{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "Plot Antarctic Tide Range\n", "=========================\n", "\n", "Demonstrates plotting the tidal amplitudes around Antarctica\n", "\n", "OTIS format tidal solutions provided by Ohio State University and ESR \n", "- http://volkov.oce.orst.edu/tides/region.html \n", "- https://www.esr.org/research/polar-tide-models/list-of-polar-tide-models/\n", "- ftp://ftp.esr.org/pub/datasets/tmd/ \n", "\n", "Global Tide Model (GOT) solutions provided by Richard Ray at GSFC \n", "\n", "Finite Element Solution (FES) provided by AVISO \n", "- https://www.aviso.altimetry.fr/data/products/auxiliary-products/global-tide-fes.html\n", " \n", "#### Python Dependencies\n", " - [numpy: Scientific Computing Tools For Python](https://www.numpy.org) \n", " - [scipy: Scientific Tools for Python](https://www.scipy.org/) \n", " - [pyproj: Python interface to PROJ library](https://pypi.org/project/pyproj/) \n", " - [netCDF4: Python interface to the netCDF C library](https://unidata.github.io/netcdf4-python/) \n", " - [matplotlib: Python 2D plotting library](http://matplotlib.org/) \n", " - [cartopy: Python package designed for geospatial data processing](https://scitools.org.uk/cartopy/docs/latest/) \n", "\n", "#### Program Dependencies\n", "\n", "- `convert_ll_xy.py`: convert lat/lon points to and from projected coordinates \n", "- `read_tide_model.py`: extract tidal harmonic constants from OTIS tide models \n", "- `read_netcdf_model.py`: extract tidal harmonic constants from netcdf models \n", "- `read_GOT_model.py`: extract tidal harmonic constants from GSFC GOT models \n", "- `read_FES_model.py`: extract tidal harmonic constants from FES tide models \n", "\n", "This notebook uses Jupyter widgets to set parameters for calculating the tidal maps. \n", "The widgets can be installed as described below. \n", "```\n", "pip3 install --user ipywidgets\n", "jupyter nbextension install --user --py widgetsnbextension\n", "jupyter nbextension enable --user --py widgetsnbextension\n", "jupyter-notebook\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Load modules" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import os\n", "import pyproj\n", "import datetime\n", "import numpy as np\n", "import matplotlib\n", "matplotlib.rcParams['axes.linewidth'] = 2.0\n", "matplotlib.rcParams[\"animation.html\"] = \"jshtml\"\n", "import matplotlib.pyplot as plt\n", "import matplotlib.animation as animation\n", "import cartopy.crs as ccrs\n", "import ipywidgets as widgets\n", "from IPython.display import HTML\n", "\n", "from pyTMD.read_tide_model import extract_tidal_constants\n", "from pyTMD.read_netcdf_model import extract_netcdf_constants\n", "from pyTMD.read_GOT_model import extract_GOT_constants\n", "from pyTMD.read_FES_model import extract_FES_constants\n", "#-- autoreload\n", "%load_ext autoreload\n", "%autoreload 2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Set