jupyter_notebooks/ncar_benchmark.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "bc65f494-4fbe-4af0-85ca-e3a424b56454",
   "metadata": {},
   "source": [
    "# Access DART data from NCAR's data origin and benchmark"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "20444ba4-275a-45a7-bda5-c22b5cb5cee4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Display output of plots directly in Notebook\n",
    "import intake\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import xarray as xr\n",
    "import aiohttp\n",
    "import time\n",
    "from contextlib import contextmanager\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "63e53607-bf0a-41a4-9f72-5769197e4570",
   "metadata": {},
   "outputs": [],
   "source": [
    "import fsspec.implementations.http as fshttp\n",
    "from pelicanfs.core import PelicanFileSystem, PelicanMap, OSDFFileSystem "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9928a424-cf23-4a2f-bf16-afe7137d296f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import dask \n",
    "from dask_jobqueue import PBSCluster\n",
    "from dask.distributed import Client\n",
    "from dask.distributed import performance_report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9aba542a-3190-4da5-921d-621a970d1250",
   "metadata": {},
   "outputs": [],
   "source": [
    "init_year0  = '1991'\n",
    "init_year1  = '2020'\n",
    "final_year0 = '2071'\n",
    "final_year1 = '2100'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6211ba45-34ab-40bc-a265-cc53026f58e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # This overwrites the default scheduler with a single-threaded scheduler\n",
    "# dask.config.set(scheduler='synchronous')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "23425225-a495-424d-a8d8-6986b9d46ec0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# File paths\n",
    "rda_scratch   = '/gpfs/csfs1/collections/rda/scratch/harshah'\n",
    "rda_url       =  'https://data.rda.ucar.edu/'\n",
    "database_num  = 'd345001'\n",
    "cam6_dart_url = rda_url + database_num\n",
    "#\n",
    "https_catalog = cam6_dart_url + '/catalogs/https/'+ database_num +'-https-zarr.json'\n",
    "osdf_catalog  = cam6_dart_url + '/catalogs/osdf/'+ database_num +'-osdf-zarr.json'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ecd00a42-dc74-4f76-86c5-f8522e5ff650",
   "metadata": {},
   "source": [
    "### Create a Dask cluster"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e28b6894-0c18-4598-a2b4-0e42c946006c",
   "metadata": {},
   "source": [
    "#### Dask Introduction"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d0d246a-8c6d-4ea6-b633-ee6c6b3295fc",
   "metadata": {},
   "source": [
    "Dask is a solution that enables the scaling of Python libraries. It mimics popular scientific libraries such as numpy, pandas, and xarray that enables an easier path to parallel processing without having to refactor code.\n",
    "\n",
    "There are 3 components to parallel processing with Dask: the client, the scheduler, and the workers.\n",
    "\n",
    "The Client is best envisioned as the application that sends information to the Dask cluster. In Python applications this is handled when the client is defined with client = Client(CLUSTER_TYPE). A Dask cluster comprises of a single scheduler that manages the execution of tasks on workers. The CLUSTER_TYPE can be defined in a number of different ways.\n",
    "\n",
    "There is LocalCluster, a cluster running on the same hardware as the application and sharing the available resources, directly in Python with dask.distributed.\n",
    "\n",
    "In certain JupyterHubs Dask Gateway may be available and a dedicated dask cluster with its own resources can be created dynamically with dask.gateway.\n",
    "\n",
    "On HPC systems dask_jobqueue is used to connect to the HPC Slurm, PBS or HTCondor job schedulers to provision resources.\n",
    "\n",
    "The dask.distributed client python module can also be used to connect to existing clusters. A Dask Scheduler and Workers can be deployed in containers, or on Kubernetes, without using a Python function to create a dask cluster. The dask.distributed Client is configured to connect to the scheduler either by container name, or by the Kubernetes service name."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ebdc3cd9-afc9-4300-83d2-6c5dfbe45a43",
   "metadata": {},
   "source": [
    "#### Select the Dask cluster type\n",
    "The default will be LocalCluster as that can run on any system.\n",
    "\n",
    "If running on a HPC computer with a PBS Scheduler, set to True. Otherwise, set to False."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ab463221-621b-44ed-83fe-c13d48224fe3",
   "metadata": {},
   "outputs": [],
   "source": [
    "USE_PBS_SCHEDULER = False"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1d1a5a3-2bed-4bc5-9d9d-8a281991fca4",
   "metadata": {},
   "source": [
    "If running on Jupyter server with Dask Gateway configured, set to True. Otherwise, set to False."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "53b35384-b9bd-4a2e-b285-dc59f3b73a51",
   "metadata": {},
   "outputs": [],
   "source": [
    "USE_DASK_GATEWAY = False"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a503d50-9e09-4938-bd57-5a49be2757e9",
   "metadata": {},
   "source": [
    "#### Python function for a PBS cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d446e446-d39b-4521-961f-507aee9a04a0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a PBS cluster object\n",
    "def get_pbs_cluster():\n",
    "    \"\"\" Create cluster through dask_jobqueue.   \n",
    "    \"\"\"\n",
    "    from dask_jobqueue import PBSCluster\n",
    "    cluster = PBSCluster(\n",
    "        job_name = 'dask-osdf-24',\n",
    "        cores = 1,\n",
    "        memory = '4GiB',\n",
    "        processes = 1,\n",
    "        local_directory = rda_scratch + '/dask/spill',\n",
    "        log_directory = rda_scratch + '/dask/logs/',\n",
    "        resource_spec = 'select=1:ncpus=1:mem=4GB',\n",
    "        queue = 'casper',\n",
    "        walltime = '3:00:00',\n",
    "        #interface = 'ib0'\n",
    "        interface = 'ext'\n",
    "    )\n",
    "    return cluster"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa81bfd1-b92d-4dcc-b1ab-35a6d1102b32",
   "metadata": {},
   "source": [
    "#### Python function for a Gateway Cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "abfd3f2d-e02c-4a6e-8eb6-efcd8a53cb56",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_gateway_cluster():\n",
    "    \"\"\" Create cluster through dask_gateway\n",
    "    \"\"\"\n",
    "    from dask_gateway import Gateway\n",
    "\n",
    "    gateway = Gateway()\n",
    "    cluster = gateway.new_cluster()\n",
    "    cluster.adapt(minimum=2, maximum=4)\n",
    "    return cluster"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14e50058-b31a-41e0-a466-e2cef1a71664",
   "metadata": {},
   "source": [
    "#### Python function for a Local Cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "336ad8a8-abd0-472f-bc9d-b858dc8d4121",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_local_cluster():\n",
    "    \"\"\" Create cluster using the Jupyter server's resources\n",
    "    \"\"\"\n",
    "    from distributed import LocalCluster, performance_report\n",
    "    cluster = LocalCluster()    \n",
    "\n",
    "    cluster.scale(4)\n",
    "    return cluster"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0998bb3e-1435-45f5-a202-04e432ce5f31",
   "metadata": {},
   "source": [
    "#### Python logic to select the Dask Cluster type"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59ecabe5-8815-444a-9742-8e1275de1720",
   "metadata": {},
   "source": [
    "This uses True/False boolean logic based on the variables set in the previous cells"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e0aa8ecb-b9c3-406f-9f21-f30a77107fae",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/glade/work/harshah/conda-envs/arco_experiments/lib/python3.12/site-packages/distributed/node.py:182: UserWarning: Port 8787 is already in use.\n",
      "Perhaps you already have a cluster running?\n",
      "Hosting the HTTP server on port 43011 instead\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "# Obtain dask cluster in one of three ways\n",
    "\n",
    "if USE_PBS_SCHEDULER:\n",
    "    cluster = get_pbs_cluster()\n",
    "elif USE_DASK_GATEWAY:\n",
    "    cluster = get_gateway_cluster()\n",
    "else:\n",
    "    cluster = get_local_cluster()\n",
    "\n",
    "# Connect to cluster\n",
    "from distributed import Client\n",
    "client = Client(cluster)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "fc5e3646-1852-4d63-9638-90994b030737",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    </div>\n",
       "    <div style=\"margin-left: 48px;\">\n",
       "        <h3 style=\"margin-bottom: 0px; margin-top: 0px;\">LocalCluster</h3>\n",
       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">19f76495</p>\n",
       "        <table style=\"width: 100%; text-align: left;\">\n",
       "            <tr>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Dashboard:</strong> <a href=\"https://jupyterhub.hpc.ucar.edu/stable/user/harshah/proxy/43011/status\" target=\"_blank\">https://jupyterhub.hpc.ucar.edu/stable/user/harshah/proxy/43011/status</a>\n",
       "                </td>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Workers:</strong> 4\n",
       "                </td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Total threads:</strong> 4\n",
       "                </td>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Total memory:</strong> 16.00 GiB\n",
       "                </td>\n",
       "            </tr>\n",
       "            \n",
       "            <tr>\n",
       "    <td style=\"text-align: left;\"><strong>Status:</strong> running</td>\n",
       "    <td style=\"text-align: left;\"><strong>Using processes:</strong> True</td>\n",
       "</tr>\n",
       "\n",
       "            \n",
       "        </table>\n",
       "\n",
       "        <details>\n",
       "            <summary style=\"margin-bottom: 20px;\">\n",
       "                <h3 style=\"display: inline;\">Scheduler Info</h3>\n",
       "            </summary>\n",
       "\n",
       "            <div style=\"\">\n",
       "    <div>\n",
       "        <div style=\"width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;\"> </div>\n",
       "        <div style=\"margin-left: 48px;\">\n",
       "            <h3 style=\"margin-bottom: 0px;\">Scheduler</h3>\n",
       "            <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-fbf76e3b-a42d-4926-8e0a-ed4b633f0534</p>\n",
       "            <table style=\"width: 100%; text-align: left;\">\n",
       "                <tr>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Comm:</strong> tcp://127.0.0.1:45045\n",
       "                    </td>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Workers:</strong> 4\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Dashboard:</strong> <a href=\"https://jupyterhub.hpc.ucar.edu/stable/user/harshah/proxy/43011/status\" target=\"_blank\">https://jupyterhub.hpc.ucar.edu/stable/user/harshah/proxy/43011/status</a>\n",
       "                    </td>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Total threads:</strong> 4\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Started:</strong> Just now\n",
       "                    </td>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Total memory:</strong> 16.00 GiB\n",
       "                    </td>\n",
       "                </tr>\n",
       "            </table>\n",
       "        </div>\n",
       "    </div>\n",
       "\n",
       "    <details style=\"margin-left: 48px;\">\n",
