CCCx2050.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CDR Experiments via Pymagicc\n",
    "##### CC-BY 4.0 2020 @safiume\n",
    "##### pymagicc AGPL-3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# NBVAL_IGNORE_OUTPUT\n",
    "import sys, re\n",
    "from os import listdir\n",
    "from os.path import join, dirname\n",
    "from pprint import pprint\n",
    "import expectexception\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from datetime import datetime\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline\n",
    "import f90nml"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Disable warning supression if running locally\n",
    "import warnings\n",
    "warnings.simplefilter(\"ignore\", category=Warning, lineno=0, append=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "IPython.OutputArea.prototype._should_scroll = function(lines) { return false; }"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "pyam - INFO: Running in a notebook, setting `pyam` logging level to `logging.INFO` and adding stderr handler\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.0.0rc8+19.g7aade1e.dirty\n",
      "3.7.4 (v3.7.4:e09359112e, Jul  8 2019, 14:54:52) \n",
      "[Clang 6.0 (clang-600.0.57)]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(scmdata.run.ScmRun,)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pymagicc\n",
    "from pymagicc import MAGICC6\n",
    "from pymagicc.io import MAGICCData, read_cfg_file, NoReaderWriterError\n",
    "from pymagicc.scenarios import ( rcp26, rcp45 )\n",
    "print(pymagicc.__version__)\n",
    "print(sys.version)\n",
    "rcp26.__class__.__bases__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "## List of experiments in declines\n",
    "declines = [\"emax\", \"lmax\", \"emin\", \"lmin\"]\n",
    "SCEN_DIR = \"SCEN\"\n",
    "MAGICC6_DIR = join(\"..\", \"CDRRUN\")\n",
    "\n",
    "# Start MAGICC at 1720 or before\n",
    "# The baseline for 0 °C will be recalculated based the mean\n",
    "# temp for 1720-1800.\n",
    "## Start of MAGICC settings\n",
    "magcfg = {\"startyear\" : 1720,\n",
    "          \"endyear\" : 2500,\n",
    "          \"core_climatesensitivity\" : 2.6,  #BERN sensitivity\n",
    "          \"co2_switchfromconc2emis_year\" : 2010,\n",
    "          \"rf_mhalo_constantafteryr\" : 2250,\n",
    "          \"rf_fgas_constantafteryr\" : 2250,\n",
    "          \"out_forcing\" : 1,\n",
    "          \"out_emissions\" : 1,\n",
    "          \"out_concentrations\" : 1 }\n",
    "### End MAGICC Settings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>2005-01-01</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <th>2011-01-01</th>\n",
       "      <th>2012-01-01</th>\n",
       "      <th>2013-01-01</th>\n",
       "      <th>2014-01-01</th>\n",
       "      <th>2015-01-01</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <th>2017-01-01</th>\n",
       "      <th>2018-01-01</th>\n",
       "      <th>...</th>\n",
       "      <th>2093-01-01</th>\n",
       "      <th>2094-01-01</th>\n",
       "      <th>2095-01-01</th>\n",
       "      <th>2096-01-01</th>\n",
       "      <th>2097-01-01</th>\n",
       "      <th>2098-01-01</th>\n",
       "      <th>2099-01-01</th>\n",
       "      <th>2100-01-01</th>\n",
       "      <th>2101-01-01</th>\n",
       "      <th>2150-01-01</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>climate_model</th>\n",
       "      <th>model</th>\n",
       "      <th>region</th>\n",
       "      <th>scenario</th>\n",
       "      <th>todo</th>\n",
       "      <th>unit</th>\n",
       "      <th>variable</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">unspecified</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">CDRex</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">World</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">emin</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">SET</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">Gt C / yr</th>\n",
       "      <th>Emissions|CO2|MAGICC Fossil and Industrial</th>\n",
       "      <td>8.030</td>\n",
       "      <td>9.1209</td>\n",
       "      <td>9.4954</td>\n",
       "      <td>9.6670</td>\n",
       "      <td>9.7651</td>\n",
       "      <td>9.8475</td>\n",
       "      <td>9.8306</td>\n",
       "      <td>9.8752</td>\n",
       "      <td>10.0727</td>\n",
       "      <td>10.00</td>\n",
       "      <td>...</td>\n",
       "      <td>-13.0911</td>\n",
       "      <td>-13.5606</td>\n",
       "      <td>-14.0469</td>\n",
       "      <td>-14.5506</td>\n",
       "      <td>-15.0724</td>\n",
       "      <td>-15.6129</td>\n",
       "      <td>-16.1728</td>\n",
       "      <td>-16.8027</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Emissions|CO2|MAGICC AFOLU</th>\n",
       "      <td>1.180</td>\n",
       "      <td>1.3732</td>\n",
       "      <td>1.3204</td>\n",
       "      <td>1.3786</td>\n",
       "      <td>1.4088</td>\n",
       "      <td>1.3788</td>\n",
       "      <td>1.5191</td>\n",
       "      <td>1.4000</td>\n",
       "      <td>1.3000</td>\n",
       "      <td>1.27</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.1428</td>\n",
       "      <td>-3.1924</td>\n",
       "      <td>-3.2429</td>\n",
       "      <td>-3.2942</td>\n",
       "      <td>-3.3463</td>\n",
       "      <td>-3.3992</td>\n",
       "      <td>-3.4529</td>\n",
       "      <td>-3.4849</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mt CH4 / yr</th>\n",
       "      <th>Emissions|CH4</th>\n",
       "      <td>315.903</td>\n",
       "      <td>332.0000</td>\n",
       "      <td>335.0000</td>\n",
       "      <td>338.0000</td>\n",
       "      <td>341.0000</td>\n",
       "      <td>344.0000</td>\n",
       "      <td>347.0000</td>\n",
       "      <td>351.0000</td>\n",
       "      <td>355.0000</td>\n",
       "      <td>359.00</td>\n",
       "      <td>...</td>\n",
       "      <td>66.1609</td>\n",
       "      <td>57.1018</td>\n",
       "      <td>47.8075</td>\n",
       "      <td>38.2719</td>\n",
       "      <td>28.4887</td>\n",
       "      <td>18.4515</td>\n",
       "      <td>8.1536</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 94 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "time                                                                                             2005-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  emin     SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial       8.030   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                       1.180   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                  315.903   \n",
       "\n",
       "time                                                                                             2010-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  emin     SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial      9.1209   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                      1.3732   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                 332.0000   \n",
       "\n",
       "time                                                                                             2011-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  emin     SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial      9.4954   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                      1.3204   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                 335.0000   \n",
       "\n",
       "time                                                                                             2012-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  emin     SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial      9.6670   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                      1.3786   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                 338.0000   \n",
       "\n",
       "time                                                                                             2013-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  emin     SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial      9.7651   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                      1.4088   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                 341.0000   \n",
       "\n",
       "time                                                                                             2014-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  emin     SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial      9.8475   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                      1.3788   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                 344.0000   \n",
       "\n",
       "time                                                                                             2015-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  emin     SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial      9.8306   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                      1.5191   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                 347.0000   \n",
       "\n",
       "time                                                                                             2016-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  emin     SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial      9.8752   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                      1.4000   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                 351.0000   \n",
       "\n",
       "time                                                                                             2017-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  emin     SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial     10.0727   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                      1.3000   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                 355.0000   \n",
       "\n",
       "time                                                                                             2018-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  emin     SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial       10.00   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                        1.27   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                   359.00   \n",
       "\n",
       "time                                                                                             ...  \\\n",
       "climate_model model region scenario todo unit        variable                                    ...   \n",
       "unspecified   CDRex World  emin     SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial  ...   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                  ...   \n",
       "                                         Mt CH4 / yr Emissions|CH4                               ...   \n",
       "\n",
       "time                                                                                             2093-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  emin     SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial    -13.0911   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                     -3.1428   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                  66.1609   \n",
       "\n",
       "time                                                                                             2094-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  emin     SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial    -13.5606   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                     -3.1924   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                  57.1018   \n",
       "\n",
       "time                                                                                             2095-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  emin     SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial    -14.0469   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                     -3.2429   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                  47.8075   \n",
       "\n",
       "time                                                                                             2096-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  emin     SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial    -14.5506   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                     -3.2942   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                  38.2719   \n",
       "\n",
       "time                                                                                             2097-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  emin     SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial    -15.0724   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                     -3.3463   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                  28.4887   \n",
       "\n",
       "time                                                                                             2098-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  emin     SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial    -15.6129   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                     -3.3992   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                  18.4515   \n",
       "\n",
       "time                                                                                             2099-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  emin     SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial    -16.1728   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                     -3.4529   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                   8.1536   \n",
       "\n",
       "time                                                                                             2100-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  emin     SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial    -16.8027   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                     -3.4849   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                   0.0000   \n",
       "\n",
       "time                                                                                             2101-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  emin     SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial         0.0   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                         0.0   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                      0.0   \n",
       "\n",
       "time                                                                                             2150-01-01  \n",
       "climate_model model region scenario todo unit        variable                                                \n",
       "unspecified   CDRex World  emin     SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial         0.0  \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                         0.0  \n",
       "                                         Mt CH4 / yr Emissions|CH4                                      0.0  \n",
       "\n",
       "[3 rows x 94 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Reassign startyear to include the year 1720.\n",
    "graphstart = magcfg['startyear']\n",
    "if magcfg['startyear'] > 1720:\n",
    "    magcfg['startyear'] = 1720\n",
    "\n",
    "## load experiments scen file data\n",
    "for n, name in enumerate (declines):\n",
    "    declinefile = join(SCEN_DIR, \"ONC\" + name + \".SCEN\")\n",
    "    declines[n] = MAGICCData(declinefile,\n",
    "                             columns={\"model\": [\"CDRex\"], \"scenario\": [name]})\n",
    "\n",
    "img119 = MAGICCData(join(SCEN_DIR, 'imgs119.SCEN'), \n",
    "                    columns={\"model\": [\"IMAGE\"], \"scenario\": ['SSP119']}, inplace=True)\n",
    "declines.append(img119)\n",
    "declines[2].timeseries().head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate how much carbon to remove to achieve 300 ppm at 2050\n",
    "CRsyr = 2021\n",
    "Bkyr = 2050\n",
    "# CO₂ gas is in GtC\n",
    "AnthroC = 455.08\n",
    "LuC = 161.09\n",
    "CCCxFF = 187\n",
    "CCCxLuC = 103\n",
    "\n",
    "LuC_2050 = LuC - CCCxLuC\n",
    "landsnk_yrly = LuC_2050/((Bkyr) - CRsyr)\n",
    "landsnc_remainingYr = CCCxLuC/(2100 - Bkyr)\n",
    "\n",
    "AC_2050 = AnthroC - CCCxFF\n",
    "Peak_to_bk_yr = AC_2050/((Bkyr) - CRsyr)\n",
    "Remaining_per_yr = CCCxFF/(2100 - Bkyr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Diagnostic Output\n",
      "time                                                                                           2019-01-01\n",
      "climate_model model region scenario todo unit      variable                                              \n",
      "unspecified   CDRex World  CCCx2050 SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial       10.00\n",
      "                                                   Emissions|CO2|MAGICC AFOLU                        1.25\n",
      "time                                                                                           2041-01-01\n",
      "climate_model model region scenario todo unit      variable                                              \n",
      "unspecified   CDRex World  CCCx2050 SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial   -9.244138\n",
      "                                                   Emissions|CO2|MAGICC AFOLU                   -2.003103\n",
      "time                                                                                           2051-01-01\n",
      "climate_model model region scenario todo unit      variable                                              \n",
      "unspecified   CDRex World  CCCx2050 SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial       -3.74\n",
      "                                                   Emissions|CO2|MAGICC AFOLU                       -2.06\n"
     ]
    },
    {
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>2005-01-01</th>\n",
       "      <th>2010-01-01</th>\n",
       "      <th>2011-01-01</th>\n",
       "      <th>2012-01-01</th>\n",
       "      <th>2013-01-01</th>\n",
       "      <th>2014-01-01</th>\n",
       "      <th>2015-01-01</th>\n",
       "      <th>2016-01-01</th>\n",
       "      <th>2017-01-01</th>\n",
       "      <th>2018-01-01</th>\n",
       "      <th>...</th>\n",
       "      <th>2092-01-01</th>\n",
       "      <th>2093-01-01</th>\n",
       "      <th>2094-01-01</th>\n",
       "      <th>2095-01-01</th>\n",
       "      <th>2096-01-01</th>\n",
       "      <th>2097-01-01</th>\n",
       "      <th>2098-01-01</th>\n",
       "      <th>2099-01-01</th>\n",
       "      <th>2100-01-01</th>\n",
       "      <th>2101-01-01</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>climate_model</th>\n",
       "      <th>model</th>\n",
       "      <th>region</th>\n",
       "      <th>scenario</th>\n",
       "      <th>todo</th>\n",
       "      <th>unit</th>\n",
       "      <th>variable</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">unspecified</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">CDRex</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">World</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">CCCx2050</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">SET</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">Gt C / yr</th>\n",
       "      <th>Emissions|CO2|MAGICC Fossil and Industrial</th>\n",
       "      <td>8.030</td>\n",
       "      <td>9.1209</td>\n",
       "      <td>9.4954</td>\n",
       "      <td>9.6670</td>\n",
       "      <td>9.7651</td>\n",
       "      <td>9.8475</td>\n",
       "      <td>9.8306</td>\n",
       "      <td>9.8752</td>\n",
       "      <td>10.0727</td>\n",
       "      <td>10.00</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.74</td>\n",
       "      <td>-3.74</td>\n",
       "      <td>-3.74</td>\n",
       "      <td>-3.74</td>\n",
       "      <td>-3.74</td>\n",
       "      <td>-3.74</td>\n",
       "      <td>-3.74</td>\n",
       "      <td>-3.74</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Emissions|CO2|MAGICC AFOLU</th>\n",
       "      <td>1.180</td>\n",
       "      <td>1.3732</td>\n",
       "      <td>1.3204</td>\n",
       "      <td>1.3786</td>\n",
       "      <td>1.4088</td>\n",
       "      <td>1.3788</td>\n",
       "      <td>1.5191</td>\n",
       "      <td>1.4000</td>\n",
       "      <td>1.3000</td>\n",
       "      <td>1.27</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.06</td>\n",
       "      <td>-2.06</td>\n",
       "      <td>-2.06</td>\n",
       "      <td>-2.06</td>\n",
       "      <td>-2.06</td>\n",
       "      <td>-2.06</td>\n",
       "      <td>-2.06</td>\n",
       "      <td>-2.06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mt CH4 / yr</th>\n",
       "      <th>Emissions|CH4</th>\n",
       "      <td>315.903</td>\n",
       "      <td>332.0000</td>\n",
       "      <td>335.0000</td>\n",
       "      <td>338.0000</td>\n",
       "      <td>341.0000</td>\n",
       "      <td>344.0000</td>\n",
       "      <td>347.0000</td>\n",
       "      <td>351.0000</td>\n",
       "      <td>355.0000</td>\n",
       "      <td>359.00</td>\n",
       "      <td>...</td>\n",
       "      <td>36.00</td>\n",
       "      <td>31.50</td>\n",
       "      <td>27.00</td>\n",
       "      <td>22.50</td>\n",
       "      <td>18.00</td>\n",
       "      <td>13.50</td>\n",
       "      <td>9.00</td>\n",
       "      <td>4.50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 93 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "time                                                                                             2005-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  CCCx2050 SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial       8.030   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                       1.180   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                  315.903   \n",
       "\n",
       "time                                                                                             2010-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  CCCx2050 SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial      9.1209   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                      1.3732   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                 332.0000   \n",
       "\n",
       "time                                                                                             2011-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  CCCx2050 SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial      9.4954   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                      1.3204   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                 335.0000   \n",
       "\n",
       "time                                                                                             2012-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  CCCx2050 SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial      9.6670   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                      1.3786   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                 338.0000   \n",
       "\n",
       "time                                                                                             2013-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  CCCx2050 SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial      9.7651   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                      1.4088   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                 341.0000   \n",
       "\n",
       "time                                                                                             2014-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  CCCx2050 SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial      9.8475   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                      1.3788   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                 344.0000   \n",
       "\n",
