_drpe_v[-1])\n",
" \n",
" d.close()\n",
" \n",
" d = Dataset(os.path.join(base_path, 'internal_waves/KH{}_ADPPM_CORHO_REPPMH4/ocean.stats.nc'.format(kh)), 'r')\n",
" vel = np.sqrt(2.0 * np.mean(d.variables['KE'][240:,:] / d.variables['Mass_lay'][240:,:]))\n",
" wave_re_rho.append(vel * 5e3 / float(kh))\n",
" d.close()\n",
" \n",
" d = Dataset(os.path.join(base_path, 'internal_waves/KH{}_ADPPM_CORHO_REPPMH4/energy.nc'.format(kh)), 'r')\n",
" dt = d.variables['time'][1] - d.variables['time'][0]\n",
" \n",
" #wave_drpe_rho.append(-(d.variables['RPE_postale'][-1,0] - d.variables['RPE_postale'][480,0])\n",
" # / (dt * d.variables['RPE_postale'][480:,0].size))\n",
" #wave_drpe_rho_h.append(-np.mean((d.variables['RPE_preale'][480:,0] - d.variables['RPE_predyn'][480:,0]) / dt))\n",
" #wave_drpe_rho_v.append(-np.mean((d.variables['RPE_postale'][480:,0] - d.variables['RPE_preale'][480:,0]) / dt))\n",
" wave_drpe_rho_h.append(-np.mean(d.variables['RPE_dyndiff'][480:,0] / dt))\n",
" wave_drpe_rho_v.append(-np.mean(d.variables['RPE_alediff'][480:,0] / dt))\n",
" wave_drpe_rho.append(wave_drpe_rho_h[-1] + wave_drpe_rho_v[-1])\n",
" \n",
" d.close()\n",
" \n",
" d = Dataset(os.path.join(base_path, 'internal_waves/KH{}_ADPPM_COZT_REPPMH4/ocean.stats.nc'.format(kh)), 'r')\n",
" vel = np.sqrt(2.0 * np.mean(d.variables['KE'][240:,:] / d.variables['Mass_lay'][240:,:]))\n",
" wave_re_til.append(vel * 5e3 / float(kh))\n",
" d.close()\n",
" \n",
" d = Dataset(os.path.join(base_path, 'internal_waves/KH{}_ADPPM_COZT_REPPMH4/energy.nc'.format(kh)), 'r')\n",
" dt = d.variables['time'][1] - d.variables['time'][0]\n",
" \n",
" #wave_drpe_til.append(-(d.variables['RPE_postale'][-1,0] - d.variables['RPE_postale'][480,0])\n",
" # / (dt * d.variables['RPE_postale'][480:,0].size))\n",
" wave_drpe_til_h.append(-np.mean(d.variables['RPE_dyndiff'][480:,0] / dt))\n",
" wave_drpe_til_v.append(-np.mean(d.variables['RPE_alediff'][480:,0] / dt))\n",
" wave_drpe_til.append(wave_drpe_til_h[-1] + wave_drpe_til_v[-1])\n",
" d.close()\n",
" \n",
" d = Dataset(os.path.join(base_path, 'internal_waves/KH{}_ADPPM_COZT/ocean.stats.nc'.format(kh)), 'r')\n",
" vel = np.sqrt(2.0 * np.mean(d.variables['KE'][240:,:] / d.variables['Mass_lay'][240:,:]))\n",
" wave_re_til_lay.append(vel * 5e3 / float(kh))\n",
" d.close()\n",
" \n",
" d = Dataset(os.path.join(base_path, 'internal_waves/KH{}_ADPPM_COZT/energy.nc'.format(kh)), 'r')\n",
" dt = d.variables['time'][1] - d.variables['time'][0]\n",
" \n",
" #wave_drpe_til_lay.append(-(d.variables['RPE_postale'][-1,0] - d.variables['RPE_postale'][480,0])\n",
" # / (dt * d.variables['RPE_postale'][480:,0].size))\n",
" wave_drpe_til_lay_h.append(-np.mean(d.variables['RPE_dyndiff'][480:,0] / dt))\n",
" wave_drpe_til_lay_v.append(-np.mean(d.variables['RPE_alediff'][480:,0] / dt))\n",
" wave_drpe_til_lay.append(wave_drpe_til_lay_h[-1] + wave_drpe_til_lay_v[-1])\n",
" \n",
" d.close()\n",
" \n",
" d = Dataset(os.path.join(base_path, 'adaptive/internal_waves/KH{}_ADPPM/ocean.stats.nc'.format(kh)), 'r')\n",
" #d = Dataset(os.path.join(base_path, 'spurious-tmp/KH{}_ADPPM_COZT/ocean.stats.nc'.format(kh)), 'r')\n",
