{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Field sampling tutorial" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The particle trajectories allow us to study fields like temperature, plastic concentration or chlorophyll from a Lagrangian perspective. \n", "\n", "In this tutorial we will go through how particles can sample `Fields`, using temperature as an example. Along the way we will get to know the parcels class `Variable` (see [here](https://oceanparcels.org/gh-pages/html/#parcels.particle.Variable) for the documentation) and some of its methods. This tutorial covers several applications of a sampling setup:\n", "* [**Basic along trajectory sampling**](#Basic-sampling)\n", "* [**Sampling initial conditions**](#Sampling-initial-values)\n", "* [**Sampling initial and along-trajectory values with repeated release**](#Sampling-with-repeatdt)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Basic sampling\n", "We import the `Variable` class as well as the standard modules needed to set up a simulation." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# Modules needed for the Parcels simulation\n", "from parcels import Variable, FieldSet, ParticleSet, JITParticle, AdvectionRK4\n", "import numpy as np\n", "from datetime import timedelta as delta\n", "\n", "# To open and look at the temperature data\n", "import xarray as xr \n", "import matplotlib as mpl\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Suppose we want to study the environmental temperature for plankton drifting around a peninsula. We have a dataset with surface ocean velocities and the corresponding sea surface temperature stored in netcdf files in the folder `\"Peninsula_data\"`. Besides the velocity fields, we load the temperature field using `extra_fields={'T': 'T'}`. The particles are released on the left hand side of the domain." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "