earthaccess_https_download_megacities_los_angeles.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "5c170aac-316d-49b2-9d98-327dfcaf5105",
   "metadata": {},
   "source": [
    "# Bulk Download of Megacities Data by Species\n",
    "\n",
    "### **Summary:**\n",
    "\n",
    "This notebook contains Python code to query and extract metadata and data [**TROPESS CrIS SNPP Megacities** data products](https://daac.gsfc.nasa.gov/datasets?page=3&project=TROPESS&keywords=megacity) from the NASA Earthdata CMR API using the [**earthaccess Python library**](https://github.com/nsidc/earthaccess) for a user-defined date/time range and species type (gas and/or atmospheric parameters) as publicly hosted and managed by **GES DISC**. This notebook utilizes the [**Los Angeles Megacity** Standard Product](https://daac.gsfc.nasa.gov/datasets/TRPSDL2ALLCRSMGLOS_1/summary) for data files from 1 January 2020 to 31 December 2020, which is queried using the DOI (Digital Object Identifier; see cell #5 below). While the notebook can be adjusted for a user-defined start/end date/time and gas species (see cell #6 below), it is intialized using the NH3 (Ammonia) gas species. \n",
    "\n",
    "A .netrc file containing an individual user's **NASA Earthdata Login** credentials (not supplied with this notebook) can either be supplied by the user up-front (in the user's home directory) or created on-demand with an embedded prompt inside this notebook. If preferred to do so manually, below are the steps to creating a .netrc file:\n",
    "\n",
    "  1. Create an **Earthdata Login Account** ([clear here for details](https://urs.earthdata.nasa.gov/users/new)).\n",
    "  2. Approve access to the **NASA GES DISC Archive** in your Earthdata Login Profile ([click here for details](https://disc.gsfc.nasa.gov/earthdata-login)).\n",
    "  3. Create/modify a **.netrc** file in your home directory containing your **Earthdata Login** credentials as shown below:\n",
    "     <br>`machine urs.earthdata.nasa.gov login <your username> password <your password>`\n",
    "\n",
    "\n",
    "**Other important notes:**\n",
    "\n",
    "  1. This code was designed and tested **\"as-is\"** to run in a generic Jupyter Lab/Hub environment.\n",
    "  2. Please **\"trust\"** this notebook before executing; this will prevent errors when writing output to your local directory.\n",
    "  3. Please create a **\"data\"** directory in your local path to store data that is downloaded by this notebook.\n",
    "  4. For ease of managing your computing environment dependencies, an [**environment.yml** file](https://github.com/NASA-TROPESS/tutorials_notebooks/blob/main/environment.yml) is available. \n",
    "\n",
    "### Notebook Author / Affiliation\n",
    "\n",
    "David F. Moroni (david.f.moroni@jpl.nasa.gov) / Jet Propulsion Laboratory, Californa Institute of Technology\n",
    "\n",
    "### Date Authored\n",
    "\n",
    "16 April 2024\n",
    "\n",
    "### Acknowledgements\n",
    "\n",
    "The research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004). Government sponsorship acknowledged."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7dc1ab47-17a1-4c18-a4d9-a140a2c4043c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import earthaccess\n",
    "\n",
    "from earthaccess import Auth, Store, DataCollections, DataGranules\n",
    "auth = Auth()\n",
    "\n",
    "import requests"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c5d5641-a055-4108-b8b5-1b72f18d5fbc",
   "metadata": {},
   "source": [
    "## Verify Successful Authentication\n",
    "### Prompt for NASA Earthdata Login Credentials (if .netrc file doesn't already exist)\n",
    "### A .netrc file will be created if it doesn't already exist."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cfc34eaa-134a-4a48-8a44-76357f5b5c95",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Authenication Valid = True\n"
     ]
    }
   ],
   "source": [
    "auth = earthaccess.login(strategy=\"interactive\", persist=True)\n",
    "\n",
    "auth.login(strategy=\"netrc\")\n",
    "authvalid = auth.authenticated\n",
    "print('Authenication Valid =',authvalid)\n",
    "\n",
    "# The Store() class enables download or access to data and is instantiated with the user's auth instance.\n",
    "store = Store(auth)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ff64244-cf19-4eaa-83ba-102c7071b4dd",
   "metadata": {},
   "source": [
    "## Create a Function for CMR Catalog Requests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0f5511f1-b974-4fc4-9897-d8b26f5ca425",
   "metadata": {},
   "outputs": [],
   "source": [
    "def cmr_request(params):\n",
    "    response = requests.get(url,\n",
    "                        params=params,\n",
    "                        headers={\n",
    "                            'Accept': 'application/json',\n",
    "                        }\n",
    "                       )\n",
    "    return response"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51ee90b6-27f7-4e1c-bf7a-5e4cbab43d00",
   "metadata": {},