" vel = np.sqrt(2.0 * np.mean(d.variables['KE'][240:,:] / d.variables['Mass_lay'][240:,:]))\n",
" wave_re_adapt.append(vel * 5e3 / float(kh))\n",
" d.close()\n",
" \n",
" d = Dataset(os.path.join(base_path, 'adaptive/internal_waves/KH{}_ADPPM/energy.nc'.format(kh)), 'r')\n",
" #d = Dataset(os.path.join(base_path, 'spurious-tmp/KH{}_ADPPM_COZT/energy.nc'.format(kh)), 'r')\n",
" dt = d.variables['time'][1] - d.variables['time'][0]\n",
" \n",
" dyndiff = d.variables['RPE_preale'][:] - d.variables['RPE_predyn'][:]\n",
" wave_drpe_adapt_h.append(-np.mean(dyndiff[480:,0] / dt))\n",
" wave_drpe_adapt_v.append(-np.mean(d.variables['RPE_alediff'][480:,0] / dt))\n",
" wave_drpe_adapt.append(wave_drpe_adapt_h[-1] + wave_drpe_adapt_v[-1])\n",
" d.close()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"fig = plt.figure(figsize=(9, 10.0))\n",
"\n",
"#\n",
"# dRPE/dt total\n",
"#\n",
"ax = plt.subplot(211)\n",
"# MPAS-O z-star\n",
"plt.loglog(wave_data['gridRe'][0,:], wave_data['meanDrpeDt'][0,4:8], marker='*')\n",
"# MPAS-O z-tilde with restoring timescale 100 days\n",
"j = 5\n",
"plt.loglog(wave_data['gridRe'][0,:],\n",
" wave_data['meanDrpeDt'][0,j*wave_data['m'][0,0]:(j+1)*wave_data['m'][0,0]],\n",
" color=ax.lines[-1]._color, marker='^')\n",
"\n",
"plt.loglog(wave_data['mitgcm_Re'][0,:], wave_data['mitgcm_drpe_dt'][:,0], marker='*')\n",
"\n",
"# MOM6\n",
"plt.loglog(wave_re, wave_drpe, marker='*')\n",
"plt.loglog(wave_re_til, wave_drpe_til_lay, color=ax.lines[-1]._color, marker='^')\n",
"plt.loglog(wave_re_til, wave_drpe_til, '--', color=ax.lines[-1]._color, marker='^')\n",
"plt.loglog(wave_re_rho, wave_drpe_rho, color=ax.lines[-1]._color, marker='o')\n",
"plt.loglog(wave_re_adapt, wave_drpe_adapt, color=ax.lines[-1]._color, marker='2')\n",
"\n",
"plt.loglog(wave_data['mom_Re'][0,:], wave_data['mom_drpe_dt'][:,0], marker='*')\n",
"\n",
"ax.get_xaxis().set_ticklabels([])\n",
"plt.grid(True, which='minor', axis='y')\n",
"plt.grid(True, axis='x')\n",
"plt.ylabel('dRPE/dt (W/m²)')\n",
"plt.legend(['MPAS-O z-star', 'MPAS-O z-tilde', 'MITGCM', 'MOM6 z-star',\n",
" 'MOM6 z-tilde (level IC)', 'MOM6 z-tilde (layer IC)', 'MOM6 rho', 'MOM6 adapt', 'MOM5'],\n",
" loc='upper left', bbox_to_anchor=(1.01, 1.0), frameon=False, fontsize=9.0)\n",
"ax.text(4, 6e-4, 'a)', **text_props)\n",
"\n",
"#\n",
"# dRPE/dt split for z-star and z-tilde\n",
"#\n",
"ax = plt.subplot(212)\n",
"\n",
"# reset colours\n",
"#ax.set_prop_cycle(None)\n",
"# z-tilde split\n",
"#hzt = plt.loglog(mywave_data['gridRe_t'],\n",
"# np.mean(mywave_data['rpe_st'][:,0,10*48:], axis=1), '^', label='horiz. z-tilde')\n",
"#vzt = plt.loglog(mywave_data['gridRe_t'],\n",
"# np.mean(mywave_data['rpe_st'][:,1,10*48:], axis=1), '^', label='vert. z-tilde')\n",
"\n",
"ax.set_prop_cycle(None)\n",
"hr = plt.loglog(wave_re_rho, wave_drpe_rho_h, 'o', label='horiz. rho')\n",
"vr = plt.loglog(wave_re_rho, wave_drpe_rho_v, 'o', label='vert. rho')\n",
"\n",
"ax.set_prop_cycle(None)\n",
"ht = plt.loglog(wave_re_til, wave_drpe_til_h, '^', label='horiz. z-tilde (level IC)')\n",
"vt = plt.loglog(wave_re_til, wave_drpe_til_v, '^', label='vert. z-tilde (level IC)')\n",
"\n",
"ax.set_prop_cycle(None)\n",
