{ "cells": [ { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "# Copernicus Sentinel-5P TROPOMI - Ultraviolet Aerosol Index - Level 2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```{hint} \n", "Execute the notebook on the training platform >>\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The Copernicus [Sentinel-5 Ultraviolet Visible Near-Infrared Shortwave (UVNS) spectrometer](https://sentinels.copernicus.eu/web/sentinel/missions/sentinel-5) enables the measurement of trace gases which will improve air quality forecasts produced by the Copernicus Atmosphere Monitoring service.\n", "\n", "This notebook provides you an introduction to data from [Sentinel-5P](https://sentinels.copernicus.eu/web/sentinel/missions/sentinel-5p), the precursor instrument and proxy for data from [Sentinel-5](https://www.eumetsat.int/sentinel-5). Sentinel-5P data can be downloaded from the [Sentinel-5P Pre-Operations Data Hub](https://s5phub.copernicus.eu/dhus/#/home).\n", "\n", "The event featured is the [August Complex fire](https://www.fire.ca.gov/incidents/2020/8/16/august-complex-includes-doe-fire/) in California, USA in 2020. This was the largest wildfire in CA history, spreading over 1,000,000 acres (over 4,000 sq km). The image shown in this notebook is taken from 11 September 2020." ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "For monitoring smoke, the `TROPOMI UV Aerosol Index (UVAI)` data can be used. Positive values of UVAI (typically > about 1.0) indicate the presence of absorbing-type aerosols: \n", "- `smoke from forest fires`, \n", "- `volcanic ash`, or \n", "- `desert dust`. \n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```{admonition} Basic Facts\n", "**Spatial resolution**: `Up to 5.5* km x 3.5 km` (5.5 km in the satellite flight direction and 3.5 km in the perpendicular direction at nadir)
\n", "**Spatial coverage**: `Global`
\n", "**Revisit time**: `less than one day`
\n", "**Data availability**: `since April 2018`\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```{admonition} How to access the data\n", "Sentinel-5P Pre-Ops data are disseminated in the `netCDF` format and can be downloaded via the Copernicus Open Access Hub. You need to register for an account before downloading data. \n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Load required libraries**" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import os\n", "import xarray as xr\n", "from datetime import datetime\n", "import numpy as np\n", "from netCDF4 import Dataset\n", "import pandas as pd\n", "\n", "# Python libraries for visualization\n", "import matplotlib.pyplot as plt\n", "import matplotlib.colors\n", "import matplotlib.cm as cm\n", "from matplotlib.axes import Axes\n", "import cartopy\n", "import cartopy.crs as ccrs\n", "from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER\n", "from cartopy.mpl.geoaxes import GeoAxes\n", "GeoAxes._pcolormesh_patched = Axes.pcolormesh\n", "from skimage import exposure\n", "\n", "import warnings\n", "warnings.filterwarnings('ignore')\n", "warnings.simplefilter(action = \"ignore\", category = RuntimeWarning)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Load helper functions**" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "%run ../functions.ipynb" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Load and browse Sentinel-5P TROPOMI Aerosol Index Level 2 data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A Sentinel-5P TROPOMI Aerosol Index Level 2 file is organised in two groups: `PRODUCT` and `METADATA`. The `PRODUCT` group stores the main data fields of the product, including `latitude`, `longitude` and the variable itself. The `METADATA` group provides additional metadata items.\n", "\n", "Sentinel-5P TROPOMI variables have the following dimensions:\n", "* `scanline`: the number of measurements in the granule / along-track dimension index\n", "* `ground_pixel`: the number of spectra in a measurement / across-track dimension index\n", "* `time`: time reference for the data\n", "* `corner`: pixel corner index\n", "\n", "Sentinel-5P TROPOMI data is disseminated in `netCDF`. You can load several `netCDF` files with the `open_mfdataset()` function of the xarray library. In order to load the variable as part of a Sentinel-5P data files, you have to specify the following keyword arguments: \n", "- `concat_dim='scanline'`: to concatenate the dimensions along the scanline\n", "- `combine='nested'`: to combine the data of an n-dimensionsional array into one by using a succession of concatenate and merge operations along each dimension of the grid.\n", "- `group='PRODUCT'`: to load the `PRODUCT` group" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can load all the datasets available for one day into one xarray object by using `scanline` as concatanation dimension." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