       "        <summary style=\"margin-bottom: 20px;\">\n",
       "            <h3 style=\"display: inline;\">Workers</h3>\n",
       "        </summary>\n",
       "\n",
       "        \n",
       "        <div style=\"margin-bottom: 20px;\">\n",
       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
       "            <div style=\"margin-left: 48px;\">\n",
       "            <details>\n",
       "                <summary>\n",
       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 0</h4>\n",
       "                </summary>\n",
       "                <table style=\"width: 100%; text-align: left;\">\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:39633\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 1\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"https://jupyterhub.hpc.ucar.edu/stable/user/harshah/proxy/32857/status\" target=\"_blank\">https://jupyterhub.hpc.ucar.edu/stable/user/harshah/proxy/32857/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 4.00 GiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Nanny: </strong> tcp://127.0.0.1:44883\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\"></td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
       "                            <strong>Local directory: </strong> /glade/derecho/scratch/harshah/tmp/dask-scratch-space/worker-nmx8gyv9\n",
       "                        </td>\n",
       "                    </tr>\n",
       "\n",
       "                    \n",
       "\n",
       "                    \n",
       "\n",
       "                </table>\n",
       "            </details>\n",
       "            </div>\n",
       "        </div>\n",
       "        \n",
       "        <div style=\"margin-bottom: 20px;\">\n",
       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
       "            <div style=\"margin-left: 48px;\">\n",
       "            <details>\n",
       "                <summary>\n",
       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 1</h4>\n",
       "                </summary>\n",
       "                <table style=\"width: 100%; text-align: left;\">\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:37735\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 1\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"https://jupyterhub.hpc.ucar.edu/stable/user/harshah/proxy/33247/status\" target=\"_blank\">https://jupyterhub.hpc.ucar.edu/stable/user/harshah/proxy/33247/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 4.00 GiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Nanny: </strong> tcp://127.0.0.1:40219\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\"></td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
       "                            <strong>Local directory: </strong> /glade/derecho/scratch/harshah/tmp/dask-scratch-space/worker-e6wsuy6k\n",
       "                        </td>\n",
       "                    </tr>\n",
       "\n",
       "                    \n",
       "\n",
       "                    \n",
       "\n",
       "                </table>\n",
       "            </details>\n",
       "            </div>\n",
       "        </div>\n",
       "        \n",
       "        <div style=\"margin-bottom: 20px;\">\n",
       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
       "            <div style=\"margin-left: 48px;\">\n",
       "            <details>\n",
       "                <summary>\n",
       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 2</h4>\n",
       "                </summary>\n",
       "                <table style=\"width: 100%; text-align: left;\">\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:41017\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 1\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"https://jupyterhub.hpc.ucar.edu/stable/user/harshah/proxy/42717/status\" target=\"_blank\">https://jupyterhub.hpc.ucar.edu/stable/user/harshah/proxy/42717/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 4.00 GiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Nanny: </strong> tcp://127.0.0.1:46437\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\"></td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
       "                            <strong>Local directory: </strong> /glade/derecho/scratch/harshah/tmp/dask-scratch-space/worker-nxgbqfqb\n",
       "                        </td>\n",
       "                    </tr>\n",
       "\n",
       "                    \n",
       "\n",
       "                    \n",
       "\n",
       "                </table>\n",
       "            </details>\n",
       "            </div>\n",
       "        </div>\n",
       "        \n",
       "        <div style=\"margin-bottom: 20px;\">\n",
       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
       "            <div style=\"margin-left: 48px;\">\n",
       "            <details>\n",
       "                <summary>\n",
       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 3</h4>\n",
       "                </summary>\n",
       "                <table style=\"width: 100%; text-align: left;\">\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:42185\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 1\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"https://jupyterhub.hpc.ucar.edu/stable/user/harshah/proxy/37505/status\" target=\"_blank\">https://jupyterhub.hpc.ucar.edu/stable/user/harshah/proxy/37505/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 4.00 GiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Nanny: </strong> tcp://127.0.0.1:43113\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\"></td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
       "                            <strong>Local directory: </strong> /glade/derecho/scratch/harshah/tmp/dask-scratch-space/worker-h4a42ocm\n",
       "                        </td>\n",
       "                    </tr>\n",
       "\n",
       "                    \n",
       "\n",
       "                    \n",
       "\n",
       "                </table>\n",
       "            </details>\n",
       "            </div>\n",
       "        </div>\n",
       "        \n",
       "\n",
       "    </details>\n",
       "</div>\n",
       "\n",
       "        </details>\n",
       "    </div>\n",
       "</div>"
      ],
      "text/plain": [
       "LocalCluster(19f76495, 'tcp://127.0.0.1:45045', workers=4, threads=4, memory=16.00 GiB)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Scale the cluster and display cluster dashboard URL\n",
    "# cluster.scale(4)\n",
    "cluster"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e248333-8828-46db-a491-5697a103b485",
   "metadata": {},
   "source": [
    "## Access the data from NCAR's Research Data Archive using intake"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ad1d1906-d2f5-4cd9-83b2-81a7bbdf62e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['https://data.rda.ucar.edu/d345001/hourly6/HR.zarr',\n",
       "       'https://data.rda.ucar.edu/d345001/hourly6/TSA.zarr',\n",
       "       'https://data.rda.ucar.edu/d345001/hourly6/EFLX_LH_TOT.zarr',\n",
       "       'https://data.rda.ucar.edu/d345001/hourly6/ER.zarr',\n",
       "       'https://data.rda.ucar.edu/d345001/weekly/VS.zarr',\n",
       "       'https://data.rda.ucar.edu/d345001/weekly/PS.zarr',\n",
       "       'https://data.rda.ucar.edu/d345001/weekly/Q.zarr',\n",
       "       'https://data.rda.ucar.edu/d345001/weekly/US.zarr',\n",
       "       'https://data.rda.ucar.edu/d345001/weekly/CLDICE.zarr',\n",
       "       'https://data.rda.ucar.edu/d345001/weekly/T.zarr',\n",
       "       'https://data.rda.ucar.edu/d345001/weekly/CLDLIQ.zarr'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_https_test = intake.open_esm_datastore(https_catalog)\n",
    "df_https_test.df['path'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "4a88f4cf-7e6b-47bd-afd7-6351d16a7cdd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['osdf:///ncar/rda/d345001/hourly6/HR.zarr',\n",
       "       'osdf:///ncar/rda/d345001/hourly6/TSA.zarr',\n",
       "       'osdf:///ncar/rda/d345001/hourly6/EFLX_LH_TOT.zarr',\n",
       "       'osdf:///ncar/rda/d345001/hourly6/ER.zarr',\n",
       "       'osdf:///ncar/rda/d345001/weekly/VS.zarr',\n",
       "       'osdf:///ncar/rda/d345001/weekly/PS.zarr',\n",
       "       'osdf:///ncar/rda/d345001/weekly/Q.zarr',\n",
       "       'osdf:///ncar/rda/d345001/weekly/US.zarr',\n",
       "       'osdf:///ncar/rda/d345001/weekly/CLDICE.zarr',\n",
       "       'osdf:///ncar/rda/d345001/weekly/T.zarr',\n",
       "       'osdf:///ncar/rda/d345001/weekly/CLDLIQ.zarr'], dtype=object)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_osdf_test = intake.open_esm_datastore(osdf_catalog)\n",
    "df_osdf_test.df['path'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "97b85f5b-0d19-4a91-b9fc-e1acac9a6275",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_var = 'PS'\n",
    "col_subset_https = df_https_test.search(variable=data_var)\n",
    "col_subset_osdf  = df_osdf_test.search(variable=data_var)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5011d8df-aa93-41ea-a163-9682bdd5b0cd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--> The keys in the returned dictionary of datasets are constructed as follows:\n",
      "\t'variable.frequency.component.vertical_levels'\n"
     ]
    },
    {
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       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
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       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
       "        background: #F44336;\n",
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       "</style>\n"
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       "<IPython.core.display.HTML object>"
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     "output_type": "display_data"
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       "\n",
       "    <div>\n",
       "      <progress value='1' class='' max='1' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
       "      100.00% [1/1 00:02&lt;00:00]\n",
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Dataset dictionary keys:\n",
      " dict_keys(['PS.weekly.atm.1'])\n"
     ]
    }
   ],
   "source": [
    "dsets_https = col_subset_https.to_dataset_dict(zarr_kwargs={\"consolidated\": True})\n",
    "#\n",
    "print(f\"\\nDataset dictionary keys:\\n {dsets_https.keys()}\")\n",
    "# Load the first dataset and display a summary.\n",
    "dataset_key = list(dsets_https.keys())[0]\n",
    "#\n",
    "ds_https = dsets_https[dataset_key]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "9d66c159-3218-4c25-92ea-6417d322a7ed",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--> The keys in the returned dictionary of datasets are constructed as follows:\n",
      "\t'variable.frequency.component.vertical_levels'\n"
     ]
    },
    {
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       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
       "        background-size: auto;\n",
       "    }\n",
       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
       "    }\n",
       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
       "        background: #F44336;\n",
       "    }\n",
       "</style>\n"
      ],
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       "<IPython.core.display.HTML object>"
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      "text/html": [
       "\n",
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       "      <progress value='1' class='' max='1' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
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   "source": [
