Updated-minimize-time-to-science.ipynb

{
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  {
   "cell_type": "markdown",
   "id": "98c63a35-00eb-4bad-99cc-724d1eeab986",
   "metadata": {},
   "source": [
    "# TRT KPI: Minimize Time to Science\n",
    "### IN PROGRESS: Updated in PI 22.2 (Spring 2022) \n",
    "\n",
    "The following KPIs are measured in this notebook:\n",
    "\n",
    "* Number of lines of code for a given workflow in the cloud / Number of lines for same workflow on-prem\n",
    "* Run time for a given workflow in the cloud / run time for same workflow on-prem\n",
    "\n",
    "#### Workflows: \n",
    "* Basic data search, customize, access, plotting, with a collection that is available on-prem and in Earthdata Cloud.\n",
    "\n",
    "* Data tested (updated in PI 22.2):\n",
    "    * Using Cloud Metrics to select popular service combination:\n",
    "        * Synchronous, L2SS, NetCDF, Spatial & variable request\n",
    "            * Can we filter by non-admin and by collection requested?\n",
    "    * Working off of [Openscapes OPeNDAP tutorial](https://nasa-openscapes.github.io/2021-Cloud-Hackathon/tutorials/06_S6_OPeNDAP_Access_Gridding.html)\n",
    "    * Switching from UAT to PROD examples\n",
    "\n",
    "```\n",
    "ShortName = 'JASON_CS_S6A_L2_ALT_LR_RED_OST_NRT_F'\n",
    "concept_id = 'C1968980576-POCLOUD'\n",
    "```\n",
    "\n",
    "* On Prem subsetting:\n",
    "    * [PO.DAAC python script: Subset L1/L2 using OPeNDAP](https://podaac-tools.jpl.nasa.gov/drive/files/common/sw/subsetting/subset_dataset_l2.py)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "abebc153-6a9a-4af0-bd62-6b665c25f148",
   "metadata": {},
   "source": [
    "## Import Packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9c94c173-8a36-496f-95a4-30d6635ef786",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "#cloud workflow\n",
    "import requests\n",
    "from pprint import pprint\n",
    "from harmony import BBox, Client, Collection, Request, LinkType\n",
    "from harmony.config import Environment\n",
    "import datetime as dt\n",
    "from pystac import Catalog\n",
    "from pystac_client import Client\n",
    "import s3fs\n",
    "import xarray as xr"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e471f9db-ce34-49ca-82fb-744077d2f2b4",
   "metadata": {},
   "source": [
    "## On-prem Workflow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5eeb1492-6539-4563-a169-56f2fa75ddd3",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c6cb7b96-ea76-421c-b98d-699b47dc9ef7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "a0591866-7ec5-408b-9ad9-8b7f45ff0762",
   "metadata": {},
   "source": [
    "## Cloud Workflow"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1102fdc4-a151-47af-9bd2-7c57203f0cdb",
   "metadata": {},
   "source": [
    "### 1. Determine subsetting service options"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a138c27-e876-46f7-8e18-5234df9f38a7",
   "metadata": {
    "tags": []
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   "source": [
    "#### Steps Involved (NEED TO UPDATE):\n",
    "\n",
    "* Add step to identify collection of interest\n",
    "\n",
    "```\n",
    "Here we are jumping ahead and already know the `concept_id` we are interested in, by browsing cloud-hosted datasets from PO.DAAC in Earthdata Search: https://search.earthdata.nasa.gov/portal/podaac-cloud/search. \n",
    "\n",
    "((Non-Code) Determine precise data product short name (perhaps already known by users)\n",
    "1. Set data product short name in code)\n",
    "\n",
    "(##### Alternative for 12-17\n",
    "\n",
    "10. (Non-Code) Go to Earthdata Search\n",
    "1. (Non-Code) Search for data product short name or similar\n",
    "1. (Non-Code) Select correct collection, revealing CMR Concept ID\n",
    "1. Copy/paste the CMR Concept ID into code)\n",
    "\n",
    "We are going to focus on `MODIS_A-JPL-L2P-v2019.0`: GHRSST Level 2P Global Sea Surface Skin Temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Aqua satellite (GDS2). Let's first save this as a variable that we can use later on once we request data from Harmony.\n",
    "\n",
    "We will view the top-level metadata for this collection to see what additional service and variable metadata exist.\n",
    "\n",
    "We need to isolate the services returned for this dataset:\n",
    "\n",
    "Inspect the first service returned. Now we're going to search the services endpoint to view that individual service's metadata, like we did with our dataset above. This time, we're explicitly setting the format of the response to umm-json in the Accept Header in order to see detailed metadata about the service.\n",
    "\n",
    "```\n",
    "\n",
    "1. Set the token as a request parameter\n",
    "1. Set desired CMR output format for collections (using the default requires more steps to get at the desired information)\n",
    "1. Perform CMR collection search using the collection-related search fields\n",
    "1. Parse the search result\n",
    "1. Retrieve collection from the search result\n",
    "1. Retrieve associated service IDs from the collection\n",
    "1. Set desired (different) output format for services\n",
    "1. Format a query to fetch the service for each service ID (why isn't this a link relation?)\n",
    "1. Perform CMR service search for each each service ID\n",
    "1. Parse the search result\n",
    "1. Retrieve service from the search result\n",
