science: Update initial CO2 concentrations

fund-model · Feb 24, 2014 · 610d1dd · 610d1dd
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Showing 8 changed files with 219 additions and 5 deletions.
diff --git a/Fund/Data/Base/cbox10.csv b/Fund/Data/Base/cbox10.csv
@@ -1,2 +1,2 @@
 # FUND scenario
-283.53
+296.002949511
diff --git a/Fund/Data/Base/cbox20.csv b/Fund/Data/Base/cbox20.csv
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 # FUND scenario
-5.62
+5.52417779186
diff --git a/Fund/Data/Base/cbox30.csv b/Fund/Data/Base/cbox30.csv
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 # FUND scenario
-6.29
+6.65150094285
diff --git a/Fund/Data/Base/cbox40.csv b/Fund/Data/Base/cbox40.csv
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 # FUND scenario
-2.19
+2.39635475726
diff --git a/Fund/Data/Base/cbox50.csv b/Fund/Data/Base/cbox50.csv
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 # FUND scenario
-0.15
+0.17501699667
diff --git a/calibration/co2cycle/RCP85_EMISSIONS.xls b/calibration/co2cycle/RCP85_EMISSIONS.xls
diff --git a/calibration/co2cycle/RCP85_MIDYEAR_CONCENTRATIONS.xls b/calibration/co2cycle/RCP85_MIDYEAR_CONCENTRATIONS.xls
diff --git a/calibration/co2cycle/fund_co2_cycle.ipynb b/calibration/co2cycle/fund_co2_cycle.ipynb
@@ -0,0 +1,214 @@
+{
+ "metadata": {
+  "name": ""
+ },
+ "nbformat": 3,
+ "nbformat_minor": 0,
+ "worksheets": [
+  {
+   "cells": [
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "import pandas"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 1
+    },
+    {
+     "cell_type": "heading",
+     "level": 1,
+     "metadata": {},
+     "source": [
+      "FUND carbon cycle"
+     ]
+    },
+    {
+     "cell_type": "heading",
+     "level": 2,
+     "metadata": {},
+     "source": [
+      "I. Introduction"
+     ]
+    },
+    {
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "This file calibrates the initial values for the five boxes of the carbon cycle component. The FUND carbon cycle is run with historical emissions from the RCP data set up to 1950 to compute the CO2 content of each of the five boxes in 1950. An additional calibration factor is computed to force the 1950 concentrations to match observed concentrations in that year."
+     ]
+    },
+    {
+     "cell_type": "heading",
+     "level": 2,
+     "metadata": {},
+     "source": [
+      "II. Data sources"
+     ]
+    },
+    {
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "Data obtained from http://www.pik-potsdam.de/~mmalte/rcps/ on 11/15/2013 by Anthoff."
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "rcp_emissions = pandas.read_excel('RCP85_EMISSIONS.xls', 'RCP85_EMISSIONS', skiprows=37, index_col=0)\n",
+      "rcp_emissions.index.name='year'"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 2
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "rcp_concentrations = pandas.read_excel('RCP85_MIDYEAR_CONCENTRATIONS.xls', 'RCP85_MIDYEAR_CONCENTRATIONS', skiprows=38, index_col=0)\n",
+      "rcp_concentrations.index.name='year'"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 3
+    },
+    {
+     "cell_type": "heading",
+     "level": 2,
+     "metadata": {},
+     "source": [
+      "III. Computation"
+     ]
+    },
+    {
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "Run the FUND carbon cycle with RCP historical emissions data."
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "# Convert to FUND units\n",
+      "emissions = rcp_emissions['FossilCO2'].values * 1000.0\n",
+      "\n",
+      "# Parameters\n",
+      "co2decay = numpy.array([1.0, exp(-1.0/363.0), exp(-1.0/74.0),exp(-1.0/17.0),exp(-1.0/2.0)])\n",
+      "co2frac = numpy.array([0.13,0.2,0.32,0.25,0.1])\n",
+      "\n",
+      "# State variables\n",
+      "cbox = numpy.zeros((len(emissions),5))\n",
+      "acco2 = numpy.zeros(len(emissions))\n",
+      "\n",
+      "# Initial values\n",
+      "cbox[0,0]=rcp_concentrations['CO2'][0]\n",
+      "acco2[0] = cbox[0,:].sum()\n",
+      "\n",
+      "# Transition function\n",
+      "for t in range(0,len(emissions)-1):\n",
+      "    cbox[t+1,:] = cbox[t,:] * co2decay[:] + 0.000471 * co2frac[:] * emissions[t]\n",
+      "    acco2[t+1] = cbox[t+1,:].sum()\n",
+      "    \n",
+      "fund_concentrations = pandas.DataFrame(acco2,index=rcp_emissions.index)\n",
+      "fund_boxes = pandas.DataFrame(cbox,index=rcp_emissions.index)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 4
+    },
+    {
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "Compute a calibration factor that forces CO2 concentrations as computed by the FUND component to match observed concentrations in 1950."
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "calibration_factor = rcp_concentrations['CO2'].loc[1950]/fund_concentrations.loc[1950][0]"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 5
+    },
+    {
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "Display initial CO2 concentrations per box in 1950 for FUND with the calibration factor applied. Those are the initial values used in FUND."
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "numpy.round(fund_boxes.loc[1950]*calibration_factor,2)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 6,
+       "text": [
+        "0    296.00\n",
+        "1      5.52\n",
+        "2      6.65\n",
+        "3      2.40\n",
+        "4      0.18\n",
+        "Name: 1950.0, dtype: float64"
+       ]
+      }
+     ],
+     "prompt_number": 6
+    },
+    {
+     "cell_type": "heading",
+     "level": 2,
+     "metadata": {},
+     "source": [
+      "IV. Output"
+     ]
+    },
+    {
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "Write the input files for the model."
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "for i in range(5):\n",
+      "    with open('../../Fund/Data/Base/cbox%s0.csv'%(i+1),'w') as f:\n",
+      "        f.write('# FUND scenario\\n')\n",
+      "        f.write(str(fund_boxes.loc[1950][i]*calibration_factor))\n",
+      "        f.write('\\n')"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 7
+    }
+   ],
+   "metadata": {}
+  }
+ ]
+}