{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "Looking at high-frequency oscillation in nowcast green ssh at Point Atkinson 15 minute files." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import netCDF4 as nc\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import os\n", "import datetime\n", "\n", "from salishsea_tools import nc_tools\n", "\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## A sample nowcast-green output" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [], "source": [ "f = nc.Dataset('/results/SalishSea/nowcast-green/08mar16/PointAtkinson.nc')\n", "\n", "ssh = f.variables['sossheig'][:,0,0]\n", "ts =nc_tools.timestamp(f,np.arange(ssh.shape[0]))\n", "dates = [d.datetime for d in ts]" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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Az2Bhn83svLCPqaODDnLNTBs2+I4kmuzuIb9FfTyEap4mCBE5A9gWTK53I/Ak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\n4AvgbOCcZOdM9k0aY4ypOZ8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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(dates,ssh)\n", "plt.title(dates[0].strftime('%Y-%m-%d'))\n", "plt.ylabel('ssh [m]')" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([-0.17877117, 0.06571084, 0.06571084, 0.32868201, 0.32868201,\n", " 0.59840339, 0.59840339, 0.85108906, 0.85108906, 1.05518746], dtype=float32)" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ssh[-10:]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* Saw-tooth like behaviour and repeated values.\n", "* Could this be because 15 minutes is not divisible by out 40 second time step?" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "### Other NEMO 3.6 output (with 40s timestep)\n", "Tested\n", "* 15 minute output\n", "* 10 minute output\n", "* 20 minute output" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "10 minute output\n", "last 8 ssh: [ -8.49195659e-01 -7.13157475e-01 -5.74840605e-01 -4.34347630e-01\n", " -2.90346920e-01 -1.45057648e-01 8.20399509e-05 1.43809989e-01]\n", "15 minute output\n", "last 8 ssh: [-1.37539923 -1.37539923 -1.01599765 -1.01599765 -0.61179161 -0.61179161\n", " -0.18381555 -0.18381555]\n", "20 minute output\n", "last 8 ssh: [-1.79265356 -1.60702991 -1.40031064 -1.1705935 -0.9154433 -0.64399904\n", " -0.36234728 -0.0724878 ]\n" ] }, { "data": { "text/plain": [ "(735790.0, 735791.0)" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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VqlU59l25ciWjR4/G1dUVCwsLpk+fjr+/P5mZmU99/L59+1K9enXMzc2ZPHky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\nJ7pWVSST8OJIpZpKERER8Str1hxkVccB3PnLVDb16UO2vq3gbw3RukP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uQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "rundir = '/ocean/nsoontie/MEOPAR/SalishSea/results/mixing_paper/holl_jul/'\n", "times = [10,15,20]\n", "fig,ax = plt.subplots(1,1,figsize=(15,5))\n", "for time in times:\n", " f = nc.Dataset(os.path.join(rundir,'PointAtkinson_{}.nc'.format(time)))\n", " ssh = f.variables['sossheig'][:,0,0]\n", " ts =nc_tools.timestamp(f,np.arange(ssh.shape[0]))\n", " dates = [d.datetime for d in ts]\n", " ax.plot(dates, ssh,label ='{} minute output'.format(time) )\n", " ax.legend(loc=0)\n", " ax.set_ylabel('ssh [m]')\n", " print('{} minute output'.format(time))\n", " print('last 8 ssh: ', ssh[-8:])\n", "ax.set_xlim([datetime.datetime(2015,7,11),datetime.datetime(2015,7,12)])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* This saw-tooth behaviour is not present in the 10 minute and 20 minute outputs. So, I think we should switch to 10 minute output in nowcast-green. The behaviors is an artifact of \n", "* Unfortunately, this run went unstable in Boundary Pass at 15 m depth after ~15000 time steps. Using \n", " * 40s timestep\n", " * kappa/mu=10\n", " * background visc= 1e-5\n", " * background diff=1e-6 \n", " * hollingsworth correction\n", " * rn_bfri2 = 2e-3\n", " * ln_loglayer=T\n", " * rn_bfri2_max = 1.e-1\n", " * rn_bfrz0=0.0015\n", " * bathy2\n", " * TS4 tides\n", "\n", "It was in the middle of a spring tides. A run without hollingsworth correction was stable.\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "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": "3.4.4" } }, "nbformat": 4, "nbformat_minor": 0 }