scipy2022_demo.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8cbd8226-af23-41d4-bb9c-d7d79da013eb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# need to install this manually (since it is not on the pangeo notebook image)\n",
    "# !mamba install xmip -y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c2e74c64-3c9e-4a49-a2d9-24e1558ca7f2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import xmip\n",
    "# xmip.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "33629906-6cc7-4d88-a170-341b7a3edd8d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-07-11 23:49:07,731 - distributed.diskutils - INFO - Found stale lock file and directory '/home/jovyan/presentation_scipy22_cmip/dask-worker-space/worker-1qr2e564', purging\n"
     ]
    },
    {
     "data": {
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       "<div>\n",
       "    <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\"> </div>\n",
       "    <div style=\"margin-left: 48px;\">\n",
       "        <h3 style=\"margin-bottom: 0px;\">Client</h3>\n",
       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-0e075750-0174-11ed-8ab0-1a12b88f47f2</p>\n",
       "        <table style=\"width: 100%; text-align: left;\">\n",
       "\n",
       "        <tr>\n",
       "        \n",
       "            <td style=\"text-align: left;\"><strong>Connection method:</strong> Cluster object</td>\n",
       "            <td style=\"text-align: left;\"><strong>Cluster type:</strong> distributed.LocalCluster</td>\n",
       "        \n",
       "        </tr>\n",
       "\n",
       "        \n",
       "            <tr>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Dashboard: </strong> <a href=\"/user/jbusecke/proxy/8787/status\" target=\"_blank\">/user/jbusecke/proxy/8787/status</a>\n",
       "                </td>\n",
       "                <td style=\"text-align: left;\"></td>\n",
       "            </tr>\n",
       "        \n",
       "\n",
       "        </table>\n",
       "\n",
       "        \n",
       "            <details>\n",
       "            <summary style=\"margin-bottom: 20px;\"><h3 style=\"display: inline;\">Cluster Info</h3></summary>\n",
       "            <div class=\"jp-RenderedHTMLCommon jp-RenderedHTML jp-mod-trusted jp-OutputArea-output\">\n",
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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;\">8c0cf7c7</p>\n",
       "        <table style=\"width: 100%; text-align: left;\">\n",
       "            <tr>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Dashboard:</strong> <a href=\"/user/jbusecke/proxy/8787/status\" target=\"_blank\">/user/jbusecke/proxy/8787/status</a>\n",
       "                </td>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Workers:</strong> 1\n",
       "                </td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Total threads:</strong> 16\n",
       "                </td>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Total memory:</strong> 58.88 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-5cb8809d-c0cb-42c0-8b87-29a4f6dcf837</p>\n",
       "            <table style=\"width: 100%; text-align: left;\">\n",
       "                <tr>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Comm:</strong> tcp://127.0.0.1:35965\n",
       "                    </td>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Workers:</strong> 1\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Dashboard:</strong> <a href=\"/user/jbusecke/proxy/8787/status\" target=\"_blank\">/user/jbusecke/proxy/8787/status</a>\n",
       "                    </td>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Total threads:</strong> 16\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> 58.88 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://127.0.0.1:45735\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 16\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"/user/jbusecke/proxy/36493/status\" target=\"_blank\">/user/jbusecke/proxy/36493/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 58.88 GiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Nanny: </strong> tcp://127.0.0.1:37689\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> /home/jovyan/presentation_scipy22_cmip/dask-worker-space/worker-pya599lv\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>\n",
