{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Evolution of the atmospheric CO$_2$ concentration since 1958\n", "\n", "Data obtained [here](https://scrippsco2.ucsd.edu/assets/data/atmospheric/stations/in_situ_co2/monthly/monthly_in_situ_co2_mlo.csv)\n", "\n", "\n", "## 1. Import Data\n", "Check if the DATA has already been downloaded to avoid downloading the data at every execution . If not, it download it and import it." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "from os.path import exists" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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416.92 \n", "773 773 2022 04 44666 2022.2877 420.02 417.25 \n", "774 774 2022 05 44696 2022.3699 420.77 417.36 \n", "775 775 2022 06 44727 2022.4548 420.68 418.09 \n", "776 776 2022 07 44757 2022.5370 418.68 417.87 \n", "777 777 2022 08 44788 2022.6219 416.76 418.31 \n", "778 778 2022 09 44819 2022.7068 415.41 418.91 \n", "779 779 2022 10 44849 2022.7890 415.31 418.93 \n", "780 780 2022 11 44880 2022.8740 417.04 419.31 \n", "781 781 2022 12 44910 2022.9562 418.57 419.49 \n", "782 782 2023 01 44941 2023.0411 419.24 419.17 \n", "783 783 2023 02 44972 2023.1260 420.33 419.55 \n", "784 784 2023 03 45000 2023.2027 420.51 418.97 \n", "785 785 2023 04 45031 2023.2877 422.73 419.95 \n", "786 786 2023 05 45061 2023.3699 423.78 420.36 \n", "787 787 2023 06 45092 2023.4548 423.39 420.80 \n", "788 788 2023 07 45122 2023.5370 -99.99 -99.99 \n", "789 789 2023 08 45153 2023.6219 -99.99 -99.99 \n", "790 790 2023 09 45184 2023.7068 -99.99 -99.99 \n", "791 791 2023 10 45214 2023.7890 -99.99 -99.99 \n", "792 792 2023 11 45245 2023.8740 -99.99 -99.99 \n", "793 793 2023 12 45275 2023.9562 -99.99 -99.99 \n", "\n", " fit seasonally CO2 seasonally Sta \n", "0 adjusted fit filled adjusted filled NaN \n", "1 [ppm] [ppm] [ppm] [ppm] NaN \n", "2 -99.99 -99.99 -99.99 -99.99 MLO \n", "3 -99.99 -99.99 -99.99 -99.99 MLO \n", "4 316.19 314.91 315.71 314.44 MLO \n", "5 317.30 314.99 317.45 315.16 MLO \n", "6 317.89 315.07 317.51 314.69 MLO \n", "7 317.27 315.15 317.27 315.15 MLO \n", "8 315.86 315.22 315.87 315.20 MLO \n", "9 313.97 315.29 314.93 316.21 MLO \n", "10 312.44 315.35 313.21 316.11 MLO \n", "11 312.42 315.41 312.42 315.41 MLO \n", "12 313.61 315.46 313.33 315.21 MLO \n", "13 314.77 315.52 314.67 315.43 MLO \n", "14 315.64 315.57 315.58 315.52 MLO \n", "15 316.29 315.63 316.49 315.84 MLO \n", "16 316.98 315.70 316.65 315.38 MLO \n", "17 318.09 315.77 317.72 315.42 MLO \n", "18 318.68 315.85 318.29 315.46 MLO \n", "19 318.07 315.94 318.15 316.00 MLO \n", "20 316.67 316.03 316.54 315.87 MLO \n", "21 314.80 316.13 314.80 316.09 MLO \n", "22 313.30 316.22 313.84 316.75 MLO \n", "23 313.31 316.31 313.33 316.34 MLO \n", "24 314.53 316.40 314.81 316.69 MLO \n", "25 315.72 316.48 315.58 316.35 MLO \n", "26 316.63 316.56 316.43 316.37 MLO \n", "27 317.29 316.64 316.98 316.33 MLO \n", "28 318.03 316.72 317.58 316.28 MLO \n", "29 319.14 316.79 319.03 316.70 MLO \n", ".. ... ... ... ... ... \n", "764 416.95 416.18 416.65 415.85 MLO \n", "765 414.78 416.36 414.34 415.89 MLO \n", "766 413.04 416.55 412.90 416.40 MLO \n", "767 413.14 416.74 413.55 417.16 MLO \n", "768 414.69 416.92 414.82 417.08 MLO \n", "769 416.19 417.10 416.43 417.36 MLO \n", "770 417.34 417.26 418.01 417.94 MLO \n", "771 418.21 417.42 418.99 418.21 MLO \n", "772 419.11 417.56 418.45 416.92 MLO \n", "773 420.50 417.71 420.02 417.25 MLO \n", "774 421.27 417.86 420.77 417.36 MLO \n", "775 420.60 418.03 420.68 418.09 MLO \n", "776 418.98 418.21 418.68 417.87 MLO \n", "777 416.80 418.40 416.76 418.31 MLO \n", "778 415.07 418.59 415.41 418.91 MLO \n", "779 415.18 418.78 415.31 418.93 MLO \n", "780 416.74 418.98 417.04 419.31 MLO \n", "781 418.27 419.18 418.57 419.49 MKO \n", "782 419.46 419.38 419.24 419.17 MKO \n", "783 420.38 419.59 420.33 419.55 MKO \n", "784 421.34 419.79 420.51 418.97 MLO \n", "785 422.81 420.01 422.73 419.95 MLO \n", "786 423.65 420.23 423.78 420.36 MLO \n", "787 423.03 420.46 423.39 420.80 MLO \n", "788 -99.99 -99.99 -99.99 -99.99 MLO \n", "789 -99.99 -99.99 -99.99 -99.99 MLO \n", "790 -99.99 -99.99 -99.99 -99.99 MLO \n", "791 -99.99 -99.99 -99.99 -99.99 MLO \n", "792 -99.99 -99.99 -99.99 -99.99 MLO \n", "793 -99.99 -99.99 -99.99 -99.99 MLO \n", "\n", "[794 rows x 12 columns]" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data_url = \"https://scrippsco2.ucsd.edu/assets/data/atmospheric/stations/in_situ_co2/monthly/monthly_in_situ_co2_mlo.csv\"\n", "\n", "#boo Check if file has already been downloaded to not download the data at every execution\n", "boo=exists(\"DATA.csv\")\n", "\n", "if boo:\n", " raw_data=raw_data = pd.read_csv(\"DATA.csv\")\n", "else: \n", " raw_data = pd.read_csv(data_url,skiprows=57)\n", " raw_data.to_csv(\"DATA.csv\")\n", "\n", "raw_data\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2. Data formatting\n", "\n", "The raw data is not ready for analysis. \n", "The two first lines are used to comment the rows:\n", "- **Line 0:** used to comment the nature of the row\n", "- **Line 1:** used to comment the unit of the row\n", "\n", "We start by deleting the two lines:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Unnamed: 0YrMnDateDateCO2seasonallyfitseasonallyCO2seasonallySta
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11Excel[ppm][ppm][ppm][ppm][ppm][ppm]NaN
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" ], "text/plain": [ " Unnamed: 0 Yr Mn Date Date CO2 seasonally \\\n", "0 0 adjusted \n", "1 1 Excel [ppm] [ppm] \n", "\n", " fit seasonally CO2 seasonally Sta \n", "0 adjusted fit filled adjusted filled NaN \n", "1 [ppm] [ppm] [ppm] [ppm] NaN " ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data[raw_data.isnull().any(axis=1)]" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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786786202305450612023.3699423.78420.36423.65420.23423.78420.36MLO
787787202306450922023.4548423.39420.80423.03420.46423.39420.80MLO
788788202307451222023.5370-99.99-99.99-99.99-99.99-99.99-99.99MLO
789789202308451532023.6219-99.99-99.99-99.99-99.99-99.99-99.99MLO
790790202309451842023.7068-99.99-99.99-99.99-99.99-99.99-99.99MLO
