{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "788a509b-3a11-4c62-a3bb-e6f3338084a4",
   "metadata": {},
   "source": [
    "# Quick Tutorial\n",
    "\n",
    "There are mainly two methods for using Herbie\n",
    "1. When working with *one* file at a time, you should use the `Herbie` class imported from `herbie.archive` to create Herbie objects.\n",
    "1. When working with *many* files at a time across different dates and forecast lead times, there are some helper functions in `herbie.tools`.\n",
    "\n",
    "> [**More examples**](https://blaylockbk.github.io/Herbie/_build/html/user_guide/notebooks/index.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a77a8bdc",
   "metadata": {},
   "source": [
    "## Creating a Herbie Object\n",
    "The `Herbie` class gives you the details about an single GRIB2 file with methods to download the file, open with xarray, and subset the file by variable.\n",
    "\n",
    "What does this class do? When you specify a datetime, model type, and forecast lead time, Herbie will search the different archive sources for the file you are requesting. By default, it searches for the HRRR model (`model='hrrr'`) surface fields (`product='sfc'`) for the zero-hour lead time (`fxx=0'`)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "65e46e83-ff7a-4f1b-9a8d-1e1d47607ee9",
   "metadata": {},
   "outputs": [],
   "source": [
    "from herbie.archive import Herbie"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d59e5d48-1717-4138-aa51-63f33f8c1204",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on class Herbie in module herbie.archive:\n",
      "\n",
      "class Herbie(builtins.object)\n",
      " |  Herbie(date=None, *, valid_date=None, model='hrrr', fxx=0, product=None, priority=None, save_dir=WindowsPath('C:/Users/blayl_depgywe/data'), overwrite=False, verbose=True, **kwargs)\n",
      " |  \n",
      " |  Locate GRIB2 file at one of the archive sources.\n",
      " |  \n",
      " |  Parameters\n",
      " |  ----------\n",
      " |  date : pandas-parsable datetime\n",
      " |      *Model initialization datetime*.\n",
      " |      If None, then must set ``valid_date``.\n",
      " |  valid_date : pandas-parsable datetime\n",
      " |      Model valid datetime. Must set when ``date`` is None.\n",
      " |  fxx : int\n",
      " |      Forecast lead time in hours. Available lead times depend on\n",
      " |      the model type and model version. Range is model and run\n",
      " |      dependant.\n",
      " |  model : {'hrrr', 'hrrrak', 'rap', 'gfs', 'gfs_wave', 'ecmwf', 'rrfs', etc.}\n",
      " |      Model name as defined in the models template folder. CASE INSENSITIVE\n",
      " |      Some examples:\n",
      " |      - ``'hrrr'`` HRRR contiguous United States model\n",
      " |      - ``'hrrrak'`` HRRR Alaska model (alias ``'alaska'``)\n",
      " |      - ``'rap'`` RAP model\n",
      " |      - ``'ecmwf'`` ECMWF open data forecat products\n",
      " |  product : {'sfc', 'prs', 'nat', 'subh'}\n",
      " |      Output variable product file type. If not specified, will\n",
      " |      use first product in model template file. CASE SENSITIVE.\n",
      " |      For example, the HRRR model has these products:\n",
      " |      - ``'sfc'`` surface fields\n",
      " |      - ``'prs'`` pressure fields\n",
      " |      - ``'nat'`` native fields\n",
      " |      - ``'subh'`` subhourly fields\n",
      " |  member : None or int\n",
      " |      Some ensemble models (e.g. the future RRFS) will need to\n",
      " |      specify an ensemble member.\n",
      " |  priority : list or str\n",
      " |      List of model sources to get the data in the order of\n",
      " |      download priority. CASE INSENSITIVE. Some example data\n",
      " |      sources and the default priority order are listed below.\n",
      " |      - ``'aws'`` Amazon Web Services (Big Data Program)\n",
      " |      - ``'nomads'`` NOAA's NOMADS server\n",
      " |      - ``'google'`` Google Cloud Platform (Big Data Program)\n",
      " |      - ``'azure'`` Microsoft Azure (Big Data Program)\n",
      " |      - ``'pando'`` University of Utah Pando Archive (gateway 1)\n",
      " |      - ``'pando2'`` University of Utah Pando Archive (gateway 2)\n",
      " |  save_dir : str or pathlib.Path\n",
      " |      Location to save GRIB2 files locally. Default save directory\n",
      " |      is set in ``~/.config/herbie/config.cfg``.\n",
      " |  Overwrite : bool\n",
      " |      If True, look for GRIB2 files even if local copy exists.\n",
      " |      If False (default), use the local copy (still need to find\n",
      " |      the idx file).\n",
      " |  **kwargs\n",
      " |      Any other paremeter needed to satisfy the conditions in the\n",
      " |      model template file (e.g., nest=2, other_label='run2')\n",
      " |  \n",
      " |  Methods defined here:\n",
      " |  \n",
      " |  __init__(self, date=None, *, valid_date=None, model='hrrr', fxx=0, product=None, priority=None, save_dir=WindowsPath('C:/Users/blayl_depgywe/data'), overwrite=False, verbose=True, **kwargs)\n",
      " |      Specify model output and find GRIB2 file at one of the sources.\n",
      " |  \n",
      " |  __repr__(self)\n",
      " |      Representation in Notebook\n",
      " |  \n",
      " |  __str__(self)\n",
      " |      When Herbie class object is printed, print all properties\n",
      " |  \n",
      " |  download(self, searchString=None, *, source=None, save_dir=None, overwrite=None, verbose=None, errors='warn')\n",
      " |      Download file from source.\n",
      " |      \n",
      " |      Subsetting by variable follows the same principles described here:\n",
      " |      https://www.cpc.ncep.noaa.gov/products/wesley/fast_downloading_grib.html\n",
      " |      \n",
      " |      Parameters\n",
      " |      ----------\n",
      " |      searchString : str\n",
      " |          If None, download the full file. Else, use regex to subset\n",
      " |          the file by specific variables and levels.\n",
      " |          .. include:: ../../user_guide/searchString.rst\n",
      " |      source : {'nomads', 'aws', 'google', 'azure', 'pando', 'pando2'}\n",
      " |          If None, download GRIB2 file from self.grib2 which is\n",
      " |          the first location the GRIB2 file was found from the\n",
      " |          priority lists when this class was initialized. Else, you\n",
      " |          may specify the source to force downloading it from a\n",
      " |          different location.\n",
      " |      save_dir : str or pathlib.Path\n",
      " |          Location to save the model output files.\n",
      " |          If None, uses the default or path specified in __init__.\n",
      " |          Else, changes the path files are saved.\n",
      " |      overwrite : bool\n",
      " |          If True, overwrite existing files. Default will skip\n",
      " |          downloading if the full file exists. Not applicable when\n",
      " |          when searchString is not None because file subsets might\n",
      " |          be unique.\n",
      " |      errors : {'warn', 'raise'}\n",
      " |          When an error occurs, send a warning or raise a value error.\n",
      " |  \n",
      " |  find_grib(self, overwrite=False)\n",
      " |      Find a GRIB file from the archive sources\n",
      " |      \n",
      " |      Returns\n",
      " |      -------\n",
      " |      1) The URL or pathlib.Path to the GRIB2 files that exists\n",
      " |      2) The source of the GRIB2 file\n",
      " |  \n",
      " |  find_idx(self)\n",
      " |      Find an index file for the GRIB file\n",
      " |  \n",
      " |  get_localFilePath(self, searchString=None)\n",
      " |      Get path to local file\n",
      " |  \n",
      " |  index_as_dataframe = <functools.cached_property object>\n",
      " |      Read and cache the full index file\n",
      " |  \n",
      " |  read_idx(self, searchString=None)\n",
      " |      Inspect the GRIB2 file contents by reading the index file.\n",
      " |      \n",
      " |      This reads index files created with the wgrib2 utility.\n",
      " |      \n",
      " |      Parameters\n",
      " |      ----------\n",
      " |      searchString : str\n",
      " |          Filter dataframe by a searchString regular expression.\n",
      " |          Searches for strings in the index file lines, specifically\n",
      " |          the variable, level, and forecast_time columns.\n",
      " |          Execute ``_searchString_help()`` for examples of a good\n",
      " |          searchString.\n",
      " |      \n",
      " |          .. include:: ../../user_guide/searchString.rst\n",
      " |      \n",
      " |      Returns\n",
      " |      -------\n",
      " |      A Pandas DataFrame of the index file.\n",
      " |  \n",
      " |  xarray(self, searchString=None, backend_kwargs={}, remove_grib=True, **download_kwargs)\n",
      " |      Open GRIB2 data as xarray DataSet\n",
      " |      \n",
      " |      Parameters\n",
      " |      ----------\n",
      " |      searchString : str\n",
      " |          Variables to read into xarray Dataset\n",
      " |      remove_grib : bool\n",
      " |          If True, grib file will be removed ONLY IF it didn't exist\n",
      " |          before we downloaded it.\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Readonly properties defined here:\n",
      " |  \n",
      " |  __logo__\n",
      " |      For Fun, show the Herbie Logo\n",
      " |  \n",
      " |  get_localFileName\n",
      " |      Predict Local File Name\n",
      " |  \n",
      " |  get_remoteFileName\n",
      " |      Predict Remote File Name\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Data descriptors defined here:\n",
      " |  \n",
      " |  __dict__\n",
      " |      dictionary for instance variables (if defined)\n",
      " |  \n",
      " |  __weakref__\n",
      " |      list of weak references to the object (if defined)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(Herbie)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e36c0a3b-0b4f-4bcb-9a95-b12f6ebda1d5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🏋🏻‍♂️ Found \u001b[32m2022-Apr-23 00:00 UTC F00\u001b[0m [HRRR] [product=sfc] GRIB2 file from \u001b[31maws\u001b[0m and index file from \u001b[31maws\u001b[0m.                                                                                                                                                       \n"
     ]
    }
   ],
   "source": [
    "H = Herbie(\"2022-4-23 00:00\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56b74e93-ae24-4277-ad7a-3b01538d9528",
   "metadata": {},
   "source": [
    "The Herbie object tells us a file matching our request was found on Amazon Web Services (AWS)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77ec27df-751e-43b3-95c2-5ed4b53d1969",
   "metadata": {},
   "source": [
    "We can display some of details from the Herbie object by printing it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1bfbcc2a-8b9d-4128-93cc-63837ba2c545",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "\u001b[48;2;240;234;210m                                             \u001b[0m\n",
      "\u001b[48;2;240;234;210m   \u001b[38;2;136;33;27m█ \u001b[38;2;12;53;118m██ \u001b[38;2;0;0;0m                                    \u001b[0m\n",
      "\u001b[48;2;240;234;210m   \u001b[38;2;136;33;27m█ \u001b[38;2;12;53;118m██ \u001b[38;2;0;0;0m┏━┓ ┏━┓            ┏━┓   ┏━┓        \u001b[0m\n",
      "\u001b[48;2;240;234;210m   \u001b[38;2;136;33;27m█ \u001b[38;2;12;53;118m██ \u001b[38;2;0;0;0m┃ ┃ ┃ ┃┏━━━━┓┏━┓┏━┓┃ ┃   ┏━┓┏━━━━┓  \u001b[0m\n",
      "\u001b[48;2;240;234;210m   \u001b[38;2;136;33;27m█ \u001b[38;2;12;53;118m██ \u001b[38;2;0;0;0m┃ ┗━┛ ┃┃ ━━ ┃┃ ┏━━┛┃ ┗━━┓┃ ┃┃ ━━ ┃  \u001b[0m\n",
      "\u001b[48;2;240;234;210m   \u001b[38;2;136;33;27m█ \u001b[38;2;12;53;118m██ \u001b[38;2;0;0;0m┃ ┏━┓ ┃┃ ━━━┓┃ ┃   ┃ ━━ ┃┃ ┃┃ ━━━┓  \u001b[0m\n",
      "\u001b[48;2;240;234;210m   \u001b[38;2;136;33;27m█ \u001b[38;2;12;53;118m██ \u001b[38;2;0;0;0m┗━┛ ┗━┛┗━━━━┛┗━┛   ┗━━━━┛┗━┛┗━━━━┛  \u001b[0m\n",
      "\u001b[48;2;240;234;210m   \u001b[38;2;136;33;27m█ \u001b[38;2;12;53;118m██ \u001b[38;2;0;0;0m                                    \u001b[0m\n",
      "\u001b[48;2;240;234;210m    \u001b[38;2;0;0;0m       🏁 Retrieve NWP Model Data 🏁     \u001b[0m\n",
      "\u001b[48;2;240;234;210m                                             \u001b[0m\n",
      "\n",
      "    \n",
      "self.DESCRIPTION=High-Resolution Rapid Refresh - CONUS\n",
      "self.DETAILS={'NOMADS product description': 'https://www.nco.ncep.noaa.gov/pmb/products/hrrr/', 'University of Utah HRRR archive': 'http://hrrr.chpc.utah.edu/'}\n",
      "self.EXPECT_IDX_FILE=remote\n",
      "self.IDX_STYLE=wgrib2\n",
      "self.LOCALFILE=hrrr.t00z.wrfsfcf00.grib2\n",
      "self.PRODUCTS={'sfc': '2D surface level fields; 3-km resolution', 'prs': '3D pressure level fields; 3-km resolution', 'nat': 'Native level fields; 3-km resolution', 'subh': 'Subhourly grids; 3-km resolution'}\n",
      "self.SOURCES={'aws': 'https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr.20220423/conus/hrrr.t00z.wrfsfcf00.grib2', 'nomads': 'https://nomads.ncep.noaa.gov/pub/data/nccf/com/hrrr/prod/hrrr.20220423/conus/hrrr.t00z.wrfsfcf00.grib2', 'google': 'https://storage.googleapis.com/high-resolution-rapid-refresh/hrrr.20220423/conus/hrrr.t00z.wrfsfcf00.grib2', 'azure': 'https://noaahrrr.blob.core.windows.net/hrrr/hrrr.20220423/conus/hrrr.t00z.wrfsfcf00.grib2', 'pando': 'https://pando-rgw01.chpc.utah.edu/hrrr/sfc/20220423/hrrr.t00z.wrfsfcf00.grib2', 'pando2': 'https://pando-rgw02.chpc.utah.edu/hrrr/sfc/20220423/hrrr.t00z.wrfsfcf00.grib2'}\n",
      "self.fxx=0\n",
      "self.get_localFileName=hrrr.t00z.wrfsfcf00.grib2\n",
      "self.get_remoteFileName=hrrr.t00z.wrfsfcf00.grib2\n",
      "self.grib=https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr.20220423/conus/hrrr.t00z.wrfsfcf00.grib2\n",
      "self.grib_source=aws\n",
      "self.idx=https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr.20220423/conus/hrrr.t00z.wrfsfcf00.grib2.idx\n",
      "self.idx_source=aws\n",
      "self.model=hrrr\n",
      "self.overwrite=False\n",
      "self.product=sfc\n",
      "self.product_description=2D surface level fields; 3-km resolution\n",
      "self.searchString_help=\n",
      "Use regular expression to search for lines in the index file.\n",
      "Here are some examples you can use for the wgrib2-style `searchString`\n",
      "\n",
      "    ============================= ===============================================\n",
      "    ``searchString=``             Messages that will be downloaded\n",
      "    ============================= ===============================================\n",
      "    \":TMP:2 m\"                    Temperature at 2 m.\n",
      "    \":TMP:\"                       Temperature fields at all levels.\n",
      "    \":UGRD:.* mb\"                 U Wind at all pressure levels.\n",
      "    \":500 mb:\"                    All variables on the 500 mb level.\n",
      "    \":APCP:\"                      All accumulated precipitation fields.\n",
      "    \":APCP:surface:0-[1-9]*\"      Accumulated precip since initialization time\n",
      "    \":APCP:surface:[1-9]*-[1-9]*\" Accumulated precip over last hour\n",
      "    \":UGRD:10 m\"                  U wind component at 10 meters.\n",
      "    \":(U|V)GRD:(10|80) m\"         U and V wind component at 10 and 80 m.\n",
      "    \":(U|V)GRD:\"                  U and V wind component at all levels.\n",
      "    \":(?:U|V)GRD:[0-9]+ hybrid\"   U and V wind components at all hybrid levels\n",
      "    \":(?:U|V)GRD:[0-9]+ mb\"        U and V wind components at all pressure levels\n",
      "    \":.GRD:\"                      (Same as above)\n",
      "    \":(TMP|DPT):\"                 Temperature and Dew Point for all levels .\n",
      "    \":(TMP|DPT|RH):\"              TMP, DPT, and Relative Humidity for all levels.\n",
      "    \":REFC:\"                      Composite Reflectivity\n",
      "    \":surface:\"                   All variables at the surface.\n",
      "    ============================= ===============================================\n",
      "\n",
      "If you need help with regular expression, search the web or look at\n",
      "this cheatsheet: https://www.petefreitag.com/cheatsheets/regex/.\n",
      "\n",
      "self.verbose=True\n"
     ]
    }
   ],
   "source": [
    "print(H)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95334a72-4dc0-4224-a8a5-6cea27444acf",
   "metadata": {},
   "source": [
    " Now lets look at the GRIB2 and index file URLs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5972c525-20a7-4f9d-b599-2d71343ebc42",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr.20220423/conus/hrrr.t00z.wrfsfcf00.grib2\n",
      "https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr.20220423/conus/hrrr.t00z.wrfsfcf00.grib2.idx\n"
     ]
    }
   ],
   "source": [
    "print(H.grib)\n",
    "print(H.idx)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b89bd8f-8ca6-40ed-9c4c-7d29225bd0e1",
   "metadata": {},
   "source": [
    "Generally, you will only need to search for files using the default source priority order. But you can change the priority order if you wish."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1bd64505-e4c9-4ef9-94ca-17e12a7845e5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🏋🏻‍♂️ Found \u001b[32m2022-Jan-05 00:00 UTC F00\u001b[0m [HRRR] [product=sfc] GRIB2 file from \u001b[31mpando\u001b[0m and index file from \u001b[31mpando\u001b[0m.                                                                                                                                                       \n"
     ]
    }
   ],
   "source": [
    "# Specify the source priority to only look on Pando\n",
    "H = Herbie(\"2022-1-5\", priority=\"pando\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "75d6c983-1ac5-4e7d-9cf5-2a90ed415581",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "💔 Did not find a GRIB2 or Index File for \u001b[32m2022-Jan-05 00:00 UTC F00\u001b[0m HRRR                                                                                                     \n"
     ]
    }
   ],
   "source": [
    "# Specify the source priority to only look on NOMADS\n",
    "H = Herbie(\"2022-1-5\", priority=\"nomads\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dee200b4-4faa-44a4-a901-3d1561f6721d",
   "metadata": {},
   "source": [
    "It doesn't look like the file was found on the NOMADS server. We can tell Herbie to look at AWS after looking at NOMADS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f22896aa-aed7-4059-8fde-ee8c7e55ee70",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🏋🏻‍♂️ Found \u001b[32m2021-May-05 00:00 UTC F00\u001b[0m [HRRR] [product=sfc] GRIB2 file from \u001b[31maws\u001b[0m and index file from \u001b[31maws\u001b[0m.                                                                                                                                                       \n"
     ]
    }
   ],
   "source": [
    "# Specify the source priority.\n",
    "H = Herbie(\"2021-5-5\", priority=[\"nomads\", \"aws\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f6a8102-b501-4fdb-ace6-88399d5486fd",
   "metadata": {},
   "source": [
    "Ok, lets ask for the 15-hour forecast from our requested datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6ed326b8-4da2-4382-b1b1-1f280d77e6cb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🏋🏻‍♂️ Found \u001b[32m2021-May-05 00:00 UTC F15\u001b[0m [HRRR] [product=sfc] GRIB2 file from \u001b[31maws\u001b[0m and index file from \u001b[31maws\u001b[0m.                                                                                                                                                       \n"
     ]
    }
   ],
   "source": [
    "H = Herbie(\"2021-5-5\", fxx=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8602e63d-d704-4a9f-bb3a-be6891e1e849",
   "metadata": {},
   "source": [
    "We can also tell Herbie that the datetime we are requesting is the valid time. Herbie will adjust the model run time by the lead time requested."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "26b2f41e-ed96-48af-9a72-164f0f3e15ae",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🏋🏻‍♂️ Found \u001b[32m2021-May-04 09:00 UTC F15\u001b[0m [HRRR] [product=sfc] GRIB2 file from \u001b[31mlocal\u001b[0m and index file from \u001b[31maws\u001b[0m.                                                                                                                                                       \n"
     ]
    }
   ],
   "source": [
    "H = Herbie(valid_date=\"2021-5-5\", fxx=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89971867-d8f5-4b8d-b51f-ff88e4b7a997",
   "metadata": {},
   "source": [
    "### Download a Full File\n",
    "If the file exists at one of the source locations, Herbie can download the full file to your local drive."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "38c0b21e-a803-4ccf-bd6c-844aeb8801b2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🏋🏻‍♂️ Found \u001b[32m2021-May-04 09:00 UTC F15\u001b[0m [HRRR] [product=sfc] GRIB2 file from \u001b[31maws\u001b[0m and index file from \u001b[31maws\u001b[0m.                                                                                                                                                       \n",
      "👨🏻‍🏭 Created directory: [C:\\Users\\blayl_depgywe\\data\\hrrr\\20210504]\n",
      "✅ Success! Downloaded HRRR from \u001b[38;5;202maws                 \u001b[0m\n",
      "\tsrc: https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr.20210504/conus/hrrr.t09z.wrfsfcf15.grib2\n",
      "\tdst: C:\\Users\\blayl_depgywe\\data\\hrrr\\20210504\\hrrr.t09z.wrfsfcf15.grib2\n"
     ]
    }
   ],
   "source": [
    "H = Herbie(valid_date=\"2021-5-5\", fxx=15)\n",
    "H.download(verbose=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "036d9d5c-dd29-41b7-a9c5-daa7e12f8471",
   "metadata": {},
   "source": [
    "Since we downloaded the file, now when you ask Herbie for the file, it will tell you that the file is stored locally. (Since the index files are never downloaded, we still search the source locations for the index file)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "8b32c7c5-9da5-439d-82d8-4ac9cd5b4a6e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🏋🏻‍♂️ Found \u001b[32m2021-May-04 09:00 UTC F15\u001b[0m [HRRR] [product=sfc] GRIB2 file from \u001b[31mlocal\u001b[0m and index file from \u001b[31maws\u001b[0m.                                                                                                                                                       \n"
     ]
    }
   ],
   "source": [
    "H = Herbie(valid_date=\"2021-5-5\", fxx=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9a8adea4-e41d-429b-9c7d-337296feab70",
   "metadata": {},
   "source": [
    "### Download a Subset File\n",
    "Often you don't need the full file, just a few variables. Because the index files tell us the byte range of each variable or GRIB message, we can download that portion of the file. Thus, files can be subsetted by variable. (Note that Herbie cannot subset the file by geographic area).\n",
    "\n",
    "In this example, we will download all variables for the 1-h forecast for variables that are 2 m above ground."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "fdd46244-4c7a-4414-b9e4-09b5064a9b50",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🏋🏻‍♂️ Found \u001b[32m2021-May-04 09:00 UTC F15\u001b[0m [HRRR] [product=sfc] GRIB2 file from \u001b[31mlocal\u001b[0m and index file from \u001b[31maws\u001b[0m.                                                                                                                                                       \n",
      "📇 Download subset: [HRRR] model [sfc] product run at \u001b[32m2021-May-04 09:00 UTC F15\u001b[0m                                                            \n",
      " cURL from file://C:\\Users\\blayl_depgywe\\data\\hrrr\\20210504\\hrrr.t09z.wrfsfcf15.grib2\n",
      "  58  \u001b[34m:LTPINX:2 m above ground:15 hour fcst\u001b[0m\n",
      "  71  \u001b[34m:TMP:2 m above ground:15 hour fcst\u001b[0m\n",
      "  72  \u001b[34m:POT:2 m above ground:15 hour fcst\u001b[0m\n",
      "  73  \u001b[34m:SPFH:2 m above ground:15 hour fcst\u001b[0m\n",
      "  74  \u001b[34m:DPT:2 m above ground:15 hour fcst\u001b[0m\n",
      "  75  \u001b[34m:RH:2 m above ground:15 hour fcst\u001b[0m\n",
      "💾 Saved the above subset to C:\\Users\\blayl_depgywe\\data\\hrrr\\20210504\\hrrr.t09z.wrfsfcf15.grib2.subset_cac774946a4df951a374b169e9345aa6ab9ed8b0\n"
     ]
    }
   ],
   "source": [
    "# The full file already exists on Local Disk\n",
    "H = Herbie(valid_date=\"2021-5-5\", fxx=15)\n",
    "H.download(\":2 m\", verbose=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b45fb1a-36f7-4093-bb0e-b3dcdc5a35a4",
   "metadata": {},
   "source": [
    "If we ask to download this file again, Herbie tells us we already have a local copy. But we can overwrite if you need to."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d5481b93-74af-4772-8af1-a845ffbbc268",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🏋🏻‍♂️ Found \u001b[32m2021-May-04 09:00 UTC F15\u001b[0m [HRRR] [product=sfc] GRIB2 file from \u001b[31mlocal\u001b[0m and index file from \u001b[31maws\u001b[0m.                                                                                                                                                       \n",
      "📇 Download subset: [HRRR] model [sfc] product run at \u001b[32m2021-May-04 09:00 UTC F15\u001b[0m                                                            \n",
      " cURL from file://C:\\Users\\blayl_depgywe\\data\\hrrr\\20210504\\hrrr.t09z.wrfsfcf15.grib2\n",
      "  58  \u001b[34m:LTPINX:2 m above ground:15 hour fcst\u001b[0m\n",
      "  71  \u001b[34m:TMP:2 m above ground:15 hour fcst\u001b[0m\n",
      "  72  \u001b[34m:POT:2 m above ground:15 hour fcst\u001b[0m\n",
      "  73  \u001b[34m:SPFH:2 m above ground:15 hour fcst\u001b[0m\n",
      "  74  \u001b[34m:DPT:2 m above ground:15 hour fcst\u001b[0m\n",
      "  75  \u001b[34m:RH:2 m above ground:15 hour fcst\u001b[0m\n",
      "💾 Saved the above subset to C:\\Users\\blayl_depgywe\\data\\hrrr\\20210504\\hrrr.t09z.wrfsfcf15.grib2.subset_cac774946a4df951a374b169e9345aa6ab9ed8b0\n"
     ]
    }
   ],
   "source": [
    "# The Subset File Already Exists\n",
    "H = Herbie(valid_date=\"2021-5-5\", fxx=15)\n",
    "H.download(\":2 m\", verbose=True, overwrite=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "874b0050-ebe9-4937-a794-0d8cf1b704ba",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🏋🏻‍♂️ Found \u001b[32m2021-May-04 09:00 UTC F15\u001b[0m [HRRR] [product=sfc] GRIB2 file from \u001b[31maws\u001b[0m and index file from \u001b[31maws\u001b[0m.                                                                                                                                                       \n",
      "🚛💨  Download Progress: 100.00% of 158.5 MB\r"
     ]
    }
   ],
   "source": [
    "# Now download the full file with overwrite\n",
    "H = Herbie(valid_date=\"2021-5-5\", fxx=15, overwrite=True)\n",
    "H.download()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46f8aa30-731a-449d-86ee-836ecf9585ca",
   "metadata": {},
   "source": [
    "### Index files and Subset Search String\n",
    "\n",
    "Each GRIB2 file should include a companion inventory or index file. The GRIB2 filename usually has the **.idx** suffix appended to the end of the filename. This file is important because it tells us the byte range of each variable GRIB message, which enables us to do a partial download of the file using cURL.\n",
    "\n",
    "The magic trick for subsetting the data for what you want comes down to the search string. Herbie uses regular expression to search for lines in the index file to match which grib messages to download. Some examples are as follows.\n",
    "\n",
    " ``searchString``               |  Messages that will be downloaded\n",
    "--------------------------------|-----------------------------------------------\n",
    " `\":TMP:2 m\"`                   | Temperature at 2 m.\n",
    " `\":TMP:\"`                      | Temperature fields at all levels.\n",
    " `\":UGRD:.* mb\"`                | U Wind at all pressure levels.\n",
    " `\":500 mb:\"`                   | All variables on the 500 mb level.\n",
    " `\":APCP:\"`                     | All accumulated precipitation fiel\n",
    " `\":APCP:surface:0-[1-9]*\"`     | Accumulated precip since initializ\n",
    " `\":APCP:surface:[1-9]*-[1-9]*\"`| Accumulated precip over last hour\n",
    " `\":UGRD:10 m\"`                 | U wind component at 10 meters.\n",
    " `\":(?:U\\|V)GRD:(?:10\\|80) m\"`  | U and V wind component at 10 and 8\n",
    " `\":(?:U\\|V)GRD:\"`              | U and V wind component at all leve\n",
    " `\":.GRD:\"`                     | (Same as above)\n",
    " `\":(?:TMP\\|DPT):\"`             | Temperature and Dew Point for all \n",
    " `\":(?:TMP\\|DPT\\|RH):\"`         | TMP, DPT, and Relative Humidity fo\n",
    " `\":REFC:\"`                     | Composite Reflectivity\n",
    " `\":surface:\"`                  | All variables at the surface.\n",
    "\n",
    "If you need help with regular expression, search the web\n",
    "or look at this [cheatsheet](https://www.petefreitag.com/cheatsheets/regex/)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ea954a6-0384-405e-be51-9c8b2c03d7d3",
   "metadata": {},
   "source": [
    "Herbie reads the index file into a Pandas Dataframe. The regular expression searches the \"search_this\" column to match rows in the index file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "a815cfb1-303b-4f2e-9817-68fdc9aa8645",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>grib_message</th>\n",
       "      <th>start_byte</th>\n",
       "      <th>end_byte</th>\n",
       "      <th>range</th>\n",
       "      <th>reference_time</th>\n",
       "      <th>valid_time</th>\n",
       "      <th>variable</th>\n",
       "      <th>level</th>\n",
       "      <th>forecast_time</th>\n",
       "      <th>search_this</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>636814</td>\n",
       "      <td>0-636814</td>\n",
       "      <td>2021-05-04 09:00:00</td>\n",
       "      <td>2021-05-05</td>\n",
       "      <td>REFC</td>\n",
       "      <td>entire atmosphere</td>\n",
       "      <td>15 hour fcst</td>\n",
       "      <td>:REFC:entire atmosphere:15 hour fcst</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>636814</td>\n",
       "      <td>962034</td>\n",
       "      <td>636814-962034</td>\n",
       "      <td>2021-05-04 09:00:00</td>\n",
       "      <td>2021-05-05</td>\n",
       "      <td>RETOP</td>\n",
       "      <td>cloud top</td>\n",
       "      <td>15 hour fcst</td>\n",
       "      <td>:RETOP:cloud top:15 hour fcst</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>962034</td>\n",
       "      <td>1603774</td>\n",
       "      <td>962034-1603774</td>\n",
       "      <td>2021-05-04 09:00:00</td>\n",
       "      <td>2021-05-05</td>\n",
       "      <td>var discipline=0 center=7 local_table=1 parmca...</td>\n",
       "      <td>entire atmosphere</td>\n",
       "      <td>15 hour fcst</td>\n",
       "      <td>:var discipline=0 center=7 local_table=1 parmc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1603774</td>\n",
       "      <td>1910611</td>\n",
       "      <td>1603774-1910611</td>\n",
       "      <td>2021-05-04 09:00:00</td>\n",
       "      <td>2021-05-05</td>\n",
       "      <td>VIL</td>\n",
       "      <td>entire atmosphere</td>\n",
       "      <td>15 hour fcst</td>\n",
       "      <td>:VIL:entire atmosphere:15 hour fcst</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1910611</td>\n",
       "      <td>3239678</td>\n",
       "      <td>1910611-3239678</td>\n",
       "      <td>2021-05-04 09:00:00</td>\n",
       "      <td>2021-05-05</td>\n",
       "      <td>VIS</td>\n",
       "      <td>surface</td>\n",
       "      <td>15 hour fcst</td>\n",
       "      <td>:VIS:surface:15 hour fcst</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>169</td>\n",
       "      <td>151936733</td>\n",
       "      <td>151937231</td>\n",
       "      <td>151936733-151937231</td>\n",
       "      <td>2021-05-04 09:00:00</td>\n",
       "      <td>2021-05-05</td>\n",
       "      <td>ICEC</td>\n",
       "      <td>surface</td>\n",
       "      <td>15 hour fcst</td>\n",
       "      <td>:ICEC:surface:15 hour fcst</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>170</td>\n",
       "      <td>151937231</td>\n",
       "      <td>153642912</td>\n",
       "      <td>151937231-153642912</td>\n",
       "      <td>2021-05-04 09:00:00</td>\n",
       "      <td>2021-05-05</td>\n",
       "      <td>SBT123</td>\n",
       "      <td>top of atmosphere</td>\n",
       "      <td>15 hour fcst</td>\n",
       "      <td>:SBT123:top of atmosphere:15 hour fcst</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>171</td>\n",
       "      <td>153642912</td>\n",
       "      <td>155314328</td>\n",
       "      <td>153642912-155314328</td>\n",
       "      <td>2021-05-04 09:00:00</td>\n",
       "      <td>2021-05-05</td>\n",
       "      <td>SBT124</td>\n",
       "      <td>top of atmosphere</td>\n",
       "      <td>15 hour fcst</td>\n",
       "      <td>:SBT124:top of atmosphere:15 hour fcst</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>172</td>\n",
       "      <td>155314328</td>\n",
       "      <td>156883538</td>\n",
       "      <td>155314328-156883538</td>\n",
       "      <td>2021-05-04 09:00:00</td>\n",
       "      <td>2021-05-05</td>\n",
       "      <td>SBT113</td>\n",
       "      <td>top of atmosphere</td>\n",
       "      <td>15 hour fcst</td>\n",
       "      <td>:SBT113:top of atmosphere:15 hour fcst</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>173</td>\n",
       "      <td>156883538</td>\n",
       "      <td></td>\n",
       "      <td>156883538-</td>\n",
       "      <td>2021-05-04 09:00:00</td>\n",
       "      <td>2021-05-05</td>\n",
       "      <td>SBT114</td>\n",
       "      <td>top of atmosphere</td>\n",
       "      <td>15 hour fcst</td>\n",
       "      <td>:SBT114:top of atmosphere:15 hour fcst</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>173 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     grib_message  start_byte   end_byte                range  \\\n",
       "0               1           0     636814             0-636814   \n",
       "1               2      636814     962034        636814-962034   \n",
       "2               3      962034    1603774       962034-1603774   \n",
       "3               4     1603774    1910611      1603774-1910611   \n",
       "4               5     1910611    3239678      1910611-3239678   \n",
       "..            ...         ...        ...                  ...   \n",
       "168           169   151936733  151937231  151936733-151937231   \n",
       "169           170   151937231  153642912  151937231-153642912   \n",
       "170           171   153642912  155314328  153642912-155314328   \n",
       "171           172   155314328  156883538  155314328-156883538   \n",
       "172           173   156883538                      156883538-   \n",
       "\n",
       "         reference_time valid_time  \\\n",
       "0   2021-05-04 09:00:00 2021-05-05   \n",
       "1   2021-05-04 09:00:00 2021-05-05   \n",
       "2   2021-05-04 09:00:00 2021-05-05   \n",
       "3   2021-05-04 09:00:00 2021-05-05   \n",
       "4   2021-05-04 09:00:00 2021-05-05   \n",
       "..                  ...        ...   \n",
       "168 2021-05-04 09:00:00 2021-05-05   \n",
       "169 2021-05-04 09:00:00 2021-05-05   \n",
       "170 2021-05-04 09:00:00 2021-05-05   \n",
       "171 2021-05-04 09:00:00 2021-05-05   \n",
       "172 2021-05-04 09:00:00 2021-05-05   \n",
       "\n",
       "                                              variable              level  \\\n",
       "0                                                 REFC  entire atmosphere   \n",
       "1                                                RETOP          cloud top   \n",
       "2    var discipline=0 center=7 local_table=1 parmca...  entire atmosphere   \n",
       "3                                                  VIL  entire atmosphere   \n",
       "4                                                  VIS            surface   \n",
       "..                                                 ...                ...   \n",
       "168                                               ICEC            surface   \n",
       "169                                             SBT123  top of atmosphere   \n",
       "170                                             SBT124  top of atmosphere   \n",
       "171                                             SBT113  top of atmosphere   \n",
       "172                                             SBT114  top of atmosphere   \n",
       "\n",
       "    forecast_time                                        search_this  \n",
       "0    15 hour fcst               :REFC:entire atmosphere:15 hour fcst  \n",
       "1    15 hour fcst                      :RETOP:cloud top:15 hour fcst  \n",
       "2    15 hour fcst  :var discipline=0 center=7 local_table=1 parmc...  \n",
       "3    15 hour fcst                :VIL:entire atmosphere:15 hour fcst  \n",
       "4    15 hour fcst                          :VIS:surface:15 hour fcst  \n",
       "..            ...                                                ...  \n",
       "168  15 hour fcst                         :ICEC:surface:15 hour fcst  \n",
       "169  15 hour fcst             :SBT123:top of atmosphere:15 hour fcst  \n",
       "170  15 hour fcst             :SBT124:top of atmosphere:15 hour fcst  \n",
       "171  15 hour fcst             :SBT113:top of atmosphere:15 hour fcst  \n",
       "172  15 hour fcst             :SBT114:top of atmosphere:15 hour fcst  \n",
       "\n",
       "[173 rows x 10 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "H.read_idx()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "52fa4830-d2c7-4a81-a09c-34e459e8d80a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>36906392</td>\n",
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       "      <td>2021-05-04 09:00:00</td>\n",
       "      <td>2021-05-05</td>\n",
       "      <td>UGRD</td>\n",
       "      <td>80 m above ground</td>\n",
       "      <td>15 hour fcst</td>\n",
       "      <td>:UGRD:80 m above ground:15 hour fcst</td>\n",
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       "      <td>VGRD</td>\n",
       "      <td>80 m above ground</td>\n",
       "      <td>15 hour fcst</td>\n",
       "      <td>:VGRD:80 m above ground:15 hour fcst</td>\n",
       "    </tr>\n",
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       "      <td>52662153</td>\n",
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       "      <td>2021-05-04 09:00:00</td>\n",
       "      <td>2021-05-05</td>\n",
       "      <td>UGRD</td>\n",
       "      <td>10 m above ground</td>\n",
       "      <td>15 hour fcst</td>\n",
       "      <td>:UGRD:10 m above ground:15 hour fcst</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>78</td>\n",
       "      <td>55043768</td>\n",
       "      <td>57425383</td>\n",
       "      <td>55043768-57425383</td>\n",
       "      <td>2021-05-04 09:00:00</td>\n",
       "      <td>2021-05-05</td>\n",
       "      <td>VGRD</td>\n",
       "      <td>10 m above ground</td>\n",
       "      <td>15 hour fcst</td>\n",
       "      <td>:VGRD:10 m above ground:15 hour fcst</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "    grib_message  start_byte  end_byte              range      reference_time  \\\n",
       "59            60    36906392  38106734  36906392-38106734 2021-05-04 09:00:00   \n",
       "60            61    38106734  39269979  38106734-39269979 2021-05-04 09:00:00   \n",
       "76            77    52662153  55043768  52662153-55043768 2021-05-04 09:00:00   \n",
       "77            78    55043768  57425383  55043768-57425383 2021-05-04 09:00:00   \n",
       "\n",
       "   valid_time variable              level forecast_time  \\\n",
       "59 2021-05-05     UGRD  80 m above ground  15 hour fcst   \n",
       "60 2021-05-05     VGRD  80 m above ground  15 hour fcst   \n",
       "76 2021-05-05     UGRD  10 m above ground  15 hour fcst   \n",
       "77 2021-05-05     VGRD  10 m above ground  15 hour fcst   \n",
       "\n",
       "                             search_this  \n",
       "59  :UGRD:80 m above ground:15 hour fcst  \n",
       "60  :VGRD:80 m above ground:15 hour fcst  \n",
       "76  :UGRD:10 m above ground:15 hour fcst  \n",
       "77  :VGRD:10 m above ground:15 hour fcst  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# See what messages will be downloaded by a search string.\n",
    "H.read_idx(\"(?:U|V)GRD:(?:10|80) m\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "d5a41d97-00ff-46db-b4c0-450c90ae3dbe",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\blayl_depgywe\\BB_python\\Herbie\\herbie\\archive.py:634: UserWarning: This pattern is interpreted as a regular expression, and has match groups. To actually get the groups, use str.extract.\n",
      "  logic = df.search_this.str.contains(searchString)\n"
     ]
    },
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       "      <th></th>\n",
       "      <th>grib_message</th>\n",
       "      <th>start_byte</th>\n",
       "      <th>end_byte</th>\n",
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       "      <td>2021-05-05</td>\n",
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       "      <td>2021-05-05</td>\n",
       "      <td>VGRD</td>\n",
       "      <td>500 mb</td>\n",
       "      <td>15 hour fcst</td>\n",
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       "      <td>2021-05-05</td>\n",
       "      <td>UGRD</td>\n",
       "      <td>850 mb</td>\n",
       "      <td>15 hour fcst</td>\n",
       "      <td>:UGRD:850 mb:15 hour fcst</td>\n",
       "    </tr>\n",
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       "      <td>20120596</td>\n",
       "      <td>20748701</td>\n",
       "      <td>20120596-20748701</td>\n",
       "      <td>2021-05-04 09:00:00</td>\n",
       "      <td>2021-05-05</td>\n",
       "      <td>VGRD</td>\n",
       "      <td>850 mb</td>\n",
       "      <td>15 hour fcst</td>\n",
       "      <td>:VGRD:850 mb:15 hour fcst</td>\n",
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       "  </tbody>\n",
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       "    grib_message  start_byte  end_byte              range      reference_time  \\\n",
       "16            17    11102539  11718442  11102539-11718442 2021-05-04 09:00:00   \n",
       "17            18    11718442  12320354  11718442-12320354 2021-05-04 09:00:00   \n",
       "27            28    19477225  20120596  19477225-20120596 2021-05-04 09:00:00   \n",
       "28            29    20120596  20748701  20120596-20748701 2021-05-04 09:00:00   \n",
       "\n",
       "   valid_time variable   level forecast_time                search_this  \n",
       "16 2021-05-05     UGRD  500 mb  15 hour fcst  :UGRD:500 mb:15 hour fcst  \n",
       "17 2021-05-05     VGRD  500 mb  15 hour fcst  :VGRD:500 mb:15 hour fcst  \n",
       "27 2021-05-05     UGRD  850 mb  15 hour fcst  :UGRD:850 mb:15 hour fcst  \n",
       "28 2021-05-05     VGRD  850 mb  15 hour fcst  :VGRD:850 mb:15 hour fcst  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# See what messages will be downloaded by a search string.\n",
    "H.read_idx(\"(U|V)GRD:[8|5][0|5]0 mb\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba02a764-6038-4970-a260-7b54591d1484",
   "metadata": {},
   "source": [
    "Here's another example: download all variables at 500 mb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "7d2a72c4-fdde-4050-afcc-e6f45239752f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🏋🏻‍♂️ Found \u001b[32m2022-Mar-05 12:00 UTC F00\u001b[0m [HRRR] [product=sfc] GRIB2 file from \u001b[31maws\u001b[0m and index file from \u001b[31maws\u001b[0m.                                                                                                                                                       \n",
      "👨🏻‍🏭 Created directory: [C:\\Users\\blayl_depgywe\\data\\hrrr\\20220305]\n",
      "📇 Download subset: [HRRR] model [sfc] product run at \u001b[32m2022-Mar-05 12:00 UTC F00\u001b[0m                                                            \n",
      " cURL from https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr.20220305/conus/hrrr.t12z.wrfsfcf00.grib2\n",
      "  14  \u001b[34m:HGT:500 mb:anl\u001b[0m\n",
      "  15  \u001b[34m:TMP:500 mb:anl\u001b[0m\n",
      "  16  \u001b[34m:DPT:500 mb:anl\u001b[0m\n",
      "  17  \u001b[34m:UGRD:500 mb:anl\u001b[0m\n",
      "  18  \u001b[34m:VGRD:500 mb:anl\u001b[0m\n",
      "💾 Saved the above subset to C:\\Users\\blayl_depgywe\\data\\hrrr\\20220305\\hrrr.t12z.wrfsfcf00.grib2.subset_8a05a62e3e874603b5d6b37737904e0ec526ce1a\n"
     ]
    }
   ],
   "source": [
    "# Download a different Subset of File the local file\n",
    "H = Herbie(valid_date=\"2022-3-5 12:00\", fxx=0)\n",
    "H.download(\":500 mb:\", verbose=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47ade0a2",
   "metadata": {},
   "source": [
    "Herbie creates a unique filename for the subsetted files when it is downloaded."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "fd28d45d-bb17-4e72-8578-50a2221808fd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "WindowsPath('C:/Users/blayl_depgywe/data/hrrr/20220305/hrrr.t12z.wrfsfcf00.grib2.subset_8a05a62e3e874603b5d6b37737904e0ec526ce1a')"
      ]
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     "execution_count": 24,
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   "source": [
    "# Show path to subset file. You should check if this path exists or not.\n",
    "H.get_localFilePath(\":500 mb\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab80cb77-03f7-4aeb-8271-8b666259443b",
   "metadata": {},
   "source": [
    "### Read GRIB2 file with xarray\n",
    "Herbie can read GRIB2 files with xarray via cfgrib. By default, if the file requested does not already exist on local disk, Herbie will delete the file after it is loaded into memory (if on Linux; removing file does not work on Windows.). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "07149b05-5fa0-4e18-a1f8-e75e49646a37",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🏋🏻‍♂️ Found \u001b[32m2022-Apr-02 06:00 UTC F00\u001b[0m [HRRR] [product=sfc] GRIB2 file from \u001b[31maws\u001b[0m and index file from \u001b[31maws\u001b[0m.                                                                                                                                                       \n",
      "👨🏻‍🏭 Created directory: [C:\\Users\\blayl_depgywe\\data\\hrrr\\20220402]\n",
      "📇 Download subset: [HRRR] model [sfc] product run at \u001b[32m2022-Apr-02 06:00 UTC F00\u001b[0m                                                            \n",
      " cURL from https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr.20220402/conus/hrrr.t06z.wrfsfcf00.grib2\n",
      "  14  \u001b[34m:HGT:500 mb:anl\u001b[0m\n",
      "  15  \u001b[34m:TMP:500 mb:anl\u001b[0m\n",
      "  16  \u001b[34m:DPT:500 mb:anl\u001b[0m\n",
      "  17  \u001b[34m:UGRD:500 mb:anl\u001b[0m\n",
      "  18  \u001b[34m:VGRD:500 mb:anl\u001b[0m\n",
      "💾 Saved the above subset to C:\\Users\\blayl_depgywe\\data\\hrrr\\20220402\\hrrr.t06z.wrfsfcf00.grib2.subset_8a05a62e3e874603b5d6b37737904e0ec526ce1a\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\blayl_depgywe\\BB_python\\Herbie\\herbie\\archive.py:950: UserWarning: sorry, on windows I couldn't remove the file.\n",
      "  warnings.warn(\"sorry, on windows I couldn't remove the file.\")\n"
     ]
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       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:              (y: 1059, x: 1799)\n",
       "Coordinates:\n",
       "    time                 datetime64[ns] 2022-04-02T06:00:00\n",
       "    step                 timedelta64[ns] 00:00:00\n",
       "    isobaricInhPa        float64 500.0\n",
       "    latitude             (y, x) float64 21.14 21.15 21.15 ... 47.86 47.85 47.84\n",
       "    longitude            (y, x) float64 237.3 237.3 237.3 ... 299.0 299.0 299.1\n",
       "    valid_time           datetime64[ns] 2022-04-02T06:00:00\n",
       "Dimensions without coordinates: y, x\n",
       "Data variables:\n",
       "    t                    (y, x) float32 267.3 267.3 267.3 ... 250.7 250.8 250.8\n",
       "    u                    (y, x) float32 6.373 6.373 6.373 ... -2.002 -1.94 -1.94\n",
       "    v                    (y, x) float32 -4.079 -4.079 -4.079 ... 18.8 19.17\n",
       "    gh                   (y, x) float32 5.853e+03 5.853e+03 ... 5.308e+03\n",
       "    dpt                  (y, x) float32 244.5 244.4 244.2 ... 229.5 229.4 229.2\n",
       "    gribfile_projection  object None\n",
       "Attributes:\n",
       "    GRIB_edition:            2\n",
       "    GRIB_centre:             kwbc\n",
       "    GRIB_centreDescription:  US National Weather Service - NCEP\n",
       "    GRIB_subCentre:          0\n",
       "    Conventions:             CF-1.7\n",
       "    institution:             US National Weather Service - NCEP\n",
       "    model:                   hrrr\n",
       "    product:                 sfc\n",
       "    description:             High-Resolution Rapid Refresh - CONUS\n",
       "    remote_grib:             https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr....\n",
       "    local_grib:              C:\\Users\\blayl_depgywe\\data\\hrrr\\20220402\\hrrr.t...\n",
       "    searchString:            :500 mb</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-499660a7-d71d-484f-8f83-31e16fb7b171' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-499660a7-d71d-484f-8f83-31e16fb7b171' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>y</span>: 1059</li><li><span>x</span>: 1799</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c9d17f67-e7bb-4cc6-a07c-760375f1711f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c9d17f67-e7bb-4cc6-a07c-760375f1711f' class='xr-section-summary' >Coordinates: <span>(6)</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>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-04-02T06:00:00</div><input id='attrs-fdffec45-94a3-427e-9b50-7b03e19dfca9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fdffec45-94a3-427e-9b50-7b03e19dfca9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0522cf5c-1b69-4d7c-908b-52b6aba589da' class='xr-var-data-in' type='checkbox'><label for='data-0522cf5c-1b69-4d7c-908b-52b6aba589da' 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>initial time of forecast</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-04-02T06:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>00:00:00</div><input id='attrs-76206ead-3e98-4bee-9dab-128d9185b191' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-76206ead-3e98-4bee-9dab-128d9185b191' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41f3493f-966b-47e1-9846-30f1baade227' class='xr-var-data-in' type='checkbox'><label for='data-41f3493f-966b-47e1-9846-30f1baade227' 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 since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>array(0, dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>isobaricInhPa</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>500.0</div><input id='attrs-afdc0e9f-1111-4f90-96c8-eb6283e53c18' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-afdc0e9f-1111-4f90-96c8-eb6283e53c18' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e977145-7ab8-4db6-9c3c-4b1414a57490' class='xr-var-data-in' type='checkbox'><label for='data-9e977145-7ab8-4db6-9c3c-4b1414a57490' 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>pressure</dd><dt><span>units :</span></dt><dd>hPa</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>stored_direction :</span></dt><dd>decreasing</dd><dt><span>standard_name :</span></dt><dd>air_pressure</dd></dl></div><div class='xr-var-data'><pre>array(500.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>21.14 21.15 21.15 ... 47.85 47.84</div><input id='attrs-3b140f09-3e3a-40ba-89a9-33596aa78750' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b140f09-3e3a-40ba-89a9-33596aa78750' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa100cb6-9e9a-40e2-851e-6c62eaa993b2' class='xr-var-data-in' type='checkbox'><label for='data-fa100cb6-9e9a-40e2-851e-6c62eaa993b2' 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>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([[21.138123  , 21.14511004, 21.1520901 , ..., 21.1545089 ,\n",
       "        21.14753125, 21.14054663],\n",
       "       [21.16299459, 21.1699845 , 21.17696744, ..., 21.17938723,\n",
       "        21.1724067 , 21.16541921],\n",
       "       [21.18786863, 21.19486142, 21.20184723, ..., 21.20426802,\n",
       "        21.19728462, 21.19029425],\n",
       "       ...,\n",
       "       [47.78955926, 47.799849  , 47.81012868, ..., 47.81369093,\n",
       "        47.80341474, 47.79312849],\n",
       "       [47.81409316, 47.82438621, 47.8346692 , ..., 47.83823259,\n",
       "        47.8279531 , 47.81766354],\n",
       "       [47.8386235 , 47.84891986, 47.85920615, ..., 47.86277069,\n",
       "        47.85248789, 47.84219502]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>237.3 237.3 237.3 ... 299.0 299.1</div><input id='attrs-0f9807bc-5822-4ded-8d04-26f660ae1404' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0f9807bc-5822-4ded-8d04-26f660ae1404' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa5b84bb-2bb2-4934-bb90-67bcf83d6bc6' class='xr-var-data-in' type='checkbox'><label for='data-aa5b84bb-2bb2-4934-bb90-67bcf83d6bc6' 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>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([[237.280472  , 237.30713868, 237.3338097 , ..., 287.6569408 ,\n",
       "        287.68361332, 287.71028151],\n",
       "       [237.27297501, 237.29964881, 237.32632695, ..., 287.66442108,\n",
       "        287.69110073, 287.71777603],\n",
       "       [237.26547368, 237.2921546 , 237.31883986, ..., 287.6719057 ,\n",
       "        287.69859247, 287.7252749 ],\n",
       "       ...,\n",
       "       [225.9351904 , 225.97171577, 226.00825329, ..., 298.97907406,\n",
       "        299.0156158 , 299.05214538],\n",
       "       [225.91986142, 225.95639874, 225.99294822, ..., 298.99437498,\n",
       "        299.03092868, 299.06747022],\n",
       "       [225.90452027, 225.94106954, 225.97763099, ..., 299.00968806,\n",
       "        299.04625373, 299.08280723]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>valid_time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-04-02T06:00:00</div><input id='attrs-b8f499c5-344e-465a-9b31-515c890464aa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b8f499c5-344e-465a-9b31-515c890464aa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3eaef419-39fa-4c18-bfeb-4cc9e2214d4c' class='xr-var-data-in' type='checkbox'><label for='data-3eaef419-39fa-4c18-bfeb-4cc9e2214d4c' 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>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-04-02T06:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2797db1d-b066-421a-8ead-c16e8b9e6116' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2797db1d-b066-421a-8ead-c16e8b9e6116' class='xr-section-summary' >Data variables: <span>(6)</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>t</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>267.3 267.3 267.3 ... 250.8 250.8</div><input id='attrs-a0b84ee7-64d5-4a61-8090-5e334ded9b11' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a0b84ee7-64d5-4a61-8090-5e334ded9b11' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de13f943-2b62-443f-a7cd-40ce6cc8a96c' class='xr-var-data-in' type='checkbox'><label for='data-de13f943-2b62-443f-a7cd-40ce6cc8a96c' 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>GRIB_paramId :</span></dt><dd>130</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1905141</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>3000.0</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>3000.0</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>262.5</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1799</dd><dt><span>GRIB_Ny :</span></dt><dd>1059</dd><dt><span>GRIB_cfName :</span></dt><dd>air_temperature</dd><dt><span>GRIB_cfVarName :</span></dt><dd>t</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal can be secant or tangent, conical or bipolar</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>21.138123</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>237.280472</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>Temperature</dd><dt><span>GRIB_parameterName :</span></dt><dd>Temperature</dd><dt><span>GRIB_parameterUnits :</span></dt><dd>K</dd><dt><span>GRIB_shortName :</span></dt><dd>t</dd><dt><span>GRIB_stepRange :</span></dt><dd>0</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>grid_mapping :</span></dt><dd>gribfile_projection</dd></dl></div><div class='xr-var-data'><pre>array([[267.30746, 267.30746, 267.30746, ..., 267.55746, 267.55746,\n",
       "        267.55746],\n",
       "       [267.30746, 267.30746, 267.30746, ..., 267.55746, 267.55746,\n",
       "        267.49496],\n",
       "       [267.30746, 267.30746, 267.30746, ..., 267.49496, 267.49496,\n",
       "        267.49496],\n",
       "       ...,\n",
       "       [245.24496, 245.24496, 245.24496, ..., 250.74496, 250.74496,\n",
       "        250.80746],\n",
       "       [245.24496, 245.24496, 245.24496, ..., 250.74496, 250.74496,\n",
       "        250.80746],\n",
       "       [245.24496, 245.24496, 245.18246, ..., 250.74496, 250.80746,\n",
       "        250.80746]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>6.373 6.373 6.373 ... -1.94 -1.94</div><input id='attrs-77a16ee8-dff2-4a7c-b248-d9b66918c505' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-77a16ee8-dff2-4a7c-b248-d9b66918c505' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb7307fc-33fb-4fc7-b808-0826e3dfee18' class='xr-var-data-in' type='checkbox'><label for='data-bb7307fc-33fb-4fc7-b808-0826e3dfee18' 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>GRIB_paramId :</span></dt><dd>131</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1905141</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>3000.0</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>3000.0</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>262.5</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1799</dd><dt><span>GRIB_Ny :</span></dt><dd>1059</dd><dt><span>GRIB_cfName :</span></dt><dd>eastward_wind</dd><dt><span>GRIB_cfVarName :</span></dt><dd>u</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal can be secant or tangent, conical or bipolar</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>21.138123</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>237.280472</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>U component of wind</dd><dt><span>GRIB_parameterName :</span></dt><dd>u-component of wind</dd><dt><span>GRIB_parameterUnits :</span></dt><dd>m s-1</dd><dt><span>GRIB_shortName :</span></dt><dd>u</dd><dt><span>GRIB_stepRange :</span></dt><dd>0</dd><dt><span>GRIB_units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>U component of wind</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>standard_name :</span></dt><dd>eastward_wind</dd><dt><span>grid_mapping :</span></dt><dd>gribfile_projection</dd></dl></div><div class='xr-var-data'><pre>array([[ 6.372527 ,  6.372527 ,  6.372527 , ..., -2.5024729, -2.5024729,\n",
       "        -2.5649729],\n",
       "       [ 6.372527 ,  6.372527 ,  6.372527 , ..., -2.4399729, -2.5024729,\n",
       "        -2.5024729],\n",
       "       [ 6.372527 ,  6.372527 ,  6.372527 , ..., -2.4399729, -2.4399729,\n",
       "        -2.4399729],\n",
       "       ...,\n",
       "       [22.872528 , 22.747528 , 22.685028 , ..., -1.9399729, -1.9399729,\n",
       "        -1.9399729],\n",
       "       [22.872528 , 22.810028 , 22.685028 , ..., -1.9399729, -1.9399729,\n",
       "        -1.9399729],\n",
       "       [22.872528 , 22.810028 , 22.685028 , ..., -2.0024729, -1.9399729,\n",
       "        -1.9399729]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-4.079 -4.079 -4.079 ... 18.8 19.17</div><input id='attrs-3a0030ce-dd70-40cc-97e4-92d0b7b3776e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a0030ce-dd70-40cc-97e4-92d0b7b3776e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-58bd9d0e-d94c-41f3-90a7-fa38dff75da8' class='xr-var-data-in' type='checkbox'><label for='data-58bd9d0e-d94c-41f3-90a7-fa38dff75da8' 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>GRIB_paramId :</span></dt><dd>132</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1905141</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>3000.0</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>3000.0</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>262.5</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1799</dd><dt><span>GRIB_Ny :</span></dt><dd>1059</dd><dt><span>GRIB_cfName :</span></dt><dd>northward_wind</dd><dt><span>GRIB_cfVarName :</span></dt><dd>v</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal can be secant or tangent, conical or bipolar</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>21.138123</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>237.280472</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>V component of wind</dd><dt><span>GRIB_parameterName :</span></dt><dd>v-component of wind</dd><dt><span>GRIB_parameterUnits :</span></dt><dd>m s-1</dd><dt><span>GRIB_shortName :</span></dt><dd>v</dd><dt><span>GRIB_stepRange :</span></dt><dd>0</dd><dt><span>GRIB_units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>V component of wind</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>standard_name :</span></dt><dd>northward_wind</dd><dt><span>grid_mapping :</span></dt><dd>gribfile_projection</dd></dl></div><div class='xr-var-data'><pre>array([[ -4.079487 ,  -4.079487 ,  -4.079487 , ...,  -3.3294868,\n",