       "time                                                                                             2015-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  CCCx2050 SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial      9.8306   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                      1.5191   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                 347.0000   \n",
       "\n",
       "time                                                                                             2016-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  CCCx2050 SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial      9.8752   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                      1.4000   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                 351.0000   \n",
       "\n",
       "time                                                                                             2017-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  CCCx2050 SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial     10.0727   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                      1.3000   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                 355.0000   \n",
       "\n",
       "time                                                                                             2018-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  CCCx2050 SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial       10.00   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                        1.27   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                   359.00   \n",
       "\n",
       "time                                                                                             ...  \\\n",
       "climate_model model region scenario todo unit        variable                                    ...   \n",
       "unspecified   CDRex World  CCCx2050 SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial  ...   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                  ...   \n",
       "                                         Mt CH4 / yr Emissions|CH4                               ...   \n",
       "\n",
       "time                                                                                             2092-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  CCCx2050 SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial       -3.74   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                       -2.06   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                    36.00   \n",
       "\n",
       "time                                                                                             2093-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  CCCx2050 SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial       -3.74   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                       -2.06   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                    31.50   \n",
       "\n",
       "time                                                                                             2094-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  CCCx2050 SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial       -3.74   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                       -2.06   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                    27.00   \n",
       "\n",
       "time                                                                                             2095-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  CCCx2050 SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial       -3.74   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                       -2.06   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                    22.50   \n",
       "\n",
       "time                                                                                             2096-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  CCCx2050 SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial       -3.74   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                       -2.06   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                    18.00   \n",
       "\n",
       "time                                                                                             2097-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  CCCx2050 SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial       -3.74   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                       -2.06   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                    13.50   \n",
       "\n",
       "time                                                                                             2098-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  CCCx2050 SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial       -3.74   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                       -2.06   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                     9.00   \n",
       "\n",
       "time                                                                                             2099-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  CCCx2050 SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial       -3.74   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                       -2.06   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                     4.50   \n",
       "\n",
       "time                                                                                             2100-01-01  \\\n",
       "climate_model model region scenario todo unit        variable                                                 \n",
       "unspecified   CDRex World  CCCx2050 SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial         0.0   \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                         0.0   \n",
       "                                         Mt CH4 / yr Emissions|CH4                                      0.0   \n",
       "\n",
       "time                                                                                             2101-01-01  \n",
       "climate_model model region scenario todo unit        variable                                                \n",
       "unspecified   CDRex World  CCCx2050 SET  Gt C / yr   Emissions|CO2|MAGICC Fossil and Industrial         0.0  \n",
       "                                                     Emissions|CO2|MAGICC AFOLU                         0.0  \n",
       "                                         Mt CH4 / yr Emissions|CH4                                      0.0  \n",
       "\n",
       "[3 rows x 93 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Copy lmin data into new experiment\n",
    "CCCx2050 = declines[3]\n",
    "CCC_df = CCCx2050.timeseries()\n",
    "\n",
    "# Kigali reference for later\n",
    "# kigali_yrs = 2019,2024,2025,2029,2034,2036\n",
    "# ki_mo_gasses_F = HFC134a, HFC245fa, HFC277ea, \n",
    "#                 HFC4310, HFC32, HFC125, HFC143a, HFC23\n",
    "# sf6-eu 30% by 2030\n",
    "\n",
    "ems_ff = 'Emissions|CO2|MAGICC Fossil and Industrial'\n",
    "ems_luc = 'Emissions|CO2|MAGICC AFOLU'\n",
    "emsf = ('unspecified','CDRex','World','CCCx2050','SET','Gt C / yr', ems_ff)\n",
    "emsluc = ('unspecified','CDRex','World','CCCx2050','SET','Gt C / yr',ems_luc)\n",
    "\n",
    "CCC_df = CCC_df.rename(index={\"lmin\":\"CCCx2050\"})\n",
    "\n",
    "# Zero out data past 2099 \n",
    "CCC_df.loc[emsf, datetime(2100,1,1,0) : datetime(2150,1,1,0)] = 0\n",
    "CCC_df.loc[emsluc, datetime(2100,1,1,0) : datetime(2150,1,1,0)] = 0\n",
    "\n",
    "# Set removal according to forumlas in previous cell\n",
    "CCC_df.loc[emsluc, datetime(2021,1,1) : datetime(2049,1,1)] = -landsnk_yrly\n",
    "CCC_df.loc[emsluc, datetime(2050,1,1) : datetime(2099,1,1)] = -landsnc_remainingYr\n",
    "CCC_df.loc[emsf, datetime(2021,1,1) : datetime(2049,1,1)] = -Peak_to_bk_yr\n",
    "CCC_df.loc[emsf, datetime(2050,1,1) : datetime(2099,1,1)] = -Remaining_per_yr \n",
    "\n",