"htl = plt.loglog(wave_re_til_lay, wave_drpe_til_lay_h, 's', label='horiz. z-tilde (layer IC)')\n",
"vtl = plt.loglog(wave_re_til_lay, wave_drpe_til_lay_v, 's', label='vert. z-tilde (layer IC)')\n",
"\n",
"ax.set_prop_cycle(None)\n",
"ha = plt.loglog(wave_re_adapt, wave_drpe_adapt_h, '2', label='horiz. adapt')\n",
"va = plt.loglog(wave_re_adapt, wave_drpe_adapt_v, '2', label='vert. adapt')\n",
"\n",
"ax.set_prop_cycle(None)\n",
"# z-star split\n",
"hzs = plt.loglog(wave_re, wave_drpe_h, '*', label='horiz. z-star')\n",
"vzs = plt.loglog(wave_re, wave_drpe_v, '*', label='vert. z-star')\n",
"\n",
"plt.grid(True, which='minor', axis='y')\n",
"plt.xlabel('grid Reynolds number')\n",
"plt.ylabel('dRPE/dt (W/m²)')\n",
"plt.legend(handles=[h[0] for h in [hzs, vzs, ht, vt, htl, vtl, ha, va, hr, vr]],\n",
" loc='upper left', bbox_to_anchor=(1.01, 1.0), frameon=False, fontsize=9.0)\n",
"ax.text(4, 2e-5, 'b)', **text_props)\n",
"\n",
"plt.tight_layout()\n",
"plt.savefig(os.path.expanduser('~/phd/writing/thesis/figures/internal_waves_drpe.pdf'), bbox_inches='tight')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Baroclinic Eddies"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"eddies_data = scipy.io.loadmat('data/m62_bcl_ch_131028.mat')\n",
"eddies_data['meanDrpeDt1km100day'][0,0] = 1.593383e-4\n",
"eddies_10_quad_data = scipy.io.loadmat('data/m83QuadHex10km.mat')\n",
"eddies_4_quad_data = scipy.io.loadmat('data/m83QuadHex4km.mat')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Figure 7\n",
"\n",
"Snapshot of initial condition and surface temperature at different viscosities."
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 500x400 with 4 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"kh_hi = '200'\n",
"kh_lo = '1'\n",
"dhi = Dataset(os.path.join(base_path, 'baroclinic_eddies_DX1_KH{}_ADPPM_COZ.nc'.format(kh_hi)), 'r')\n",
"dlo = Dataset(os.path.join(base_path, 'baroclinic_eddies_DX1_KH{}_ADPPM_COZ.nc'.format(kh_lo)), 'r')\n",
"d = Dataset(os.path.join(base_path, 'baroclinic_eddies_input_1.nc'), 'r')\n",
"\n",
"z_min, z_max = d.variables['temp'][0,:,:].min(), d.variables['temp'][0,:,:].max()\n",
"\n",
"cmap = cm.RdBu_r\n",
"\n",
"fig = plt.figure(figsize=(5,4))\n",
"\n",
"ax = plt.subplot(131)\n",
"# use multiples of 40km for axis label\n",
"loc = plticker.MultipleLocator(40)\n",
"\n",
"im = plt.pcolormesh(d.variables['x'][:] / 1e3,\n",
" d.variables['y'][:] / 1e3,\n",
" d.variables['temp'][0,:,:],\n",
" vmin=z_min, vmax=z_max, linewidth=0, rasterized=True, cmap=cmap)\n",
"plt.xlabel('x (km)')\n",
"plt.ylabel('y (km)')\n",
"ax.xaxis.set_major_locator(loc)\n",
"ax.text(15, 465, 'a)', color='white', **text_props)\n",
"\n",
"ax = plt.subplot(132)\n",
"plt.pcolormesh(dlo.variables['xh'][:],\n",
" dlo.variables['yh'][:],\n",
" dlo.variables['temp'][-1,0,:,:],\n",
" vmin=z_min, vmax=z_max, linewidth=0, rasterized=True, cmap=cmap)\n",
"plt.xlabel('x (km)')\n",
"ax.xaxis.set_major_locator(loc)\n",
"ax.yaxis.set_ticklabels([])\n",
"ax.text(15, 465, 'b)', color='white', **text_props)\n",
"\n",
"ax = plt.subplot(133)\n",
"plt.pcolormesh(dhi.variables['xh'][:],\n",
" dhi.variables['yh'][:],\n",
" dhi.variables['temp'][-1,0,:,:],\n",