       "         -3.3919868,  -3.4544868],\n",
       "       [ -4.079487 ,  -4.079487 ,  -4.079487 , ...,  -3.3294868,\n",
       "         -3.3919868,  -3.3919868],\n",
       "       [ -4.141987 ,  -4.141987 ,  -4.079487 , ...,  -3.3294868,\n",
       "         -3.3294868,  -3.3919868],\n",
       "       ...,\n",
       "       [-15.391987 , -15.454487 , -15.516987 , ...,  18.483013 ,\n",
       "         18.795513 ,  19.108013 ],\n",
       "       [-15.329487 , -15.391987 , -15.454487 , ...,  18.483013 ,\n",
       "         18.795513 ,  19.170513 ],\n",
       "       [-15.266987 , -15.329487 , -15.391987 , ...,  18.483013 ,\n",
       "         18.795513 ,  19.170513 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gh</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>5.853e+03 5.853e+03 ... 5.308e+03</div><input id='attrs-0b324978-c84f-49d0-939a-23746fd3ce3f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b324978-c84f-49d0-939a-23746fd3ce3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4a2d35eb-128d-40e6-8b4b-414e9b85a75d' class='xr-var-data-in' type='checkbox'><label for='data-4a2d35eb-128d-40e6-8b4b-414e9b85a75d' 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>GRIB_paramId :</span></dt><dd>156</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1905141</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>3000.0</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>3000.0</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>262.5</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1799</dd><dt><span>GRIB_Ny :</span></dt><dd>1059</dd><dt><span>GRIB_cfName :</span></dt><dd>geopotential_height</dd><dt><span>GRIB_cfVarName :</span></dt><dd>gh</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal can be secant or tangent, conical or bipolar</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>21.138123</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>237.280472</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>Geopotential height</dd><dt><span>GRIB_parameterName :</span></dt><dd>Geopotential height</dd><dt><span>GRIB_parameterUnits :</span></dt><dd>gpm</dd><dt><span>GRIB_shortName :</span></dt><dd>gh</dd><dt><span>GRIB_stepRange :</span></dt><dd>0</dd><dt><span>GRIB_units :</span></dt><dd>gpm</dd><dt><span>long_name :</span></dt><dd>Geopotential height</dd><dt><span>units :</span></dt><dd>gpm</dd><dt><span>standard_name :</span></dt><dd>geopotential_height</dd><dt><span>grid_mapping :</span></dt><dd>gribfile_projection</dd></dl></div><div class='xr-var-data'><pre>array([[5852.5586, 5852.5273, 5852.5273, ..., 5878.9023, 5878.8086,\n",
       "        5878.715 ],\n",
       "       [5852.2773, 5852.2773, 5852.246 , ..., 5878.965 , 5878.84  ,\n",
       "        5878.715 ],\n",
       "       [5852.0273, 5851.996 , 5851.996 , ..., 5878.996 , 5878.84  ,\n",
       "        5878.6836],\n",
       "       ...,\n",
       "       [5466.9336, 5466.715 , 5466.496 , ..., 5304.871 , 5305.6836,\n",
       "        5306.496 ],\n",
       "       [5466.1523, 5465.871 , 5465.621 , ..., 5305.465 , 5306.2773,\n",
       "        5307.121 ],\n",
       "       [5465.371 , 5465.0586, 5464.746 , ..., 5306.09  , 5306.9023,\n",
       "        5307.715 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dpt</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>244.5 244.4 244.2 ... 229.4 229.2</div><input id='attrs-f7d13448-cde7-432f-8e20-3bf9b8107a2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7d13448-cde7-432f-8e20-3bf9b8107a2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85e2aef7-5b06-46f7-a6a7-bfc737019c8e' class='xr-var-data-in' type='checkbox'><label for='data-85e2aef7-5b06-46f7-a6a7-bfc737019c8e' 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>GRIB_paramId :</span></dt><dd>3017</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1905141</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>3000.0</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>3000.0</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>262.5</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1799</dd><dt><span>GRIB_Ny :</span></dt><dd>1059</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>dpt</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal can be secant or tangent, conical or bipolar</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>21.138123</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>237.280472</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>Dew point temperature</dd><dt><span>GRIB_parameterName :</span></dt><dd>Dew point temperature</dd><dt><span>GRIB_parameterUnits :</span></dt><dd>K</dd><dt><span>GRIB_shortName :</span></dt><dd>dpt</dd><dt><span>GRIB_stepRange :</span></dt><dd>0</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Dew point temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>grid_mapping :</span></dt><dd>gribfile_projection</dd></dl></div><div class='xr-var-data'><pre>array([[244.49979, 244.37479, 244.18729, ..., 240.68729, 240.68729,\n",
       "        240.74979],\n",
       "       [244.49979, 244.49979, 244.37479, ..., 240.68729, 240.74979,\n",
       "        240.81229],\n",
       "       [244.43729, 244.43729, 244.31229, ..., 240.74979, 240.81229,\n",
       "        240.81229],\n",
       "       ...,\n",
       "       [239.74979, 239.74979, 239.74979, ..., 229.62479, 229.43729,\n",
       "        229.37479],\n",
       "       [239.81229, 239.81229, 239.74979, ..., 229.56229, 229.37479,\n",
       "        229.37479],\n",
       "       [239.87479, 239.81229, 239.74979, ..., 229.49979, 229.37479,\n",
       "        229.24979]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gribfile_projection</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>None</div><input id='attrs-a540ab3c-a0a2-4a18-a37b-cdd3c0d26c8a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a540ab3c-a0a2-4a18-a37b-cdd3c0d26c8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7176032d-43bd-4f9b-b84a-07ca0ee47dbd' class='xr-var-data-in' type='checkbox'><label for='data-7176032d-43bd-4f9b-b84a-07ca0ee47dbd' 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>crs_wkt :</span></dt><dd>PROJCRS[&quot;unknown&quot;,BASEGEOGCRS[&quot;unknown&quot;,DATUM[&quot;unknown&quot;,ELLIPSOID[&quot;unknown&quot;,6371229,0,LENGTHUNIT[&quot;metre&quot;,1,ID[&quot;EPSG&quot;,9001]]]],PRIMEM[&quot;Greenwich&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8901]]],CONVERSION[&quot;unknown&quot;,METHOD[&quot;Lambert Conic Conformal (2SP)&quot;,ID[&quot;EPSG&quot;,9802]],PARAMETER[&quot;Latitude of false origin&quot;,38.5,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8821]],PARAMETER[&quot;Longitude of false origin&quot;,262.5,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8822]],PARAMETER[&quot;Latitude of 1st standard parallel&quot;,38.5,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8823]],PARAMETER[&quot;Latitude of 2nd standard parallel&quot;,38.5,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8824]],PARAMETER[&quot;Easting at false origin&quot;,0,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8826]],PARAMETER[&quot;Northing at false origin&quot;,0,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8827]]],CS[Cartesian,2],AXIS[&quot;(E)&quot;,east,ORDER[1],LENGTHUNIT[&quot;metre&quot;,1,ID[&quot;EPSG&quot;,9001]]],AXIS[&quot;(N)&quot;,north,ORDER[2],LENGTHUNIT[&quot;metre&quot;,1,ID[&quot;EPSG&quot;,9001]]]]</dd><dt><span>semi_major_axis :</span></dt><dd>6371229.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6371229.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>unknown</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>unknown</dd><dt><span>horizontal_datum_name :</span></dt><dd>unknown</dd><dt><span>projected_crs_name :</span></dt><dd>unknown</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>(38.5, 38.5)</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>38.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>262.5</dd><dt><span>false_easting :</span></dt><dd>0.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>long_name :</span></dt><dd>HRRR model grid projection</dd></dl></div><div class='xr-var-data'><pre>array(None, dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-eed2b8c7-71f1-4441-b8cb-c33bb6865464' class='xr-section-summary-in' type='checkbox'  ><label for='section-eed2b8c7-71f1-4441-b8cb-c33bb6865464' class='xr-section-summary' >Attributes: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>GRIB_edition :</span></dt><dd>2</dd><dt><span>GRIB_centre :</span></dt><dd>kwbc</dd><dt><span>GRIB_centreDescription :</span></dt><dd>US National Weather Service - NCEP</dd><dt><span>GRIB_subCentre :</span></dt><dd>0</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>institution :</span></dt><dd>US National Weather Service - NCEP</dd><dt><span>model :</span></dt><dd>hrrr</dd><dt><span>product :</span></dt><dd>sfc</dd><dt><span>description :</span></dt><dd>High-Resolution Rapid Refresh - CONUS</dd><dt><span>remote_grib :</span></dt><dd>https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr.20220402/conus/hrrr.t06z.wrfsfcf00.grib2</dd><dt><span>local_grib :</span></dt><dd>C:\\Users\\blayl_depgywe\\data\\hrrr\\20220402\\hrrr.t06z.wrfsfcf00.grib2.subset_8a05a62e3e874603b5d6b37737904e0ec526ce1a</dd><dt><span>searchString :</span></dt><dd>:500 mb</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:              (y: 1059, x: 1799)\n",
       "Coordinates:\n",
       "    time                 datetime64[ns] 2022-04-02T06:00:00\n",
       "    step                 timedelta64[ns] 00:00:00\n",
       "    isobaricInhPa        float64 500.0\n",
       "    latitude             (y, x) float64 21.14 21.15 21.15 ... 47.86 47.85 47.84\n",
       "    longitude            (y, x) float64 237.3 237.3 237.3 ... 299.0 299.0 299.1\n",
       "    valid_time           datetime64[ns] 2022-04-02T06:00:00\n",
       "Dimensions without coordinates: y, x\n",
       "Data variables:\n",
       "    t                    (y, x) float32 267.3 267.3 267.3 ... 250.7 250.8 250.8\n",
       "    u                    (y, x) float32 6.373 6.373 6.373 ... -2.002 -1.94 -1.94\n",
       "    v                    (y, x) float32 -4.079 -4.079 -4.079 ... 18.8 19.17\n",
       "    gh                   (y, x) float32 5.853e+03 5.853e+03 ... 5.308e+03\n",
       "    dpt                  (y, x) float32 244.5 244.4 244.2 ... 229.5 229.4 229.2\n",
       "    gribfile_projection  object None\n",
       "Attributes:\n",
       "    GRIB_edition:            2\n",
       "    GRIB_centre:             kwbc\n",
       "    GRIB_centreDescription:  US National Weather Service - NCEP\n",
       "    GRIB_subCentre:          0\n",
       "    Conventions:             CF-1.7\n",
       "    institution:             US National Weather Service - NCEP\n",
       "    model:                   hrrr\n",
       "    product:                 sfc\n",
       "    description:             High-Resolution Rapid Refresh - CONUS\n",
       "    remote_grib:             https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr....\n",
       "    local_grib:              C:\\Users\\blayl_depgywe\\data\\hrrr\\20220402\\hrrr.t...\n",
       "    searchString:            :500 mb"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read file with xarray that does not exists on disk\n",
    "H = Herbie(\"2022-4-2 06:00\", fxx=0)\n",
    "Hx = H.xarray(\":500 mb\", verbose=True)\n",
    "Hx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "4b059270-ab87-4778-8613-65df7cd4f90c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Notice that the local grib subset file does not exists locally because it was removed\n",
    "Hx.attrs[\"local_grib\"].exists()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "5c031219-0c67-490b-9131-103b41d40a0b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🏋🏻‍♂️ Found \u001b[32m2021-May-06 00:00 UTC F00\u001b[0m [HRRR] [product=sfc] GRIB2 file from \u001b[31maws\u001b[0m and index file from \u001b[31maws\u001b[0m.                                                                                                                                                       \n",
      "👨🏻‍🏭 Created directory: [C:\\Users\\blayl_depgywe\\data\\hrrr\\20210506]\n"
     ]
    },
    {
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       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:              (y: 1059, x: 1799)\n",
       "Coordinates:\n",
       "    time                 datetime64[ns] 2021-05-06\n",
       "    step                 timedelta64[ns] 00:00:00\n",
       "    isobaricInhPa        float64 500.0\n",
       "    latitude             (y, x) float64 21.14 21.15 21.15 ... 47.86 47.85 47.84\n",
       "    longitude            (y, x) float64 237.3 237.3 237.3 ... 299.0 299.0 299.1\n",
       "    valid_time           datetime64[ns] 2021-05-06\n",
       "Dimensions without coordinates: y, x\n",
       "Data variables:\n",
       "    t                    (y, x) float32 ...\n",
       "    u                    (y, x) float32 ...\n",
       "    v                    (y, x) float32 ...\n",
       "    gh                   (y, x) float32 ...\n",
       "    dpt                  (y, x) float32 ...\n",
       "    gribfile_projection  object None\n",
       "Attributes:\n",
       "    GRIB_edition:            2\n",
       "    GRIB_centre:             kwbc\n",
       "    GRIB_centreDescription:  US National Weather Service - NCEP\n",
       "    GRIB_subCentre:          0\n",
       "    Conventions:             CF-1.7\n",
       "    institution:             US National Weather Service - NCEP\n",
       "    model:                   hrrr\n",
       "    product:                 sfc\n",
       "    description:             High-Resolution Rapid Refresh - CONUS\n",
       "    remote_grib:             https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr....\n",
       "    local_grib:              C:\\Users\\blayl_depgywe\\data\\hrrr\\20210506\\hrrr.t...\n",
       "    searchString:            :500 mb</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-f561287b-66b9-4cee-9e43-93172e25ec68' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f561287b-66b9-4cee-9e43-93172e25ec68' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>y</span>: 1059</li><li><span>x</span>: 1799</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-2f071306-5be2-4a41-a3b6-40c28397caea' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2f071306-5be2-4a41-a3b6-40c28397caea' class='xr-section-summary' >Coordinates: <span>(6)</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>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-05-06</div><input id='attrs-df1092a9-57f2-4166-a5a2-e81606217b74' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-df1092a9-57f2-4166-a5a2-e81606217b74' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-82c5177f-7e9d-4285-ab55-c3fbd5139477' class='xr-var-data-in' type='checkbox'><label for='data-82c5177f-7e9d-4285-ab55-c3fbd5139477' 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>initial time of forecast</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2021-05-06T00:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>00:00:00</div><input id='attrs-b2c96346-d201-4ed9-b548-c39efca1e9cf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2c96346-d201-4ed9-b548-c39efca1e9cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db93acd4-6950-4ce8-9ad7-1b2b97ffa984' class='xr-var-data-in' type='checkbox'><label for='data-db93acd4-6950-4ce8-9ad7-1b2b97ffa984' 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 since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>array(0, dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>isobaricInhPa</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>500.0</div><input id='attrs-075741c0-0c07-451e-b1f5-2a5576a0794e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-075741c0-0c07-451e-b1f5-2a5576a0794e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ea45e01-6cb3-4a8a-bc3f-b9e17f4828ea' class='xr-var-data-in' type='checkbox'><label for='data-3ea45e01-6cb3-4a8a-bc3f-b9e17f4828ea' 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>pressure</dd><dt><span>units :</span></dt><dd>hPa</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>stored_direction :</span></dt><dd>decreasing</dd><dt><span>standard_name :</span></dt><dd>air_pressure</dd></dl></div><div class='xr-var-data'><pre>array(500.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>21.14 21.15 21.15 ... 47.85 47.84</div><input id='attrs-3dc0ee68-cbf2-4a10-9f6f-0ed5dfa156f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3dc0ee68-cbf2-4a10-9f6f-0ed5dfa156f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-82e07caa-3261-4edc-bdc3-68189ae855c9' class='xr-var-data-in' type='checkbox'><label for='data-82e07caa-3261-4edc-bdc3-68189ae855c9' 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>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([[21.138123  , 21.14511004, 21.1520901 , ..., 21.1545089 ,\n",