    "# rewrite CCCx2050 from timeseries and wrap in MAGICCData\n",
    "CCCx2050 = MAGICCData(CCC_df.copy())\n",
    "#CCC_df.to_csv('CCCx2050.csv')\n",
    "\n",
    "CCC_flat = CCC_df.copy()\n",
    "CCC_flat.loc[emsf, datetime(2051,1,1,0) : datetime(2150,1,1,0)] = 0\n",
    "CCC_flat.loc[emsluc, datetime(2051,1,1,0) : datetime(2150,1,1,0)] = 0\n",
    "CCC_flat = CCC_flat.rename(index={\"CCCx2050\":\"CCCxflat\"})\n",
    "CCCxflat = MAGICCData(CCC_flat.copy())\n",
    "\n",
    "print(\"Diagnostic Output\")\n",
    "print(CCC_df.head(2).iloc[:,[10]])\n",
    "print(CCC_df.head(2).iloc[:,[32]])\n",
    "print(CCC_df.head(2).iloc[:,[42]])\n",
    "CCCx2050.timeseries().head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Force sample rcp26 to end CR at 2101\n",
    "rcp26df = rcp26.timeseries()\n",
    "rcp26df = rcp26df.rename(columns={datetime(2125,1,1,0):datetime(2101,1,1,0)})\n",
    "rcp26df.loc[:, datetime(2101,1,1,0) : datetime(2500,1,1,0)] = 0\n",
    "rcp26 = MAGICCData(rcp26df.copy())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Scenarios\n",
    "\n",
    "The five RCP scenarios and experimental declines are loaded as DataFrames in pyhector. They contain the following emissions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>2000-01-01 00:00:00</th>\n",
       "      <th>2001-01-01 00:00:00</th>\n",
       "      <th>2002-01-01 00:00:00</th>\n",
       "      <th>2003-01-01 00:00:00</th>\n",
       "      <th>2004-01-01 00:00:00</th>\n",
       "      <th>2005-01-01 00:00:00</th>\n",
       "      <th>2006-01-01 00:00:00</th>\n",
       "      <th>2007-01-01 00:00:00</th>\n",
       "      <th>2010-01-01 00:00:00</th>\n",
       "      <th>2020-01-01 00:00:00</th>\n",
       "      <th>2030-01-01 00:00:00</th>\n",
       "      <th>2040-01-01 00:00:00</th>\n",
       "      <th>2050-01-01 00:00:00</th>\n",
       "      <th>2060-01-01 00:00:00</th>\n",
       "      <th>2070-01-01 00:00:00</th>\n",
       "      <th>2080-01-01 00:00:00</th>\n",
       "      <th>2090-01-01 00:00:00</th>\n",
       "      <th>2100-01-01 00:00:00</th>\n",
       "      <th>2101-01-01 00:00:00</th>\n",
       "      <th>2500-01-01 00:00:00</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>climate_model</th>\n",
       "      <th>model</th>\n",
       "      <th>region</th>\n",
       "      <th>scenario</th>\n",
       "      <th>todo</th>\n",
       "      <th>unit</th>\n",
       "      <th>variable</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">unspecified</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">IMAGE</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">World</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">RCP26</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">SET</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">Gt C / yr</th>\n",
       "      <th>Emissions|CO2|MAGICC Fossil and Industrial</th>\n",
       "      <td>6.7350</td>\n",
       "      <td>6.896</td>\n",
       "      <td>6.9490</td>\n",
       "      <td>7.2860</td>\n",
       "      <td>7.6720</td>\n",
       "      <td>7.9710</td>\n",
       "      <td>8.1426</td>\n",
       "      <td>8.3135</td>\n",
       "      <td>8.8214</td>\n",
       "      <td>9.2876</td>\n",
       "      <td>7.1569</td>\n",
       "      <td>4.5349</td>\n",
       "      <td>3.1855</td>\n",
       "      <td>1.4192</td>\n",
       "      <td>0.1156</td>\n",
       "      <td>-0.4329</td>\n",
       "      <td>-0.8704</td>\n",
       "      <td>-0.9308</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Emissions|CO2|MAGICC AFOLU</th>\n",
       "      <td>1.1488</td>\n",
       "      <td>1.132</td>\n",
       "      <td>1.2317</td>\n",
       "      <td>1.2256</td>\n",
       "      <td>1.2428</td>\n",
       "      <td>1.1955</td>\n",
       "      <td>1.1677</td>\n",
       "      <td>1.1399</td>\n",
       "      <td>1.0565</td>\n",
       "      <td>0.9728</td>\n",
       "      <td>0.7888</td>\n",
       "      <td>0.4889</td>\n",
       "      <td>0.2012</td>\n",
       "      <td>0.6153</td>\n",
       "      <td>0.5382</td>\n",
       "      <td>0.5498</td>\n",
       "      <td>0.6024</td>\n",
       "      <td>0.5112</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "time                                                                                           2000-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo unit      variable                                                          \n",
       "unspecified   IMAGE World  RCP26    SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial               6.7350   \n",
       "                                                   Emissions|CO2|MAGICC AFOLU                               1.1488   \n",
       "\n",
       "time                                                                                           2001-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo unit      variable                                                          \n",
       "unspecified   IMAGE World  RCP26    SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial                6.896   \n",
       "                                                   Emissions|CO2|MAGICC AFOLU                                1.132   \n",
       "\n",
       "time                                                                                           2002-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo unit      variable                                                          \n",
       "unspecified   IMAGE World  RCP26    SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial               6.9490   \n",
       "                                                   Emissions|CO2|MAGICC AFOLU                               1.2317   \n",
       "\n",
       "time                                                                                           2003-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo unit      variable                                                          \n",
       "unspecified   IMAGE World  RCP26    SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial               7.2860   \n",
       "                                                   Emissions|CO2|MAGICC AFOLU                               1.2256   \n",
       "\n",
       "time                                                                                           2004-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo unit      variable                                                          \n",
       "unspecified   IMAGE World  RCP26    SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial               7.6720   \n",
       "                                                   Emissions|CO2|MAGICC AFOLU                               1.2428   \n",
       "\n",
       "time                                                                                           2005-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo unit      variable                                                          \n",
       "unspecified   IMAGE World  RCP26    SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial               7.9710   \n",
       "                                                   Emissions|CO2|MAGICC AFOLU                               1.1955   \n",
       "\n",
       "time                                                                                           2006-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo unit      variable                                                          \n",
       "unspecified   IMAGE World  RCP26    SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial               8.1426   \n",
       "                                                   Emissions|CO2|MAGICC AFOLU                               1.1677   \n",
       "\n",
       "time                                                                                           2007-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo unit      variable                                                          \n",
       "unspecified   IMAGE World  RCP26    SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial               8.3135   \n",