       "            </details>\n",
       "        \n",
       "\n",
       "    </div>\n",
       "</div>"
      ],
      "text/plain": [
       "<Client: 'tcp://127.0.0.1:35965' processes=1 threads=16, memory=58.88 GiB>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import dask\n",
    "from distributed import LocalCluster, Client\n",
    "\n",
    "dask.config.set(**{\"distributed.dashboard.link\": \"/user/{JUPYTERHUB_USER}/proxy/{port}/status\"})\n",
    "cluster = LocalCluster(n_workers=1)\n",
    "client = Client(cluster)\n",
    "client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6ed9c8c1-41a4-4142-9df9-a2cb633651de",
   "metadata": {},
   "outputs": [],
   "source": [
    "from xmip.preprocessing import combined_preprocessing\n",
    "from xmip.postprocessing import match_metrics, pick_first_member\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format='retina'\n",
    "\n",
    "from xarrayutils.plotting import shaded_line_plot\n",
    "\n",
    "from functools import reduce\n",
    "from tqdm.auto import tqdm\n",
    "import xarray as xr\n",
    "import pandas as pd\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3e7ce3c9-dd22-4556-89d8-a489eed0e121",
   "metadata": {},
   "outputs": [],
   "source": [
    "def _maybe_make_list(a):\n",
    "    if isinstance(a,str):\n",
    "        return [a]\n",
    "    else:\n",
    "        return a\n",
    "\n",
    "def search_and_load_zarr(df, preprocess=combined_preprocessing, **kwargs):\n",
    "    # parse kwargs to dataframe index list\n",
    "    filter_list = [df[k].isin(_maybe_make_list(v)) for k,v in kwargs.items()]\n",
    "    index = reduce(lambda a,b: a & b, filter_list, True)\n",
    "    df_filtered = df.loc[index]\n",
    "    stores = df_filtered['zstore'].tolist()\n",
    "    instance_ids = ['.'.join(s.split('/')[3:-1]) for s in stores]\n",
    "    ddict = {}\n",
    "    iter_list = list(zip(instance_ids, stores))\n",
    "    for iid, sto in tqdm(iter_list):\n",
    "        try:\n",
    "            ds = xr.open_zarr(sto, consolidated=True, use_cftime=True)\n",
    "            # ds = xr.open_dataset(sto, engine='zarr', consolidated=True, use_cftime=True, chunks={'time':3})\n",
    "            if preprocess:\n",
    "                ds = preprocess(ds)\n",
    "            ddict[iid] = ds\n",
    "        except Exception as e:\n",
    "            print(f\"{iid} failed with {e}\")\n",
    "    return ddict\n",
    "\n",
    "df = pd.read_csv(\"https://storage.googleapis.com/cmip6/pangeo-cmip6.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "5a0f2c32-3738-4316-ad80-6ed91b68fee1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2e9e45a52acb4786818328171a0fbb7e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6ca54399f3f1414e83234a776cee050f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# choosing a subset of models (to reduce the compute time, and some unresolved issues)\n",
    "# The commented models have many members and increase the loading time significantly\n",
    "source_ids = [\n",
    " # 'ACCESS-ESM1-5',\n",
    " 'CAS-ESM2-0',\n",
    " 'CMCC-ESM2',\n",
    " # 'CNRM-ESM2-1',\n",
    " 'E3SM-1-1-ECA',\n",
    " 'FGOALS-g3',\n",
    " 'GFDL-CM4',\n",
    " 'GFDL-ESM4',\n",
    " 'ICON-ESM-LR',\n",
    " 'INM-CM5-0',\n",
    " # 'IPSL-CM6A-LR',\n",
    " 'KACE-1-0-G',\n",
    " 'KIOST-ESM',\n",
    " 'MCM-UA-1-0',\n",
    " # 'MIROC6',\n",
    " 'MPI-ESM1-2-LR',\n",
    " 'MRI-ESM2-0',\n",
    " 'NorESM2-MM',\n",
    " 'SAM0-UNICON',\n",
    " 'TaiESM1',\n",
    "]\n",
    "\n",
    "grid_labels = ['gn']\n",
    "activity_ids = ['CMIP', 'ScenarioMIP']\n",
    "experiment_ids = [\n",
    "        'historical',\n",
    "        'ssp126',\n",
    "        'ssp245',\n",
    "        'ssp370',\n",
    "        'ssp585',\n",
    "    ]\n",
    "\n",
    "data = search_and_load_zarr(\n",
    "    df,\n",
    "    source_id=source_ids,\n",
    "    variable_id='tos',\n",
    "    activity_id = activity_ids,\n",
    "    experiment_id=experiment_ids,\n",
    "    table_id='Omon',\n",