<xarray.Dataset>\n",
       "Dimensions:                          (scanline: 12079, ground_pixel: 450, time: 1, corner: 4)\n",
       "Coordinates:\n",
       "  * scanline                         (scanline) float64 0.0 1.0 ... 3.734e+03\n",
       "  * ground_pixel                     (ground_pixel) float64 0.0 1.0 ... 449.0\n",
       "  * time                             (time) datetime64[ns] 2020-09-11\n",
       "  * corner                           (corner) float64 0.0 1.0 2.0 3.0\n",
       "    latitude                         (time, scanline, ground_pixel) float32 dask.array<chunksize=(1, 4172, 450), meta=np.ndarray>\n",
       "    longitude                        (time, scanline, ground_pixel) float32 dask.array<chunksize=(1, 4172, 450), meta=np.ndarray>\n",
       "Data variables:\n",
       "    delta_time                       (time, scanline) datetime64[ns] dask.array<chunksize=(1, 4172), meta=np.ndarray>\n",
       "    time_utc                         (time, scanline) object dask.array<chunksize=(1, 4172), meta=np.ndarray>\n",
       "    qa_value                         (time, scanline, ground_pixel) float32 dask.array<chunksize=(1, 4172, 450), meta=np.ndarray>\n",
       "    aerosol_index_354_388            (time, scanline, ground_pixel) float32 dask.array<chunksize=(1, 4172, 450), meta=np.ndarray>\n",
       "    aerosol_index_340_380            (time, scanline, ground_pixel) float32 dask.array<chunksize=(1, 4172, 450), meta=np.ndarray>\n",
       "    aerosol_index_354_388_precision  (time, scanline, ground_pixel) float32 dask.array<chunksize=(1, 4172, 450), meta=np.ndarray>\n",
       "    aerosol_index_340_380_precision  (time, scanline, ground_pixel) float32 dask.array<chunksize=(1, 4172, 450), meta=np.ndarray>
" ], "text/plain": [ "\n", "Dimensions: (scanline: 12079, ground_pixel: 450, time: 1, corner: 4)\n", "Coordinates:\n", " * scanline (scanline) float64 0.0 1.0 ... 3.734e+03\n", " * ground_pixel (ground_pixel) float64 0.0 1.0 ... 449.0\n", " * time (time) datetime64[ns] 2020-09-11\n", " * corner (corner) float64 0.0 1.0 2.0 3.0\n", " latitude (time, scanline, ground_pixel) float32 dask.array\n", " longitude (time, scanline, ground_pixel) float32 dask.array\n", "Data variables:\n", " delta_time (time, scanline) datetime64[ns] dask.array\n", " time_utc (time, scanline) object dask.array\n", " qa_value (time, scanline, ground_pixel) float32 dask.array\n", " aerosol_index_354_388 (time, scanline, ground_pixel) float32 dask.array\n", " aerosol_index_340_380 (time, scanline, ground_pixel) float32 dask.array\n", " aerosol_index_354_388_precision (time, scanline, ground_pixel) float32 dask.array\n", " aerosol_index_340_380_precision (time, scanline, ground_pixel) float32 dask.array" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "s5p_mf = xr.open_mfdataset('../data/sentinel-5p/uvai/2020/09/11/*.nc', concat_dim='scanline', combine='nested', group='PRODUCT')\n", "s5p_mf\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You see that the loaded data object contains of four dimensions and seven data variables:\n", "* **Dimensions**:\n", " * `scanline` \n", " * `ground_pixel`\n", " * `time`\n", " * `corner`\n", "\n", "\n", "* **Data variables**:\n", " * `delta_time`: the offset of individual measurements within the granule, given in milliseconds\n", " * `time_utc`: valid time stamp of the data\n", " * `qa_value`: quality descriptor, varying between 0 (nodata) and 1 (full quality data).\n", " * `aerosol_index_354_388`: Aerosol index from 354 and 388 nm\n", " * `aerosol_index_340_380`: Aerosol index from 340 and 380 nm\n", " * `aerosol_index_354_388_precision`: Precision of aerosol index from 354 and 388 nm\n", " * `aerosol_index_340_380_precision`: Precision of aerosol index from 340 and 380 nm" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Retrieve the variable 'Aerosol index from 340 and 380 nm' as xarray.DataArray" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can specify one variable of interest by putting the name of the variable into square brackets `[]` and get more detailed information about the variable. E.g. `aerosol_index_340_380` is the 'Aerosol index from 340 and 380 nm' and has three dimensions, `time`, `scanline` and `ground_pixel` respectively." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