       "        21.14753125, 21.14054663],\n",
       "       [21.16299459, 21.1699845 , 21.17696744, ..., 21.17938723,\n",
       "        21.1724067 , 21.16541921],\n",
       "       [21.18786863, 21.19486142, 21.20184723, ..., 21.20426802,\n",
       "        21.19728462, 21.19029425],\n",
       "       ...,\n",
       "       [47.78955926, 47.799849  , 47.81012868, ..., 47.81369093,\n",
       "        47.80341474, 47.79312849],\n",
       "       [47.81409316, 47.82438621, 47.8346692 , ..., 47.83823259,\n",
       "        47.8279531 , 47.81766354],\n",
       "       [47.8386235 , 47.84891986, 47.85920615, ..., 47.86277069,\n",
       "        47.85248789, 47.84219502]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>237.3 237.3 237.3 ... 299.0 299.1</div><input id='attrs-01181ee7-908e-48c3-9193-59b0ab118d73' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-01181ee7-908e-48c3-9193-59b0ab118d73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-085c8e5b-50e1-4b21-9e45-d5c0c21d306b' class='xr-var-data-in' type='checkbox'><label for='data-085c8e5b-50e1-4b21-9e45-d5c0c21d306b' 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>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([[237.280472  , 237.30713868, 237.3338097 , ..., 287.6569408 ,\n",
       "        287.68361332, 287.71028151],\n",
       "       [237.27297501, 237.29964881, 237.32632695, ..., 287.66442108,\n",
       "        287.69110073, 287.71777603],\n",
       "       [237.26547368, 237.2921546 , 237.31883986, ..., 287.6719057 ,\n",
       "        287.69859247, 287.7252749 ],\n",
       "       ...,\n",
       "       [225.9351904 , 225.97171577, 226.00825329, ..., 298.97907406,\n",
       "        299.0156158 , 299.05214538],\n",
       "       [225.91986142, 225.95639874, 225.99294822, ..., 298.99437498,\n",
       "        299.03092868, 299.06747022],\n",
       "       [225.90452027, 225.94106954, 225.97763099, ..., 299.00968806,\n",
       "        299.04625373, 299.08280723]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>valid_time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-05-06</div><input id='attrs-607d3aaa-5505-4efb-b694-9ecf85974a48' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-607d3aaa-5505-4efb-b694-9ecf85974a48' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a333639-19e9-4e53-8155-6bcb4d367ce7' class='xr-var-data-in' type='checkbox'><label for='data-7a333639-19e9-4e53-8155-6bcb4d367ce7' 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>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2021-05-06T00:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2977cde6-421a-46e2-9c2a-76402b978c73' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2977cde6-421a-46e2-9c2a-76402b978c73' class='xr-section-summary' >Data variables: <span>(6)</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>t</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d02b96fa-bd47-4b4b-bf3e-dcd31f835bbf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d02b96fa-bd47-4b4b-bf3e-dcd31f835bbf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8cf7b4ff-2d55-4e52-a203-6c1d3b584e51' class='xr-var-data-in' type='checkbox'><label for='data-8cf7b4ff-2d55-4e52-a203-6c1d3b584e51' 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>GRIB_paramId :</span></dt><dd>130</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1905141</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>3000.0</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>3000.0</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>262.5</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1799</dd><dt><span>GRIB_Ny :</span></dt><dd>1059</dd><dt><span>GRIB_cfName :</span></dt><dd>air_temperature</dd><dt><span>GRIB_cfVarName :</span></dt><dd>t</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal can be secant or tangent, conical or bipolar</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>21.138123</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>237.280472</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>Temperature</dd><dt><span>GRIB_parameterName :</span></dt><dd>Temperature</dd><dt><span>GRIB_parameterUnits :</span></dt><dd>K</dd><dt><span>GRIB_shortName :</span></dt><dd>t</dd><dt><span>GRIB_stepRange :</span></dt><dd>0</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>grid_mapping :</span></dt><dd>gribfile_projection</dd></dl></div><div class='xr-var-data'><pre>[1905141 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-443ce24b-3c96-47be-8a6b-c8478f1d3e41' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-443ce24b-3c96-47be-8a6b-c8478f1d3e41' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1751b9c7-8384-45a4-987d-aa6d02821c20' class='xr-var-data-in' type='checkbox'><label for='data-1751b9c7-8384-45a4-987d-aa6d02821c20' 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>GRIB_paramId :</span></dt><dd>131</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1905141</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>3000.0</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>3000.0</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>262.5</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1799</dd><dt><span>GRIB_Ny :</span></dt><dd>1059</dd><dt><span>GRIB_cfName :</span></dt><dd>eastward_wind</dd><dt><span>GRIB_cfVarName :</span></dt><dd>u</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal can be secant or tangent, conical or bipolar</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>21.138123</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>237.280472</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>U component of wind</dd><dt><span>GRIB_parameterName :</span></dt><dd>u-component of wind</dd><dt><span>GRIB_parameterUnits :</span></dt><dd>m s-1</dd><dt><span>GRIB_shortName :</span></dt><dd>u</dd><dt><span>GRIB_stepRange :</span></dt><dd>0</dd><dt><span>GRIB_units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>U component of wind</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>standard_name :</span></dt><dd>eastward_wind</dd><dt><span>grid_mapping :</span></dt><dd>gribfile_projection</dd></dl></div><div class='xr-var-data'><pre>[1905141 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5133e316-f7c0-43e1-a664-2ee3bf439506' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5133e316-f7c0-43e1-a664-2ee3bf439506' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1b17090-f412-4e61-9917-96983e58117f' class='xr-var-data-in' type='checkbox'><label for='data-f1b17090-f412-4e61-9917-96983e58117f' 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>GRIB_paramId :</span></dt><dd>132</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1905141</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>3000.0</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>3000.0</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>262.5</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1799</dd><dt><span>GRIB_Ny :</span></dt><dd>1059</dd><dt><span>GRIB_cfName :</span></dt><dd>northward_wind</dd><dt><span>GRIB_cfVarName :</span></dt><dd>v</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal can be secant or tangent, conical or bipolar</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>21.138123</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>237.280472</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>V component of wind</dd><dt><span>GRIB_parameterName :</span></dt><dd>v-component of wind</dd><dt><span>GRIB_parameterUnits :</span></dt><dd>m s-1</dd><dt><span>GRIB_shortName :</span></dt><dd>v</dd><dt><span>GRIB_stepRange :</span></dt><dd>0</dd><dt><span>GRIB_units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>V component of wind</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>standard_name :</span></dt><dd>northward_wind</dd><dt><span>grid_mapping :</span></dt><dd>gribfile_projection</dd></dl></div><div class='xr-var-data'><pre>[1905141 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gh</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b249046e-0399-4900-ae2a-3c2df3da910a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b249046e-0399-4900-ae2a-3c2df3da910a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-49edc578-40f9-4fb5-b8a7-c3f587904ef9' class='xr-var-data-in' type='checkbox'><label for='data-49edc578-40f9-4fb5-b8a7-c3f587904ef9' 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>GRIB_paramId :</span></dt><dd>156</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1905141</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>3000.0</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>3000.0</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>262.5</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1799</dd><dt><span>GRIB_Ny :</span></dt><dd>1059</dd><dt><span>GRIB_cfName :</span></dt><dd>geopotential_height</dd><dt><span>GRIB_cfVarName :</span></dt><dd>gh</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal can be secant or tangent, conical or bipolar</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>21.138123</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>237.280472</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>Geopotential height</dd><dt><span>GRIB_parameterName :</span></dt><dd>Geopotential height</dd><dt><span>GRIB_parameterUnits :</span></dt><dd>gpm</dd><dt><span>GRIB_shortName :</span></dt><dd>gh</dd><dt><span>GRIB_stepRange :</span></dt><dd>0</dd><dt><span>GRIB_units :</span></dt><dd>gpm</dd><dt><span>long_name :</span></dt><dd>Geopotential height</dd><dt><span>units :</span></dt><dd>gpm</dd><dt><span>standard_name :</span></dt><dd>geopotential_height</dd><dt><span>grid_mapping :</span></dt><dd>gribfile_projection</dd></dl></div><div class='xr-var-data'><pre>[1905141 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dpt</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b0b8edab-5162-4baf-a1e0-f56b7f342636' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0b8edab-5162-4baf-a1e0-f56b7f342636' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5fbff77-5cfd-4e11-9cce-332ac22abdf5' class='xr-var-data-in' type='checkbox'><label for='data-f5fbff77-5cfd-4e11-9cce-332ac22abdf5' 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>GRIB_paramId :</span></dt><dd>3017</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1905141</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>3000.0</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>3000.0</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>38.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>262.5</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1799</dd><dt><span>GRIB_Ny :</span></dt><dd>1059</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>dpt</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal can be secant or tangent, conical or bipolar</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>21.138123</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>237.280472</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>Dew point temperature</dd><dt><span>GRIB_parameterName :</span></dt><dd>Dew point temperature</dd><dt><span>GRIB_parameterUnits :</span></dt><dd>K</dd><dt><span>GRIB_shortName :</span></dt><dd>dpt</dd><dt><span>GRIB_stepRange :</span></dt><dd>0</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Dew point temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>grid_mapping :</span></dt><dd>gribfile_projection</dd></dl></div><div class='xr-var-data'><pre>[1905141 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gribfile_projection</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>None</div><input id='attrs-5a6f39f6-16f9-4ab5-872d-1ca1cac5ff3d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a6f39f6-16f9-4ab5-872d-1ca1cac5ff3d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-803b277a-50db-4c7d-a209-2717564f4583' class='xr-var-data-in' type='checkbox'><label for='data-803b277a-50db-4c7d-a209-2717564f4583' 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>crs_wkt :</span></dt><dd>PROJCRS[&quot;unknown&quot;,BASEGEOGCRS[&quot;unknown&quot;,DATUM[&quot;unknown&quot;,ELLIPSOID[&quot;unknown&quot;,6371229,0,LENGTHUNIT[&quot;metre&quot;,1,ID[&quot;EPSG&quot;,9001]]]],PRIMEM[&quot;Greenwich&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8901]]],CONVERSION[&quot;unknown&quot;,METHOD[&quot;Lambert Conic Conformal (2SP)&quot;,ID[&quot;EPSG&quot;,9802]],PARAMETER[&quot;Latitude of false origin&quot;,38.5,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8821]],PARAMETER[&quot;Longitude of false origin&quot;,262.5,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8822]],PARAMETER[&quot;Latitude of 1st standard parallel&quot;,38.5,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8823]],PARAMETER[&quot;Latitude of 2nd standard parallel&quot;,38.5,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8824]],PARAMETER[&quot;Easting at false origin&quot;,0,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8826]],PARAMETER[&quot;Northing at false origin&quot;,0,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8827]]],CS[Cartesian,2],AXIS[&quot;(E)&quot;,east,ORDER[1],LENGTHUNIT[&quot;metre&quot;,1,ID[&quot;EPSG&quot;,9001]]],AXIS[&quot;(N)&quot;,north,ORDER[2],LENGTHUNIT[&quot;metre&quot;,1,ID[&quot;EPSG&quot;,9001]]]]</dd><dt><span>semi_major_axis :</span></dt><dd>6371229.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6371229.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>unknown</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>unknown</dd><dt><span>horizontal_datum_name :</span></dt><dd>unknown</dd><dt><span>projected_crs_name :</span></dt><dd>unknown</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>(38.5, 38.5)</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>38.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>262.5</dd><dt><span>false_easting :</span></dt><dd>0.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>long_name :</span></dt><dd>HRRR model grid projection</dd></dl></div><div class='xr-var-data'><pre>array(None, dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cda0f023-d1b1-4a2e-b522-2952a9e7ea40' class='xr-section-summary-in' type='checkbox'  ><label for='section-cda0f023-d1b1-4a2e-b522-2952a9e7ea40' class='xr-section-summary' >Attributes: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>GRIB_edition :</span></dt><dd>2</dd><dt><span>GRIB_centre :</span></dt><dd>kwbc</dd><dt><span>GRIB_centreDescription :</span></dt><dd>US National Weather Service - NCEP</dd><dt><span>GRIB_subCentre :</span></dt><dd>0</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>institution :</span></dt><dd>US National Weather Service - NCEP</dd><dt><span>model :</span></dt><dd>hrrr</dd><dt><span>product :</span></dt><dd>sfc</dd><dt><span>description :</span></dt><dd>High-Resolution Rapid Refresh - CONUS</dd><dt><span>remote_grib :</span></dt><dd>https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr.20210506/conus/hrrr.t00z.wrfsfcf00.grib2</dd><dt><span>local_grib :</span></dt><dd>C:\\Users\\blayl_depgywe\\data\\hrrr\\20210506\\hrrr.t00z.wrfsfcf00.grib2.subset_8a05a62e3e874603b5d6b37737904e0ec526ce1a</dd><dt><span>searchString :</span></dt><dd>:500 mb</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:              (y: 1059, x: 1799)\n",