    "1. Retrieve associated service options from the service\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6ebda40d-f036-4a6c-86d9-c3752bb23cbb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 2 µs, sys: 0 ns, total: 2 µs\n",
      "Wall time: 4.77 µs\n",
      "['S1962070864-POCLOUD', 'S2004184019-POCLOUD', 'S2153799015-POCLOUD', 'S2227193226-POCLOUD']\n",
      "{'hits': 1,\n",
      " 'items': [{'meta': {'concept-id': 'S1962070864-POCLOUD',\n",
      "                     'concept-type': 'service',\n",
      "                     'deleted': False,\n",
      "                     'format': 'application/vnd.nasa.cmr.umm+json',\n",
      "                     'native-id': 'POCLOUD_podaac_l2_cloud_subsetter',\n",
      "                     'provider-id': 'POCLOUD',\n",
      "                     'revision-date': '2022-05-31T23:46:37.054Z',\n",
      "                     'revision-id': 25,\n",
      "                     'user-id': 'chen5510'},\n",
      "            'umm': {'AccessConstraints': 'None',\n",
      "                    'Description': 'Endpoint for subsetting L2 Subsetter via '\n",
      "                                   'Harmony',\n",
      "                    'LongName': 'PODAAC Level 2 Cloud Subsetter',\n",
      "                    'MetadataSpecification': {'Name': 'UMM-S',\n",
      "                                              'URL': 'https://cdn.earthdata.nasa.gov/umm/service/v1.5.0',\n",
      "                                              'Version': '1.5.0'},\n",
      "                    'Name': 'PODAAC L2 Cloud Subsetter',\n",
      "                    'OperationMetadata': [{'OperationName': 'SPATIAL_SUBSETTING'},\n",
      "                                          {'OperationName': 'VARIABLE_SUBSETTING'},\n",
      "                                          {'OperationName': 'TEMPORAL_SUBSETTING'}],\n",
      "                    'ServiceKeywords': [{'ServiceCategory': 'EARTH SCIENCE '\n",
      "                                                            'SERVICES',\n",
      "                                         'ServiceTerm': 'SUBSETTING/SUPERSETTING',\n",
      "                                         'ServiceTopic': 'DATA MANAGEMENT/DATA '\n",
      "                                                         'HANDLING'}],\n",
      "                    'ServiceOptions': {'Subset': {'SpatialSubset': {'BoundingBox': {'AllowMultipleValues': False},\n",
      "                                                                    'Shapefile': [{'Format': 'ESRI'},\n",
      "                                                                                  {'Format': 'KML'},\n",
      "                                                                                  {'Format': 'GeoJSON'}]},\n",
      "                                                  'TemporalSubset': {'AllowMultipleValues': False},\n",
      "                                                  'VariableSubset': {'AllowMultipleValues': True}},\n",
      "                                       'SupportedReformattings': [{'SupportedInputFormat': 'HDF5',\n",
      "                                                                   'SupportedOutputFormats': ['NETCDF-4']},\n",
      "                                                                  {'SupportedInputFormat': 'NETCDF-4',\n",
      "                                                                   'SupportedOutputFormats': ['NETCDF-4']}]},\n",
      "                    'ServiceOrganizations': [{'LongName': 'Physical '\n",
      "                                                          'Oceanography '\n",
      "                                                          'Distributed Active '\n",
      "                                                          'Archive Center, Jet '\n",
      "                                                          'Propulsion '\n",
      "                                                          'Laboratory, NASA',\n",
      "                                              'Roles': ['ORIGINATOR'],\n",
      "                                              'ShortName': 'NASA/JPL/PODAAC'}],\n",
      "                    'Type': 'Harmony',\n",
      "                    'URL': {'Description': 'PROJECT HOME PAGE',\n",
      "                            'URLValue': 'https://harmony.earthdata.nasa.gov'},\n",
      "                    'Version': '1.5.0'}}],\n",
      " 'took': 21}\n"
     ]
    }
   ],
   "source": [
    "%time \n",
    "\n",
    "url = 'https://cmr.earthdata.nasa.gov/search'\n",
    "collection_url = f'{url}/{\"collections\"}'\n",
    "\n",
    "short_name= 'MODIS_A-JPL-L2P-v2019.0'\n",
    "concept_id = 'C1940473819-POCLOUD'\n",
    "\n",
    "response = requests.get(collection_url, \n",
    "                        params={\n",
    "                            'concept_id': concept_id,\n",
    "                            },\n",
    "                        headers={\n",
    "                            'Accept': 'application/json'\n",
    "                            }\n",
    "                       )\n",
    "response = response.json()\n",
    "# pprint(response)\n",
    "\n",
    "services = response['feed']['entry'][0]['associations']['services']\n",
    "print(services)\n",
    "\n",
    "service_url = \"https://cmr.earthdata.nasa.gov/search/services\"\n",
    "\n",
    "service_response = requests.get(service_url, \n",
    "                        params={\n",
    "                            'concept_id': services[0],\n",
    "                            },\n",