791791202310452142023.7890-99.99-99.99-99.99-99.99-99.99-99.99MLO
792792202311452452023.8740-99.99-99.99-99.99-99.99-99.99-99.99MLO
793793202312452752023.9562-99.99-99.99-99.99-99.99-99.99-99.99MLO
\n", "

792 rows × 12 columns

\n", "
" ], "text/plain": [ " Unnamed: 0 Yr Mn Date Date CO2 seasonally \\\n", "2 2 1958 01 21200 1958.0411 -99.99 -99.99 \n", "3 3 1958 02 21231 1958.1260 -99.99 -99.99 \n", "4 4 1958 03 21259 1958.2027 315.71 314.44 \n", "5 5 1958 04 21290 1958.2877 317.45 315.16 \n", "6 6 1958 05 21320 1958.3699 317.51 314.69 \n", "7 7 1958 06 21351 1958.4548 -99.99 -99.99 \n", "8 8 1958 07 21381 1958.5370 315.87 315.20 \n", "9 9 1958 08 21412 1958.6219 314.93 316.21 \n", "10 10 1958 09 21443 1958.7068 313.21 316.11 \n", "11 11 1958 10 21473 1958.7890 -99.99 -99.99 \n", "12 12 1958 11 21504 1958.8740 313.33 315.21 \n", "13 13 1958 12 21534 1958.9562 314.67 315.43 \n", "14 14 1959 01 21565 1959.0411 315.58 315.52 \n", "15 15 1959 02 21596 1959.1260 316.49 315.84 \n", "16 16 1959 03 21624 1959.2027 316.65 315.38 \n", "17 17 1959 04 21655 1959.2877 317.72 315.42 \n", "18 18 1959 05 21685 1959.3699 318.29 315.46 \n", "19 19 1959 06 21716 1959.4548 318.15 316.00 \n", "20 20 1959 07 21746 1959.5370 316.54 315.87 \n", "21 21 1959 08 21777 1959.6219 314.80 316.09 \n", "22 22 1959 09 21808 1959.7068 313.84 316.75 \n", "23 23 1959 10 21838 1959.7890 313.33 316.34 \n", "24 24 1959 11 21869 1959.8740 314.81 316.69 \n", "25 25 1959 12 21899 1959.9562 315.58 316.35 \n", "26 26 1960 01 21930 1960.0410 316.43 316.37 \n", "27 27 1960 02 21961 1960.1257 316.98 316.33 \n", "28 28 1960 03 21990 1960.2049 317.58 316.28 \n", "29 29 1960 04 22021 1960.2896 319.03 316.70 \n", "30 30 1960 05 22051 1960.3716 320.03 317.20 \n", "31 31 1960 06 22082 1960.4563 319.58 317.45 \n", ".. ... ... ... ... ... ... ... \n", "764 764 2021 07 44392 2021.5370 416.65 415.85 \n", "765 765 2021 08 44423 2021.6219 414.34 415.89 \n", "766 766 2021 09 44454 2021.7068 412.90 416.40 \n", "767 767 2021 10 44484 2021.7890 413.55 417.16 \n", "768 768 2021 11 44515 2021.8740 414.82 417.08 \n", "769 769 2021 12 44545 2021.9562 416.43 417.36 \n", "770 770 2022 01 44576 2022.0411 418.01 417.94 \n", "771 771 2022 02 44607 2022.1260 418.99 418.21 \n", "772 772 2022 03 44635 2022.2027 418.45 416.92 \n", "773 773 2022 04 44666 2022.2877 420.02 417.25 \n", "774 774 2022 05 44696 2022.3699 420.77 417.36 \n", "775 775 2022 06 44727 2022.4548 420.68 418.09 \n", "776 776 2022 07 44757 2022.5370 418.68 417.87 \n", "777 777 2022 08 44788 2022.6219 416.76 418.31 \n", "778 778 2022 09 44819 2022.7068 415.41 418.91 \n", "779 779 2022 10 44849 2022.7890 415.31 418.93 \n", "780 780 2022 11 44880 2022.8740 417.04 419.31 \n", "781 781 2022 12 44910 2022.9562 418.57 419.49 \n", "782 782 2023 01 44941 2023.0411 419.24 419.17 \n", "783 783 2023 02 44972 2023.1260 420.33 419.55 \n", "784 784 2023 03 45000 2023.2027 420.51 418.97 \n", "785 785 2023 04 45031 2023.2877 422.73 419.95 \n", "786 786 2023 05 45061 2023.3699 423.78 420.36 \n", "787 787 2023 06 45092 2023.4548 423.39 420.80 \n", "788 788 2023 07 45122 2023.5370 -99.99 -99.99 \n", "789 