    "    grid_label='gn',\n",
    ")\n",
    "area_data = search_and_load_zarr(\n",
    "    df,\n",
    "    source_id=source_ids,\n",
    "    experiment_id = experiment_ids + ['piControl'],\n",
    "    variable_id='areacello',\n",
    "    table_id='Ofx',\n",
    "    grid_label='gn',\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76a0b7a9-34da-4d5c-b001-b2b1d4adc642",
   "metadata": {},
   "source": [
    "## xMIP: Match cell area to datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "443d1422-9c56-40b2-b701-e38fee2f830a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processed 138 datasets.\n",
      "Exact matches:{'areacello': 0}\n",
      "Other matches:{'areacello': 138}\n",
      "No match found:{'areacello': 0}\n"
     ]
    }
   ],
   "source": [
    "data_with_metrics = match_metrics(\n",
    "    data,\n",
    "    area_data,\n",
    "    ['areacello'],\n",
    "    print_statistics=True\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6de6e032-4d58-4410-a236-9f684e1a1045",
   "metadata": {},
   "source": [
    "## xMIP: Pick only one member to speed things up"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "8cb8da43-84d3-4122-b5c4-a8d05a33fed1",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_first = pick_first_member(data_with_metrics)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3dc6970e-d299-4960-8303-ad7f0962d82a",
   "metadata": {},
   "source": [
    "## Create averaged timeseries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "a3a5c678-5836-40d0-8045-6bf226c29ca4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "GFDL-ESM4.gn.historical.Omon.tos\n",
      "GFDL-CM4.gn.ssp245.Omon.tos\n",
      "GFDL-CM4.gn.historical.Omon.tos\n",
      "GFDL-ESM4.gn.ssp585.Omon.tos\n",
      "GFDL-ESM4.gn.ssp245.Omon.tos\n",
      "GFDL-ESM4.gn.ssp370.Omon.tos\n",
      "GFDL-ESM4.gn.ssp126.Omon.tos\n",
      "GFDL-CM4.gn.ssp585.Omon.tos\n",
      "SAM0-UNICON.gn.historical.Omon.tos\n",
      "MPI-ESM1-2-LR.gn.ssp245.Omon.tos\n",
      "MPI-ESM1-2-LR.gn.ssp126.Omon.tos\n",
      "MPI-ESM1-2-LR.gn.historical.Omon.tos\n",
      "MPI-ESM1-2-LR.gn.ssp585.Omon.tos\n",
      "MPI-ESM1-2-LR.gn.ssp370.Omon.tos\n",
      "MCM-UA-1-0.gn.historical.Omon.tos\n",
      "MCM-UA-1-0.gn.ssp585.Omon.tos\n",
      "MCM-UA-1-0.gn.ssp126.Omon.tos\n",
      "MCM-UA-1-0.gn.ssp245.Omon.tos\n",
      "MCM-UA-1-0.gn.ssp370.Omon.tos\n",
      "MRI-ESM2-0.gn.historical.Omon.tos\n",
      "MRI-ESM2-0.gn.ssp245.Omon.tos\n",
      "MRI-ESM2-0.gn.ssp370.Omon.tos\n",
      "FGOALS-g3.gn.historical.Omon.tos\n",
      "MRI-ESM2-0.gn.ssp126.Omon.tos\n",
      "MRI-ESM2-0.gn.ssp585.Omon.tos\n",
      "NorESM2-MM.gn.ssp126.Omon.tos\n",
      "NorESM2-MM.gn.ssp245.Omon.tos\n",
      "NorESM2-MM.gn.ssp585.Omon.tos\n",
      "NorESM2-MM.gn.ssp370.Omon.tos\n",
      "NorESM2-MM.gn.historical.Omon.tos\n",
      "FGOALS-g3.gn.ssp245.Omon.tos\n",
      "FGOALS-g3.gn.ssp126.Omon.tos\n",
      "FGOALS-g3.gn.ssp585.Omon.tos\n",
      "FGOALS-g3.gn.ssp370.Omon.tos\n",
      "TaiESM1.gn.historical.Omon.tos\n",
      "CAS-ESM2-0.gn.ssp585.Omon.tos\n",
      "CAS-ESM2-0.gn.ssp370.Omon.tos\n",
      "CAS-ESM2-0.gn.ssp245.Omon.tos\n",
      "CAS-ESM2-0.gn.ssp126.Omon.tos\n",
      "CMCC-ESM2.gn.historical.Omon.tos\n",
      "CMCC-ESM2.gn.ssp126.Omon.tos\n",
      "CMCC-ESM2.gn.ssp585.Omon.tos\n",
      "CMCC-ESM2.gn.ssp245.Omon.tos\n",
      "CMCC-ESM2.gn.ssp370.Omon.tos\n",
      "TaiESM1.gn.ssp370.Omon.tos\n",
      "TaiESM1.gn.ssp585.Omon.tos\n",
      "TaiESM1.gn.ssp245.Omon.tos\n",
      "TaiESM1.gn.ssp126.Omon.tos\n"
     ]
    }
   ],
   "source": [
    "data_timeseries = {}\n",
    "for k,ds in data_first.items():\n",
    "    \n",
    "    print(k)\n",
    "    # This is the core of the analysis. A one-liner thanks to xarray. \n",
    "    timeseries = ds.tos.weighted(ds.areacello.fillna(0)).mean(['x', 'y']).load()\n",
    "    \n",
    "    timeseries.attrs = {k:v for k,v in ds.attrs.items()}\n",
    "    data_timeseries[k] = timeseries"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "290c56d9-6ad6-4427-a2a2-507d23dc131d",
   "metadata": {},
   "source": [
    "## Concatenate experiments into xarray datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "1da70c98-66bc-48a3-a65c-45d5b8e5d051",