" vmin=z_min, vmax=z_max, linewidth=0, rasterized=True, cmap=cmap)\n",
"plt.xlabel('x (km)')\n",
"ax.yaxis.set_ticklabels([])\n",
"ax.xaxis.set_major_locator(loc)\n",
"ax.text(15, 465, 'c)', color='white', **text_props)\n",
"\n",
"plt.subplots_adjust(hspace=0.1)\n",
"\n",
"\n",
"#plt.tight_layout(h_pad=0.1)\n",
"# put a colourbar off to the side\n",
"cbar_ax = fig.add_axes([0.94, 0.15, 0.04, 0.7])\n",
"fig.colorbar(im, cax=cbar_ax)\n",
"\n",
"d.close()\n",
"dlo.close()\n",
"dhi.close()\n",
"\n",
"plt.savefig('figures/eddies_snapshot_dx1.pdf', bbox_inches='tight')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Figure 8\n",
"\n",
"dRPE/dt for different models for different horizontal resolutions"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"# calculate drpe and gridRe\n",
"\n",
"eddy_dx = ['10', '4', '1']\n",
"eddy_kh = ['1', '5', '10', '20', '200']\n",
"\n",
"eddy_re = {}\n",
"eddy_re_rho = {}\n",
"eddy_re_adapt = {}\n",
"\n",
"eddy_drpe = {}\n",
"eddy_drpe_h = {}\n",
"eddy_drpe_v = {}\n",
"\n",
"eddy_drpe_rho = {}\n",
"eddy_drpe_rho_h = {}\n",
"eddy_drpe_rho_v = {}\n",
"\n",
"eddy_drpe_adapt = {}\n",
"eddy_drpe_adapt_h = {}\n",
"eddy_drpe_adapt_v = {}\n",
"\n",
"for dx in eddy_dx:\n",
" eddy_re[dx] = []\n",
" eddy_re_rho[dx] = []\n",
" eddy_re_adapt[dx] = []\n",
" eddy_drpe[dx] = []\n",
" eddy_drpe_h[dx] = []\n",
" eddy_drpe_v[dx] = []\n",
" eddy_drpe_rho[dx] = []\n",
" eddy_drpe_rho_h[dx] = []\n",
" eddy_drpe_rho_v[dx] = []\n",
" eddy_drpe_adapt[dx] = []\n",
" eddy_drpe_adapt_h[dx] = []\n",
" eddy_drpe_adapt_v[dx] = []\n",
" \n",
" for kh in eddy_kh:\n",
" # calculate gridRe for Z\n",
" d = Dataset(os.path.join(base_path, 'baroclinic_eddies/DX{}_KH{}_ADPPM_COZ/ocean.stats.nc'.format(dx, kh)), 'r')\n",
" vel = np.sqrt(2.0 * np.mean(d.variables['KE'][:] / d.variables['Mass_lay'][:]))\n",
" eddy_re[dx].append(vel * float(dx) * 1e3 / float(kh))\n",
" d.close()\n",
"\n",
" d = Dataset(os.path.join(base_path, 'baroclinic_eddies/DX{}_KH{}_ADPPM_COZ/energy.nc'.format(dx, kh)), 'r')\n",
" dt = d.variables['time'][1] - d.variables['time'][0]\n",
" \n",
" #eddy_drpe[dx].append(-np.diff(d.variables['RPE_postale'][:,0]).mean() / dt)\n",
" eddy_drpe_h[dx].append(-np.mean(d.variables['RPE_dyndiff'][:,0] / dt))\n",
" eddy_drpe_v[dx].append(-np.mean(d.variables['RPE_alediff'][:,0] / dt))\n",
" eddy_drpe[dx].append(eddy_drpe_h[dx][-1] + eddy_drpe_v[dx][-1])\n",
" d.close()\n",
" \n",
" d = Dataset(os.path.join(base_path, 'baroclinic_eddies/DX{}_KH{}_ADPPM_CORHO/ocean.stats.nc'.format(dx, kh)), 'r')\n",
" vel = np.sqrt(2.0 * np.mean(d.variables['KE'][:] / d.variables['Mass_lay'][:]))\n",
" eddy_re_rho[dx].append(vel * float(dx) * 1e3 / float(kh))\n",
" d.close()\n",
"\n",
" d = Dataset(os.path.join(base_path, 'baroclinic_eddies/DX{}_KH{}_ADPPM_CORHO/energy.nc'.format(dx, kh)), 'r')\n",
" dt = d.variables['time'][1] - d.variables['time'][0]\n",
"\n",
" #eddy_drpe_rho[dx].append(np.diff(d.variables['RPE_postale'][:,0]).mean() / dt)\n",
" eddy_drpe_rho_h[dx].append(-np.mean(d.variables['RPE_dyndiff'][:,0] / dt))\n",
" eddy_drpe_rho_v[dx].append(-np.mean(d.variables['RPE_alediff'][:,0] / dt))\n",