    "dsets_osdf  = col_subset_osdf.to_dataset_dict()\n",
    "ds_osdf     = dsets_osdf[dataset_key]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "472b639c-e81f-4e56-8f2b-7ffd0a029bba",
   "metadata": {},
   "outputs": [
    {
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       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
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       "\n",
       "html[theme=dark],\n",
       "body[data-theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
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       "  --xr-border-color: #1F1F1F;\n",
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       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
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       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
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       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  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",
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       "\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",
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       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
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       "\n",
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       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
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       "\n",
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       "\n",
       ".xr-section-details {\n",
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       ".xr-array-preview,\n",
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       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
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       "}\n",
       "\n",
       ".xr-dim-list {\n",
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       "\n",
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       "\n",
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       "  font-weight: bold;\n",
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       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
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       "}\n",
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       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
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       "\n",
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       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
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       "\n",
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       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
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       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
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       ".xr-index-name div,\n",
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       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
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       "\n",
       "dl.xr-attrs {\n",
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       "  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",
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       "  width: auto;\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
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       "\n",
       ".xr-attrs dt:hover span {\n",
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       "  background: var(--xr-background-color);\n",
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       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
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       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;PS&#x27; (member_id: 80, time: 471, lat: 192, lon: 288)&gt; Size: 17GB\n",
       "dask.array&lt;open_dataset-PS, shape=(80, 471, 192, 288), dtype=float64, chunksize=(80, 80, 32, 32), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "  * lat        (lat) float32 768B -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
       "  * lon        (lon) float32 1kB 0.0 1.25 2.5 3.75 ... 355.0 356.2 357.5 358.8\n",
       "  * member_id  (member_id) int64 640B 1 2 3 4 5 6 7 8 ... 74 75 76 77 78 79 80\n",
       "  * time       (time) datetime64[ns] 4kB 2011-01-03 2011-01-10 ... 2019-12-30\n",
       "Attributes:\n",
       "    long_name:  Surface pressure\n",
       "    units:      Pa</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'PS'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 80</li><li><span class='xr-has-index'>time</span>: 471</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-0716e9f2-283d-402c-89e4-77ec9325a25d' class='xr-array-in' type='checkbox' checked><label for='section-0716e9f2-283d-402c-89e4-77ec9325a25d' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(80, 80, 32, 32), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 15.52 GiB </td>\n",
       "                        <td> 50.00 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (80, 471, 192, 288) </td>\n",
       "                        <td> (80, 80, 32, 32) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 324 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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       "</table></div></div></li><li class='xr-section-item'><input id='section-167843da-7365-4de9-84e0-96cab65c7091' class='xr-section-summary-in' type='checkbox'  checked><label for='section-167843da-7365-4de9-84e0-96cab65c7091' class='xr-section-summary' >Coordinates: <span>(4)</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 class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-d99e8d42-abf0-4e04-8331-02701fbd7351' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d99e8d42-abf0-4e04-8331-02701fbd7351' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4217e7df-58e5-463b-a539-7fc3d641dbf3' class='xr-var-data-in' type='checkbox'><label for='data-4217e7df-58e5-463b-a539-7fc3d641dbf3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057594, -88.11518 , -87.172775, -86.23037 , -85.28796 ,\n",
       "       -84.34555 , -83.403145, -82.46073 , -81.518326, -80.57591 , -79.63351 ,\n",
       "       -78.6911  , -77.74869 , -76.80628 , -75.86388 , -74.92146 , -73.97906 ,\n",
       "       -73.03665 , -72.09424 , -71.15183 , -70.20943 , -69.26701 , -68.32461 ,\n",
       "       -67.3822  , -66.43979 , -65.49738 , -64.55498 , -63.612564, -62.67016 ,\n",
       "       -61.72775 , -60.78534 , -59.842934, -58.900524, -57.958115, -57.015705,\n",
       "       -56.0733  , -55.13089 , -54.18848 , -53.246075, -52.303665, -51.361256,\n",
       "       -50.41885 , -49.47644 , -48.53403 , -47.59162 , -46.649216, -45.706806,\n",
       "       -44.764397, -43.82199 , -42.87958 , -41.937172, -40.994766, -40.052357,\n",
       "       -39.109947, -38.167538, -37.225132, -36.282722, -35.340313, -34.397907,\n",
       "       -33.455498, -32.51309 , -31.57068 , -30.628273, -29.685863, -28.743456,\n",
       "       -27.801046, -26.858639, -25.916231, -24.973822, -24.031414, -23.089005,\n",
       "       -22.146597, -21.20419 , -20.26178 , -19.319372, -18.376963, -17.434555,\n",
       "       -16.492147, -15.549738, -14.607329, -13.664922, -12.722513, -11.780105,\n",
       "       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,\n",
       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
       "        11.780105,  12.722513,  13.664922,  14.607329,  15.549738,  16.492147,\n",
       "        17.434555,  18.376963,  19.319372,  20.26178 ,  21.20419 ,  22.146597,\n",
       "        23.089005,  24.031414,  24.973822,  25.916231,  26.858639,  27.801046,\n",
       "        28.743456,  29.685863,  30.628273,  31.57068 ,  32.51309 ,  33.455498,\n",
       "        34.397907,  35.340313,  36.282722,  37.225132,  38.167538,  39.109947,\n",
       "        40.052357,  40.994766,  41.937172,  42.87958 ,  43.82199 ,  44.764397,\n",
       "        45.706806,  46.649216,  47.59162 ,  48.53403 ,  49.47644 ,  50.41885 ,\n",
       "        51.361256,  52.303665,  53.246075,  54.18848 ,  55.13089 ,  56.0733  ,\n",
       "        57.015705,  57.958115,  58.900524,  59.842934,  60.78534 ,  61.72775 ,\n",
       "        62.67016 ,  63.612564,  64.55498 ,  65.49738 ,  66.43979 ,  67.3822  ,\n",
       "        68.32461 ,  69.26701 ,  70.20943 ,  71.15183 ,  72.09424 ,  73.03665 ,\n",
       "        73.97906 ,  74.92146 ,  75.86388 ,  76.80628 ,  77.74869 ,  78.6911  ,\n",
       "        79.63351 ,  80.57591 ,  81.518326,  82.46073 ,  83.403145,  84.34555 ,\n",
       "        85.28796 ,  86.23037 ,  87.172775,  88.11518 ,  89.057594,  90.      ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-2f41abc6-f985-47a7-8f15-6706e1a6e3b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2f41abc6-f985-47a7-8f15-6706e1a6e3b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da48ddc1-365c-4a78-9333-78c3a441d55c' class='xr-var-data-in' type='checkbox'><label for='data-da48ddc1-365c-4a78-9333-78c3a441d55c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 ... 75 76 77 78 79 80</div><input id='attrs-4eb9fae9-5f63-4e58-9034-6d8753cebfdd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4eb9fae9-5f63-4e58-9034-6d8753cebfdd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-298b2c60-3f55-43d0-871f-49a560c18c28' class='xr-var-data-in' type='checkbox'><label for='data-298b2c60-3f55-43d0-871f-49a560c18c28' 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([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17, 18,\n",
       "       19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36,\n",
       "       37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54,\n",
       "       55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72,\n",
       "       73, 74, 75, 76, 77, 78, 79, 80])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2011-01-03 ... 2019-12-30</div><input id='attrs-f351d74b-8dcc-495b-98f0-c27f6be53104' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f351d74b-8dcc-495b-98f0-c27f6be53104' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0069d4fa-b0a8-433c-b8aa-21f2a344a747' class='xr-var-data-in' type='checkbox'><label for='data-0069d4fa-b0a8-433c-b8aa-21f2a344a747' 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;2011-01-03T00:00:00.000000000&#x27;, &#x27;2011-01-10T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-01-17T00:00:00.000000000&#x27;, ..., &#x27;2019-12-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2019-12-23T00:00:00.000000000&#x27;, &#x27;2019-12-30T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fde85014-11e6-4ec2-8aa8-26d7f2c1e00a' class='xr-section-summary-in' type='checkbox'  ><label for='section-fde85014-11e6-4ec2-8aa8-26d7f2c1e00a' class='xr-section-summary' >Indexes: <span>(4)</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-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ca57c600-227f-40fc-997e-e8f9ffc3378e' class='xr-index-data-in' type='checkbox'/><label for='index-ca57c600-227f-40fc-997e-e8f9ffc3378e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0,  -89.0575942993164, -88.11518096923828,\n",
       "       -87.17277526855469,  -86.2303695678711, -85.28795623779297,\n",
       "       -84.34555053710938, -83.40314483642578, -82.46073150634766,\n",
       "       -81.51832580566406,\n",
       "       ...\n",
       "        81.51832580566406,  82.46073150634766,  83.40314483642578,\n",
       "        84.34555053710938,  85.28795623779297,   86.2303695678711,\n",
       "        87.17277526855469,  88.11518096923828,   89.0575942993164,\n",