       "                                                   Emissions|CO2|MAGICC AFOLU                               1.1399   \n",
       "\n",
       "time                                                                                           2010-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo unit      variable                                                          \n",
       "unspecified   IMAGE World  RCP26    SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial               8.8214   \n",
       "                                                   Emissions|CO2|MAGICC AFOLU                               1.0565   \n",
       "\n",
       "time                                                                                           2020-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo unit      variable                                                          \n",
       "unspecified   IMAGE World  RCP26    SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial               9.2876   \n",
       "                                                   Emissions|CO2|MAGICC AFOLU                               0.9728   \n",
       "\n",
       "time                                                                                           2030-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo unit      variable                                                          \n",
       "unspecified   IMAGE World  RCP26    SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial               7.1569   \n",
       "                                                   Emissions|CO2|MAGICC AFOLU                               0.7888   \n",
       "\n",
       "time                                                                                           2040-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo unit      variable                                                          \n",
       "unspecified   IMAGE World  RCP26    SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial               4.5349   \n",
       "                                                   Emissions|CO2|MAGICC AFOLU                               0.4889   \n",
       "\n",
       "time                                                                                           2050-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo unit      variable                                                          \n",
       "unspecified   IMAGE World  RCP26    SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial               3.1855   \n",
       "                                                   Emissions|CO2|MAGICC AFOLU                               0.2012   \n",
       "\n",
       "time                                                                                           2060-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo unit      variable                                                          \n",
       "unspecified   IMAGE World  RCP26    SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial               1.4192   \n",
       "                                                   Emissions|CO2|MAGICC AFOLU                               0.6153   \n",
       "\n",
       "time                                                                                           2070-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo unit      variable                                                          \n",
       "unspecified   IMAGE World  RCP26    SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial               0.1156   \n",
       "                                                   Emissions|CO2|MAGICC AFOLU                               0.5382   \n",
       "\n",
       "time                                                                                           2080-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo unit      variable                                                          \n",
       "unspecified   IMAGE World  RCP26    SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial              -0.4329   \n",
       "                                                   Emissions|CO2|MAGICC AFOLU                               0.5498   \n",
       "\n",
       "time                                                                                           2090-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo unit      variable                                                          \n",
       "unspecified   IMAGE World  RCP26    SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial              -0.8704   \n",
       "                                                   Emissions|CO2|MAGICC AFOLU                               0.6024   \n",
       "\n",
       "time                                                                                           2100-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo unit      variable                                                          \n",
       "unspecified   IMAGE World  RCP26    SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial              -0.9308   \n",
       "                                                   Emissions|CO2|MAGICC AFOLU                               0.5112   \n",
       "\n",
       "time                                                                                           2101-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo unit      variable                                                          \n",
       "unspecified   IMAGE World  RCP26    SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial                  0.0   \n",
       "                                                   Emissions|CO2|MAGICC AFOLU                                  0.0   \n",
       "\n",
       "time                                                                                           2500-01-01 00:00:00  \n",
       "climate_model model region scenario todo unit      variable                                                         \n",
       "unspecified   IMAGE World  RCP26    SET  Gt C / yr Emissions|CO2|MAGICC Fossil and Industrial                  0.0  \n",
       "                                                   Emissions|CO2|MAGICC AFOLU                                  0.0  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#rcp26.filter(region='World').timeseries().loc[:,datetime(2090,1,1,0):datetime(2101,1,1,0)]\n",
    "rcp26.filter(region='World').timeseries().head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rcp26.filter(region='World').head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "They are split up in regions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rcp26[\"region\"].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "They have the following units:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#pymagicc.units\n",
    "rcp26[\"unit\"].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "categories_to_plot = rcp26[\"variable\"].drop_duplicates().tolist()\n",
    "\n",
    "for g in rcp26.filter(\n",
    "    variable=categories_to_plot,\n",
    "    year=range(2000, 2150)\n",
    ").groupby(\"variable\"):\n",
    "    plt.figure(figsize=(12, 7))\n",
    "    g.lineplot(hue=\"region\").set_title(g.get_unique_meta(\"variable\", True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "categories_to_plot = rcp26[\"variable\"].drop_duplicates().tolist()\n",
    "\n",
    "for g in CCCx2050.filter(\n",
    "    region=\"World\",\n",
    "    variable=categories_to_plot,\n",
    "    year=range(2000, 2150)\n",
    ").groupby(\"variable\"):\n",
    "    plt.figure(figsize=(12, 7))\n",
    "    g.lineplot(hue=\"scenario\").set_title(g.get_unique_meta(\"variable\", True))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Running MAGICC\n",
    "\n",
    "A single `pymagicc` run doesn't take long and returns a Pandas Dict.\n",
    "(If not on Windows, the very first run might be slower due to setting up Wine.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Adjust baseline temp to the mean of 1720 to 1800 \n",
    "# per https://doi.org/10.1175/BAMS-D-16-0007.1\n",
    "\n",
    "styr = 1720\n",
    "eyr = 1800\n",
    "sitv = 2.6\n",
    "lsitv = sitv - 1.5\n",