789 2023 08 45153 2023.6219 -99.99 -99.99 \n", "790 790 2023 09 45184 2023.7068 -99.99 -99.99 \n", "791 791 2023 10 45214 2023.7890 -99.99 -99.99 \n", "792 792 2023 11 45245 2023.8740 -99.99 -99.99 \n", "793 793 2023 12 45275 2023.9562 -99.99 -99.99 \n", "\n", " fit seasonally CO2 seasonally Sta \n", "2 -99.99 -99.99 -99.99 -99.99 MLO \n", "3 -99.99 -99.99 -99.99 -99.99 MLO \n", "4 316.19 314.91 315.71 314.44 MLO \n", "5 317.30 314.99 317.45 315.16 MLO \n", "6 317.89 315.07 317.51 314.69 MLO \n", "7 317.27 315.15 317.27 315.15 MLO \n", "8 315.86 315.22 315.87 315.20 MLO \n", "9 313.97 315.29 314.93 316.21 MLO \n", "10 312.44 315.35 313.21 316.11 MLO \n", "11 312.42 315.41 312.42 315.41 MLO \n", "12 313.61 315.46 313.33 315.21 MLO \n", "13 314.77 315.52 314.67 315.43 MLO \n", "14 315.64 315.57 315.58 315.52 MLO \n", "15 316.29 315.63 316.49 315.84 MLO \n", "16 316.98 315.70 316.65 315.38 MLO \n", "17 318.09 315.77 317.72 315.42 MLO \n", "18 318.68 315.85 318.29 315.46 MLO \n", "19 318.07 315.94 318.15 316.00 MLO \n", "20 316.67 316.03 316.54 315.87 MLO \n", "21 314.80 316.13 314.80 316.09 MLO \n", "22 313.30 316.22 313.84 316.75 MLO \n", "23 313.31 316.31 313.33 316.34 MLO \n", "24 314.53 316.40 314.81 316.69 MLO \n", "25 315.72 316.48 315.58 316.35 MLO \n", "26 316.63 316.56 316.43 316.37 MLO \n", "27 317.29 316.64 316.98 316.33 MLO \n", "28 318.03 316.72 317.58 316.28 MLO \n", "29 319.14 316.79 319.03 316.70 MLO \n", "30 319.70 316.87 320.03 317.20 MLO \n", "31 319.04 316.93 319.58 317.45 MLO \n", ".. ... ... ... ... ... \n", "764 416.95 416.18 416.65 415.85 MLO \n", "765 414.78 416.36 414.34 415.89 MLO \n", "766 413.04 416.55 412.90 416.40 MLO \n", "767 413.14 416.74 413.55 417.16 MLO \n", "768 414.69 416.92 414.82 417.08 MLO \n", "769 416.19 417.10 416.43 417.36 MLO \n", "770 417.34 417.26 418.01 417.94 MLO \n", "771 418.21 417.42 418.99 418.21 MLO \n", "772 419.11 417.56 418.45 416.92 MLO \n", "773 420.50 417.71 420.02 417.25 MLO \n", "774 421.27 417.86 420.77 417.36 MLO \n", "775 420.60 418.03 420.68 418.09 MLO \n", "776 418.98 418.21 418.68 417.87 MLO \n", "777 416.80 418.40 416.76 418.31 MLO \n", "778 415.07 418.59 415.41 418.91 MLO \n", "779 415.18 418.78 415.31 418.93 MLO \n", "780 416.74 418.98 417.04 419.31 MLO \n", "781 418.27 419.18 418.57 419.49 MKO \n", "782 419.46 419.38 419.24 419.17 MKO \n", "783 420.38 419.59 420.33 419.55 MKO \n", "784 421.34 419.79 420.51 418.97 MLO \n", "785 422.81 420.01 422.73 419.95 MLO \n", "786 423.65 420.23 423.78 420.36 MLO \n", "787 423.03 420.46 423.39 420.80 MLO \n", "788 -99.99 -99.99 -99.99 -99.99 MLO \n", "789 -99.99 -99.99 -99.99 -99.99 MLO \n", "790 -99.99 -99.99 -99.99 -99.99 MLO \n", "791 -99.99 -99.99 -99.99 -99.99 MLO \n", "792 -99.99 -99.99 -99.99 -99.99 MLO \n", "793 -99.99 -99.99 -99.99 -99.99 MLO \n", "\n", "[792 rows x 12 columns]" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data = raw_data.dropna().copy()\n", "data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We now need to convert the data from string to float in order to plot it.