    "                        headers={\n",
    "                            'Accept': 'application/vnd.nasa.cmr.umm_results+json'\n",
    "                            }\n",
    "                       )\n",
    "service_response = service_response.json()\n",
    "pprint(service_response)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a50d29ed-fedc-4728-9d2a-83c346a3a102",
   "metadata": {},
   "source": [
    "### 2. Determine variables for collection of interest"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9949fc2e-3338-424a-a7de-aff393938180",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Steps Involved (NEED TO UPDATE):\n",
    "\n",
    "```\n",
    "Several variable records are returned. Again, like we did for services, we'll search the variables endpoint to view an individual variable's metadata, and we'll print out the list of variables for our dataset. \n",
    "\n",
    "Next, print out a simple list of all associated variable names by looping the same variable response we submitted above, this time for each variable:\n",
    "```\n",
    "\n",
    "34. Retrieve associated variable IDs from the collection\n",
    "1. Set desired (different) output format for variables\n",
    "1. Format a query to fetch the service for each variable ID (why isn't this a link relation?)\n",
    "1. Perform CMR variable search for each variable ID\n",
    "1. Parse the search result\n",
    "1. Retrieve variable from the search result\n",
    "1. Retrieve variable names from the variable\n",
    "\n",
    "##### Notes\n",
    "* Assumes we could reuse the already-searched and parsed collection record from service lookup step with refactoring\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "000c1c91-a5b6-4cc7-8185-5d4537e4fd94",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1 µs, sys: 1 µs, total: 2 µs\n",
      "Wall time: 4.53 µs\n",
      "['V1997812737-POCLOUD', 'V1997812697-POCLOUD', 'V2112014688-POCLOUD', 'V1997812756-POCLOUD', 'V1997812688-POCLOUD', 'V1997812670-POCLOUD', 'V1997812724-POCLOUD', 'V2112014684-POCLOUD', 'V1997812701-POCLOUD', 'V1997812681-POCLOUD', 'V2112014686-POCLOUD', 'V1997812663-POCLOUD', 'V1997812676-POCLOUD', 'V1997812744-POCLOUD', 'V1997812714-POCLOUD']\n",
      "['sses_standard_deviation_4um',\n",
      " 'l2p_flags',\n",
      " 'time',\n",
      " 'dt_analysis',\n",
      " 'sses_standard_deviation',\n",
      " 'sst_dtime',\n",
      " 'sses_bias_4um',\n",
      " 'lat',\n",
      " 'sea_surface_temperature_4um',\n",
      " 'sses_bias',\n",
      " 'lon',\n",
      " 'sea_surface_temperature',\n",
      " 'quality_level',\n",
      " 'wind_speed',\n",
      " 'quality_level_4um']\n"
     ]
    }
   ],
   "source": [
    "%time \n",
    "\n",
    "variables = response['feed']['entry'][0]['associations']['variables']\n",
    "print(variables)\n",
    "\n",
    "var_url = \"https://cmr.earthdata.nasa.gov/search/variables\"\n",
    "var_response = requests.get(var_url, \n",
    "                        params={\n",
    "                            'concept_id': variables[0],\n",
    "                            },\n",
    "                        headers={\n",
    "                            'Accept': 'application/vnd.nasa.cmr.umm_results+json'\n",
    "                            }\n",
    "                       )\n",
    "var_response = var_response.json()\n",
    "#pprint(var_response)\n",
    "\n",
    "var_list = []\n",
    "for i in range(len(variables)):\n",
    "    var_response = requests.get(var_url, \n",
    "                            params={\n",
    "                                'concept_id': variables[i],\n",
    "                                },\n",
    "                            headers={\n",
    "                                'Accept': 'application/vnd.nasa.cmr.umm_results+json'\n",
    "                                }\n",
    "                           )\n",
    "    var_response = var_response.json()\n",
    "    var_list.append(var_response['items'][0]['umm']['Name'])\n",
    "\n",
    "pprint(var_list)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fb49e7a-176f-49b8-8548-783aa0b79914",
   "metadata": {},
   "source": [
    "### 3. Request variable subset\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18151715-0024-4e9b-b19d-56aa45949ce9",
   "metadata": {},
   "source": [
    "#### Steps Involved (NEED TO UPDATE):\n",
    "\n",
    "'''\n",
    "We can check on the progress of a processing job with status(). This method blocks while communicating with the server but returns quickly.\n",
    "\n",
    "Depending on the size of the request, it may be helpful to wait until the request has completed processing before the remainder of the code is executed. The wait_for_processing() method will block subsequent lines of code while optionally showing a progress bar.\n",
    "'''\n",
    "\n",
    "41. Create Harmony client with previously obtained auth (or set up / use .netrc)\n",
    "1. Construct Harmony request object using desired spatial / temporal / variables\n",
    "1. Submit the Harmony request, obtaining a Job ID"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d63e7531-98c3-4fe8-a6e1-a0de83899e9a",
   "metadata": {},
   "source": [
    "### 2. Declare time and bounding box search parameters\n",
    "\n",
    "_Using a bounding box that will cover granules supported in on-prem OPeNDAP and L2SS_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7e04f6da-8512-4c38-8d6f-3a13adde6dfa",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 2 µs, sys: 0 ns, total: 2 µs\n",