    "hsitv = 5.2\n",
    "\n",
    "selectftr = {\n",
    "    \"region\": \"World\",\n",
    "    \"variable\": \"Surface Temperature\",\n",
    "    \"year\": range(magcfg[\"startyear\"], magcfg[\"endyear\"]),\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def meanbln(scen,mgdata,**cfgs):\n",
    "    origts = mgdata.timeseries()\n",
    "    default = pymagicc.run(scen, **cfgs)\n",
    "    pmean = default.filter(**selectftr).timeseries().loc[:,datetime(styr, 1, 1): datetime(eyr, 1, 1)].T.mean()\n",
    "    defaultts = default.timeseries()\n",
    "    updated = defaultts.xs((selectftr['variable']),level = ('variable'), drop_level=False).add(pmean[0])\n",
    "    origts.loc[updated.index.values] = updated\n",
    "    return(MAGICCData(origts.copy()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "vars = [\"Surface Temperature\",\"Radiative Forcing\",\n",
    "        \"Atmospheric Concentrations|CO2\",\"Emissions|CO2|MAGICC Fossil and Industrial\",\n",
    "        \"Emissions|CO2|MAGICC AFOLU\"]\n",
    "x = (datetime(graphstart, 1, 1), datetime(magcfg[\"endyear\"], 1, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3.96 s, sys: 211 ms, total: 4.17 s\n",
      "Wall time: 10.2 s\n"
     ]
    }
   ],
   "source": [
    "res = \"\"\n",
    "%time res = pymagicc.run(rcp26, **magcfg)  #need to create res of type MAGICCData\n",
    "res = meanbln(rcp26,res,**magcfg)\n",
    "\n",
    "# Toggle to run and graph all the experiments\n",
    "#declines.append(CCCxflat)\n",
    "#declines.append(CCCx2050)\n",
    "\n",
    "#for scen in declines:\n",
    "#    tmprs = pymagicc.run(scen, **magcfg)\n",
    "#    res = res.append(meanbln(scen, tmprs, **magcfg))\n",
    "    \n",
    "#for cccsn in CCCxflat,CCCx2050:\n",
    "#    tmprs = pymagicc.run(CCCx2050, **magcfg)\n",
    "#    res = res.append(meanbln(CCCx2050,tmprs,**magcfg))\n",
    "\n",
    "tmprs = pymagicc.run(CCCx2050, **magcfg)\n",
    "res = meanbln(CCCx2050,tmprs,**magcfg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Graph Output from previous cell"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1728x2304 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots((len(vars)), 1, figsize=(24, 32))\n",
    "for n, var in enumerate(vars):\n",
    "    res.filter(variable=var,region=[\"World\",\"*Nor*Ocean\"]).lineplot(hue=\"scenario\", style=\"region\", ax=axes[n])\n",
    "    ylab = res.filter(variable=var)[\"unit\"].iloc[[0]].all() \n",
    "    if ylab == 'K':\n",
    "        ylab = '°C'\n",
    "    axes[n].set_ylabel(ylab)\n",
    "    axes[n].set_title(var)                        \n",
    "    axes[n].set_xlim(x)\n",
    "    axes[n].legend(loc='upper right')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1728x2304 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots((len(vars)), 1, figsize=(24, 32))\n",
    "for n, var in enumerate(vars):\n",
    "    res.filter(variable=var,region=\"*Nor*Ocean\").lineplot(hue=\"scenario\", style=\"region\", ax=axes[n])\n",
    "    ylab = res.filter(variable=var)[\"unit\"].iloc[[0]].all()\n",
    "    if ylab == 'K':\n",
    "        ylab = '°C'\n",
    "    axes[n].set_ylabel(ylab)\n",
    "    axes[n].set_title(var)\n",
    "    axes[n].set_xlim(x)\n",
    "    axes[n].legend(loc='upper right')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Diagnostic Output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "climate_model  model  region  scenario  todo          unit       variable                                  \n",
      "MAGICC6        CDRex  World   CCCx2050  not_relevant  ppm        Atmospheric Concentrations|CO2                417.306080\n",
      "                                                      W / m^2    Radiative Forcing                               2.720494\n",
      "                                                      K          Surface Temperature                             1.074107\n",
      "                                                      Gt C / yr  Emissions|CO2|MAGICC Fossil and Industrial      0.000000\n",
      "                                                                 Emissions|CO2|MAGICC AFOLU                      0.000000\n",
      "Name: 2020-01-01 00:00:00, dtype: float64\n",
      "climate_model  model  region  scenario  todo          unit       variable                                  \n",
      "MAGICC6        CDRex  World   CCCx2050  not_relevant  Gt C / yr  Emissions|CO2|MAGICC Fossil and Industrial    0.0\n",
      "Name: 2020-01-01 00:00:00, dtype: float64\n",
      "Cumulative CO₂ 1750 to 2020\n",
      "climate_model  model  region  scenario  todo          unit       variable                                  \n",
      "MAGICC6        CDRex  World   CCCx2050  not_relevant  Gt C / yr  Emissions|CO2|MAGICC Fossil and Industrial    455.086294\n",
      "dtype: float64\n",
      "Cumulative CO₂ 1750 to 2020\n",
      "climate_model  model  region  scenario  todo          unit       variable                  \n",
      "MAGICC6        CDRex  World   CCCx2050  not_relevant  Gt C / yr  Emissions|CO2|MAGICC AFOLU    161.08761\n",
      "dtype: float64\n",
      "climate_model  model  region  scenario  todo          unit       variable                                  \n",
      "MAGICC6        CDRex  World   CCCx2050  not_relevant  ppm        Atmospheric Concentrations|CO2                298.132810\n",
      "                                                      W / m^2    Radiative Forcing                               0.939112\n",
      "                                                      K          Surface Temperature                             0.550050\n",
      "                                                      Gt C / yr  Emissions|CO2|MAGICC Fossil and Industrial     -3.740000\n",
      "                                                                 Emissions|CO2|MAGICC AFOLU                     -2.060000\n",
      "Name: 2050-01-01 00:00:00, dtype: float64\n",
      "climate_model  model  region  scenario  todo          unit       variable                                  \n",
      "MAGICC6        CDRex  World   CCCx2050  not_relevant  Gt C / yr  Emissions|CO2|MAGICC Fossil and Industrial   -3.74\n",
      "Name: 2050-01-01 00:00:00, dtype: float64\n",
      "Cumulative CO₂ 1750 to 2050\n",
      "climate_model  model  region  scenario  todo          unit       variable                                  \n",
      "MAGICC6        CDRex  World   CCCx2050  not_relevant  Gt C / yr  Emissions|CO2|MAGICC Fossil and Industrial    183.267394\n",
      "dtype: float64\n",
      "Cumulative CO₂ 1750 to 2050\n",
      "climate_model  model  region  scenario  todo          unit       variable                  \n",
      "MAGICC6        CDRex  World   CCCx2050  not_relevant  Gt C / yr  Emissions|CO2|MAGICC AFOLU    100.93771\n",
      "dtype: float64\n",
      "climate_model  model  region  scenario  todo          unit       variable                                  \n",
      "MAGICC6        CDRex  World   CCCx2050  not_relevant  ppm        Atmospheric Concentrations|CO2                245.939120\n",
      "                                                      W / m^2    Radiative Forcing                              -0.130925\n",
      "                                                      K          Surface Temperature                             0.077091\n",
      "                                                      Gt C / yr  Emissions|CO2|MAGICC Fossil and Industrial      0.000000\n",
      "                                                                 Emissions|CO2|MAGICC AFOLU                      0.000000\n",
      "Name: 2100-01-01 00:00:00, dtype: float64\n",
      "climate_model  model  region  scenario  todo          unit       variable                                  \n",
      "MAGICC6        CDRex  World   CCCx2050  not_relevant  Gt C / yr  Emissions|CO2|MAGICC Fossil and Industrial    0.0\n",
      "Name: 2100-01-01 00:00:00, dtype: float64\n",
      "Cumulative CO₂ 1750 to 2100\n",
      "climate_model  model  region  scenario  todo          unit       variable                                  \n",
      "MAGICC6        CDRex  World   CCCx2050  not_relevant  Gt C / yr  Emissions|CO2|MAGICC Fossil and Industrial    0.007394\n",