       "Coordinates:\n",
       "    time                 datetime64[ns] 2021-05-06\n",
       "    step                 timedelta64[ns] 00:00:00\n",
       "    isobaricInhPa        float64 500.0\n",
       "    latitude             (y, x) float64 21.14 21.15 21.15 ... 47.86 47.85 47.84\n",
       "    longitude            (y, x) float64 237.3 237.3 237.3 ... 299.0 299.0 299.1\n",
       "    valid_time           datetime64[ns] 2021-05-06\n",
       "Dimensions without coordinates: y, x\n",
       "Data variables:\n",
       "    t                    (y, x) float32 ...\n",
       "    u                    (y, x) float32 ...\n",
       "    v                    (y, x) float32 ...\n",
       "    gh                   (y, x) float32 ...\n",
       "    dpt                  (y, x) float32 ...\n",
       "    gribfile_projection  object None\n",
       "Attributes:\n",
       "    GRIB_edition:            2\n",
       "    GRIB_centre:             kwbc\n",
       "    GRIB_centreDescription:  US National Weather Service - NCEP\n",
       "    GRIB_subCentre:          0\n",
       "    Conventions:             CF-1.7\n",
       "    institution:             US National Weather Service - NCEP\n",
       "    model:                   hrrr\n",
       "    product:                 sfc\n",
       "    description:             High-Resolution Rapid Refresh - CONUS\n",
       "    remote_grib:             https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr....\n",
       "    local_grib:              C:\\Users\\blayl_depgywe\\data\\hrrr\\20210506\\hrrr.t...\n",
       "    searchString:            :500 mb"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# You can tell xarray not to delete the grib2 file\n",
    "H = Herbie(\"2021-5-6\", fxx=0)\n",
    "Hx = H.xarray(\":500 mb\", remove_grib=False)\n",
    "Hx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "38f564af-aacd-415b-ae94-f6c4a0b172a6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The local grib does exists\n",
    "Hx.attrs[\"local_grib\"].exists()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94fe2e80-0a4f-4e4e-ae4c-20f1be18a7ec",
   "metadata": {},
   "source": [
    "## Working with multiple Herbie objects\n",
    "Use the **fast Herbie** functions when you want to work with multiple files at once. Fast Herbie uses multithreading to increase the speed of sequentially creating Herbie objects. \n",
    "\n",
    "Creating a Herbie object is a lot of network traffic (Herbie check if a GRIB2 file exits at a lot of different remote archives and also looks for index files). Herbie also downloads the GRIB2 files, which is also mainly done over the network, and reading the data into xarray depends on the downloads.\n",
    "\n",
    "Multithreading is useful for I/O bound tasks. As I understand, communication across the internet falls under this category. So multi threads can be helpful when creating many Herbie objects.\n",
    "\n",
    "- Creating lots of Herbie objects (`herbie.tools.fast_Herbie`)\n",
    "- Downloading lots of files (`herbie.tools.fast_Herbie_download`)\n",
    "- Loading lots of files into xarray (`herbie.tools.fast_Herbie_xarray`)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "85d6fb3b-6cc3-4c95-a75b-5becc4259be5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from herbie.tools import fast_Herbie, fast_Herbie_download, fast_Herbie_xarray\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "31fbec98-4bd3-4e13-825f-57e9fdc72b51",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use pandas to create a list of Datetimes\n",
    "DATES = pd.date_range(\"2022-01-01\", periods=6, freq=\"1H\")\n",
    "\n",
    "# Create a list of forecast lead times\n",
    "fxx = [0, 1, 2, 3, 4, 5, 6]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c075c1ac",
   "metadata": {},
   "source": [
    "### Fast Herbie\n",
    "Create many Herbie objects for all the dates and lead times requested."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "48eb2d74-b449-4ef0-bcbf-ff7e7dfefb94",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(42,\n",
       " [[HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 00:00 UTC F00\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 00:00 UTC F01\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 00:00 UTC F02\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 00:00 UTC F03\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 00:00 UTC F04\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 00:00 UTC F05\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 00:00 UTC F06\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 01:00 UTC F00\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 01:00 UTC F01\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 01:00 UTC F02\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 01:00 UTC F03\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 01:00 UTC F04\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 01:00 UTC F05\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 01:00 UTC F06\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 02:00 UTC F00\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 02:00 UTC F01\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 02:00 UTC F02\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 02:00 UTC F03\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 02:00 UTC F04\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 02:00 UTC F05\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 02:00 UTC F06\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 03:00 UTC F00\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 03:00 UTC F01\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 03:00 UTC F02\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 03:00 UTC F03\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 03:00 UTC F04\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 03:00 UTC F05\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 03:00 UTC F06\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 04:00 UTC F00\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 04:00 UTC F01\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 04:00 UTC F02\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 04:00 UTC F03\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 04:00 UTC F04\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 04:00 UTC F05\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 04:00 UTC F06\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 05:00 UTC F00\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 05:00 UTC F01\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 05:00 UTC F02\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 05:00 UTC F03\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 05:00 UTC F04\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 05:00 UTC F05\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 05:00 UTC F06\u001b[0m])"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create many Herbie objects (for all dates and lead times requested)\n",
    "HH = fast_Herbie(DATES=DATES, fxx=fxx)\n",
    "len(HH), HH"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3861c06",
   "metadata": {},
   "source": [
    "### Fast Herbie Download\n",
    "Download the files for a subset of many Herbie objects"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "c90982ea",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "👨🏻‍🏭 Created directory: [C:\\Users\\blayl_depgywe\\data\\hrrr\\20220101]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'passed': [[HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 00:00 UTC F00\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 00:00 UTC F01\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 00:00 UTC F02\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 00:00 UTC F03\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 00:00 UTC F04\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 00:00 UTC F05\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 00:00 UTC F06\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 01:00 UTC F00\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 01:00 UTC F01\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 01:00 UTC F02\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 01:00 UTC F03\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 01:00 UTC F04\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 01:00 UTC F05\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 01:00 UTC F06\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 02:00 UTC F00\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 02:00 UTC F01\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 02:00 UTC F02\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 02:00 UTC F03\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 02:00 UTC F04\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 02:00 UTC F05\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 02:00 UTC F06\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 03:00 UTC F00\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 03:00 UTC F01\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 03:00 UTC F02\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 03:00 UTC F03\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 03:00 UTC F04\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 03:00 UTC F05\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 03:00 UTC F06\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 04:00 UTC F00\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 04:00 UTC F01\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 04:00 UTC F02\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 04:00 UTC F03\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 04:00 UTC F04\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 04:00 UTC F05\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 04:00 UTC F06\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 05:00 UTC F00\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 05:00 UTC F01\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 05:00 UTC F02\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 05:00 UTC F03\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 05:00 UTC F04\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 05:00 UTC F05\u001b[0m,\n",
       "  [HRRR] model [sfc] product run at \u001b[32m2022-Jan-01 05:00 UTC F06\u001b[0m],\n",
       " 'failed': []}"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Download those Herbie objects (subset by 2-m temperature)\n",
    "a = fast_Herbie_download(DATES=DATES, fxx=fxx, searchString=\"TMP:2 m\")\n",
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbcc5d9f",
   "metadata": {},
   "source": [
    "### Fast Herbie xarray\n",
    "Read the data into an xarray DataFrame. Notice that this concatenates all the files along the datetime (t) and lead time (f) dimensions. \n",
    "\n",
    "> NOTE: The searchString ***must*** return data on the same hyper cube (data must be on the same type of level; see cfgrib for more details). For instance, you shouldn't load 2-m and 500 hPa data in the same object. \n",
    "\n",
    "> WARNING: Could run into memory limit if requesting too much data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "bd8274b7",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\blayl_depgywe\\BB_python\\Herbie\\herbie\\archive.py:950: UserWarning: sorry, on windows I couldn't remove the file.\n",
      "  warnings.warn(\"sorry, on windows I couldn't remove the file.\")\n",
      "C:\\Users\\blayl_depgywe\\BB_python\\Herbie\\herbie\\archive.py:950: UserWarning: sorry, on windows I couldn't remove the file.\n",
      "  warnings.warn(\"sorry, on windows I couldn't remove the file.\")\n",
      "C:\\Users\\blayl_depgywe\\BB_python\\Herbie\\herbie\\archive.py:950: UserWarning: sorry, on windows I couldn't remove the file.\n",
      "  warnings.warn(\"sorry, on windows I couldn't remove the file.\")\n",
      "C:\\Users\\blayl_depgywe\\BB_python\\Herbie\\herbie\\archive.py:950: UserWarning: sorry, on windows I couldn't remove the file.\n",
      "  warnings.warn(\"sorry, on windows I couldn't remove the file.\")\n",
      "C:\\Users\\blayl_depgywe\\BB_python\\Herbie\\herbie\\archive.py:950: UserWarning: sorry, on windows I couldn't remove the file.\n",
      "  warnings.warn(\"sorry, on windows I couldn't remove the file.\")\n"
     ]
    },
    {
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       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:              (t: 3, f: 2, y: 1059, x: 1799)\n",
       "Coordinates:\n",
       "    time                 (t) datetime64[ns] 2022-01-01 ... 2022-01-01T02:00:00\n",
       "    step                 (f) timedelta64[ns] 00:00:00 06:00:00\n",
       "    heightAboveGround    float64 10.0\n",
       "    latitude             (y, x) float64 21.14 21.15 21.15 ... 47.86 47.85 47.84\n",
       "    longitude            (y, x) float64 237.3 237.3 237.3 ... 299.0 299.0 299.1\n",
       "    valid_time           (f, t) datetime64[ns] 2022-01-01 ... 2022-01-01T08:0...\n",
       "Dimensions without coordinates: t, f, y, x\n",
       "Data variables:\n",
       "    u10                  (f, t, y, x) float32 -3.392 -3.33 ... -1.313 -1.375\n",
       "    v10                  (f, t, y, x) float32 -5.777 -5.777 ... 2.929 2.991\n",
       "    gribfile_projection  (f, t) object None None None None None None</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-e266e43c-8f9a-4c99-bb5c-f93feea83635' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e266e43c-8f9a-4c99-bb5c-f93feea83635' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>t</span>: 3</li><li><span>f</span>: 2</li><li><span>y</span>: 1059</li><li><span>x</span>: 1799</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-76e10d14-f28b-4734-8cd5-05b97f01cafb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-76e10d14-f28b-4734-8cd5-05b97f01cafb' class='xr-section-summary' >Coordinates: <span>(6)</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>time</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-01-01T02:00:00</div><input id='attrs-643b2ba4-fa2b-48b9-941a-83ee5ca3b8df' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-643b2ba4-fa2b-48b9-941a-83ee5ca3b8df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29c7e72c-569a-4751-a2ce-f395547c8640' class='xr-var-data-in' type='checkbox'><label for='data-29c7e72c-569a-4751-a2ce-f395547c8640' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-01T01:00:00.000000000&#x27;,\n",