\n", "\n", "**`data.keys()`** gives us the name of each row which allow us to treat the data row by row. " ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['Unnamed: 0', ' Yr', ' Mn', ' Date', ' Date', ' CO2',\n", " 'seasonally', ' fit', ' seasonally', ' CO2', ' seasonally',\n", " ' Sta'],\n", " dtype='object')" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.keys()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "data[\" Date\"]=[float(element) for element in data[' Date']]\n", "x=data[\" Date\"]\n", "\n", "data[\" CO2\"]=[float(element) for element in data[' CO2']]\n", "y=data[\" CO2\"]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 3. Plotting the data\n", "\n", "We are now able to plot the CO$_2$ concentration for every years." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.plot(x,y)\n", "plt.show" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**We can see that some missing values are represented by the -99.99 value.**\n", "\n", "Before we can continue, we need to delete this values:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def cleandata(element):\n", " newvalue=element\n", " if(element==-99.99):\n", " newvalue=np.nan\n", " return newvalue\n", "\n", "data[\" CO2\"]=[cleandata(element) for element in data[' CO2']]\n", "datacleaned = data.dropna().copy()\n", "data\n", "x2=datacleaned[\" Date\"]\n", "y2=datacleaned[\" CO2\"]\n", "plt.plot(x2,y2,label=\"DATA\")\n", "plt.legend()\n", "plt.show;" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 4. Analysis\n", "\n", "As shown in the previous plot, we can see a *high* frequency oscillation coupled to a slow increase.\n", "\n", "For the analysis, we want to isolate the oscilating contributionn from the continuous curve. For that we **assume** that this slow curve can be described by a square function with three parameters: $f(x)=a.x^2+b.x+c$" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from scipy.optimize import curve_fit\n", "\n", "def fitfunc(x, a, b, c):\n", " return a*x*x+b*x + c\n", "\n", "popt,pcov=curve_fit(fitfunc,x2,y2)\n", "plt.figure()\n", "plt.plot(x2,y2,label=\"DATA\")\n", "plt.plot(x2,fitfunc(x2,*popt),label=\"Fit\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In **first approximation** we can say that this square fit is matching well the experimental data.\n", "\n", "We can ensure this claim by isolating the oscilating contribution which should oscilate around 0." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure()\n", "plt.plot(x2,y2-fitfunc(x2,*popt),label=\"Background subed\")\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 4. Result of the extrapolation\n", "\n", "Now that we are conviced by the $x^2$ fit, we can extrapolate the data for the year 2025." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure()\n", "plt.plot(x2,y2,label=\"DATA\")\n", "plt.plot(np.linspace(1960,2027,200),fitfunc(np.linspace(1960,2027,200),*popt),label=\"Fit Extrapolation\",ls=\"--\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**The extrapolation would indicate a concentration around 424.246 $[$ppm$]$** in 2025" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 2 }