" eddy_drpe_rho[dx].append(eddy_drpe_rho_h[dx][-1] + eddy_drpe_rho_v[dx][-1])\n",
" d.close()\n",
" \n",
" d = Dataset(os.path.join(base_path, 'adaptive/baroclinic_eddies/DX{}_KH{}_ADPPMH3/ocean.stats.nc'.format(dx, kh)), 'r')\n",
" vel = np.sqrt(2.0 * np.mean(d.variables['KE'][:] / d.variables['Mass_lay'][:]))\n",
" eddy_re_adapt[dx].append(vel * float(dx) * 1e3 / float(kh))\n",
" d.close()\n",
" \n",
" d = Dataset(os.path.join(base_path, 'adaptive/baroclinic_eddies/DX{}_KH{}_ADPPMH3/energy.nc'.format(dx, kh)), 'r')\n",
" dt = d.variables['time'][1] - d.variables['time'][0]\n",
" \n",
" dyndiff = d.variables['RPE_preale'][:] - d.variables['RPE_predyn'][:]\n",
" eddy_drpe_adapt_h[dx].append(-np.mean(dyndiff[:,0] / dt))\n",
" eddy_drpe_adapt_v[dx].append(-np.mean(d.variables['RPE_alediff'][:,0] / dt))\n",
" eddy_drpe_adapt[dx].append(eddy_drpe_adapt_h[dx][-1] + eddy_drpe_adapt_v[dx][-1])\n",
" d.close()"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"for nk in ['10', '40']:\n",
" eddy_re['nk' + nk] = []\n",
" eddy_drpe['nk' + nk] = []\n",
" eddy_drpe_h['nk' + nk] = []\n",
" eddy_drpe_v['nk' + nk] = []\n",
"\n",
" for kh in eddy_kh:\n",
" d = Dataset(os.path.join(base_path, 'baroclinic_eddies/DX1_NK{}_KH{}_COZ/ocean.stats.nc'.format(nk, kh)), 'r')\n",
" vel = np.sqrt(2.0 * np.mean(d.variables['KE'][:] / d.variables['Mass_lay'][:]))\n",
" eddy_re['nk' + nk].append(vel * float(dx) * 1e3 / float(kh))\n",
" d.close()\n",
"\n",
" d = Dataset(os.path.join(base_path, 'baroclinic_eddies/DX1_NK{}_KH{}_COZ/energy.nc'.format(nk, kh)), 'r')\n",
" dt = d.variables['time'][1] - d.variables['time'][0]\n",
"\n",
" #eddy_drpe['nk' + nk].append(-np.diff(d.variables['RPE_postale'][:,0]).mean() / dt)\n",
" eddy_drpe_h['nk' + nk].append(-np.mean(d.variables['RPE_dyndiff'][:,0] / dt))\n",
" eddy_drpe_v['nk' + nk].append(-np.mean(d.variables['RPE_alediff'][:,0] / dt))\n",
" eddy_drpe['nk' + nk].append(eddy_drpe_h['nk' + nk][-1] + eddy_drpe_v['nk' + nk][-1])\n",
" d.close()"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 600x1000 with 3 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(6, 10))\n",
"\n",
"#\n",
"# 10km horizontal\n",
"#\n",
"ax = plt.subplot(311)\n",
"\n",
"# MPAS-O hex\n",
"vel_scale = np.sqrt(2 * eddies_data['keMeanTime10km'][0])\n",
"gridRe = 10e3 * vel_scale[5:10] / eddies_data['nu_h'][0]\n",
"plt.loglog(gridRe, eddies_data['meanDrpeDt10km320day'][0,5:10], marker='*', label='MPAS-O')\n",
"\n",
"# MPAS-O quad\n",
"#vel_scale = np.sqrt(2 * eddies_10_quad_data['keMeanTimeQuadHex10km'][0])\n",
"#gridRe = 10e3 * vel_scale[0:5] / eddies_data['nu_h'][0]\n",
"#plt.loglog(gridRe, eddies_10_quad_data['meanDrpeDtQuadHex10km'][0,0:5],\n",
"# marker='s', label='MPAS-O quad', color=ax.lines[-1]._color)\n",
"\n",
"# MITGCM\n",
"plt.loglog(eddies_data['mitgcm_10km_Re'][0,[5,0,1,2,3]],\n",
" eddies_data['mitgcm_10km_drpe_dt'][[5,0,1,2,3],0],\n",
" marker='*', label='MITGCM')\n",
"\n",
"# MOM6\n",
"plt.loglog(eddy_re['10'], eddy_drpe['10'], marker='*', label='MOM6')\n",
"#plt.loglog(eddy_re_rho['10'], eddy_drpe_rho_h['10'], marker='^', color=ax.lines[-1]._color, label='MOM6 rho (horiz.)')\n",