       "                     90.0],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9934dede-812d-4b6d-a373-ea94c62fbd5f' class='xr-index-data-in' type='checkbox'/><label for='index-9934dede-812d-4b6d-a373-ea94c62fbd5f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,\n",
       "        11.25,\n",
       "       ...\n",
       "        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,\n",
       "       358.75],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f8d30bbc-9ff4-4d9d-a26e-55afe59ac3ee' class='xr-index-data-in' type='checkbox'/><label for='index-f8d30bbc-9ff4-4d9d-a26e-55afe59ac3ee' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17, 18,\n",
       "       19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36,\n",
       "       37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54,\n",
       "       55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72,\n",
       "       73, 74, 75, 76, 77, 78, 79, 80],\n",
       "      dtype=&#x27;int64&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6189e885-f7da-4c0d-9479-37243d73e2db' class='xr-index-data-in' type='checkbox'/><label for='index-6189e885-f7da-4c0d-9479-37243d73e2db' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2011-01-03 00:00:00&#x27;, &#x27;2011-01-10 00:00:00&#x27;,\n",
       "               &#x27;2011-01-17 00:00:00&#x27;, &#x27;2011-01-24 00:00:00&#x27;,\n",
       "               &#x27;2011-01-31 00:00:00&#x27;, &#x27;2011-02-07 00:00:00&#x27;,\n",
       "               &#x27;2011-02-14 00:00:00&#x27;, &#x27;2011-02-21 00:00:00&#x27;,\n",
       "               &#x27;2011-02-28 00:00:00&#x27;, &#x27;2011-03-07 00:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2019-10-28 00:00:00&#x27;, &#x27;2019-11-04 00:00:00&#x27;,\n",
       "               &#x27;2019-11-11 00:00:00&#x27;, &#x27;2019-11-18 00:00:00&#x27;,\n",
       "               &#x27;2019-11-25 00:00:00&#x27;, &#x27;2019-12-02 00:00:00&#x27;,\n",
       "               &#x27;2019-12-09 00:00:00&#x27;, &#x27;2019-12-16 00:00:00&#x27;,\n",
       "               &#x27;2019-12-23 00:00:00&#x27;, &#x27;2019-12-30 00:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=471, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3160ddfc-9adb-4896-882d-7eb6b15ae765' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3160ddfc-9adb-4896-882d-7eb6b15ae765' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Surface pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'PS' (member_id: 80, time: 471, lat: 192, lon: 288)> Size: 17GB\n",
       "dask.array<open_dataset-PS, shape=(80, 471, 192, 288), dtype=float64, chunksize=(80, 80, 32, 32), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * lat        (lat) float32 768B -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
       "  * lon        (lon) float32 1kB 0.0 1.25 2.5 3.75 ... 355.0 356.2 357.5 358.8\n",
       "  * member_id  (member_id) int64 640B 1 2 3 4 5 6 7 8 ... 74 75 76 77 78 79 80\n",
       "  * time       (time) datetime64[ns] 4kB 2011-01-03 2011-01-10 ... 2019-12-30\n",
       "Attributes:\n",
       "    long_name:  Surface pressure\n",
       "    units:      Pa"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_osdf  = ds_osdf.PS\n",
    "ds_https = ds_https.PS\n",
    "ds_osdf"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dec3fb01-39fb-4e91-9680-39691101cf43",
   "metadata": {},
   "source": [
    "## Data Access Speed tests\n",
    "- We will now test how long it takes to access data (via OSDF and https-only prrotocols) for various sizes using the above array"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0facf4b-db9a-4a29-b1ed-4748f6fd4181",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "### Prepare data subsets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6a64ab54-ba3b-43db-92dc-d96848eab246",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define file path for CSV\n",
    "csv_file_path = \"ncar_benchmark_results.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "ef0b9a69-9fb2-4484-bb28-29c962c22d42",
   "metadata": {},
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       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-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-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-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",
       ".xr-no-icon {\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.DataArray &#x27;PS&#x27; (time: 130)&gt; Size: 1kB\n",
       "dask.array&lt;getitem, shape=(130,), dtype=float64, chunksize=(80,), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "    lat        float32 4B -90.0\n",
       "    lon        float32 4B 0.0\n",
       "    member_id  int64 8B 1\n",
       "  * time       (time) datetime64[ns] 1kB 2011-01-03 2011-01-10 ... 2013-06-17\n",
       "Attributes:\n",
       "    long_name:  Surface pressure\n",
       "    units:      Pa</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'PS'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 130</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-69278c62-02ee-4cee-b43b-a250177d43e6' class='xr-array-in' type='checkbox' checked><label for='section-69278c62-02ee-4cee-b43b-a250177d43e6' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(80,), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.02 kiB </td>\n",
       "                        <td> 640 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (130,) </td>\n",
       "                        <td> (80,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 2 chunks in 4 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"73\" y1=\"0\" x2=\"73\" y2=\"25\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >130</text>\n",
       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></div></li><li class='xr-section-item'><input id='section-19437a58-1842-4015-a240-371dd45eb659' class='xr-section-summary-in' type='checkbox'  checked><label for='section-19437a58-1842-4015-a240-371dd45eb659' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-90.0</div><input id='attrs-5af8adb9-bea5-4da2-b633-895c01e82902' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5af8adb9-bea5-4da2-b633-895c01e82902' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a86b7744-cbb3-4dfc-b815-c0a34d8192bd' class='xr-var-data-in' type='checkbox'><label for='data-a86b7744-cbb3-4dfc-b815-c0a34d8192bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array(-90., dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-a34965e7-cb2c-4aa7-bdea-f0b3c7d329f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a34965e7-cb2c-4aa7-bdea-f0b3c7d329f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d29b4439-4d32-4208-907a-02a88908def3' class='xr-var-data-in' type='checkbox'><label for='data-d29b4439-4d32-4208-907a-02a88908def3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array(0., dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>member_id</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-2bf8180b-fce3-4839-990e-0d8c48482e3c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2bf8180b-fce3-4839-990e-0d8c48482e3c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d497cb21-5f36-4b76-904b-31b9b23640e8' class='xr-var-data-in' type='checkbox'><label for='data-d497cb21-5f36-4b76-904b-31b9b23640e8' 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(1)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2011-01-03 ... 2013-06-17</div><input id='attrs-48363fd5-015f-45a0-8262-f62ca59486d6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-48363fd5-015f-45a0-8262-f62ca59486d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e6a6211-e6da-4dcd-9233-289d412102f5' class='xr-var-data-in' type='checkbox'><label for='data-4e6a6211-e6da-4dcd-9233-289d412102f5' 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;2011-01-03T00:00:00.000000000&#x27;, &#x27;2011-01-10T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-01-17T00:00:00.000000000&#x27;, &#x27;2011-01-24T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-01-31T00:00:00.000000000&#x27;, &#x27;2011-02-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-02-14T00:00:00.000000000&#x27;, &#x27;2011-02-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-02-28T00:00:00.000000000&#x27;, &#x27;2011-03-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-03-14T00:00:00.000000000&#x27;, &#x27;2011-03-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-03-28T00:00:00.000000000&#x27;, &#x27;2011-04-04T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-04-11T00:00:00.000000000&#x27;, &#x27;2011-04-18T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-04-25T00:00:00.000000000&#x27;, &#x27;2011-05-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-05-09T00:00:00.000000000&#x27;, &#x27;2011-05-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-05-23T00:00:00.000000000&#x27;, &#x27;2011-05-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-06-06T00:00:00.000000000&#x27;, &#x27;2011-06-13T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-06-20T00:00:00.000000000&#x27;, &#x27;2011-06-27T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-07-04T00:00:00.000000000&#x27;, &#x27;2011-07-11T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-07-18T00:00:00.000000000&#x27;, &#x27;2011-07-25T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-08-01T00:00:00.000000000&#x27;, &#x27;2011-08-01T06:00:00.000000000&#x27;,\n",
       "       &#x27;2011-08-08T00:00:00.000000000&#x27;, &#x27;2011-08-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-08-22T00:00:00.000000000&#x27;, &#x27;2011-08-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-09-05T00:00:00.000000000&#x27;, &#x27;2011-09-12T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-09-19T00:00:00.000000000&#x27;, &#x27;2011-09-26T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-10-03T00:00:00.000000000&#x27;, &#x27;2011-10-10T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-10-17T00:00:00.000000000&#x27;, &#x27;2011-10-24T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-10-31T00:00:00.000000000&#x27;, &#x27;2011-11-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-11-14T00:00:00.000000000&#x27;, &#x27;2011-11-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-11-28T00:00:00.000000000&#x27;, &#x27;2011-12-05T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-12-12T00:00:00.000000000&#x27;, &#x27;2011-12-19T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-12-26T00:00:00.000000000&#x27;, &#x27;2012-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-01-09T00:00:00.000000000&#x27;, &#x27;2012-01-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-01-23T00:00:00.000000000&#x27;, &#x27;2012-01-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-02-06T00:00:00.000000000&#x27;, &#x27;2012-02-13T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-02-20T00:00:00.000000000&#x27;, &#x27;2012-02-27T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-03-05T00:00:00.000000000&#x27;, &#x27;2012-03-12T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-03-19T00:00:00.000000000&#x27;, &#x27;2012-03-26T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-04-02T00:00:00.000000000&#x27;, &#x27;2012-04-09T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-04-16T00:00:00.000000000&#x27;, &#x27;2012-04-23T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-04-30T00:00:00.000000000&#x27;, &#x27;2012-05-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-05-14T00:00:00.000000000&#x27;, &#x27;2012-05-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-05-28T00:00:00.000000000&#x27;, &#x27;2012-06-04T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-06-11T00:00:00.000000000&#x27;, &#x27;2012-06-18T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-06-25T00:00:00.000000000&#x27;, &#x27;2012-07-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-07-09T00:00:00.000000000&#x27;, &#x27;2012-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-07-23T00:00:00.000000000&#x27;, &#x27;2012-07-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-08-06T00:00:00.000000000&#x27;, &#x27;2012-08-13T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-08-20T00:00:00.000000000&#x27;, &#x27;2012-08-27T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-09-03T00:00:00.000000000&#x27;, &#x27;2012-09-10T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-09-17T00:00:00.000000000&#x27;, &#x27;2012-09-24T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-10-01T00:00:00.000000000&#x27;, &#x27;2012-10-08T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-10-15T00:00:00.000000000&#x27;, &#x27;2012-10-22T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-10-29T00:00:00.000000000&#x27;, &#x27;2012-11-05T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-11-12T00:00:00.000000000&#x27;, &#x27;2012-11-19T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-11-26T00:00:00.000000000&#x27;, &#x27;2012-12-03T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-12-10T00:00:00.000000000&#x27;, &#x27;2012-12-17T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-12-24T00:00:00.000000000&#x27;, &#x27;2012-12-31T00:00:00.000000000&#x27;,\n",