parameters for program\n", "\n", "- Model directory \n", "- Tide model \n", "- Date to run " ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "#-- set the directory with tide models\n", "dirText = widgets.Text(\n", " value=os.getcwd(),\n", " description='Directory:',\n", " disabled=False\n", ")\n", "\n", "#-- dropdown menu for setting tide model\n", "model_list = ['CATS0201','CATS2008','TPXO9-atlas','TPXO9-atlas-v2',\n", " 'TPXO9-atlas-v3','TPXO9.1','TPXO8-atlas','TPXO7.2',\n", " 'GOT4.7','GOT4.8','GOT4.10','FES2014']\n", "modelDropdown = widgets.Dropdown(\n", " options=model_list,\n", " value='CATS2008',\n", " description='Model:',\n", " disabled=False,\n", ")\n", "\n", "#-- display widgets for setting directory, model\n", "widgets.VBox([dirText,modelDropdown])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Setup tide model parameters" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "#-- directory with tide models\n", "tide_dir = os.path.expanduser(dirText.value)\n", "MODEL = modelDropdown.value\n", "if (MODEL == 'CATS0201'):\n", " grid_file = os.path.join(tide_dir,'cats0201_tmd','grid_CATS')\n", " model_file = os.path.join(tide_dir,'cats0201_tmd','h0_CATS02_01')\n", " model_format = 'OTIS'\n", " EPSG = '4326'\n", " TYPE = 'z'\n", "elif (MODEL == 'CATS2008'):\n", " grid_file = os.path.join(tide_dir,'CATS2008','grid_CATS2008')\n", " model_file = os.path.join(tide_dir,'CATS2008','hf.CATS2008.out')\n", " model_format = 'OTIS'\n", " EPSG = 'CATS2008'\n", " TYPE = 'z'\n", "elif (MODEL == 'TPXO9-atlas'):\n", " model_directory = os.path.join(tide_dir,'TPXO9_atlas')\n", " grid_file = 'grid_tpxo9_atlas.nc.gz'\n", " model_files = ['h_q1_tpxo9_atlas_30.nc.gz','h_o1_tpxo9_atlas_30.nc.gz',\n", " 'h_p1_tpxo9_atlas_30.nc.gz','h_k1_tpxo9_atlas_30.nc.gz',\n", " 'h_n2_tpxo9_atlas_30.nc.gz','h_m2_tpxo9_atlas_30.nc.gz',\n", " 'h_s2_tpxo9_atlas_30.nc.gz','h_k2_tpxo9_atlas_30.nc.gz',\n", " 'h_m4_tpxo9_atlas_30.nc.gz','h_ms4_tpxo9_atlas_30.nc.gz',\n", " 'h_mn4_tpxo9_atlas_30.nc.gz','h_2n2_tpxo9_atlas_30.nc.gz']\n", " model_format = 'netcdf'\n", " TYPE = 'z'\n", " SCALE = 1.0/1000.0\n", "elif (MODEL == 'TPXO9-atlas-v2'):\n", " model_directory = os.path.join(tide_dir,'TPXO9_atlas_v2')\n", " grid_file = 'grid_tpxo9_atlas_30_v2.nc.gz'\n", " model_files = ['h_q1_tpxo9_atlas_30_v2.nc.gz','h_o1_tpxo9_atlas_30_v2.nc.gz',\n", " 'h_p1_tpxo9_atlas_30_v2.nc.gz','h_k1_tpxo9_atlas_30_v2.nc.gz',\n", " 'h_n2_tpxo9_atlas_30_v2.nc.gz','h_m2_tpxo9_atlas_30_v2.nc.gz',\n", " 'h_s2_tpxo9_atlas_30_v2.nc.gz','h_k2_tpxo9_atlas_30_v2.nc.gz',\n", " 'h_m4_tpxo9_atlas_30_v2.nc.gz','h_ms4_tpxo9_atlas_30_v2.nc.gz',\n", " 'h_mn4_tpxo9_atlas_30_v2.nc.gz','h_2n2_tpxo9_atlas_30_v2.nc.gz']\n", " model_format = 'netcdf'\n", " TYPE = 'z'\n", " SCALE = 1.0/1000.0\n", "elif (MODEL == 'TPXO9.1'):\n", " grid_file = os.path.join(tide_dir,'TPXO9.1','DATA','grid_tpxo9')\n", " model_file = os.path.join(tide_dir,'TPXO9.1','DATA','h_tpxo9.v1')\n", " model_format = 'OTIS'\n", " EPSG = '4326'\n", " TYPE = 'z'\n", "elif (MODEL == 'TPXO8-atlas'):\n", " grid_file = os.path.join(tide_dir,'tpxo8_atlas','grid_tpxo8atlas_30_v1')\n", " model_file = os.path.join(tide_dir,'tpxo8_atlas','hf.tpxo8_atlas_30_v1')\n", " model_format = 'ATLAS'\n", " EPSG = '4326'\n", " TYPE = 'z'\n", "elif (MODEL == 'TPXO7.2'):\n", " grid_file = os.path.join(tide_dir,'TPXO7.2_tmd','grid_tpxo7.2')\n", " model_file = os.path.join(tide_dir,'TPXO7.2_tmd','h_tpxo7.2')\n", " model_format = 'OTIS'\n", " EPSG = '4326'\n", " TYPE = 'z'\n", "elif (MODEL == 'GOT4.7'):\n", " model_directory = os.path.join(tide_dir,'GOT4.7','grids_oceantide')\n", " model_files = ['q1.d.gz','o1.d.gz','p1.d.gz','k1.d.gz','n2.d.gz',\n", " 'm2.d.gz','s2.d.gz','k2.d.gz','s1.d.gz','m4.d.gz']\n", " c = ['q1','o1','p1','k1','n2','m2','s2','k2','s1','m4']\n", " model_format = 'GOT'\n", " SCALE = 1.0/100.0\n", "elif (MODEL == 'GOT4.8'):\n", " model_directory = os.path.join(tide_dir,'got4.8','grids_oceantide')\n", " model_files = ['q1.d.gz','o1.d.gz','p1.d.gz','k1.d.gz','n2.d.gz',\n", " 'm2.d.gz','s2.d.gz','k2.d.gz','s1.d.gz','m4.d.gz']\n", " c = ['q1','o1','p1','k1','n2','m2','s2','k2','s1','m4']\n", " model_format = 'GOT'\n", " SCALE = 1.0/100.0\n", "elif (MODEL == 'GOT4.10'):\n", " model_directory = os.path.join(tide_dir,'GOT4.10c','grids_oceantide')\n", " model_files = ['q1.d.gz','o1.d.gz','p1.d.gz','k1.d.gz','n2.d.gz',\n", " 'm2.d.gz','s2.d.gz','k2.d.gz','s1.d.gz','m4.d.gz']\n", " c = ['q1','o1','p1','k1','n2','m2','s2','k2','s1','m4']\n", " model_format = 'GOT'\n", " SCALE = 1.0/100.0\n", "elif (MODEL == 'FES2014'):\n", " model_directory = os.path.join(tide_dir,'fes2014','ocean_tide')\n", " model_files = ['2n2.nc.gz','eps2.nc.gz','j1.nc.gz','k1.nc.gz',\n", " 'k2.nc.gz','l2.nc.gz','la2.nc.gz','m2.nc.gz','m3.nc.gz','m4.nc.gz',\n", " 'm6.nc.gz','m8.nc.gz','mf.nc.gz','mks2.nc.gz','mm.nc.gz',\n", " 'mn4.nc.gz','ms4.nc.gz','msf.nc.gz','msqm.nc.gz','mtm.nc.gz',\n", " 'mu2.nc.gz','n2.nc.gz','n4.nc.gz','nu2.nc.gz','o1.nc.gz','p1.nc.gz',\n", " 'q1.nc.gz','r2.nc.gz','s1.nc.gz','s2.nc.gz','s4.nc.gz','sa.nc.gz',\n", " 'ssa.nc.gz','t2.nc.gz']\n", " c = ['2n2','eps2','j1','k1','k2','l2','lambda2','m2','m3','m4','m6',\n", " 'm8','mf','mks2','mm','mn4','ms4','msf','msqm','mtm','mu2','n2',\n", " 'n4','nu2','o1','p1','q1','r2','s1','s2','s4','sa','ssa','t2']\n", " model_format = 'FES'\n", " TYPE = 'z'\n", " SCALE = 1.0/100.0" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Setup coordinates for calculating tides" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "#-- create an image around Antarctica\n", "xlimits = [-560.*5e3,560.*5e3]\n", "ylimits = [-560.*5e3,560.