      "Wall time: 4.53 µs\n",
      "344da0d9-fb81-47ba-bcee-202e52467fa8\n"
     ]
    }
   ],
   "source": [
    "%time\n",
    "\n",
    "from harmony import BBox, Client, Collection, Request, LinkType\n",
    "\n",
    "harmony_client = Client()\n",
    "\n",
    "request = Request(\n",
    "    collection=Collection(id=short_name),\n",
    "    spatial=BBox(-97.77667,21.20806,-83.05197,30.16605),\n",
    "    temporal={\n",
    "        'start': dt.datetime(2021, 8, 20),\n",
    "        'stop': dt.datetime(2021, 8, 21),\n",
    "    },\n",
    ")\n",
    "\n",
    "job_id = harmony_client.submit(request)\n",
    "print(job_id)\n",
    "\n",
    "harmony_client.status(job_id)\n",
    "\n",
    "harmony_client.wait_for_processing(job_id, show_progress=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2c6a4713-f4da-48e9-aa0e-8ff411a4c1d5",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " [ Processing: 100% ] |###################################################| [|]\n"
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "8c54a75b-764b-486c-ab8b-dd86db3a7e4d",
   "metadata": {},
   "source": [
    "### 4. Retrieve AWS Credentials"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27698225-4569-4df4-9b8b-829c69834bcf",
   "metadata": {},
   "source": [
    "#### Steps Involved (NEED TO UPDATE):\n",
    "\n",
    "44. Obtain AWS Credentials for in-region use"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "varied-finger",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3 µs, sys: 0 ns, total: 3 µs\n",
      "Wall time: 5.01 µs\n"
     ]
    }
   ],
   "source": [
    "%time\n",
    "\n",
    "creds = harmony_client.aws_credentials()\n",
    "# print(creds)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47190d57-bfa8-40d5-acec-3f394968151a",
   "metadata": {},
   "source": [
    "### 5. Read in Data using xarray"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "310cda91-470b-4fcb-ae24-490ec8af5b9d",
   "metadata": {},
   "source": [
    "#### Steps Involved (NEED TO UPDATE):\n",
    "\n",
    "45. Retrieve s3 URLs returned from Harmony\n",
    "1. Create a file system using `s3fs` in order to read into `xarray`\n",
    "1. Open the file system using h5py\n",
    "1. Create xarray dataset from selected variables of interest in h5py object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9aeace95-acf2-499e-84e9-008ce4123da8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 2 µs, sys: 1 µs, total: 3 µs\n",
      "Wall time: 5.01 µs\n",
      "['s3://harmony-prod-staging/public/podaac/l2-subsetter/8289859e-a4a7-4a3e-bbee-8758ec5462f5/20210820203501-JPL-L2P_GHRSST-SSTskin-MODIS_A-D-v02.0-fv01.0_subsetted.nc4',\n",
      " 's3://harmony-prod-staging/public/podaac/l2-subsetter/8289859e-a4a7-4a3e-bbee-8758ec5462f5/20210820190001-JPL-L2P_GHRSST-SSTskin-MODIS_A-D-v02.0-fv01.0_subsetted.nc4',\n",
      " 's3://harmony-prod-staging/public/podaac/l2-subsetter/8289859e-a4a7-4a3e-bbee-8758ec5462f5/20210820185501-JPL-L2P_GHRSST-SSTskin-MODIS_A-D-v02.0-fv01.0_subsetted.nc4',\n",
      " 's3://harmony-prod-staging/public/podaac/l2-subsetter/8289859e-a4a7-4a3e-bbee-8758ec5462f5/20210820093501-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0.nc4',\n",
      " 's3://harmony-prod-staging/public/podaac/l2-subsetter/8289859e-a4a7-4a3e-bbee-8758ec5462f5/20210820080001-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0_subsetted.nc4',\n",
      " 's3://harmony-prod-staging/public/podaac/l2-subsetter/8289859e-a4a7-4a3e-bbee-8758ec5462f5/20210820062501-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0.nc4']\n"
     ]
    },
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                  (nj: 543, ni: 948, time: 1)\n",
       "Coordinates:\n",
       "    lat                      (nj, ni, time) float32 ...\n",
       "    lon                      (nj, ni, time) float32 ...\n",
       "  * time                     (time) datetime64[ns] 2021-08-20T19:00:01\n",
       "Dimensions without coordinates: nj, ni\n",
       "Data variables:\n",
       "    sea_surface_temperature  (time, nj, ni) float32 ...\n",
       "    sst_dtime                (time, nj, ni) timedelta64[ns] ...\n",
       "    quality_level            (time, nj, ni) float32 ...\n",
       "    sses_bias                (time, nj, ni) float32 ...\n",
       "    sses_standard_deviation  (time, nj, ni) float32 ...\n",
       "    l2p_flags                (time, nj, ni) int16 ...\n",
       "    chlorophyll_a            (time, nj, ni) float32 ...\n",
       "    K_490                    (time, nj, ni) float32 ...\n",
       "    wind_speed               (time, nj, ni) float32 ...\n",
       "    dt_analysis              (time, nj, ni) float32 ...\n",
       "Attributes: (12/50)\n",
       "    Conventions:                CF-1.7, ACDD-1.3\n",
       "    title:                      MODIS Aqua L2P SST\n",
       "    summary:                    Sea surface temperature retrievals produced a...\n",
       "    references:                 GHRSST Data Processing Specification v2r5\n",
       "    institution:                NASA/JPL/OBPG/RSMAS\n",
       "    history:                    MODIS L2P created at JPL PO.DAAC\\n2022-06-13 ...\n",
       "    ...                         ...\n",
       "    processing_level:           L2P\n",
       "    cdm_data_type:              swath\n",
       "    startDirection:             Ascending\n",
       "    endDirection:               Ascending\n",
       "    day_night_flag:             Day\n",