   "source": [
    "## Check that the CMR catalog can be accessed\n",
    "\n",
    "If \"200, CMR is accessible\" is returned, the catalog can be accessed!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "421eb4a9-0916-431e-9943-a037ad9e78f6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "200, CMR is accessible\n"
     ]
    }
   ],
   "source": [
    "url = 'https://cmr.earthdata.nasa.gov/search/collections'\n",
    "\n",
    "# Create our request for finding cloud-hosted granules, and check that we can access CMR\n",
    "response = cmr_request({\n",
    "                        'cloud_hosted': 'True',\n",
    "                        'has_granules': 'True'\n",
    "                        })\n",
    "\n",
    "if response.status_code == 200:\n",
    "    print(str(response.status_code) + \", CMR is accessible\")\n",
    "else:\n",
    "    print(str(response.status_code) + \", CMR is not accessible, check for outages\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a5e8372a-de69-4d9d-a5f4-400179f00299",
   "metadata": {},
   "source": [
    "## Query CMR for the dataset shortname using the DOI (digital object identifier)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3db80512-8299-44ea-ad9d-44b1bc32c7a6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "https://cmr.earthdata.nasa.gov/search/collections.json?doi=10.5067/0QPQFIXDET1X\n",
      "Short Name = TRPSDL2ALLCRSMGLOS\n"
     ]
    }
   ],
   "source": [
    "# CMR API base url\n",
    "cmrurl='https://cmr.earthdata.nasa.gov/search/' # define the base url of NASA's CMR API as the variable `cmrurl`\n",
    "doi = '10.5067/0QPQFIXDET1X'                   # TROPESS dataset DOI\n",
    "\n",
    "doisearch = cmrurl + 'collections.json?doi=' + doi\n",
    "print(doisearch)\n",
    "\n",
    "shortname = requests.get(doisearch).json()['feed']['entry'][0]['short_name']\n",
    "print('Short Name = '+shortname)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8d1b296-1fa0-4e91-b492-67f4feb1e973",
   "metadata": {},
   "source": [
    "## Specify input parameters and execute the CMR query for matching granules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "38f49c33-1a8e-4d78-94e1-39f2715cbefc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Granule hits: 366\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[Collection: {'ShortName': 'TRPSDL2ALLCRSMGLOS', 'Version': '1'}\n",
       " Spatial coverage: {'HorizontalSpatialDomain': {'Geometry': {'BoundingRectangles': [{'WestBoundingCoordinate': -120.0, 'EastBoundingCoordinate': -117.0, 'NorthBoundingCoordinate': 36.0, 'SouthBoundingCoordinate': 33.0}]}}}\n",
       " Temporal coverage: {'RangeDateTime': {'BeginningDateTime': '2020-01-01T00:00:00.000Z', 'EndingDateTime': '2020-01-01T23:59:59.000Z'}}\n",
       " Size(MB): 0.32215404510498047\n",
       " Data: ['https://data.gesdisc.earthdata.nasa.gov/data/TROPESS_MegaCities_Standard/TRPSDL2ALLCRSMGLOS.1/2020/TROPESS_CrIS-SNPP_L2_Standard_NH3_20200101_MUSES_R1p12_SC_MGLOS_F0p6.nc']]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Define the start and end date/time (YYYY-MM-DD).\n",
    "start_time = '2020-01-01'\n",
    "end_time = '2020-12-31'\n",
    "\n",
    "# Select Species Type; options include:  TATM, CH4, HDO, H2O, NH3, PAN, O3\n",
    "species = 'NH3'\n",
    "\n",
    "# CMR Query for Data Granules\n",
    "query = DataGranules().granule_name('*'+species+'*').short_name(shortname).temporal(start_time, end_time)\n",
    "\n",
    "# How many granules are located in the query?\n",
    "print(f\"Granule hits: {query.hits()}\")\n",
    "\n",
    "# Extract all available granule metadata from the query; invoking \"-1\" for all avaialble granules.\n",
    "granules = query.get()\n",
    "\n",
    "# Print sample list of granule metadata\n",
    "granules[0:1]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ba1ad1e-961d-4488-af5f-89c199815b9e",
   "metadata": {},
   "source": [
    "## If previous cell produced nonzero Granule hits, execute next cell to download the data files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "49d592b6-1487-4f5f-aa0e-b702ccb59738",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " Getting 366 granules, approx download size: 0.12 GB\n",
      "Accessing cloud dataset using dataset endpoint credentials: https://data.gesdisc.earthdata.nasa.gov/s3credentials\n",
      "Downloaded: data/TROPESS_CrIS-SNPP_L2_Standard_NH3_20200101_MUSES_R1p12_SC_MGLOS_F0p6.nc\n",
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     ]
    }
   ],
   "source": [
    "try:\n",
    "    files = store.get(granules[:], local_path=\"./data\")\n",
    "except Exception as e:\n",
    "    print(f\"Error: {e}, we are probably not using this code in the Amazon cloud. Trying external links...\")\n",
    "    # There is hope, even if we are not in the Amazon cloud we can still get the data\n",
    "    files = store.get(granules[:], access=\"external\", local_path=\"./data\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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