   "metadata": {},
   "outputs": [],
   "source": [
    "# debug version\n",
    "timeseries_hist_datasets = []\n",
    "timeseries_ssp126_datasets = []\n",
    "timeseries_ssp245_datasets = []\n",
    "timeseries_ssp370_datasets = []\n",
    "timeseries_ssp585_datasets = []\n",
    "\n",
    "for k,ds in data_timeseries.items():\n",
    "    # Separate experiments\n",
    "    out = ds.convert_calendar('standard')\n",
    "    out = out.sel(time=slice('1850', '2100'))# cut extended runs\n",
    "    out = out.assign_coords(source_id=ds.source_id)\n",
    "    if ds.experiment_id == 'historical':\n",
    "        # CMIP\n",
    "        if len(out.time)==1980:\n",
    "            timeseries_hist_datasets.append(out)\n",
    "        else:\n",
    "            print(f\"found {len(ds.time)} for {k}\")\n",
    "    else:\n",
    "        #scenarioMIP\n",
    "        if len(out.time)!=1032:\n",
    "            print(f\"found {len(out.time)} for {k}\")\n",
    "            # print(ds.time)\n",
    "        else:\n",
    "            if ds.experiment_id == 'ssp126':\n",
    "                timeseries_ssp126_datasets.append(out)\n",
    "            elif ds.experiment_id == 'ssp245':\n",
    "                timeseries_ssp245_datasets.append(out)\n",
    "            elif ds.experiment_id == 'ssp370':\n",
    "                timeseries_ssp370_datasets.append(out)\n",
    "            elif ds.experiment_id == 'ssp585':\n",
    "                timeseries_ssp585_datasets.append(out)            \n",
    "\n",
    "concat_kwargs = dict(\n",
    "    dim='source_id',\n",
    "    join='override',\n",
    "    compat='override',\n",
    "    coords='minimal'\n",
    ") \n",
    "timeseries_hist = xr.concat(timeseries_hist_datasets, **concat_kwargs)\n",
    "timeseries_ssp126 = xr.concat(timeseries_ssp126_datasets, **concat_kwargs)\n",
    "timeseries_ssp245 = xr.concat(timeseries_ssp245_datasets, **concat_kwargs)\n",
    "timeseries_ssp370 = xr.concat(timeseries_ssp370_datasets, **concat_kwargs)\n",
    "timeseries_ssp585 = xr.concat(timeseries_ssp585_datasets, **concat_kwargs)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66c1036f-683a-48cb-8eb4-44d5d75a65ba",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Calculate anomaly to base period (1950-1980)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "00a7faeb-f579-498e-8abf-40c4b7348d18",
   "metadata": {},
   "outputs": [],
   "source": [
    "base_period = timeseries_hist.sel(time=slice('1950','1980')).mean('time')\n",
    "smoothing_window = 12*2 # higher than IPCC to compensate for missing member mean\n",
    "\n",
    "hist = (timeseries_hist - base_period).rolling(time=smoothing_window).mean()\n",
    "ssp126 = (timeseries_ssp126 - base_period).rolling(time=smoothing_window).mean()\n",
    "ssp245 = (timeseries_ssp245 - base_period).rolling(time=smoothing_window).mean()\n",
    "ssp370 = (timeseries_ssp370 - base_period).rolling(time=smoothing_window).mean()\n",
    "ssp585 = (timeseries_ssp585 - base_period).rolling(time=smoothing_window).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "aa157588-c10d-43d5-a077-b0493ab8f029",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f2131ccb3d0>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 302,
       "width": 715
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "plot_kwargs = dict(spread_style='quantile', spreads=[0.5])\n",
    "\n",
    "plt.figure(figsize=[12,5])\n",
    "\n",
    "shaded_line_plot(hist, 'source_id', **plot_kwargs, line_kwargs=dict(label='historical'))\n",
    "shaded_line_plot(ssp126, 'source_id', **plot_kwargs, line_kwargs=dict(label='ssp126'))\n",
    "shaded_line_plot(ssp245, 'source_id', **plot_kwargs, line_kwargs=dict(label='ssp245'))\n",
    "shaded_line_plot(ssp370, 'source_id', **plot_kwargs, line_kwargs=dict(label='ssp370'))\n",
    "shaded_line_plot(ssp585, 'source_id', **plot_kwargs, line_kwargs=dict(label='ssp585'))\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d7d1b281-9d8e-4691-beff-efbc9eade7b2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "87389d6e-b2ae-4625-b5c4-2abbfbfd6461",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}