       "    history_json:               [{&quot;date_time&quot;: &quot;2022-06-13T21:00:01.055953+00...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e99b686d-d6ac-43f5-a00a-8a54de1dae5d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e99b686d-d6ac-43f5-a00a-8a54de1dae5d' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>nj</span>: 543</li><li><span>ni</span>: 948</li><li><span class='xr-has-index'>time</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-899aa580-709e-48f0-9c91-9826cdd86b56' class='xr-section-summary-in' type='checkbox'  checked><label for='section-899aa580-709e-48f0-9c91-9826cdd86b56' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(nj, ni, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5f961aac-caf5-40f1-90fd-c9a3e2d7cbaa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5f961aac-caf5-40f1-90fd-c9a3e2d7cbaa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29cf18a6-2d33-41d5-9c6d-b68fb1f44263' class='xr-var-data-in' type='checkbox'><label for='data-29cf18a6-2d33-41d5-9c6d-b68fb1f44263' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>comment :</span></dt><dd>geographical coordinates, WGS84 projection</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>[514764 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(nj, ni, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ee326787-d102-422e-9004-bf365332032f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee326787-d102-422e-9004-bf365332032f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d2639666-9339-4499-9b28-a6c0cea8e299' class='xr-var-data-in' type='checkbox'><label for='data-d2639666-9339-4499-9b28-a6c0cea8e299' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>comment :</span></dt><dd>geographical coordinates, WGS84 projection</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>[514764 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-08-20T19:00:01</div><input id='attrs-94a0288f-4456-45b0-886b-628224f1927a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94a0288f-4456-45b0-886b-628224f1927a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d2751713-3f47-4c14-9eee-f6a2f0789bfd' class='xr-var-data-in' type='checkbox'><label for='data-d2751713-3f47-4c14-9eee-f6a2f0789bfd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>reference time of sst file</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>time of first sensor observation</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-08-20T19:00:01.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8c768fe9-469a-4f04-8406-78e7faf795c9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8c768fe9-469a-4f04-8406-78e7faf795c9' class='xr-section-summary' >Data variables: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>sea_surface_temperature</span></div><div class='xr-var-dims'>(time, nj, ni)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-49341bf7-08fe-48a8-8782-a694d78b7f67' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-49341bf7-08fe-48a8-8782-a694d78b7f67' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47c5188a-a1f0-48e1-b9f7-9fa012c06b4a' class='xr-var-data-in' type='checkbox'><label for='data-47c5188a-a1f0-48e1-b9f7-9fa012c06b4a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>sea surface temperature</dd><dt><span>standard_name :</span></dt><dd>sea_surface_skin_temperature</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>-1000</dd><dt><span>valid_max :</span></dt><dd>10000</dd><dt><span>comment :</span></dt><dd>sea surface temperature from thermal IR (11 um) channels</dd><dt><span>source :</span></dt><dd>NASA and University of Miami</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>[514764 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sst_dtime</span></div><div class='xr-var-dims'>(time, nj, ni)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ee1e26c5-e5d6-4417-b48c-ee4e7b5b59fa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee1e26c5-e5d6-4417-b48c-ee4e7b5b59fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc59b799-f7bf-4ba3-9204-6b242ddbff01' class='xr-var-data-in' type='checkbox'><label for='data-dc59b799-f7bf-4ba3-9204-6b242ddbff01' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time difference from reference time</dd><dt><span>valid_min :</span></dt><dd>-32767</dd><dt><span>valid_max :</span></dt><dd>32767</dd><dt><span>comment :</span></dt><dd>time plus sst_dtime gives seconds after 00:00:00 UTC January 1, 1981</dd><dt><span>coverage_content_type :</span></dt><dd>referenceInformation</dd></dl></div><div class='xr-var-data'><pre>[514764 values with dtype=timedelta64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quality_level</span></div><div class='xr-var-dims'>(time, nj, ni)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ac58e62a-9864-47cb-88df-5765ee40574d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac58e62a-9864-47cb-88df-5765ee40574d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3649750-0a7d-4cde-b3a4-7297d79a65ea' class='xr-var-data-in' type='checkbox'><label for='data-c3649750-0a7d-4cde-b3a4-7297d79a65ea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>quality level of SST pixel</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>5</dd><dt><span>comment :</span></dt><dd>thermal IR SST proximity confidence value; signed byte array: WARNING Some applications are unable to properly handle signed byte values. If values are encountered &gt; 127, please subtract 256 from this reported value</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5]</dd><dt><span>flag_meanings :</span></dt><dd>no_data bad_data worst_quality low_quality acceptable_quality best_quality</dd><dt><span>coverage_content_type :</span></dt><dd>qualityInformation</dd></dl></div><div class='xr-var-data'><pre>[514764 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sses_bias</span></div><div class='xr-var-dims'>(time, nj, ni)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-49cb50f0-d286-46d2-94c3-78b0299cf799' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-49cb50f0-d286-46d2-94c3-78b0299cf799' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9ef58cc5-0e8c-42f9-be64-836945f9aba9' class='xr-var-data-in' type='checkbox'><label for='data-9ef58cc5-0e8c-42f9-be64-836945f9aba9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>SSES bias error based on proximity confidence flags</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>-127</dd><dt><span>valid_max :</span></dt><dd>127</dd><dt><span>comment :</span></dt><dd>thermal IR SST bias error; signed byte array: WARNING Some applications are unable to properly handle signed byte values. If values are encountered &gt; 127, please subtract 256 from this reported value</dd><dt><span>coverage_content_type :</span></dt><dd>auxiliaryInformation</dd></dl></div><div class='xr-var-data'><pre>[514764 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sses_standard_deviation</span></div><div class='xr-var-dims'>(time, nj, ni)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b318c9b3-bbde-4144-8d28-974b47aea590' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b318c9b3-bbde-4144-8d28-974b47aea590' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5dbcadb3-ab8a-42db-894c-0ab72cc12954' class='xr-var-data-in' type='checkbox'><label for='data-5dbcadb3-ab8a-42db-894c-0ab72cc12954' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>SSES standard deviation error based on proximity confidence flags</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>-127</dd><dt><span>valid_max :</span></dt><dd>127</dd><dt><span>comment :</span></dt><dd>thermal IR SST standard deviation error; signed byte array: WARNING Some applications are unable to properly handle signed byte values. If values are encountered &gt; 127, please subtract 256 from this reported value</dd><dt><span>coverage_content_type :</span></dt><dd>auxiliaryInformation</dd></dl></div><div class='xr-var-data'><pre>[514764 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>l2p_flags</span></div><div class='xr-var-dims'>(time, nj, ni)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-54a140b7-e64d-4f4f-8672-cbf9fa3633cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-54a140b7-e64d-4f4f-8672-cbf9fa3633cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a65bc9a2-4d08-49d5-b81b-6dcc61fc7042' class='xr-var-data-in' type='checkbox'><label for='data-a65bc9a2-4d08-49d5-b81b-6dcc61fc7042' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>L2P flags</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>16</dd><dt><span>comment :</span></dt><dd>These flags can be used to further filter data variables</dd><dt><span>flag_meanings :</span></dt><dd>microwave land ice lake river</dd><dt><span>flag_masks :</span></dt><dd>[ 1  2  4  8 16]</dd><dt><span>coverage_content_type :</span></dt><dd>qualityInformation</dd></dl></div><div class='xr-var-data'><pre>[514764 values with dtype=int16]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>chlorophyll_a</span></div><div class='xr-var-dims'>(time, nj, ni)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-bd7c708e-85bf-4206-a377-c2479c331c47' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd7c708e-85bf-4206-a377-c2479c331c47' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-95f63ddc-741a-4f63-acdb-796620d4502e' class='xr-var-data-in' type='checkbox'><label for='data-95f63ddc-741a-4f63-acdb-796620d4502e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Chlorophyll Concentration, OC3 Algorithm</dd><dt><span>units :</span></dt><dd>mg m^-3</dd><dt><span>valid_min :</span></dt><dd>0.001</dd><dt><span>valid_max :</span></dt><dd>100.0</dd><dt><span>comment :</span></dt><dd>non L2P core field</dd><dt><span>coverage_content_type :</span></dt><dd>auxiliaryInformation</dd></dl></div><div class='xr-var-data'><pre>[514764 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>K_490</span></div><div class='xr-var-dims'>(time, nj, ni)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3c574e45-0e32-474a-befb-83deeb3ddb50' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c574e45-0e32-474a-befb-83deeb3ddb50' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f68d61cd-b7f5-4869-93e9-e11580446446' class='xr-var-data-in' type='checkbox'><label for='data-f68d61cd-b7f5-4869-93e9-e11580446446' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Diffuse attenuation coefficient at 490 nm (OBPG)</dd><dt><span>units :</span></dt><dd>m^-1</dd><dt><span>valid_min :</span></dt><dd>50</dd><dt><span>valid_max :</span></dt><dd>30000</dd><dt><span>comment :</span></dt><dd>non L2P core field</dd><dt><span>coverage_content_type :</span></dt><dd>auxiliaryInformation</dd></dl></div><div class='xr-var-data'><pre>[514764 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wind_speed</span></div><div class='xr-var-dims'>(time, nj, ni)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2ec115f9-3204-43d9-8710-1b2db33cd78d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2ec115f9-3204-43d9-8710-1b2db33cd78d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c54eb007-fd98-4e51-b693-8f746a89d4f5' class='xr-var-data-in' type='checkbox'><label for='data-c54eb007-fd98-4e51-b693-8f746a89d4f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>10m wind speed</dd><dt><span>standard_name :</span></dt><dd>wind_speed</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>valid_min :</span></dt><dd>-127</dd><dt><span>valid_max :</span></dt><dd>127</dd><dt><span>comment :</span></dt><dd>Wind at 10 meters above the sea surface</dd><dt><span>source :</span></dt><dd>TBD.  