{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n# Seafloor oil spill\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from datetime import timedelta\nfrom opendrift.readers import reader_netCDF_CF_generic\nfrom opendrift.models.openoil import OpenOil\n\no = OpenOil(loglevel=20) # Set loglevel to 0 for debug information\n\n# Norkyst\nreader_norkyst = reader_netCDF_CF_generic.Reader(o.test_data_folder() + '14Jan2016_NorKyst_z_3d/NorKyst-800m_ZDEPTHS_his_00_3Dsubset.nc')\n#reader_norkyst = reader_netCDF_CF_generic.Reader('https://thredds.met.no/thredds/dodsC/sea/norkyst800m/1h/aggregate_be')\n\no.add_reader([reader_norkyst])\no.set_config('environment:fallback:x_wind', 3)\no.set_config('environment:fallback:y_wind', 7)\no.set_config('drift:vertical_mixing', True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Setting the range of droplet sizes for the seafloor release\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "o.set_config('seed:droplet_size_distribution','uniform')\no.set_config('seed:droplet_diameter_min_subsea', 0.0001)\no.set_config('seed:droplet_diameter_max_subsea', 0.0005)\n\n# 'normal' and 'lognormal' distributions can also be specified\n# o.set_config('seed:droplet_size_distribution','lognormal')\n# o.set_config('seed:droplet_diameter_mu',0.001) # 1 mm\n# o.set_config('seed:droplet_diameter_sigma',0.0008) # 0.8 mm" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Seeding some particles\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "time = [reader_norkyst.start_time,\n reader_norkyst.start_time + timedelta(hours=1)]\no.seed_elements(lon=4.5, lat=62.0, z='seafloor', radius=0, number=3000,\n time=time, oil_type='GENERIC DIESEL')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Running model with a small timestep to resolve the boyant rising\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "o.run(duration=timedelta(hours=6), time_step=60, time_step_output=60)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Print and plot results\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "print(o)\n\no.animation_profile(markersize='z', color='z')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "o.animate_vertical_distribution(bins=30, subsamplingstep=5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "o.plot_oil_budget()" ] } ], "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": "3.11.6" } }, "nbformat": 4, "nbformat_minor": 0 }