"plt.loglog(eddy_re_adapt['10'], eddy_drpe_adapt['10'], 's', color=ax.lines[-1]._color, label='MOM6 adapt')\n",
"\n",
"# MOM5\n",
"plt.loglog(eddies_data['mom_10km_Re'][0], eddies_data['mom_10km_drpe_dt'][:,0], marker='*', label='MOM5')\n",
"\n",
"ax.set_xlim(.2, 1e3)\n",
"ax.set_ylim(1e-6, 3e-3)\n",
"plt.grid(True, which='minor', axis='y')\n",
"plt.ylabel('dRPE/dt (W/m²)')\n",
"ax.xaxis.set_ticklabels([])\n",
"\n",
"leg = plt.legend(loc='lower right')\n",
"leg.get_frame().set_linewidth(0)\n",
"ax.text(.3, 1.5e-3, 'a)', **text_props)\n",
"\n",
"#\n",
"# 4km horizontal\n",
"#\n",
"ax = plt.subplot(312)\n",
"\n",
"# MPAS-O hex\n",
"vel_scale = np.sqrt(2 * eddies_data['keMeanTime4km'][0])\n",
"gridRe = 4e3 * vel_scale[5:10] / eddies_data['nu_h'][0]\n",
"plt.loglog(gridRe, eddies_data['meanDrpeDt4km320day'][0,5:10], marker='*', label='MPAS-O')\n",
"\n",
"# MPAS-O quad\n",
"#vel_scale = np.sqrt(2 * eddies_4_quad_data['keMeanTimeQuadHex4km'][0])\n",
"#gridRe = 4e3 * vel_scale[0:5] / eddies_data['nu_h'][0]\n",
"#plt.loglog(gridRe, eddies_4_quad_data['meanDrpeDtQuadHex4km'][0,0:5],\n",
"# marker='s', label='MPAS-O quad', color=ax.lines[-1]._color)\n",
"\n",
"# MITGCM\n",
"plt.loglog(eddies_data['mitgcm_4km_Re'][0,[5,0,1,2,3]],\n",
" eddies_data['mitgcm_4km_drpe_dt'][[5,0,1,2,3],0],\n",
" marker='*', label='MITGCM')\n",
"\n",
"# MOM6\n",
"plt.loglog(eddy_re['4'], eddy_drpe['4'], marker='*', label='MOM6')\n",
"#plt.loglog(eddy_re_rho['4'], eddy_drpe_rho_h['4'], marker='^', color=ax.lines[-1]._color, label='MOM6 rho (horiz.)')\n",
"plt.loglog(eddy_re_adapt['4'], eddy_drpe_adapt['4'], 's', color=ax.lines[-1]._color, label='MOM6 adapt')\n",
"\n",
"# MOM5\n",
"plt.loglog(eddies_data['mom_4km_Re'][0], eddies_data['mom_4km_drpe_dt'][:,0],\n",
" marker='*', label='MOM5')\n",
"\n",
"ax.set_xlim(.2, 1e3)\n",
"ax.set_ylim(1e-6, 3e-3)\n",
"plt.grid(True, which='minor', axis='y')\n",
"plt.ylabel('dRPE/dt (W/m²)')\n",
"ax.xaxis.set_ticklabels([])\n",
"\n",
"leg = plt.legend(loc='lower right')\n",
"leg.get_frame().set_linewidth(0)\n",
"ax.text(.3, 1.5e-3, 'b)', **text_props)\n",
"\n",
"#\n",
"# 1km horizontal\n",
"#\n",
"ax = plt.subplot(313)\n",
"\n",
"# MPAS-O hex\n",
"vel_scale = np.sqrt(2 * eddies_data['keMeanTime1km'][0])\n",
"gridRe = 1e3 * vel_scale[0:5] / eddies_data['nu_h'][0]\n",
"plt.loglog(gridRe, eddies_data['meanDrpeDt1km100day'][0,:], marker='*', label='MPAS-O')\n",
"\n",
"# MITGCM\n",
"plt.loglog(eddies_data['mitgcm_1km_Re'][0,[3,0,1,2]], eddies_data['mitgcm_1km_drpe_dt'][[3,0,1,2],0],\n",
" marker='*', label='MITGCM')\n",
"\n",
"# MOM6\n",
"plt.loglog(eddy_re['1'], eddy_drpe['1'], marker='*', label='MOM6')\n",
"#plt.loglog(eddy_re_rho['1'], eddy_drpe_rho_h['1'], marker='^', color=ax.lines[-1]._color, label='MOM6 rho (horiz.)')\n",
"plt.loglog(eddy_re_adapt['1'], eddy_drpe_adapt['1'], 's', color=ax.lines[-1]._color, label='MOM6 adapt')\n",
"\n",
"# MOM5\n",
"plt.loglog(eddies_data['mom_1km_Re'][0], eddies_data['mom_1km_drpe_dt'][:,0],\n",
" marker='*', label='MOM5')\n",
"\n",
"ax.set_xlim(.2, 1e3)\n",
"ax.set_ylim(1e-6, 3e-3)\n",
"plt.grid(True, which='minor', axis='y')\n",
"plt.ylabel('dRPE/dt (W/m²)')\n",
"plt.xlabel('grid Reynolds number')\n",