       "       &#x27;2013-01-07T00:00:00.000000000&#x27;, &#x27;2013-01-14T00:00:00.000000000&#x27;,\n",
       "       &#x27;2013-01-21T00:00:00.000000000&#x27;, &#x27;2013-01-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2013-02-04T00:00:00.000000000&#x27;, &#x27;2013-02-11T00:00:00.000000000&#x27;,\n",
       "       &#x27;2013-02-18T00:00:00.000000000&#x27;, &#x27;2013-02-25T00:00:00.000000000&#x27;,\n",
       "       &#x27;2013-03-04T00:00:00.000000000&#x27;, &#x27;2013-03-11T00:00:00.000000000&#x27;,\n",
       "       &#x27;2013-03-18T00:00:00.000000000&#x27;, &#x27;2013-03-25T00:00:00.000000000&#x27;,\n",
       "       &#x27;2013-04-01T00:00:00.000000000&#x27;, &#x27;2013-04-08T00:00:00.000000000&#x27;,\n",
       "       &#x27;2013-04-15T00:00:00.000000000&#x27;, &#x27;2013-04-22T00:00:00.000000000&#x27;,\n",
       "       &#x27;2013-04-29T00:00:00.000000000&#x27;, &#x27;2013-05-06T00:00:00.000000000&#x27;,\n",
       "       &#x27;2013-05-13T00:00:00.000000000&#x27;, &#x27;2013-05-20T00:00:00.000000000&#x27;,\n",
       "       &#x27;2013-05-27T00:00:00.000000000&#x27;, &#x27;2013-06-03T00:00:00.000000000&#x27;,\n",
       "       &#x27;2013-06-10T00:00:00.000000000&#x27;, &#x27;2013-06-17T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-54e64b82-17db-4b57-b964-5967216cc894' class='xr-section-summary-in' type='checkbox'  ><label for='section-54e64b82-17db-4b57-b964-5967216cc894' class='xr-section-summary' >Indexes: <span>(1)</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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4788e312-8747-4d13-a1da-d30d95580323' class='xr-index-data-in' type='checkbox'/><label for='index-4788e312-8747-4d13-a1da-d30d95580323' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2011-01-03 00:00:00&#x27;, &#x27;2011-01-10 00:00:00&#x27;,\n",
       "               &#x27;2011-01-17 00:00:00&#x27;, &#x27;2011-01-24 00:00:00&#x27;,\n",
       "               &#x27;2011-01-31 00:00:00&#x27;, &#x27;2011-02-07 00:00:00&#x27;,\n",
       "               &#x27;2011-02-14 00:00:00&#x27;, &#x27;2011-02-21 00:00:00&#x27;,\n",
       "               &#x27;2011-02-28 00:00:00&#x27;, &#x27;2011-03-07 00:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2013-04-15 00:00:00&#x27;, &#x27;2013-04-22 00:00:00&#x27;,\n",
       "               &#x27;2013-04-29 00:00:00&#x27;, &#x27;2013-05-06 00:00:00&#x27;,\n",
       "               &#x27;2013-05-13 00:00:00&#x27;, &#x27;2013-05-20 00:00:00&#x27;,\n",
       "               &#x27;2013-05-27 00:00:00&#x27;, &#x27;2013-06-03 00:00:00&#x27;,\n",
       "               &#x27;2013-06-10 00:00:00&#x27;, &#x27;2013-06-17 00:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=130, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-00fe7397-c6a6-4675-a2d0-081e28ce03dd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-00fe7397-c6a6-4675-a2d0-081e28ce03dd' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Surface pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div></li></ul></div></div>"
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      "text/plain": [
       "<xarray.DataArray 'PS' (time: 130)> Size: 1kB\n",
       "dask.array<getitem, shape=(130,), dtype=float64, chunksize=(80,), chunktype=numpy.ndarray>\n",
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       "  * time       (time) datetime64[ns] 1kB 2011-01-03 2011-01-10 ... 2013-06-17\n",
       "Attributes:\n",
       "    long_name:  Surface pressure\n",
       "    units:      Pa"
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     },
     "execution_count": 21,
     "metadata": {},
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   "source": [
    "ds_osdf_1Kb  = ds_osdf.isel(lat=0,lon=0,member_id=0).isel(time=np.arange(130))\n",
    "ds_https_1Kb = ds_https.isel(lat=0,lon=0,member_id=0).isel(time=np.arange(130))\n",
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       "  <text x=\"7.532098\" y=\"107.532098\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.532098,107.532098)\">3</text>\n",
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       "</table></div></div></li><li class='xr-section-item'><input id='section-fcd1b91a-4143-4c8d-beab-4275933fb5a0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fcd1b91a-4143-4c8d-beab-4275933fb5a0' class='xr-section-summary' >Coordinates: <span>(4)</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 class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-ca0cf6c4-a3d4-437e-b003-c0cc5eb4886f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca0cf6c4-a3d4-437e-b003-c0cc5eb4886f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c04111f-5798-4b8d-a235-03b314358cae' class='xr-var-data-in' type='checkbox'><label for='data-3c04111f-5798-4b8d-a235-03b314358cae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057594, -88.11518 , -87.172775, -86.23037 , -85.28796 ,\n",
       "       -84.34555 , -83.403145, -82.46073 , -81.518326, -80.57591 , -79.63351 ,\n",
       "       -78.6911  , -77.74869 , -76.80628 , -75.86388 , -74.92146 , -73.97906 ,\n",
       "       -73.03665 , -72.09424 , -71.15183 , -70.20943 , -69.26701 , -68.32461 ,\n",
       "       -67.3822  , -66.43979 , -65.49738 , -64.55498 , -63.612564, -62.67016 ,\n",
       "       -61.72775 , -60.78534 , -59.842934, -58.900524, -57.958115, -57.015705,\n",
       "       -56.0733  , -55.13089 , -54.18848 , -53.246075, -52.303665, -51.361256,\n",
       "       -50.41885 , -49.47644 , -48.53403 , -47.59162 , -46.649216, -45.706806,\n",
       "       -44.764397, -43.82199 , -42.87958 , -41.937172, -40.994766, -40.052357,\n",
       "       -39.109947, -38.167538, -37.225132, -36.282722, -35.340313, -34.397907,\n",
       "       -33.455498, -32.51309 , -31.57068 , -30.628273, -29.685863, -28.743456,\n",
       "       -27.801046, -26.858639, -25.916231, -24.973822, -24.031414, -23.089005,\n",
       "       -22.146597, -21.20419 , -20.26178 , -19.319372, -18.376963, -17.434555,\n",
       "       -16.492147, -15.549738, -14.607329, -13.664922, -12.722513, -11.780105,\n",
       "       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,\n",
       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
       "        11.780105,  12.722513,  13.664922,  14.607329,  15.549738,  16.492147,\n",
       "        17.434555,  18.376963,  19.319372,  20.26178 ,  21.20419 ,  22.146597,\n",
       "        23.089005,  24.031414,  24.973822,  25.916231,  26.858639,  27.801046,\n",
       "        28.743456,  29.685863,  30.628273,  31.57068 ,  32.51309 ,  33.455498,\n",
       "        34.397907,  35.340313,  36.282722,  37.225132,  38.167538,  39.109947,\n",
       "        40.052357,  40.994766,  41.937172,  42.87958 ,  43.82199 ,  44.764397,\n",
       "        45.706806,  46.649216,  47.59162 ,  48.53403 ,  49.47644 ,  50.41885 ,\n",
       "        51.361256,  52.303665,  53.246075,  54.18848 ,  55.13089 ,  56.0733  ,\n",
       "        57.015705,  57.958115,  58.900524,  59.842934,  60.78534 ,  61.72775 ,\n",
       "        62.67016 ,  63.612564,  64.55498 ,  65.49738 ,  66.43979 ,  67.3822  ,\n",
       "        68.32461 ,  69.26701 ,  70.20943 ,  71.15183 ,  72.09424 ,  73.03665 ,\n",
       "        73.97906 ,  74.92146 ,  75.86388 ,  76.80628 ,  77.74869 ,  78.6911  ,\n",
       "        79.63351 ,  80.57591 ,  81.518326,  82.46073 ,  83.403145,  84.34555 ,\n",
       "        85.28796 ,  86.23037 ,  87.172775,  88.11518 ,  89.057594,  90.      ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-4636cd76-e530-4d84-a049-630e3addfccf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4636cd76-e530-4d84-a049-630e3addfccf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3426a7e4-7e2f-49dc-8576-e9ae81329d2c' class='xr-var-data-in' type='checkbox'><label for='data-3426a7e4-7e2f-49dc-8576-e9ae81329d2c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>2 3 4</div><input id='attrs-4ed91f63-cdc6-4f51-a9ff-5c947e8f7c81' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4ed91f63-cdc6-4f51-a9ff-5c947e8f7c81' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4dd40190-9a97-435a-869a-0c30e70e35bc' class='xr-var-data-in' type='checkbox'><label for='data-4dd40190-9a97-435a-869a-0c30e70e35bc' 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([2, 3, 4])</pre></div></li><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'>2011-01-03</div><input id='attrs-98737eb5-5d80-45e3-acc7-847ab321902e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-98737eb5-5d80-45e3-acc7-847ab321902e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee83d683-2fb3-40e0-a652-3f9118ec706f' class='xr-var-data-in' type='checkbox'><label for='data-ee83d683-2fb3-40e0-a652-3f9118ec706f' 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;2011-01-03T00:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-38c756b6-5d97-4b11-8278-3561786b735f' class='xr-section-summary-in' type='checkbox'  ><label for='section-38c756b6-5d97-4b11-8278-3561786b735f' class='xr-section-summary' >Indexes: <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-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-27ed791f-e873-4661-b2b7-875e294bee9a' class='xr-index-data-in' type='checkbox'/><label for='index-27ed791f-e873-4661-b2b7-875e294bee9a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0,  -89.0575942993164, -88.11518096923828,\n",
       "       -87.17277526855469,  -86.2303695678711, -85.28795623779297,\n",
       "       -84.34555053710938, -83.40314483642578, -82.46073150634766,\n",
       "       -81.51832580566406,\n",
       "       ...\n",
       "        81.51832580566406,  82.46073150634766,  83.40314483642578,\n",
       "        84.34555053710938,  85.28795623779297,   86.2303695678711,\n",
       "        87.17277526855469,  88.11518096923828,   89.0575942993164,\n",
       "                     90.0],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-79be7950-150d-49ea-bb9a-f0b121341a8f' class='xr-index-data-in' type='checkbox'/><label for='index-79be7950-150d-49ea-bb9a-f0b121341a8f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,\n",
       "        11.25,\n",
       "       ...\n",
       "        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,\n",
       "       358.75],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3a69be13-e76b-440a-83ce-9ffd08631854' class='xr-index-data-in' type='checkbox'/><label for='index-3a69be13-e76b-440a-83ce-9ffd08631854' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([2, 3, 4], dtype=&#x27;int64&#x27;, name=&#x27;member_id&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0fc70a34-68f1-4ff7-8c28-489fb2a960d9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0fc70a34-68f1-4ff7-8c28-489fb2a960d9' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Surface pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'PS' (member_id: 3, lat: 192, lon: 288)> Size: 1MB\n",