       "       &#x27;2022-01-01T02:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step</span></div><div class='xr-var-dims'>(f)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>00:00:00 06:00:00</div><input id='attrs-d9f24dce-598b-4764-8094-08372ffeee54' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d9f24dce-598b-4764-8094-08372ffeee54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-55bf0e1b-dd2d-49b0-b968-df04ad9e1768' class='xr-var-data-in' type='checkbox'><label for='data-55bf0e1b-dd2d-49b0-b968-df04ad9e1768' 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'></dl></div><div class='xr-var-data'><pre>array([             0, 21600000000000], dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heightAboveGround</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>10.0</div><input id='attrs-05d08e81-9c2b-4041-a316-4c36759dbc1f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-05d08e81-9c2b-4041-a316-4c36759dbc1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f126a09c-1e72-470a-8600-8d0dbae054bf' class='xr-var-data-in' type='checkbox'><label for='data-f126a09c-1e72-470a-8600-8d0dbae054bf' 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>height above the surface</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(10.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>21.14 21.15 21.15 ... 47.85 47.84</div><input id='attrs-adf06461-2f82-467a-82f8-444cab45aba8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-adf06461-2f82-467a-82f8-444cab45aba8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1953f395-1019-4403-8a36-1959e536177a' class='xr-var-data-in' type='checkbox'><label for='data-1953f395-1019-4403-8a36-1959e536177a' 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>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([[21.138123  , 21.14511004, 21.1520901 , ..., 21.1545089 ,\n",
       "        21.14753125, 21.14054663],\n",
       "       [21.16299459, 21.1699845 , 21.17696744, ..., 21.17938723,\n",
       "        21.1724067 , 21.16541921],\n",
       "       [21.18786863, 21.19486142, 21.20184723, ..., 21.20426802,\n",
       "        21.19728462, 21.19029425],\n",
       "       ...,\n",
       "       [47.78955926, 47.799849  , 47.81012868, ..., 47.81369093,\n",
       "        47.80341474, 47.79312849],\n",
       "       [47.81409316, 47.82438621, 47.8346692 , ..., 47.83823259,\n",
       "        47.8279531 , 47.81766354],\n",
       "       [47.8386235 , 47.84891986, 47.85920615, ..., 47.86277069,\n",
       "        47.85248789, 47.84219502]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>237.3 237.3 237.3 ... 299.0 299.1</div><input id='attrs-d194d89c-844c-4c9f-b1e5-b5cb8fa5b9e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d194d89c-844c-4c9f-b1e5-b5cb8fa5b9e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-833436cf-d0c0-4eeb-8436-f5249bc4de54' class='xr-var-data-in' type='checkbox'><label for='data-833436cf-d0c0-4eeb-8436-f5249bc4de54' 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>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([[237.280472  , 237.30713868, 237.3338097 , ..., 287.6569408 ,\n",
       "        287.68361332, 287.71028151],\n",
       "       [237.27297501, 237.29964881, 237.32632695, ..., 287.66442108,\n",
       "        287.69110073, 287.71777603],\n",
       "       [237.26547368, 237.2921546 , 237.31883986, ..., 287.6719057 ,\n",
       "        287.69859247, 287.7252749 ],\n",
       "       ...,\n",
       "       [225.9351904 , 225.97171577, 226.00825329, ..., 298.97907406,\n",
       "        299.0156158 , 299.05214538],\n",
       "       [225.91986142, 225.95639874, 225.99294822, ..., 298.99437498,\n",
       "        299.03092868, 299.06747022],\n",
       "       [225.90452027, 225.94106954, 225.97763099, ..., 299.00968806,\n",
       "        299.04625373, 299.08280723]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>valid_time</span></div><div class='xr-var-dims'>(f, t)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-01-01 ... 2022-01-01T08:00:00</div><input id='attrs-48700d46-c495-4165-a713-eff44b10f46f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-48700d46-c495-4165-a713-eff44b10f46f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75fa4aad-0db0-44d0-8fc7-90966692d47a' class='xr-var-data-in' type='checkbox'><label for='data-75fa4aad-0db0-44d0-8fc7-90966692d47a' 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'></dl></div><div class='xr-var-data'><pre>array([[&#x27;2022-01-01T00:00:00.000000000&#x27;, &#x27;2022-01-01T01:00:00.000000000&#x27;,\n",
       "        &#x27;2022-01-01T02:00:00.000000000&#x27;],\n",
       "       [&#x27;2022-01-01T06:00:00.000000000&#x27;, &#x27;2022-01-01T07:00:00.000000000&#x27;,\n",
       "        &#x27;2022-01-01T08:00:00.000000000&#x27;]], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-67a78dee-36c0-48e1-aa2d-b411c4985f44' class='xr-section-summary-in' type='checkbox'  checked><label for='section-67a78dee-36c0-48e1-aa2d-b411c4985f44' class='xr-section-summary' >Data variables: <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>u10</span></div><div class='xr-var-dims'>(f, t, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-3.392 -3.33 ... -1.313 -1.375</div><input id='attrs-99291b63-2da3-4482-9e24-814bf14d6efd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-99291b63-2da3-4482-9e24-814bf14d6efd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4aea86d-3512-4be5-a9ec-122c35c53526' class='xr-var-data-in' type='checkbox'><label for='data-f4aea86d-3512-4be5-a9ec-122c35c53526' 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'></dl></div><div class='xr-var-data'><pre>array([[[[-3.3920221e+00, -3.3295221e+00, -3.3295221e+00, ...,\n",
       "          -8.8295221e+00, -8.8295221e+00, -8.8295221e+00],\n",
       "         [-3.3295221e+00, -3.3295221e+00, -3.2670221e+00, ...,\n",
       "          -8.9545221e+00, -9.3295221e+00, -9.2045221e+00],\n",
       "         [-3.3295221e+00, -3.2670221e+00, -3.2045221e+00, ...,\n",
       "          -9.0170221e+00, -9.3920221e+00, -9.2045221e+00],\n",
       "         ...,\n",
       "         [ 7.1704779e+00,  7.1079779e+00,  7.0454779e+00, ...,\n",
       "           1.7047787e-01,  1.0797787e-01,  2.9547787e-01],\n",
       "         [ 7.1704779e+00,  7.1704779e+00,  7.1079779e+00, ...,\n",
       "           3.5797787e-01,  3.5797787e-01,  4.8297787e-01],\n",
       "         [ 7.1704779e+00,  7.1079779e+00,  7.1079779e+00, ...,\n",
       "           6.0797787e-01,  6.0797787e-01,  6.7047787e-01]],\n",
       "\n",
       "        [[-3.4515448e+00, -3.4515448e+00, -3.4515448e+00, ...,\n",
       "          -9.0140448e+00, -9.0140448e+00, -9.0140448e+00],\n",
       "         [-3.3890448e+00, -3.3890448e+00, -3.3890448e+00, ...,\n",
       "          -9.0140448e+00, -9.0140448e+00, -9.0140448e+00],\n",
       "         [-3.3890448e+00, -3.3265448e+00, -3.3265448e+00, ...,\n",
       "          -9.0140448e+00, -9.0140448e+00, -9.0140448e+00],\n",
       "...\n",
       "           8.6155891e-02,  2.3655891e-02, -3.8844109e-02],\n",
       "         [ 9.4611559e+00,  9.3986559e+00,  9.3361559e+00, ...,\n",
       "           2.3655891e-02, -3.8844109e-02, -1.0134411e-01],\n",
       "         [ 9.4611559e+00,  9.5236559e+00,  9.5236559e+00, ...,\n",
       "          -3.8844109e-02, -1.0134411e-01, -1.6384411e-01]],\n",
       "\n",
       "        [[-4.3126307e+00, -4.3751307e+00, -4.3751307e+00, ...,\n",
       "          -9.7501307e+00, -9.6876307e+00, -9.6876307e+00],\n",
       "         [-4.1251307e+00, -3.9376307e+00, -3.8751307e+00, ...,\n",
       "          -9.6251307e+00, -9.5626307e+00, -9.6251307e+00],\n",
       "         [-4.0626307e+00, -3.8751307e+00, -3.8126307e+00, ...,\n",
       "          -9.5626307e+00, -9.5001307e+00, -9.5626307e+00],\n",
       "         ...,\n",
       "         [ 1.0187369e+01,  9.8123693e+00,  9.7498693e+00, ...,\n",
       "          -1.3751307e+00, -1.3751307e+00, -1.3126307e+00],\n",
       "         [ 1.0187369e+01,  9.8123693e+00,  9.8123693e+00, ...,\n",
       "          -1.4376307e+00, -1.4376307e+00, -1.3751307e+00],\n",
       "         [ 1.0562369e+01,  1.0499869e+01,  1.0437369e+01, ...,\n",
       "          -1.3126307e+00, -1.3126307e+00, -1.3751307e+00]]]],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v10</span></div><div class='xr-var-dims'>(f, t, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-5.777 -5.777 ... 2.929 2.991</div><input id='attrs-8867183f-59d3-48be-914b-265d1bf64c71' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8867183f-59d3-48be-914b-265d1bf64c71' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af38177d-ade2-4aa2-bfb5-441cf828333b' class='xr-var-data-in' type='checkbox'><label for='data-af38177d-ade2-4aa2-bfb5-441cf828333b' 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'></dl></div><div class='xr-var-data'><pre>array([[[[-5.7773495, -5.7773495, -5.7148495, ..., -3.5273495,\n",
       "          -3.6523495, -4.0273495],\n",
       "         [-5.7773495, -5.7148495, -5.6523495, ..., -3.2773495,\n",
       "          -3.4648495, -3.9648495],\n",
       "         [-5.8398495, -5.7148495, -5.6523495, ..., -3.5898495,\n",
       "          -3.7148495, -3.9023495],\n",
       "         ...,\n",
       "         [-4.0898495, -4.0898495, -4.0898495, ...,  0.6601505,\n",
       "           0.7851505,  0.9101505],\n",
       "         [-4.0898495, -4.0273495, -4.0273495, ...,  0.6601505,\n",
       "           0.7851505,  0.9101505],\n",
       "         [-4.0273495, -4.0273495, -4.0273495, ...,  0.7851505,\n",
       "           0.8476505,  0.9101505]],\n",
       "\n",
       "        [[-5.544121 , -5.481621 , -5.481621 , ..., -3.7941208,\n",
       "          -3.9191208, -3.9816208],\n",
       "         [-5.606621 , -5.419121 , -5.419121 , ..., -3.6691208,\n",
       "          -3.7941208, -3.9191208],\n",
       "         [-5.606621 , -5.481621 , -5.481621 , ..., -3.6691208,\n",
       "          -3.7316208, -3.8566208],\n",
       "...\n",
       "         [-2.7430058, -2.9305058, -3.1180058, ...,  2.3194942,\n",
       "           2.3194942,  2.3194942],\n",
       "         [-2.7430058, -2.9930058, -3.2430058, ...,  2.3194942,\n",
       "           2.3194942,  2.3194942],\n",
       "         [-2.7430058, -2.9930058, -3.1180058, ...,  2.3819942,\n",
       "           2.3819942,  2.3194942]],\n",
       "\n",
       "        [[-4.2586155, -4.0711155, -4.1336155, ..., -2.0086155,\n",
       "          -2.0711155, -2.0711155],\n",
       "         [-4.2586155, -3.9461155, -4.0086155, ..., -1.8836155,\n",
       "          -1.9461155, -2.0086155],\n",
       "         [-4.2586155, -4.0086155, -4.0086155, ..., -1.8211155,\n",
       "          -1.8836155, -1.9461155],\n",
       "         ...,\n",
       "         [-2.3836155, -2.0711155, -2.0086155, ...,  2.9288845,\n",
       "           2.9288845,  2.9913845],\n",
       "         [-2.3211155, -2.0711155, -2.0711155, ...,  2.9288845,\n",
       "           2.8663845,  2.9913845],\n",
       "         [-2.3211155, -2.1961155, -2.2586155, ...,  3.0538845,\n",
       "           2.9288845,  2.9913845]]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gribfile_projection</span></div><div class='xr-var-dims'>(f, t)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>None None None None None None</div><input id='attrs-0a7570ac-a5e1-484c-b011-72c2da5fcb4c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0a7570ac-a5e1-484c-b011-72c2da5fcb4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21c4e064-217d-4aa3-abf1-d2a470fdf154' class='xr-var-data-in' type='checkbox'><label for='data-21c4e064-217d-4aa3-abf1-d2a470fdf154' 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'></dl></div><div class='xr-var-data'><pre>array([[None, None, None],\n",
       "       [None, None, None]], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fa6dcdf2-5074-4951-8cff-7d20175ba294' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-fa6dcdf2-5074-4951-8cff-7d20175ba294' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:              (t: 3, f: 2, y: 1059, x: 1799)\n",
       "Coordinates:\n",
       "    time                 (t) datetime64[ns] 2022-01-01 ... 2022-01-01T02:00:00\n",
       "    step                 (f) timedelta64[ns] 00:00:00 06:00:00\n",
       "    heightAboveGround    float64 10.0\n",
       "    latitude             (y, x) float64 21.14 21.15 21.15 ... 47.86 47.85 47.84\n",
       "    longitude            (y, x) float64 237.3 237.3 237.3 ... 299.0 299.0 299.1\n",
       "    valid_time           (f, t) datetime64[ns] 2022-01-01 ... 2022-01-01T08:0...\n",
       "Dimensions without coordinates: t, f, y, x\n",
       "Data variables:\n",
       "    u10                  (f, t, y, x) float32 -3.392 -3.33 ... -1.313 -1.375\n",
       "    v10                  (f, t, y, x) float32 -5.777 -5.777 ... 2.929 2.991\n",
       "    gribfile_projection  (f, t) object None None None None None None"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read into xarray\n",
    "ds = fast_Herbie_xarray(DATES=DATES[:3], fxx=[0, 6], searchString=\"(?:U|V)GRD:10 m\")\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "381aea29-9a58-47a7-b64b-cf80ef4529c0",
   "metadata": {},
   "source": [
    "<br>\n",
    "<br>\n",
    "<br>\n",
    "<br>\n",
    "<br>\n",
    "<br>\n",
    "<br>\n",
    "<br>\n",
    "\n",
    "## Plot with `herbie` xarray custom accessor\n",
    "\n",
    "> 🏗️ WORK IN PROGRESS\n",
    "\n",
    "This requires my [Carpenter Workshop](https://github.com/blaylockbk/Carpenter_Workshop) functions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "2d4202ea-b07b-49d4-bdda-4822e0ada875",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cfgrib variable: t\n",
      "GRIB_cfName air_temperature\n",
      "GRIB_cfVarName t\n",
      "GRIB_name Temperature\n",
      "GRIB_units K\n",
      "GRIB_typeOfLevel isobaricInhPa\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/p/home/blaylock/anaconda3/envs/basic38/lib/python3.8/site-packages/cartopy/mpl/geoaxes.py:1702: UserWarning: The input coordinates to pcolormesh are interpreted as cell centers, but are not monotonically increasing or decreasing. This may lead to incorrectly calculated cell edges, in which case, please supply explicit cell edges to pcolormesh.\n",
      "  X, Y, C, shading = self._pcolorargs('pcolormesh', *args,\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cfgrib variable: u\n",
      "GRIB_cfName eastward_wind\n",
      "GRIB_cfVarName u\n",
      "GRIB_name U component of wind\n",
      "GRIB_units m s**-1\n",
      "GRIB_typeOfLevel isobaricInhPa\n",
      "\n",
      "cfgrib variable: v\n",
      "GRIB_cfName northward_wind\n",
      "GRIB_cfVarName v\n",
      "GRIB_name V component of wind\n",
      "GRIB_units m s**-1\n",
      "GRIB_typeOfLevel isobaricInhPa\n",
      "\n",
      "cfgrib variable: gh\n",
      "GRIB_cfName geopotential_height\n",
      "GRIB_cfVarName gh\n",
      "GRIB_name Geopotential Height\n",
      "GRIB_units gpm\n",
      "GRIB_typeOfLevel isobaricInhPa\n",
      "\n",
      "cfgrib variable: dpt\n",
      "GRIB_cfName unknown\n",
      "GRIB_cfVarName dpt\n",
      "GRIB_name Dew point temperature\n",
      "GRIB_units K\n",
      "GRIB_typeOfLevel isobaricInhPa\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<GeoAxesSubplot:title={'left':'Run: 00:00 UTC 06 May 2021 F00','center':'HRRR 500 hPa','right':'Valid: 00:00 UTC 06 May 2021'}>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x750 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x750 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x750 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1500x750 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x750 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Hx.herbie.plot()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.9.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
