{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Terra/Aqua MODIS 10 km Aerosol Product"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"```{hint} \n",
"Execute the notebook on the training platform >>\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This module shows the structure of the `MODIS Aerosol Product` and how to use the data files in order to load, browse and visualize the retrieved parameter aerosol optical thickness (AOT).\n",
"\n",
"According to NASA, \"The MODIS Aerosol Product monitors the ambient aerosol optical thickness over the oceans globally and over the continents. Furthermore, the aerosol size distribution is derived over the oceans, and the aerosol type is derived over the continents. 'Fine' aerosols (anthropogenic/pollution) and 'coarse' aerosols (natural particles; e.g., dust) are also derived.\"\n",
"\n",
"\"There are two MODIS Aerosol data product files: MOD04_L2, containing data collected from the Terra platform (2000 onwards); and MYD04_L2, containing data collected from the Aqua platform (2002 onwards). Granule-level (Level 2) data are produced at a horizontal pixel size (at nadir) of 10 km x 10 km. The Dark Target Land and Ocean products are additionally provided at a horizontal pixel size (at nadir) of 3 km x 3 km within the MOD04_3K and MYD04_3K files for Terra and Aqua respectively.\" (Source)\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"```{admonition} Basic facts\n",
"**Spatial resolution**: `10 km x 10 km at nadir`
\n",
"**Spatial coverage**: `Global`
\n",
"**Data availability**: `since 2000`\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"```{admonition} How to access the data\n",
"This notebook uses the MODIS MOD04_L2 dataset from the Terra platform. This data can be ordered via the LAADS DAAC and are distributed in `HDF4-EOS` format, which is based on `HDF4`. You need to register for an Earthdata account in order to be able to download data. \n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"