"\n",
"leg = plt.legend(loc='lower right')\n",
"leg.get_frame().set_linewidth(0)\n",
"ax.text(.3, 1.5e-3, 'c)', **text_props)\n",
"\n",
"plt.tight_layout()\n",
"#plt.savefig('figures/eddies_drpe.pdf')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Figure 9\n",
"\n",
"dRPE/dt split for different horizontal vertical resolutions in MOM6"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"ename": "KeyError",
"evalue": "'nk10'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-35-7b51723c934b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 64\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 65\u001b[0m \u001b[0;31m# 100m vertical (nk = 10)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 66\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloglog\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0meddy_re\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'nk10'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0meddy_drpe_h\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'nk10'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmarker\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'o'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 67\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloglog\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0meddy_re\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'nk10'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0meddy_drpe_v\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'nk10'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'--'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmarker\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'o'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 68\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_prop_cycle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mKeyError\u001b[0m: 'nk10'"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 600x700 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = plt.figure(figsize=(6, 7))\n",
"rho = False\n",
"\n",
"#\n",
"# Varying horizontal resolution\n",
"#\n",
"ax = plt.subplot(211)\n",
"\n",
"# 10km horizontal\n",
"plt.loglog(eddy_re['10'], eddy_drpe_h['10'], marker='o')\n",
"plt.loglog(eddy_re['10'], eddy_drpe_v['10'], '--', marker='o')\n",
"if rho:\n",
" plt.loglog(eddy_re_rho['10'], eddy_drpe_rho_h['10'], marker='o')\n",
" plt.loglog(eddy_re_rho['10'], eddy_drpe_rho_v['10'], '--', marker='o')\n",
"plt.loglog(eddy_re_adapt['10'], eddy_drpe_adapt_h['10'], marker='o')\n",
"plt.loglog(eddy_re_adapt['10'], eddy_drpe_adapt_v['10'], '--', marker='o')\n",
"ax.set_prop_cycle(None)\n",
"\n",
"# 4km horizontal\n",
"plt.loglog(eddy_re['4'], eddy_drpe_h['4'], marker='s')\n",
"plt.loglog(eddy_re['4'], eddy_drpe_v['4'], '--', marker='s')\n",
"#plt.loglog(eddy_re_rho['4'], eddy_drpe_rho_h['4'], marker='s')\n",
"#plt.loglog(eddy_re_rho['4'], eddy_drpe_rho_v['4'], '--', marker='s')\n",
"plt.loglog(eddy_re_adapt['4'], eddy_drpe_adapt_h['4'], marker='s')\n",
"plt.loglog(eddy_re_adapt['4'], eddy_drpe_adapt_v['4'], '--', marker='s')\n",
"ax.set_prop_cycle(None)\n",
"\n",
"# 1km horizontal\n",