       "dask.array<getitem, shape=(3, 192, 288), dtype=float64, chunksize=(3, 32, 32), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * lat        (lat) float32 768B -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
       "  * lon        (lon) float32 1kB 0.0 1.25 2.5 3.75 ... 355.0 356.2 357.5 358.8\n",
       "  * member_id  (member_id) int64 24B 2 3 4\n",
       "    time       datetime64[ns] 8B 2011-01-03\n",
       "Attributes:\n",
       "    long_name:  Surface pressure\n",
       "    units:      Pa"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_osdf_1Mb  = ds_osdf.isel(time=0).isel(member_id =1+ np.arange(3))\n",
    "ds_https_1Mb = ds_https.isel(time=0).isel(member_id =1+ np.arange(3))\n",
    "ds_osdf_1Mb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "7ebacca2-e65b-4dfb-9df4-e1fa36d7dee5",
   "metadata": {},
   "outputs": [
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       ".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-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\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",
       ".xr-index-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",
       ".xr-index-data-in:checked ~ .xr-index-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-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-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",
       ".xr-no-icon {\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.DataArray &#x27;PS&#x27; (time: 24, lat: 192, lon: 288)&gt; Size: 11MB\n",
       "dask.array&lt;getitem, shape=(24, 192, 288), dtype=float64, chunksize=(24, 32, 32), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "  * lat        (lat) float32 768B -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
       "  * lon        (lon) float32 1kB 0.0 1.25 2.5 3.75 ... 355.0 356.2 357.5 358.8\n",
       "    member_id  int64 8B 5\n",
       "  * time       (time) datetime64[ns] 192B 2011-01-03 2011-01-10 ... 2011-06-13\n",
       "Attributes:\n",
       "    long_name:  Surface pressure\n",
       "    units:      Pa</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'PS'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 24</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-30e1809c-6d16-4f83-9813-110b097a9b99' class='xr-array-in' type='checkbox' checked><label for='section-30e1809c-6d16-4f83-9813-110b097a9b99' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(24, 32, 32), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 10.12 MiB </td>\n",
       "                        <td> 192.00 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (24, 192, 288) </td>\n",
       "                        <td> (24, 32, 32) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 54 chunks in 4 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "</table></div></div></li><li class='xr-section-item'><input id='section-ebdd05bc-7e1e-4409-ab89-4395c8d6b377' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ebdd05bc-7e1e-4409-ab89-4395c8d6b377' class='xr-section-summary' >Coordinates: <span>(4)</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 class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-85cc3a13-e785-4211-b3ff-e66a18cfccd0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-85cc3a13-e785-4211-b3ff-e66a18cfccd0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df80f695-7b96-4e52-8b91-50b77fbaaf66' class='xr-var-data-in' type='checkbox'><label for='data-df80f695-7b96-4e52-8b91-50b77fbaaf66' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057594, -88.11518 , -87.172775, -86.23037 , -85.28796 ,\n",
       "       -84.34555 , -83.403145, -82.46073 , -81.518326, -80.57591 , -79.63351 ,\n",
       "       -78.6911  , -77.74869 , -76.80628 , -75.86388 , -74.92146 , -73.97906 ,\n",
       "       -73.03665 , -72.09424 , -71.15183 , -70.20943 , -69.26701 , -68.32461 ,\n",
       "       -67.3822  , -66.43979 , -65.49738 , -64.55498 , -63.612564, -62.67016 ,\n",
       "       -61.72775 , -60.78534 , -59.842934, -58.900524, -57.958115, -57.015705,\n",
       "       -56.0733  , -55.13089 , -54.18848 , -53.246075, -52.303665, -51.361256,\n",
       "       -50.41885 , -49.47644 , -48.53403 , -47.59162 , -46.649216, -45.706806,\n",
       "       -44.764397, -43.82199 , -42.87958 , -41.937172, -40.994766, -40.052357,\n",
       "       -39.109947, -38.167538, -37.225132, -36.282722, -35.340313, -34.397907,\n",
       "       -33.455498, -32.51309 , -31.57068 , -30.628273, -29.685863, -28.743456,\n",
       "       -27.801046, -26.858639, -25.916231, -24.973822, -24.031414, -23.089005,\n",
       "       -22.146597, -21.20419 , -20.26178 , -19.319372, -18.376963, -17.434555,\n",
       "       -16.492147, -15.549738, -14.607329, -13.664922, -12.722513, -11.780105,\n",
       "       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,\n",
       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
       "        11.780105,  12.722513,  13.664922,  14.607329,  15.549738,  16.492147,\n",
       "        17.434555,  18.376963,  19.319372,  20.26178 ,  21.20419 ,  22.146597,\n",
       "        23.089005,  24.031414,  24.973822,  25.916231,  26.858639,  27.801046,\n",
       "        28.743456,  29.685863,  30.628273,  31.57068 ,  32.51309 ,  33.455498,\n",
       "        34.397907,  35.340313,  36.282722,  37.225132,  38.167538,  39.109947,\n",
       "        40.052357,  40.994766,  41.937172,  42.87958 ,  43.82199 ,  44.764397,\n",
       "        45.706806,  46.649216,  47.59162 ,  48.53403 ,  49.47644 ,  50.41885 ,\n",
       "        51.361256,  52.303665,  53.246075,  54.18848 ,  55.13089 ,  56.0733  ,\n",
       "        57.015705,  57.958115,  58.900524,  59.842934,  60.78534 ,  61.72775 ,\n",
       "        62.67016 ,  63.612564,  64.55498 ,  65.49738 ,  66.43979 ,  67.3822  ,\n",
       "        68.32461 ,  69.26701 ,  70.20943 ,  71.15183 ,  72.09424 ,  73.03665 ,\n",
       "        73.97906 ,  74.92146 ,  75.86388 ,  76.80628 ,  77.74869 ,  78.6911  ,\n",
       "        79.63351 ,  80.57591 ,  81.518326,  82.46073 ,  83.403145,  84.34555 ,\n",
       "        85.28796 ,  86.23037 ,  87.172775,  88.11518 ,  89.057594,  90.      ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-ad354776-0542-4604-be53-93338c519233' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad354776-0542-4604-be53-93338c519233' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2646750-bd6a-4f42-a0ec-b51d37a246cd' class='xr-var-data-in' type='checkbox'><label for='data-b2646750-bd6a-4f42-a0ec-b51d37a246cd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>member_id</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>5</div><input id='attrs-7f37d5fa-e591-427a-8e0b-6b1280a8fc1d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7f37d5fa-e591-427a-8e0b-6b1280a8fc1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bdb7d2a1-35ee-4e11-ab7a-e8a8261d388b' class='xr-var-data-in' type='checkbox'><label for='data-bdb7d2a1-35ee-4e11-ab7a-e8a8261d388b' 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)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2011-01-03 ... 2011-06-13</div><input id='attrs-7b775d04-fa9e-4f71-b0c5-f858b9184de3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7b775d04-fa9e-4f71-b0c5-f858b9184de3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-def1a9c3-d8af-42ed-8fd0-e2d2517eb122' class='xr-var-data-in' type='checkbox'><label for='data-def1a9c3-d8af-42ed-8fd0-e2d2517eb122' 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;2011-01-03T00:00:00.000000000&#x27;, &#x27;2011-01-10T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-01-17T00:00:00.000000000&#x27;, &#x27;2011-01-24T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-01-31T00:00:00.000000000&#x27;, &#x27;2011-02-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-02-14T00:00:00.000000000&#x27;, &#x27;2011-02-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-02-28T00:00:00.000000000&#x27;, &#x27;2011-03-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-03-14T00:00:00.000000000&#x27;, &#x27;2011-03-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-03-28T00:00:00.000000000&#x27;, &#x27;2011-04-04T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-04-11T00:00:00.000000000&#x27;, &#x27;2011-04-18T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-04-25T00:00:00.000000000&#x27;, &#x27;2011-05-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-05-09T00:00:00.000000000&#x27;, &#x27;2011-05-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-05-23T00:00:00.000000000&#x27;, &#x27;2011-05-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-06-06T00:00:00.000000000&#x27;, &#x27;2011-06-13T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2f719ddd-b688-4d39-8769-197d849cd1d5' class='xr-section-summary-in' type='checkbox'  ><label for='section-2f719ddd-b688-4d39-8769-197d849cd1d5' class='xr-section-summary' >Indexes: <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-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-453bf2b9-c62d-4600-b308-d80e4dadc230' class='xr-index-data-in' type='checkbox'/><label for='index-453bf2b9-c62d-4600-b308-d80e4dadc230' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0,  -89.0575942993164, -88.11518096923828,\n",
       "       -87.17277526855469,  -86.2303695678711, -85.28795623779297,\n",
       "       -84.34555053710938, -83.40314483642578, -82.46073150634766,\n",
       "       -81.51832580566406,\n",
       "       ...\n",
       "        81.51832580566406,  82.46073150634766,  83.40314483642578,\n",
       "        84.34555053710938,  85.28795623779297,   86.2303695678711,\n",
       "        87.17277526855469,  88.11518096923828,   89.0575942993164,\n",
       "                     90.0],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c31bd0ac-1d18-41e8-9bbd-baaf51d12ee5' class='xr-index-data-in' type='checkbox'/><label for='index-c31bd0ac-1d18-41e8-9bbd-baaf51d12ee5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,\n",
       "        11.25,\n",
       "       ...\n",
       "        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,\n",
       "       358.75],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2668bdb9-e5cc-4793-b3af-ac4be2072a95' class='xr-index-data-in' type='checkbox'/><label for='index-2668bdb9-e5cc-4793-b3af-ac4be2072a95' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2011-01-03&#x27;, &#x27;2011-01-10&#x27;, &#x27;2011-01-17&#x27;, &#x27;2011-01-24&#x27;,\n",
       "               &#x27;2011-01-31&#x27;, &#x27;2011-02-07&#x27;, &#x27;2011-02-14&#x27;, &#x27;2011-02-21&#x27;,\n",
       "               &#x27;2011-02-28&#x27;, &#x27;2011-03-07&#x27;, &#x27;2011-03-14&#x27;, &#x27;2011-03-21&#x27;,\n",
       "               &#x27;2011-03-28&#x27;, &#x27;2011-04-04&#x27;, &#x27;2011-04-11&#x27;, &#x27;2011-04-18&#x27;,\n",
       "               &#x27;2011-04-25&#x27;, &#x27;2011-05-02&#x27;, &#x27;2011-05-09&#x27;, &#x27;2011-05-16&#x27;,\n",
       "               &#x27;2011-05-23&#x27;, &#x27;2011-05-30&#x27;, &#x27;2011-06-06&#x27;, &#x27;2011-06-13&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ce36b6f9-fbf7-4c03-b238-3d99bab07c2a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ce36b6f9-fbf7-4c03-b238-3d99bab07c2a' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Surface pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'PS' (time: 24, lat: 192, lon: 288)> Size: 11MB\n",
       "dask.array<getitem, shape=(24, 192, 288), dtype=float64, chunksize=(24, 32, 32), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * lat        (lat) float32 768B -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