*5e3]\n", "spacing = [5e3,-5e3]\n", "#-- x and y coordinates\n", "x = np.arange(xlimits[0],xlimits[1]+spacing[0],spacing[0])\n", "y = np.arange(ylimits[1],ylimits[0]+spacing[1],spacing[1])\n", "xgrid,ygrid = np.meshgrid(x,y)\n", "#-- x and y dimensions\n", "nx = np.int((xlimits[1]-xlimits[0])/spacing[0])+1\n", "ny = np.int((ylimits[0]-ylimits[1])/spacing[1])+1\n", "#-- convert image coordinates from polar stereographic to latitude/longitude\n", "crs1 = pyproj.CRS.from_string(\"epsg:{0:d}\".format(3031))\n", "crs2 = pyproj.CRS.from_string(\"epsg:{0:d}\".format(4326))\n", "transformer = pyproj.Transformer.from_crs(crs1, crs2, always_xy=True)\n", "lon,lat = transformer.transform(xgrid.flatten(), ygrid.flatten())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Infer minor amplitudes from the major constituents" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "def infer_minor_amplitudes(zmajor,constituents):\n", " #-- number of constituents\n", " npts,nc = np.shape(zmajor) \n", " cindex = ['q1','o1','p1','k1','n2','m2','s2','k2']\n", " #-- re-order zmajor to correspond to cindex\n", " z8 = np.ma.zeros((npts,8))\n", " ni = 0\n", " for i,c in enumerate(cindex):\n", " j = [j for j,val in enumerate(constituents) if val == c]\n", " if j:\n", " j1, = j\n", " z8[:,i] = zmajor[:,j1]\n", " ni += 1\n", " #-- list of minor constituents\n", " minor = ['2q1','sigma1','rho1','m1','m1','chi1','pi1','phi1','theta1',\n", " 'j1','oo1','2n2','mu2','nu2','lambda2','l2','l2','t2']\n", " #-- only add minor constituents that are not on the list of major values\n", " minor_flag = [m not in constituents for m in minor]\n", " #-- estimate minor constituents\n", " zmin = np.zeros((npts,18))\n", " zmin[:,0] = 0.263*z8[:,0] - 0.0252*z8[:,1]#-- 2Q1\n", " zmin[:,1] = 0.297*z8[:,0] - 0.0264*z8[:,1]#-- sigma1\n", " zmin[:,2] = 0.164*z8[:,0] + 0.0048*z8[:,1]#-- rho1\n", " zmin[:,3] = 0.0140*z8[:,1] + 0.0101*z8[:,3]#-- M1\n", " zmin[:,4] = 0.0389*z8[:,1] + 0.0282*z8[:,3]#-- M1\n", " zmin[:,5] = 0.0064*z8[:,1] + 0.0060*z8[:,3]#-- chi1\n", " zmin[:,6] = 0.0030*z8[:,1] + 0.0171*z8[:,3]#-- pi1\n", " zmin[:,7] = -0.0015*z8[:,1] + 0.0152*z8[:,3]#-- phi1\n", " zmin[:,8] = -0.0065*z8[:,1] + 0.0155*z8[:,3]#-- theta1\n", " zmin[:,9] = -0.0389*z8[:,1] + 0.0836*z8[:,3]#-- J1\n", " zmin[:,10] = -0.0431*z8[:,1] + 0.0613*z8[:,3]#-- OO1\n", " zmin[:,11] = 0.264*z8[:,4] - 0.0253*z8[:,5]#-- 2N2\n", " zmin[:,12] = 0.298*z8[:,4] - 0.0264*z8[:,5]#-- mu2\n", " zmin[:,13] = 0.165*z8[:,4] + 0.00487*z8[:,5]#-- nu2\n", " zmin[:,14] = 0.0040*z8[:,5] + 0.0074*z8[:,6]#-- lambda2\n", " zmin[:,15] = 0.0131*z8[:,5] + 0.0326*z8[:,6]#-- L2\n", " zmin[:,16] = 0.0033*z8[:,5] + 0.0082*z8[:,6]#-- L2\n", " zmin[:,17] = 0.0585*z8[:,6]#-- t2\n", " #-- only add minor constituents that are not major\n", " return np.where(minor_flag, np.abs(zmin), 0.0)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Calculate tide map" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "#-- read tidal constants and interpolate to grid points\n", "if model_format in ('OTIS','ATLAS'):\n", " amp,ph,D,c = extract_tidal_constants(lon, lat, grid_file, model_file,\n", " EPSG, TYPE=TYPE, METHOD='spline', GRID=model_format)\n", "elif (model_format == 'netcdf'):\n", " amp,ph,D,c = extract_netcdf_constants(lon, lat, model_directory,\n", " grid_file, model_files, TYPE=TYPE, METHOD='spline', SCALE=SCALE)\n", "elif (model_format == 'GOT'):\n", " amp,ph = extract_GOT_constants(lon, lat, model_directory, model_files,\n", " METHOD='spline', SCALE=SCALE)\n", "elif (model_format == 'FES'):\n", " amp,ph = extract_FES_constants(lon, lat, model_directory, model_files,\n", " TYPE=TYPE, VERSION=MODEL, METHOD='spline', SCALE=SCALE)\n", " \n", "#-- calculate minor constituent amplitudes\n", "minor_amp = infer_minor_amplitudes(amp,c)\n", "#-- calculate sum of major and minor amplitudes\n", "tide_range = np.sum(amp,axis=1) + np.sum(minor_amp,axis=1)\n", "#-- convert from meters to centimeters\n", "tide_cm = 100.0*np.reshape(tide_range,(ny,nx))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Create plot of tidal range" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#-- plot Antarctic tide range\n", "projection = ccrs.Stereographic(central_longitude=0.0,\n", " central_latitude=-90,true_scale_latitude=-71.0)\n", "fig, ax = plt.subplots(num=1, figsize=(9,8),\n", " subplot_kw=dict(projection=projection))\n", "#-- plot tide height\n", "vmin,vmax = (0, np.max(tide_cm))\n", "extent = (xlimits[0],xlimits[1],ylimits[0],ylimits[1])\n", "im = ax.imshow(tide_cm, interpolation='nearest',\n", " vmin=vmin, vmax=vmax, transform=projection,\n", " extent=extent, origin='upper')\n", "#-- add high resolution cartopy coastlines\n", "ax.coastlines('10m')\n", "\n", "#-- Add colorbar and adjust size\n", "#-- pad = distance from main plot axis\n", "#-- extend = add extension triangles to upper and lower bounds\n", "#-- options: neither, both, min, max\n", "#-- shrink = percent size of colorbar\n", "#-- aspect = lengthXwidth aspect of colorbar\n", "cbar = plt.colorbar(im, ax=ax, pad=0.025, extend='max',\n", " extendfrac=0.0375, shrink=0.85, aspect=22.5, drawedges=False)\n", "#-- rasterized colorbar to remove lines\n", "cbar.solids.set_rasterized(True)\n", "#-- Add label to the colorbar\n", "cbar.ax.set_ylabel('{0} Tide Range'.format(MODEL), fontsize=13)\n", "cbar.ax.set_xlabel('cm', fontsize=13)\n", "cbar.ax.xaxis.set_label_coords(0.50, 1.04)\n", "#-- ticks lines all the way across\n", "cbar.ax.tick_params(which='both', width=1, length=18,\n", " labelsize=13, direction='in')\n", "\n", "#-- set x and y limits\n", "ax.set_xlim(xlimits)\n", "ax.set_ylim(ylimits)\n", "\n", "#-- stronger linewidth on frame\n", "ax.spines['geo'].set_linewidth(2.0)\n", "ax.spines['geo'].set_capstyle('projecting')\n", "#-- adjust subplot within figure\n", "fig.subplots_adjust(left=0.02,right=0.98,bottom=0.05,top=0.98)\n", "#-- show the plot\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.8.5" } }, "nbformat": 4, "nbformat_minor": 4 }