"plt.loglog(eddy_re['1'], eddy_drpe_h['1'], marker='^')\n",
"plt.loglog(eddy_re['1'], eddy_drpe_v['1'], '--', marker='^')\n",
"#plt.loglog(eddy_re_rho['1'], eddy_drpe_rho_h['1'], marker='^')\n",
"#plt.loglog(eddy_re_rho['1'], eddy_drpe_rho_v['1'], '--', marker='^')\n",
"plt.loglog(eddy_re_adapt['1'], eddy_drpe_adapt_h['1'], marker='s')\n",
"plt.loglog(eddy_re_adapt['1'], eddy_drpe_adapt_v['1'], '--', marker='s')\n",
"\n",
"plt.grid(True, which='minor', axis='y')\n",
"\n",
"leg = plt.legend(handles=[\n",
" plines.Line2D([], [], color=ax.lines[0]._color, label='horiz.'),\n",
" plines.Line2D([], [], linestyle='--', color=ax.lines[1]._color, label='vert.'),\n",
" plines.Line2D([], [], color=ax.lines[2]._color, label='horiz. adapt'),\n",
" plines.Line2D([], [], linestyle='--', color=ax.lines[3]._color, label='vert. adapt')],\n",
" loc='lower left', ncol=2)\n",
"leg.get_frame().set_linewidth(0)\n",
"ax.add_artist(leg)\n",
"\n",
"leg = plt.legend(handles=[\n",
" plines.Line2D([], [], color='k', marker='o', label=r'$\\Delta$x = 10km', linestyle=''),\n",
" plines.Line2D([], [], color='k', marker='s', label=r'$\\Delta$x = 4km', linestyle=''),\n",
" plines.Line2D([], [], color='k', marker='^', label=r'$\\Delta$x = 1km', linestyle='')],\n",
" loc='lower right')\n",
"leg.get_frame().set_linewidth(0)\n",
"plt.ylabel('dRPE/dt (W/m²)')\n",
"plt.xlabel('grid Reynolds number')\n",
"#ax.xaxis.set_ticklabels([])\n",
"\n",
"#ax.set_ylim(2e-6, 2e-3)\n",
"ax.text(0.2, 1.3e-3, 'a)', **text_props)\n",
"\n",
"#\n",
"# Varying vertical resolution\n",
"#\n",
"ax = plt.subplot(212)\n",
"\n",
"# 100m vertical (nk = 10)\n",
"plt.loglog(eddy_re['nk10'], eddy_drpe_h['nk10'], marker='o')\n",
"plt.loglog(eddy_re['nk10'], eddy_drpe_v['nk10'], '--', marker='o')\n",
"ax.set_prop_cycle(None)\n",
"\n",
"# 50m vertical (nk = 20, regular)\n",
"plt.loglog(eddy_re['1'], eddy_drpe_h['1'], marker='s')\n",
"plt.loglog(eddy_re['1'], eddy_drpe_v['1'], '--', marker='s')\n",
"ax.set_prop_cycle(None)\n",
"\n",
"# 25m vertical (nk = 40)\n",
"plt.loglog(eddy_re['nk40'], eddy_drpe_h['nk40'], marker='^')\n",
"plt.loglog(eddy_re['nk40'], eddy_drpe_v['nk40'], '--', marker='^')\n",
"\n",
"plt.grid(True, which='minor', axis='y')\n",
"\n",
"leg = plt.legend(handles=[\n",
" plines.Line2D([], [], color=ax.lines[0]._color, label='horiz.'),\n",
" plines.Line2D([], [], linestyle='--', color=ax.lines[1]._color, label='vert.')],\n",
" loc='lower center')\n",
"leg.get_frame().set_linewidth(0)\n",
"ax.add_artist(leg)\n",
"\n",
"leg = plt.legend(handles=[\n",
" plines.Line2D([], [], color='k', marker='o', label=r'$\\Delta$z = 100m', linestyle=''),\n",
" plines.Line2D([], [], color='k', marker='s', label=r'$\\Delta$z = 50m', linestyle=''),\n",
" plines.Line2D([], [], color='k', marker='^', label=r'$\\Delta$z = 25m', linestyle='')],\n",
" loc='lower right')\n",
"leg.get_frame().set_linewidth(0)\n",
"plt.xlabel('grid Reynolds number')\n",
"plt.ylabel('dRPE/dt (W/m²)')\n",
"#ax.yaxis.set_ticklabels([])\n",
"ax.set_ylim(2e-6, 2e-3)\n",
"ax.text(0.2, 1.3e-3, 'b)', **text_props)\n",
"\n",
"plt.tight_layout()\n",
"#plt.savefig('figures/eddies_drpe_split.pdf')"
]
}
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