       "  * lon        (lon) float32 1kB 0.0 1.25 2.5 3.75 ... 355.0 356.2 357.5 358.8\n",
       "    member_id  int64 8B 5\n",
       "  * time       (time) datetime64[ns] 192B 2011-01-03 2011-01-10 ... 2011-06-13\n",
       "Attributes:\n",
       "    long_name:  Surface pressure\n",
       "    units:      Pa"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_osdf_10Mb  = ds_osdf.isel(member_id =4).isel(time=np.arange(24))\n",
    "ds_https_10Mb = ds_https.isel(member_id =4).isel(time=np.arange(24))\n",
    "ds_osdf_10Mb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "673bca96-e11c-4a5b-b750-c811c8ccc55a",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_osdf_100Mb  = ds_osdf.isel(member_id =5).isel(time=np.arange(238))\n",
    "ds_https_100Mb = ds_https.isel(member_id =5).isel(time=np.arange(238))\n",
    "#ds_osdf_100Mb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "29af52c9-0c65-44a3-b172-f6a14ce5f5e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_osdf_200Mb  = ds_osdf.isel(member_id = 6)\n",
    "ds_https_200Mb = ds_https.isel(member_id =6)\n",
    "#ds_https_200Mb "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "345b40c3-e106-442b-897b-26ed1120015c",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_osdf_400Mb  = ds_osdf.isel(member_id = 7 +np.arange(2))\n",
    "ds_https_400Mb = ds_https.isel(member_id =7 + np.arange(2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "d20b7160-c1b3-46eb-b4f4-eed6e30f53b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_osdf_600Mb  = ds_osdf.isel(member_id  = 10 +np.arange(3))\n",
    "ds_https_600Mb = ds_https.isel(member_id = 10 + np.arange(3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "6bf19a51-042b-4f73-8d90-1e4fc177daef",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_osdf_800Mb  = ds_osdf.isel(member_id  = 14 +np.arange(4))\n",
    "ds_https_800Mb = ds_https.isel(member_id = 14 + np.arange(4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "5ad55e72-111b-4e09-b614-f8189610d0c7",
   "metadata": {},
   "outputs": [
    {
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       ".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",
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       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
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       "\n",
       ".xr-var-dims {\n",
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       "\n",
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       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
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       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
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       "\n",
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       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
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       ".xr-var-data,\n",
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       "\n",
       ".xr-var-name span,\n",
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       ".xr-index-name div,\n",
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       ".xr-var-data,\n",
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
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       "\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",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;PS&#x27; (member_id: 6, time: 410, lat: 192, lon: 288)&gt; Size: 1GB\n",
       "dask.array&lt;getitem, shape=(6, 410, 192, 288), dtype=float64, chunksize=(6, 80, 32, 32), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "  * lat        (lat) float32 768B -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
       "  * lon        (lon) float32 1kB 0.0 1.25 2.5 3.75 ... 355.0 356.2 357.5 358.8\n",
       "  * member_id  (member_id) int64 48B 20 21 22 23 24 25\n",
       "  * time       (time) datetime64[ns] 3kB 2011-01-03 2011-01-10 ... 2018-10-29\n",
       "Attributes:\n",
       "    long_name:  Surface pressure\n",
       "    units:      Pa</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'PS'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 6</li><li><span class='xr-has-index'>time</span>: 410</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-ee5e439f-37bf-4143-bb1d-8ac173236591' class='xr-array-in' type='checkbox' checked><label for='section-ee5e439f-37bf-4143-bb1d-8ac173236591' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(6, 80, 32, 32), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.01 GiB </td>\n",
       "                        <td> 3.75 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (6, 410, 192, 288) </td>\n",
       "                        <td> (6, 80, 32, 32) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 324 chunks in 4 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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       "       -84.34555 , -83.403145, -82.46073 , -81.518326, -80.57591 , -79.63351 ,\n",
       "       -78.6911  , -77.74869 , -76.80628 , -75.86388 , -74.92146 , -73.97906 ,\n",
       "       -73.03665 , -72.09424 , -71.15183 , -70.20943 , -69.26701 , -68.32461 ,\n",
       "       -67.3822  , -66.43979 , -65.49738 , -64.55498 , -63.612564, -62.67016 ,\n",
       "       -61.72775 , -60.78534 , -59.842934, -58.900524, -57.958115, -57.015705,\n",
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       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
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       "        28.743456,  29.685863,  30.628273,  31.57068 ,  32.51309 ,  33.455498,\n",
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       "        79.63351 ,  80.57591 ,  81.518326,  82.46073 ,  83.403145,  84.34555 ,\n",
       "        85.28796 ,  86.23037 ,  87.172775,  88.11518 ,  89.057594,  90.      ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-1a986acd-e5ff-43b2-88e4-bb5110e3c742' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a986acd-e5ff-43b2-88e4-bb5110e3c742' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e532ecb7-20a3-4c07-b0e6-c0749ed42efc' class='xr-var-data-in' type='checkbox'><label for='data-e532ecb7-20a3-4c07-b0e6-c0749ed42efc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>20 21 22 23 24 25</div><input id='attrs-3738273f-9db0-4f80-acd5-7193c7f57196' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3738273f-9db0-4f80-acd5-7193c7f57196' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93c771a0-9953-48ad-92ff-0f2af54bf81d' class='xr-var-data-in' type='checkbox'><label for='data-93c771a0-9953-48ad-92ff-0f2af54bf81d' 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([20, 21, 22, 23, 24, 25])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2011-01-03 ... 2018-10-29</div><input id='attrs-909a43dd-24b0-4570-b69d-b832937650f9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-909a43dd-24b0-4570-b69d-b832937650f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b5dd6c0-a4d6-4b71-98d7-5977c8770412' class='xr-var-data-in' type='checkbox'><label for='data-6b5dd6c0-a4d6-4b71-98d7-5977c8770412' 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;2011-01-03T00:00:00.000000000&#x27;, &#x27;2011-01-10T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-01-17T00:00:00.000000000&#x27;, ..., &#x27;2018-10-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-10-22T00:00:00.000000000&#x27;, &#x27;2018-10-29T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3077459a-94fe-49ba-ba6f-b65728f30fe8' class='xr-section-summary-in' type='checkbox'  ><label for='section-3077459a-94fe-49ba-ba6f-b65728f30fe8' class='xr-section-summary' >Indexes: <span>(4)</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-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8f257ed3-0289-4d73-b4a7-e69f00ddb19a' class='xr-index-data-in' type='checkbox'/><label for='index-8f257ed3-0289-4d73-b4a7-e69f00ddb19a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0,  -89.0575942993164, -88.11518096923828,\n",
       "       -87.17277526855469,  -86.2303695678711, -85.28795623779297,\n",
       "       -84.34555053710938, -83.40314483642578, -82.46073150634766,\n",
       "       -81.51832580566406,\n",
       "       ...\n",
       "        81.51832580566406,  82.46073150634766,  83.40314483642578,\n",
       "        84.34555053710938,  85.28795623779297,   86.2303695678711,\n",
       "        87.17277526855469,  88.11518096923828,   89.0575942993164,\n",
       "                     90.0],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-78b0665e-00d4-48d4-b85a-08bb42830d1a' class='xr-index-data-in' type='checkbox'/><label for='index-78b0665e-00d4-48d4-b85a-08bb42830d1a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,\n",
       "        11.25,\n",
       "       ...\n",
       "        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,\n",
       "       358.75],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c0db1d1b-0718-4e97-80a8-f120a3bf396f' class='xr-index-data-in' type='checkbox'/><label for='index-c0db1d1b-0718-4e97-80a8-f120a3bf396f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([20, 21, 22, 23, 24, 25], dtype=&#x27;int64&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f24020b6-0157-455c-9426-0eb6df67c747' class='xr-index-data-in' type='checkbox'/><label for='index-f24020b6-0157-455c-9426-0eb6df67c747' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2011-01-03 00:00:00&#x27;, &#x27;2011-01-10 00:00:00&#x27;,\n",
       "               &#x27;2011-01-17 00:00:00&#x27;, &#x27;2011-01-24 00:00:00&#x27;,\n",
       "               &#x27;2011-01-31 00:00:00&#x27;, &#x27;2011-02-07 00:00:00&#x27;,\n",
       "               &#x27;2011-02-14 00:00:00&#x27;, &#x27;2011-02-21 00:00:00&#x27;,\n",
       "               &#x27;2011-02-28 00:00:00&#x27;, &#x27;2011-03-07 00:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2018-08-27 00:00:00&#x27;, &#x27;2018-09-03 00:00:00&#x27;,\n",
       "               &#x27;2018-09-10 00:00:00&#x27;, &#x27;2018-09-17 00:00:00&#x27;,\n",
       "               &#x27;2018-09-24 00:00:00&#x27;, &#x27;2018-10-01 00:00:00&#x27;,\n",
       "               &#x27;2018-10-08 00:00:00&#x27;, &#x27;2018-10-15 00:00:00&#x27;,\n",
       "               &#x27;2018-10-22 00:00:00&#x27;, &#x27;2018-10-29 00:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=410, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c20651f2-1678-4210-b98f-3b5289c05480' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c20651f2-1678-4210-b98f-3b5289c05480' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Surface pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'PS' (member_id: 6, time: 410, lat: 192, lon: 288)> Size: 1GB\n",
       "dask.array<getitem, shape=(6, 410, 192, 288), dtype=float64, chunksize=(6, 80, 32, 32), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * lat        (lat) float32 768B -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
       "  * lon        (lon) float32 1kB 0.0 1.25 2.5 3.75 ... 355.0 356.2 357.5 358.8\n",
       "  * member_id  (member_id) int64 48B 20 21 22 23 24 25\n",
       "  * time       (time) datetime64[ns] 3kB 2011-01-03 2011-01-10 ... 2018-10-29\n",
       "Attributes:\n",
       "    long_name:  Surface pressure\n",
       "    units:      Pa"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_osdf_1Gb  = ds_osdf.isel(member_id  = 19 + np.arange(6)).isel(time = np.arange(410))\n",
    "ds_https_1Gb = ds_https.isel(member_id = 19 + np.arange(6)).isel(time = np.arange(410))\n",
    "ds_osdf_1Gb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "00ef6322-3487-4191-9316-b118b64be088",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ds_osdf_10Gb  = ds_osdf.isel(member_id  = 12 + np.arange(52))\n",