      "dtype: float64\n",
      "Cumulative CO₂ 1750 to 2100\n",
      "climate_model  model  region  scenario  todo          unit       variable                  \n",
      "MAGICC6        CDRex  World   CCCx2050  not_relevant  Gt C / yr  Emissions|CO2|MAGICC AFOLU   -0.00229\n",
      "dtype: float64\n",
      "climate_model  model  region  scenario  todo          unit       variable                                  \n",
      "MAGICC6        CDRex  World   CCCx2050  not_relevant  ppm        Atmospheric Concentrations|CO2                279.603080\n",
      "                                                      W / m^2    Radiative Forcing                               0.135779\n",
      "                                                      K          Surface Temperature                             0.095155\n",
      "                                                      Gt C / yr  Emissions|CO2|MAGICC Fossil and Industrial      0.000000\n",
      "                                                                 Emissions|CO2|MAGICC AFOLU                      0.000000\n",
      "Name: 2500-01-01 00:00:00, dtype: float64\n",
      "climate_model  model  region  scenario  todo          unit       variable                                  \n",
      "MAGICC6        CDRex  World   CCCx2050  not_relevant  Gt C / yr  Emissions|CO2|MAGICC Fossil and Industrial    0.0\n",
      "Name: 2500-01-01 00:00:00, dtype: float64\n",
      "Cumulative CO₂ 1750 to 2500\n",
      "climate_model  model  region  scenario  todo          unit       variable                                  \n",
      "MAGICC6        CDRex  World   CCCx2050  not_relevant  Gt C / yr  Emissions|CO2|MAGICC Fossil and Industrial    0.007394\n",
      "dtype: float64\n",
      "Cumulative CO₂ 1750 to 2500\n",
      "climate_model  model  region  scenario  todo          unit       variable                  \n",
      "MAGICC6        CDRex  World   CCCx2050  not_relevant  Gt C / yr  Emissions|CO2|MAGICC AFOLU   -0.00229\n",
      "dtype: float64\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>2045-01-01 00:00:00</th>\n",
       "      <th>2046-01-01 00:00:00</th>\n",
       "      <th>2047-01-01 00:00:00</th>\n",
       "      <th>2048-01-01 00:00:00</th>\n",
       "      <th>2049-01-01 00:00:00</th>\n",
       "      <th>2050-01-01 00:00:00</th>\n",
       "      <th>2051-01-01 00:00:00</th>\n",
       "      <th>2052-01-01 00:00:00</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>climate_model</th>\n",
       "      <th>model</th>\n",
       "      <th>region</th>\n",
       "      <th>scenario</th>\n",
       "      <th>todo</th>\n",
       "      <th>unit</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>MAGICC6</th>\n",
       "      <th>CDRex</th>\n",
       "      <th>World</th>\n",
       "      <th>CCCx2050</th>\n",
       "      <th>not_relevant</th>\n",
       "      <th>ppm</th>\n",
       "      <th>Atmospheric Concentrations|CO2</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "time                                                                                  2045-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo         unit variable                                              \n",
       "MAGICC6       CDRex World  CCCx2050 not_relevant ppm  Atmospheric Concentrations|CO2                 True   \n",
       "\n",
       "time                                                                                  2046-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo         unit variable                                              \n",
       "MAGICC6       CDRex World  CCCx2050 not_relevant ppm  Atmospheric Concentrations|CO2                 True   \n",
       "\n",
       "time                                                                                  2047-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo         unit variable                                              \n",
       "MAGICC6       CDRex World  CCCx2050 not_relevant ppm  Atmospheric Concentrations|CO2                 True   \n",
       "\n",
       "time                                                                                  2048-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo         unit variable                                              \n",
       "MAGICC6       CDRex World  CCCx2050 not_relevant ppm  Atmospheric Concentrations|CO2                 True   \n",
       "\n",
       "time                                                                                  2049-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo         unit variable                                              \n",
       "MAGICC6       CDRex World  CCCx2050 not_relevant ppm  Atmospheric Concentrations|CO2                 True   \n",
       "\n",
       "time                                                                                  2050-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo         unit variable                                              \n",
       "MAGICC6       CDRex World  CCCx2050 not_relevant ppm  Atmospheric Concentrations|CO2                False   \n",
       "\n",
       "time                                                                                  2051-01-01 00:00:00  \\\n",
       "climate_model model region scenario todo         unit variable                                              \n",
       "MAGICC6       CDRex World  CCCx2050 not_relevant ppm  Atmospheric Concentrations|CO2                False   \n",
       "\n",
       "time                                                                                  2052-01-01 00:00:00  \n",
       "climate_model model region scenario todo         unit variable                                             \n",
       "MAGICC6       CDRex World  CCCx2050 not_relevant ppm  Atmospheric Concentrations|CO2                False  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for dt in 2020,2050,2100,2500:\n",
    "    for var in vars,ems_ff:\n",
    "        print(res.filter(variable = var,\n",
    "                         region='World').timeseries().loc[:,datetime(dt,1,1)])\n",
    "    for cgas in ems_ff,ems_luc:\n",
    "        print(\"Cumulative CO₂ 1750 to\", dt)\n",
    "        print(res.filter(variable=cgas,\n",
    "                         region='World').timeseries().loc[:,datetime(1750,1,1):datetime(dt,1,1)].sum(axis=1))\n",
    "\n",
    "res.filter(variable = \"Atmospheric Concentrations|CO2\",region=\"World\").timeseries().loc[:,datetime(2045,1,1):datetime(2052,1,1)] >= 300\n",
    "#res.filter(variable = \"Atmospheric Concentrations|CO2\",region=\"World\").timeseries().loc[:,datetime(1909,1,1):datetime(1920,1,1)] >= 299\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The default parameters are the ones that were used to produce the RCP GHG concentrations (see also http://live.magicc.org/). Of course it's easy to change them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "scenario = CCCx2050\n",
    "runs = {\"default\":sitv, \n",
    "        \"low\":lsitv,\n",
    "        \"high\":hsitv}\n",
    "runsdf = {}\n",
    "mcfg = magcfg.copy()\n",
    "\n",
    "for rn in runs:\n",
    "    mcfg['core_climatesensitivity'] = runs[rn]\n",
    "    newrn = pymagicc.run(scenario, **mcfg)\n",
    "    runsdf[rn] = meanbln(scenario, newrn, **mcfg)\n",
    "\n",
    "filtering = {\"region\": \"World\", \"variable\": \"Surface Temperature\", \n",
    "             \"year\": range(1850, 2150)}\n",
    "fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(16, 9))\n",
    "runsdf['default'].filter(**filtering).line_plot(x=\"time\", ax=ax)\n",
    "plt.fill_between(\n",
    "    runsdf['default'].filter(**filtering)['time'],\n",
    "    runsdf['low'].filter(**filtering).timeseries().values.squeeze(),\n",
    "    runsdf['high'].filter(**filtering).timeseries().values.squeeze(),\n",
    "    color=\"lightgray\"\n",
    ")\n",
    "\n",
    "plt.title(\n",
    "    (f\"Experiment 300x2050 run with equilibrium climate sensitivity set to {lsitv}, {sitv}, and {hsitv}\")\n",
    ")\n",
    "plt.ylabel(\"°C\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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