Placeholder.  Currently empty</dd><dt><span>grid_mapping :</span></dt><dd>TBD</dd><dt><span>time_offset :</span></dt><dd>2.0</dd><dt><span>height :</span></dt><dd>10 m</dd><dt><span>coverage_content_type :</span></dt><dd>auxiliaryInformation</dd></dl></div><div class='xr-var-data'><pre>[514764 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dt_analysis</span></div><div class='xr-var-dims'>(time, nj, ni)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2a24c0a3-870d-4685-9167-61170020a6df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a24c0a3-870d-4685-9167-61170020a6df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b8d7f3c-b628-4174-9e18-2fb5381ce86a' class='xr-var-data-in' type='checkbox'><label for='data-1b8d7f3c-b628-4174-9e18-2fb5381ce86a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>deviation from SST reference climatology</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>-127</dd><dt><span>valid_max :</span></dt><dd>127</dd><dt><span>comment :</span></dt><dd>TBD</dd><dt><span>source :</span></dt><dd>TBD. Placeholder.  Currently empty</dd><dt><span>coverage_content_type :</span></dt><dd>auxiliaryInformation</dd></dl></div><div class='xr-var-data'><pre>[514764 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dd94c193-d637-43dc-a0ac-eb514416a9c7' class='xr-section-summary-in' type='checkbox'  ><label for='section-dd94c193-d637-43dc-a0ac-eb514416a9c7' class='xr-section-summary' >Attributes: <span>(50)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7, ACDD-1.3</dd><dt><span>title :</span></dt><dd>MODIS Aqua L2P SST</dd><dt><span>summary :</span></dt><dd>Sea surface temperature retrievals produced at the NASA OBPG for the MODIS Aqua sensor.  These have been reformatted to GHRSST GDS specifications by the JPL PO.DAAC</dd><dt><span>references :</span></dt><dd>GHRSST Data Processing Specification v2r5</dd><dt><span>institution :</span></dt><dd>NASA/JPL/OBPG/RSMAS</dd><dt><span>history :</span></dt><dd>MODIS L2P created at JPL PO.DAAC\n",
       "2022-06-13 21:00:01.055911 l2ss-py v1.5.0 (bbox=[[-97.77667, -83.05197], [21.20806, 30.16605]] cut=True)</dd><dt><span>comment :</span></dt><dd>L2P Core without DT analysis or other ancillary fields; Day, Start Node:Ascending, End Node:Ascending; WARNING Some applications are unable to properly handle signed byte values. If values are encountered &gt; 127, please subtract 256 from this reported value; Quicklook</dd><dt><span>license :</span></dt><dd>GHRSST and PO.DAAC protocol allow data use as free and open.</dd><dt><span>id :</span></dt><dd>MODIS_A-JPL-L2P-v2019.0</dd><dt><span>naming_authority :</span></dt><dd>org.ghrsst</dd><dt><span>product_version :</span></dt><dd>2019.0</dd><dt><span>uuid :</span></dt><dd>f6e1f61d-c4a4-4c17-8354-0c15e12d688b</dd><dt><span>gds_version_id :</span></dt><dd>2.0</dd><dt><span>netcdf_version_id :</span></dt><dd>4.1</dd><dt><span>date_created :</span></dt><dd>20210821T033320Z</dd><dt><span>file_quality_level :</span></dt><dd>3</dd><dt><span>spatial_resolution :</span></dt><dd>1km</dd><dt><span>start_time :</span></dt><dd>20210820T190001Z</dd><dt><span>time_coverage_start :</span></dt><dd>20210820T190001Z</dd><dt><span>stop_time :</span></dt><dd>20210820T190458Z</dd><dt><span>time_coverage_end :</span></dt><dd>20210820T190458Z</dd><dt><span>northernmost_latitude :</span></dt><dd>46.5268</dd><dt><span>southernmost_latitude :</span></dt><dd>25.2922</dd><dt><span>easternmost_longitude :</span></dt><dd>-73.6391</dd><dt><span>westernmost_longitude :</span></dt><dd>-104.66</dd><dt><span>source :</span></dt><dd>MODIS sea surface temperature observations for the OBPG</dd><dt><span>platform :</span></dt><dd>Aqua</dd><dt><span>sensor :</span></dt><dd>MODIS</dd><dt><span>metadata_link :</span></dt><dd>http://podaac.jpl.nasa.gov/ws/metadata/dataset/?format=iso&amp;shortName=MODIS_A-JPL-L2P-v2019.0</dd><dt><span>keywords :</span></dt><dd>Oceans &gt; Ocean Temperature &gt; Sea Surface Temperature</dd><dt><span>keywords_vocabulary :</span></dt><dd>NASA Global Change Master Directory (GCMD) Science Keywords</dd><dt><span>standard_name_vocabulary :</span></dt><dd>NetCDF Climate and Forecast (CF) Metadata Convention</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.01</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.01</dd><dt><span>acknowledgment :</span></dt><dd>The MODIS L2P sea surface temperature data are sponsored by NASA</dd><dt><span>creator_name :</span></dt><dd>Ed Armstrong, JPL PO.DAAC</dd><dt><span>creator_email :</span></dt><dd>edward.m.armstrong@jpl.nasa.gov</dd><dt><span>creator_url :</span></dt><dd>http://podaac.jpl.nasa.gov</dd><dt><span>project :</span></dt><dd>Group for High Resolution Sea Surface Temperature</dd><dt><span>publisher_name :</span></dt><dd>The GHRSST Project Office</dd><dt><span>publisher_url :</span></dt><dd>http://www.ghrsst.org</dd><dt><span>publisher_email :</span></dt><dd>ghrsst-po@nceo.ac.uk</dd><dt><span>processing_level :</span></dt><dd>L2P</dd><dt><span>cdm_data_type :</span></dt><dd>swath</dd><dt><span>startDirection :</span></dt><dd>Ascending</dd><dt><span>endDirection :</span></dt><dd>Ascending</dd><dt><span>day_night_flag :</span></dt><dd>Day</dd><dt><span>history_json :</span></dt><dd>[{&quot;date_time&quot;: &quot;2022-06-13T21:00:01.055953+00:00&quot;, &quot;derived_from&quot;: &quot;https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/MODIS_A-JPL-L2P-v2019.0/20210820190001-JPL-L2P_GHRSST-SSTskin-MODIS_A-D-v02.0-fv01.0.nc&quot;, &quot;program&quot;: &quot;l2ss-py&quot;, &quot;version&quot;: &quot;1.5.0&quot;, &quot;parameters&quot;: &quot;bbox=[[-97.77667, -83.05197], [21.20806, 30.16605]] cut=True&quot;, &quot;program_ref&quot;: &quot;https://cmr.earthdata.nasa.gov:443/search/concepts/S1962070864-POCLOUD&quot;, &quot;$schema&quot;: &quot;https://harmony.earthdata.nasa.gov/schemas/history/0.1.0/history-v0.1.0.json&quot;}]</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                  (nj: 543, ni: 948, time: 1)\n",
       "Coordinates:\n",
       "    lat                      (nj, ni, time) float32 ...\n",
       "    lon                      (nj, ni, time) float32 ...\n",
       "  * time                     (time) datetime64[ns] 2021-08-20T19:00:01\n",
       "Dimensions without coordinates: nj, ni\n",
       "Data variables:\n",
       "    sea_surface_temperature  (time, nj, ni) float32 ...\n",
       "    sst_dtime                (time, nj, ni) timedelta64[ns] ...\n",
       "    quality_level            (time, nj, ni) float32 ...\n",
       "    sses_bias                (time, nj, ni) float32 ...\n",
       "    sses_standard_deviation  (time, nj, ni) float32 ...\n",
       "    l2p_flags                (time, nj, ni) int16 ...\n",
       "    chlorophyll_a            (time, nj, ni) float32 ...\n",
       "    K_490                    (time, nj, ni) float32 ...\n",
       "    wind_speed               (time, nj, ni) float32 ...\n",
       "    dt_analysis              (time, nj, ni) float32 ...\n",
       "Attributes: (12/50)\n",
       "    Conventions:                CF-1.7, ACDD-1.3\n",
       "    title:                      MODIS Aqua L2P SST\n",
       "    summary:                    Sea surface temperature retrievals produced a...\n",
       "    references:                 GHRSST Data Processing Specification v2r5\n",
       "    institution:                NASA/JPL/OBPG/RSMAS\n",
       "    history:                    MODIS L2P created at JPL PO.DAAC\\n2022-06-13 ...\n",
       "    ...                         ...\n",
       "    processing_level:           L2P\n",
       "    cdm_data_type:              swath\n",
       "    startDirection:             Ascending\n",
       "    endDirection:               Ascending\n",
       "    day_night_flag:             Day\n",
       "    history_json:               [{\"date_time\": \"2022-06-13T21:00:01.055953+00..."
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%time\n",
    "\n",
    "results = harmony_client.result_urls(job_id, link_type=LinkType.s3)\n",
    "urls = list(results)\n",
    "pprint(urls)\n",
    "\n",
    "s3_fs = s3fs.S3FileSystem(\n",
    "    key=creds['aws_access_key_id'],\n",
    "    secret=creds['aws_secret_access_key'],\n",
    "    token=creds['aws_session_token'],\n",
    "    client_kwargs={'region_name':'us-west-2'},\n",
    ")\n",
    "\n",
    "f = s3_fs.open(urls[1], mode='rb')\n",
    "ds = xr.open_dataset(f)\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc9522e3-8820-4c03-900a-c7b0dd081451",
   "metadata": {
    "tags": []
   },
   "source": [
    "### 9. Plot data in place"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "06bf5f27-bed8-4441-a22c-341197177d36",
   "metadata": {},
   "source": [
    "#### Steps Involved:\n",
    "\n",
    "49. Plot each variable (collapsed as incomplete, use-case-specific, and generally just necessary)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "72244394-6756-446f-b50d-8803563036a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds.sea_surface_temperature.plot() ;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e3cd7290-830b-41ff-afe5-2bcf6603597a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bb724394-84d2-41a0-97a9-1b6e81f8da2c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "8001fea6-ed29-4444-a921-63815a7e6aeb",
   "metadata": {
    "tags": []
   },
   "source": [
    "## STAC workflow (in progress)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c1938a99-4ba6-4a7b-8e41-5741493ec741",
   "metadata": {},
   "outputs": [],
   "source": [
    "# stac_catalog_url = harmony_client.stac_catalog_url(job_id)\n",
    "# stac_catalog_url\n",
    "\n",
    "# cat = Client.open(stac_catalog_url)\n",
    "\n",
    "# print(cat.title)\n",
    "# s3_links = []\n",
    "# for item in cat.get_all_items():\n",
    "#     print(item.datetime, [asset.href for asset in item.assets.values()])\n",
    "#     s3_links.append([asset.href for asset in item.assets.values()])\n",
    "\n",
    "# import rich.table\n",
    "\n",
    "# table = rich.table.Table(\"Asset Key\", \"Descripiption\")\n",
    "# for asset_key, asset in selected_item.assets.items():\n",
    "#     # print(f\"{asset_key:<25} - {asset.title}\")\n",
    "#     table.add_row(asset_key, asset.title)\n",
    "\n",
    "# table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4f09b74a-6c27-4c9e-9082-8e611bc93c42",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f311e9be-ec99-48a2-81a3-f9de398d2fd6",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": []
  }
 ],
 "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": 5
}