    "# ds_https_10Gb = ds_https.isel(member_id = 12 + np.arange(52))\n",
    "# ds_osdf_10Gb"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7eb6c7a1-1438-4fd9-8931-46d2de1f7164",
   "metadata": {},
   "source": [
    "### Now access data and plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "32b87134-2d2d-40f5-a5ea-5795ef9a7777",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_osdf_list  = [ds_osdf_1Mb,ds_osdf_10Mb,ds_osdf_100Mb,ds_osdf_200Mb,ds_osdf_400Mb,\n",
    "                 ds_osdf_600Mb,ds_osdf_800Mb,ds_osdf_1Gb]\n",
    "ds_https_list = [ds_https_1Mb,ds_https_10Mb,ds_https_100Mb,ds_https_200Mb,ds_https_400Mb,\n",
    "                 ds_https_600Mb,ds_https_800Mb,ds_https_1Gb]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "56da4485-f3c1-44f8-acc9-ad49577ca48d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Number of data access calls\n",
    "num_calls = 7  # Modify this as needed\n",
    "n_workers = 4  # Set this to your preferred number of workers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "fd574ee1-e7c6-42ef-aa42-783b34b30f04",
   "metadata": {},
   "outputs": [],
   "source": [
    "# DiagnosticTimer class to keep track of runtimes\n",
    "class DiagnosticTimer:\n",
    "    def __init__(self):\n",
    "        self.diagnostics = []\n",
    "\n",
    "    @contextmanager\n",
    "    def time(self, **kwargs):\n",
    "        tic = time.time()\n",
    "        yield\n",
    "        toc = time.time()\n",
    "        kwargs[\"runtime\"] = toc - tic\n",
    "        self.diagnostics.append(kwargs)\n",
    "\n",
    "    def dataframe(self):\n",
    "        return pd.DataFrame(self.diagnostics)\n",
    "\n",
    "# Initialize the DiagnosticTimer\n",
    "diag_timer = DiagnosticTimer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "cdffd5fb-46c5-42ed-8135-0e9368e62bca",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function to check existing CSV file and determine missing runs\n",
    "def load_existing_results():\n",
    "    if os.path.exists(csv_file_path):\n",
    "        # Load existing CSV into DataFrame\n",
    "        existing_df = pd.read_csv(csv_file_path)\n",
    "    else:\n",
    "        # Create an empty DataFrame if the file does not exist\n",
    "        existing_df = pd.DataFrame(columns=[\"dataset_size\", \"protocol\", \"call_number\", \"runtime\", \"MBps\"])\n",
    "    return existing_df\n",
    "\n",
    "def filter_missing_runs(datasets, protocol_name, existing_df):\n",
    "    # Convert dataset sizes to MB for checking, using a list of tuples\n",
    "    dataset_sizes_mb = [(dataset, dataset.nbytes / (1024 ** 2)) for dataset in datasets]\n",
    "\n",
    "    # Identify missing dataset sizes and calls\n",
    "    filtered_datasets = []\n",
    "    for dataset, dataset_size_mb in dataset_sizes_mb:\n",
    "        for call_num in range(1, num_calls + 1):\n",
    "            # Check if this dataset size and call number combination already exists\n",
    "            if not ((existing_df[\"dataset_size\"] == dataset_size_mb) &\n",
    "                    (existing_df[\"protocol\"] == protocol_name) &\n",
    "                    (existing_df[\"call_number\"] == call_num)).any():\n",
    "                filtered_datasets.append((dataset, dataset_size_mb, call_num))\n",
    "    \n",
    "    return filtered_datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "5148af1d-a120-4f85-af51-f136c64ededb",
   "metadata": {},
   "outputs": [],
   "source": [
    "def benchmark_protocol(datasets, protocol_name, cluster=None):\n",
    "    existing_df = load_existing_results()  # Load existing results as a checkpoint\n",
    "\n",
    "    # Filter for missing runs based on existing results\n",
    "    missing_runs = filter_missing_runs(datasets, protocol_name, existing_df)\n",
    "    diag_timer = DiagnosticTimer()  # Initialize the diagnostic timer\n",
    "\n",
    "    # Process each dataset and call\n",
    "    for (dataset, dataset_size_mb, call_num) in missing_runs:\n",
    "        # Restart the Dask cluster if provided\n",
    "        if cluster is not None:\n",
    "            cluster.scale(0)  # Scale down to release worker memory\n",
    "            cluster.scale(n_workers)  # Scale up to required number of workers\n",
    "            client.wait_for_workers(n_workers)  # Wait for workers to be ready\n",
    "\n",
    "        # Inform the start of processing for this dataset and call\n",
    "        print(f\"Starting processing of dataset for protocol '{protocol_name}' (Size: {dataset_size_mb} MB) in call {call_num}\")\n",
    "\n",
    "        # Only count the time for loading dataset into memory\n",
    "        dataset_copy = dataset.copy()\n",
    "        with diag_timer.time(dataset_size=dataset_size_mb, protocol=protocol_name, call_number=call_num):\n",
    "            dataset_copy.load()  # Load the dataset into memory\n",
    "\n",
    "        # Convert the single call result to a DataFrame and add MBps column\n",
    "        call_result_df = diag_timer.dataframe().iloc[[-1]].copy()  # Get the latest diagnostic entry\n",
    "        call_result_df[\"MBps\"] = call_result_df[\"dataset_size\"] / call_result_df[\"runtime\"]\n",
    "\n",
    "        # Append this call's result to CSV\n",
    "        call_result_df.to_csv(csv_file_path, mode='a', header=not os.path.exists(csv_file_path), index=False)\n",
    "        print(f\"Appended results for protocol '{protocol_name}', call {call_num} to '{csv_file_path}'\")\n",
    "\n",
    "        # Print statement after finishing each call\n",
    "        print(f\"Finished processing dataset for protocol '{protocol_name}' in call {call_num}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "f45323ba-0edc-4cb5-8153-9b0a424242c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# def benchmark_protocol(datasets, protocol_name, cluster=None):\n",
    "#     for index, dataset in enumerate(datasets):\n",
    "#         # Calculate dataset size in MB for logging\n",
    "#         dataset_size_mb = dataset.nbytes / (1024 ** 2)\n",
    "        \n",
    "#         # Each dataset will be loaded multiple times to capture caching effect\n",
    "#         for call_num in range(num_calls):\n",
    "#             if cluster is not None:\n",
    "#                 # Scale down to zero workers to clear memory\n",
    "#                 cluster.scale(0)  # Stop all workers\n",
    "#                 cluster.scale(n_workers)  # Scale up to the required number of workers\n",
    "#                 client.wait_for_workers(n_workers)  # Wait for the workers to be ready\n",
    "\n",
    "#             # Only count the time for loading dataset into memory, excluding cluster scaling time\n",
    "#             dataset_copy = dataset.copy()\n",
    "#             with diag_timer.time(dataset_size=dataset_size_mb, protocol=protocol_name, call_number=call_num + 1):\n",
    "#                 dataset_copy.load()  # Load the dataset into memory\n",
    "#             print(f\" Finished processing dataset {index + 1} in {call_num + 1} th call\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2b27afca-d0f7-496d-8277-bd9915039755",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting processing of dataset for protocol 'HTTPS-only' (Size: 100.40625 MB) in call 3\n"
     ]
    }
   ],
   "source": [
    "# Run benchmark for each protocol\n",
    "benchmark_protocol(ds_https_list, \"HTTPS-only\",cluster=None)\n",
    "benchmark_protocol(ds_osdf_list, \"OSDF-director\",cluster=None)\n",
    "\n",
    "# Convert diagnostics to a DataFrame for analysis\n",
    "df_diagnostics = diag_timer.dataframe()\n",
    "\n",
    "# Calculate MB/s for each run\n",
    "df_diagnostics['MBps'] = df_diagnostics['dataset_size'] / df_diagnostics['runtime']\n",
    "df_diagnostics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b7ff4999-abe9-4e81-ac36-aa8faea6d7e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Plotting MBps vs data size for each protocol and call type\n",
    "# Define different alpha values for each protocol\n",
    "alpha_values = {\"HTTPS-only\": 0.8, \"OSDF-director\": 0.5}  # Adjust transparency as needed\n",
    "marker_style = {\"HTTPS-only\": \"o\", \"OSDF-director\": \"x\"}  # Define different markers for each protocol\n",
    "#\n",
    "fig, ax = plt.subplots(figsize=(10, 6))\n",
    "for protocol in [\"HTTPS-only\", \"OSDF-director\"]:\n",
    "    # First access (call_number == 1)\n",
    "    first_access = df_diagnostics[(df_diagnostics['protocol'] == protocol) & (df_diagnostics['call_number'] == 1)]\n",
    "    ax.scatter(first_access['dataset_size'], first_access['MBps'], label=f\"{protocol} - First Access\",\n",
    "            alpha=alpha_values[protocol],marker=marker_style[protocol],markersize=8)\n",
    "\n",
    "    # Subsequent access (call_number > 1)\n",
    "    subsequent_access = df_diagnostics[(df_diagnostics['protocol'] == protocol) & (df_diagnostics['call_number'] > 1)]\n",
    "    subsequent_access_avg = subsequent_access.groupby('dataset_size')['MBps'].mean()\n",
    "    ax.plot(subsequent_access_avg.index, subsequent_access_avg.values, \n",
    "            linestyle='--', label=f\"{protocol} - Subsequent Access (Avg)\",alpha=alpha_values[protocol],marker=marker_style[protocol],markersize=8)\n",
    "    \n",
    "# Customize plot appearance\n",
    "ax.set_xlabel(\"Data Size (MB)\")\n",
    "ax.set_ylabel(\"Data Access Speed (MBps)\")\n",
    "ax.set_title(\"NCAR origin benchmark\")\n",
    "ax.legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9c77b9c2-3353-4e30-a2df-b67d4abdc118",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert dataset size to categorical to control the order in the plot\n",
    "df_diagnostics['dataset_size'] = df_diagnostics['dataset_size'].astype(\"category\")\n",
    "\n",
    "# Set the order for dataset sizes to appear in ascending order\n",
    "size_order = sorted(df_diagnostics['dataset_size'].unique())\n",
    "\n",
    "# Create the box plot\n",
    "plt.figure(figsize=(12, 6))\n",
    "sns.boxplot(\n",
    "    data=df_diagnostics, \n",
    "    x=\"dataset_size\", \n",
    "    y=\"MBps\", \n",
    "    hue=\"protocol\", \n",
    "    order=size_order\n",
    ")\n",
    "\n",
    "# Customize plot appearance\n",
    "plt.xlabel(\"Data Size (MB)\")\n",
    "plt.ylabel(\"Data Access Speed (MBps)\")\n",
    "plt.title(\"NCAR to UWMadison, Dask: 4x4GiB, 7 requests\")\n",
    "plt.legend(title=\"Protocol\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4cad5c8-d223-48ae-b370-79475df5a0ac",
   "metadata": {},
   "source": [
    "### Try with a specific cache"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "abc3dd3d-296e-4845-8dce-34169280a99c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# historical_smbb_test1 = historical_smbb.isel(time=0).isel(member_id =1+ np.arange(5))\n",
    "# historical_smbb_test1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "735e1a49-5361-452f-a449-231ad8da5795",
   "metadata": {},
   "outputs": [],
   "source": [
    "# %%timeit -r2 -n3 -o\n",
    "# historical_smbb_test1.compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "035a67dc-00f6-4368-a413-75a3cf011bf8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# #Try using a specific cache\n",
    "# sdsc_cache='https://sdsc-cache.nationalresearchplatform.org:8443/aws-opendata/us-west-2/ncar-cesm2-lens/atm/monthly/'+\\\n",
    "#             'cesm2LE-historical-smbb-TREFHTMX.zarr'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "824dfccd-b3ba-4ed9-814f-a9f4810163d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# %%time\n",
    "# test_1 = xr.open_zarr(sdsc_cache).TREFHTMX.isel(time=0)\n",
    "# test_1"
   ]
  }
 ],
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