<xarray.DataArray 'aerosol_index_340_380' (scanline: 12079, ground_pixel: 450)>\n",
       "dask.array<getitem, shape=(12079, 450), dtype=float32, chunksize=(4172, 450), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * scanline      (scanline) float64 0.0 1.0 2.0 ... 3.733e+03 3.734e+03\n",
       "  * ground_pixel  (ground_pixel) float64 0.0 1.0 2.0 3.0 ... 447.0 448.0 449.0\n",
       "    time          datetime64[ns] 2020-09-11\n",
       "    latitude      (scanline, ground_pixel) float32 dask.array<chunksize=(4172, 450), meta=np.ndarray>\n",
       "    longitude     (scanline, ground_pixel) float32 dask.array<chunksize=(4172, 450), meta=np.ndarray>\n",
       "Attributes:\n",
       "    units:                   1\n",
       "    proposed_standard_name:  ultraviolet_aerosol_index\n",
       "    comment:                 Aerosol index from 380 and 340 nm\n",
       "    long_name:               Aerosol index from 380 and 340 nm\n",
       "    radiation_wavelength:    [340. 380.]\n",
       "    ancillary_variables:     aerosol_index_340_380_precision
" ], "text/plain": [ "\n", "dask.array\n", "Coordinates:\n", " * scanline (scanline) float64 0.0 1.0 2.0 ... 3.733e+03 3.734e+03\n", " * ground_pixel (ground_pixel) float64 0.0 1.0 2.0 3.0 ... 447.0 448.0 449.0\n", " time datetime64[ns] 2020-09-11\n", " latitude (scanline, ground_pixel) float32 dask.array\n", " longitude (scanline, ground_pixel) float32 dask.array\n", "Attributes:\n", " units: 1\n", " proposed_standard_name: ultraviolet_aerosol_index\n", " comment: Aerosol index from 380 and 340 nm\n", " long_name: Aerosol index from 380 and 340 nm\n", " radiation_wavelength: [340. 380.]\n", " ancillary_variables: aerosol_index_340_380_precision" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "uvai = s5p_mf.aerosol_index_340_380[0,:,:]\n", "uvai" ] }, { "cell_type": "markdown", "metadata": { "Collapsed": "false" }, "source": [ "## Create a geographical subset for California, USA" ] }, { "cell_type": "markdown", "metadata": { "Collapsed": "false" }, "source": [ "You can zoom into a region by specifying a `bounding box` of interest. Let us set the extent to California with the following bounding box information:" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "latmin=10.\n", "latmax=80.\n", "lonmin=-170.\n", "lonmax=-80." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now, let us apply the function [](functions:generate_geographical_subset) to subset the `uvai` xarray.DataArray. Let us call the new `xarray.DataArray` `uvai`." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
<xarray.DataArray 'aerosol_index_340_380' (scanline: 4550, ground_pixel: 450)>\n",
       "dask.array<where, shape=(4550, 450), dtype=float32, chunksize=(1582, 450), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * scanline      (scanline) float64 2.101e+03 2.102e+03 ... 3.559e+03 3.56e+03\n",
       "  * ground_pixel  (ground_pixel) float64 0.0 1.0 2.0 3.0 ... 447.0 448.0 449.0\n",
       "    time          datetime64[ns] 2020-09-11\n",
       "    latitude      (scanline, ground_pixel) float32 dask.array<chunksize=(1582, 450), meta=np.ndarray>\n",
       "    longitude     (scanline, ground_pixel) float32 dask.array<chunksize=(1582, 450), meta=np.ndarray>\n",
       "Attributes:\n",
       "    units:                   1\n",
       "    proposed_standard_name:  ultraviolet_aerosol_index\n",
       "    comment:                 Aerosol index from 380 and 340 nm\n",
       "    long_name:               Aerosol index from 380 and 340 nm\n",
       "    radiation_wavelength:    [340. 380.]\n",
       "    ancillary_variables:     aerosol_index_340_380_precision
" ], "text/plain": [ "\n", "dask.array\n", "Coordinates:\n", " * scanline (scanline) float64 2.101e+03 2.102e+03 ... 3.559e+03 3.56e+03\n", " * ground_pixel (ground_pixel) float64 0.0 1.0 2.0 3.0 ... 447.0 448.0 449.0\n", " time datetime64[ns] 2020-09-11\n", " latitude (scanline, ground_pixel) float32 dask.array\n", " longitude (scanline, ground_pixel) float32 dask.array\n", "Attributes:\n", " units: 1\n", " proposed_standard_name: ultraviolet_aerosol_index\n", " comment: Aerosol index from 380 and 340 nm\n", " long_name: Aerosol index from 380 and 340 nm\n", " radiation_wavelength: [340. 380.]\n", " ancillary_variables: aerosol_index_340_380_precision" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "uvai_subset = generate_geographical_subset(xarray=uvai, \n", " latmin=latmin, \n", " latmax=latmax, \n", " lonmin=lonmin, \n", " lonmax=lonmax)\n", "uvai_subset" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can extract the latitude and longitude information from the subsetted data and save them into new variables for plotting later." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "lat = uvai_subset.latitude\n", "lon = uvai_subset.longitude\n" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "## Visualize Sentinel-5P TROPOMI 'Aerosol Index from 340 and 350 nm'" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The next step is to visualize the dataset. You can use the function [](functions:visualize_pcolormesh), which makes use of matploblib's function `pcolormesh` and the [Cartopy](https://scitools.org.uk/cartopy/docs/latest/) library.\n", "\n", "With `?visualize_pcolormesh` you can open the function's docstring to see what keyword arguments are needed to prepare your plot." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "\u001b[0;31mSignature:\u001b[0m\n", "\u001b[0mvisualize_pcolormesh\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0mdata_array\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0mlongitude\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0mlatitude\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0mprojection\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0mcolor_scale\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0munit\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0mlong_name\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0mvmin\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0mvmax\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0mset_global\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0mlonmin\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m180\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0mlonmax\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m180\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0mlatmin\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m90\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0mlatmax\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m90\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", "\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;31mDocstring:\u001b[0m\n", "Visualizes a xarray.DataArray with matplotlib's pcolormesh function.\n", "\n", "Parameters:\n", " data_array(xarray.DataArray): xarray.DataArray holding the data values\n", " longitude(xarray.DataArray): xarray.DataArray holding the longitude values\n", " latitude(xarray.DataArray): xarray.DataArray holding the latitude values\n", " projection(str): a projection provided by the cartopy library, e.g. ccrs.PlateCarree()\n", " color_scale(str): string taken from matplotlib's color ramp reference\n", " unit(str): the unit of the parameter, taken from the NetCDF file if possible\n", " long_name(str): long name of the parameter, taken from the NetCDF file if possible\n", " vmin(int): minimum number on visualisation legend\n", " vmax(int): maximum number on visualisation legend\n", " set_global(boolean): optional kwarg, default is True\n", " lonmin,lonmax,latmin,latmax(float): optional kwarg, set geographic extent is set_global kwarg is set to \n", " False\n", "\u001b[0;31mFile:\u001b[0m /tmp/ipykernel_51/1857473499.py\n", "\u001b[0;31mType:\u001b[0m function\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "?visualize_pcolormesh" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(
,\n", " )" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "visualize_pcolormesh(data_array=uvai_subset,\n", " longitude=lon, \n", " latitude=lat, \n", " projection=ccrs.PlateCarree(), \n", " color_scale='afmhot_r', \n", " unit=uvai.units, \n", " long_name=uvai.long_name + ' - ' + str(uvai.time.data)[0:10], \n", " vmin=0, \n", " vmax=15, \n", " lonmin=lonmin, \n", " lonmax=lonmax, \n", " latmin=latmin, \n", " latmax=latmax, \n", " set_global=False)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### References\n", "\n", "* Copernicus Sentinel data 2020\n", "\n", "* Some code in this notebook was adapted from the following sources:\n", " * origin: https://gitlab.eumetsat.int/eumetlab/atmosphere/atmosphere/-/blob/master/20_data_exploration/242_Sentinel-5P_TROPOMI_UVAI_L2_load_browse.ipynb\n", " * copyright: 2022, EUMETSAT\n", " * license: MIT\n", " * retrieved: 2022-06-28 by Sabrina Szeto" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "```{admonition} Return to the case study\n", "Monitoring smoke transport with next-generation satellites from Metop-SG: Californian Wildfires Case Study
\n", "[](ca_part2_fig2)\n", "```" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.9.12" } }, "nbformat": 4, "nbformat_minor": 4 }