{ "cells": [ { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "# Global Temperature Predictions\n", "\n", "In the previous few sections we have looked at the data from NOAA, and explored some statistical techniques. This section is a slight deviation as we look at a new data set on Global Temperatures.\n", "Using global temperature data combined with global $\\text{CO}_2$ concentration and warming data provided by the IPCC we compare a simple model with Global warming estimates laid out in the Special Report on Emission Scenarios(SRES){cite}`SRES`." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "pycharm": { "name": "#%%\n" }, "tags": [ "remove-input" ] }, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from dur_utils import colours\n", "from numpy.lib.stride_tricks import sliding_window_view\n", "from scipy.optimize import curve_fit\n", "from scipy import stats\n", "\n", "plt.style.use(\"../CDS.mplstyle\")" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "The global Temperature data is taken from [Berkley Earth](http://berkeleyearth.org/data/). The temperature data has missing fields as with the Global $\\text{CO}_2$ data. Further, the date is formatted awkwardly into a fixed width table format with commented-out headers. Finally, the global temperature data is seasonal. Thus some data cleaning and formatting is required.\n", "\n", "When ananlysing the data, a Fourier-based fit could be applied similarly to that performed in the section on Global $\\text{CO}_2$ data. Because this section is not looking for a functional form, an average is more straightforward to implement.\n", "\n", "After cleaning the data of null fields, a moving average can be used to remove the seasonal trends." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "pycharm": { "name": "#%%\n" }, "tags": [ "remove-input" ] }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " Number of Null Values\n", "year 0\n", "month 0\n", "monthly_anomaly 1\n", "monthly_anomaly_unc 1\n", "dt 0" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Load, Format and clean\n", "path = (\n", " \"http://berkeleyearth.lbl.gov/auto/Global/Complete_TAVG_complete.txt\"\n", ")\n", "colnames = [\n", " \"year\",\n", " \"month\",\n", " \"monthly_anomaly\",\n", " \"monthly_anomaly_unc\",\n", " \"yearly_anomaly\",\n", " \"yearly_anomaly_unc\",\n", " \"5yearly_anomaly\",\n", " \"5yearly_anomaly_unc\",\n", " \"10yearly_anomaly\",\n", " \"10yearly_anomaly_unc\",\n", " \"20yearly_anomaly\",\n", " \"20yearly_anomaly_unc\",\n", "]\n", "temp_data = pd.read_fwf(path, skiprows=34, names=colnames)\n", "temp_data[\"dt\"] = temp_data[\"month\"] / 12 + temp_data[\"year\"]\n", "# remove the moving averages\n", "temp_data.drop(\n", " columns=[\n", " \"yearly_anomaly\",\n", " \"yearly_anomaly_unc\",\n", " \"5yearly_anomaly\",\n", " \"5yearly_anomaly_unc\",\n", " \"10yearly_anomaly\",\n", " \"10yearly_anomaly_unc\",\n", " \"20yearly_anomaly\",\n", " \"20yearly_anomaly_unc\",\n", " ],\n", " inplace=True,\n", ")\n", "# Format data\n", "null_sum = (temp_data.isna()).values.sum(axis=0)\n", "path_ml = \"https://gml.noaa.gov/webdata/ccgg/trends/co2/co2_mm_gl.csv\"\n", "co2_data = pd.read_csv(path_ml, header=0, comment=\"#\")\n", "\n", "pd.DataFrame(\n", " data=null_sum,\n", " index=temp_data.columns,\n", " columns=[\"Number of Null Values\"],\n", ")" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "\"\"\"\n", "The sliding window view provided by numpy is used so that\n", "The moving averages can be calculated. \n", "\n", "The window length of 120 corresponds to a 10 year average.\n", "\"\"\"\n", "temp_data = temp_data.dropna()\n", "WINDOW = 120\n", "# Sliding window weighted average:\n", "slv = sliding_window_view(temp_data, WINDOW, 0)\n", "time_midpoint = np.mean(slv[:, -1, :], axis=1)\n", "win_ave_temp = slv[:, 2, :]\n", "win_ave_unc = slv[:, 3, :]" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "def moving_ave_frame(df: pd.DataFrame, window: int) -> pd.DataFrame:\n", " \"Applies a moving average, with a fixed window size\"\n", " slv = sliding_window_view(df, window, axis=0)\n", " moving_averages = np.mean(slv, axis=2)\n", " ma_df = pd.DataFrame(moving_averages, columns=df.keys())\n", " return ma_df\n", "\n", "\n", "def moving_std_frame(df: pd.DataFrame, window: int) -> pd.DataFrame:\n", " \"Applies a moving average, provides the standard deviation\"\n", " slv = sliding_window_view(df, window, axis=0)\n", " moving_averages = np.std(slv, axis=2) / np.sqrt(window)\n", " ma_df = pd.DataFrame(moving_averages, columns=df.keys())\n", " return ma_df\n", "\n", "\n", "def lb_ub(values, sigma, factor=1):\n", " lb = values - sigma * factor\n", " ub = values + sigma * factor\n", " return lb, ub\n", "\n", "\n", "def P1(x, a0, a1):\n", " return a0 + a1 * x" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "pycharm": { "name": "#%%\n" }, "tags": [ "hide-inpupt" ] }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(1, 1, figsize=(10, 6))\n", "ave_temp = np.mean(win_ave_temp, axis=1)\n", "ave_unc = np.mean(win_ave_unc, axis=1)\n", "lb, ub = lb_ub(ave_temp, ave_unc)\n", "# Plotting\n", "ax.plot(time_midpoint, ave_temp, color=colours.durham.ink)\n", "ax.fill_between(time_midpoint, lb, ub, color=colours.durham.ink, alpha=0.2)\n", "ax.set_xlabel(\"Window Midpoint (Year)\")\n", "ax.set_ylabel(\n", " \"10 Year Moving Average of \\n \\\n", " Land Average Temperature Anomaly $(^{\\circ}C)$\"\n", ");" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "## Predictions\n", "Global temperatures provide an interesting case study for a further introduction to predictive modeling. \n", "\n", "There has already been substantial warming compared to the period from $1850-1900$. This period is set as a pre-industrial baseline{cite}`preindbaseline`. Further temperature rises will continue to increase the occurrence of extreme weather events and myriad other consequences, with an entire [IPCC](https://www.ipcc.ch/sr15/) report dedicated to the consequences of warming over $1.5^\\circ C$. The special report on emission scenarios(SRES){cite}`SRES` produced by the IPCC in 2000, details multiple families of emission scenarios with their associated warming. \n", "\n", "These scenarios are developed using six independent models. Such models use economic driving forces and predict the consequences of changing macro-economic behavior, for example, the percentage of fossil fuel used compared to renewables. \n", "\n", "These highly detailed models are beyond the scope of the section. Using $\\text{CO}_2$ concentration, a simple model can be formed to determine the change in temperature over the next 30 years.\n", "The three scenarios that will be investigated are approximations of the A1 and B1 storylines described from page 247 onwards in the [SRES](https://www.ipcc.ch/site/assets/uploads/2018/03/emissions_scenarios-1.pdf).\n", "- A1B) Continued growth in emission Rates. This scenario represents a growth-focused world with a balanced mix of energy sources. \n", "- A1T) Net-zero by 2030, no further reductions. This scenario corresponds to a growth-focused world with renewable energy sources.\n", "- B1) Net-zero by 2030, and then reducing total atmospheric carbon at the same rate it is currently produced. Corresponding to a global focus on emissions reduction.\n", "The relationship between $\\text{CO}_2$ concentration used is:\n", "\n", "```{math}\n", "T(C) = T_0 + S \\log_2(C/C_0).\n", "```\n", "Where $C$ is the concentration of $\\text{CO}_2$ and $S$ is a fitted sensitivity factor." ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "## Current Warming trend " ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "pycharm": { "name": "#%%\n" }, "tags": [ "hide-input" ] }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "trend_data = temp_data[temp_data[\"dt\"] > 1960]\n", "trend_ave = moving_ave_frame(trend_data, WINDOW)\n", "lb, ub = lb_ub(\n", " trend_ave[\"monthly_anomaly\"], trend_ave[\"monthly_anomaly_unc\"]\n", ")\n", "trend_ave.to_csv(\n", " f\"../output_files/temperature_{int(WINDOW/12)}\" \"_moving_average.csv\"\n", ")\n", "trend_fit, trend_error = curve_fit(\n", " P1,\n", " trend_ave[\"dt\"],\n", " trend_ave[\"monthly_anomaly\"],\n", " sigma=trend_ave[\"monthly_anomaly_unc\"],\n", ")\n", "gradient_lb, gradient_ub = lb_ub(trend_fit[1], trend_error[1, 1])\n", "lb, ub = lb_ub(\n", " trend_ave[\"monthly_anomaly\"], trend_ave[\"monthly_anomaly_unc\"]\n", ")\n", "# Plotting\n", "fig, ax = plt.subplots(1, 1, figsize=(10, 6))\n", "time = np.linspace(2017.3, 2055, 300)\n", "trend_lb = trend_fit - np.diagonal(trend_error)\n", "trend_ub = trend_fit + np.diagonal(trend_error)\n", "plt.fill_between(\n", " trend_ave[\"dt\"], lb, ub, alpha=0.2, color=colours.durham.ink\n", ")\n", "plt.plot(\n", " trend_ave[\"dt\"],\n", " trend_ave[\"monthly_anomaly\"],\n", " c=colours.durham.ink,\n", " label=\"Moving Average\",\n", ")\n", "plt.plot(\n", " time,\n", " P1(time, *trend_fit),\n", " linestyle=\"--\",\n", " color=colours.durham.ink,\n", " label=\"Linear Trend\",\n", ")\n", "ax.set_xlabel(\"Window Midpoint (Year)\")\n", "ax.set_ylabel(\n", " f\"{int(WINDOW / 12)} Year Moving Average of \\n\"\n", " r\"Land Average Temperature Anomaly $(^{\\circ}\\textrm{{C}})$\"\n", ")\n", "# Warming Targets\n", "x = np.linspace(1960, 2055, 100)\n", "y = np.ones_like(x)\n", "plt.plot(\n", " x,\n", " y * 1.5,\n", " color=colours.durham.red,\n", " label=\"$1.5^\\circ C$ Warming\",\n", " linestyle=\"--\",\n", ")\n", "plt.plot(\n", " x,\n", " y * 2,\n", " color=colours.durham.red,\n", " label=\"$2.0^\\circ C$ Warming\",\n", " linestyle=\"-.\",\n", ")\n", "plt.fill_between(time, P1(time, *trend_lb), P1(time, *trend_ub))\n", "plt.legend();" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "With a simple linear extrapolation of the Berkeley Earth temperature data, one can see that if the current rate of warming persists, then keeping the Global Temperature anomaly below $1.5^\\circ C$ is unlikely, moving into the future. However, this simple model is just for getting a feeling of the data. By combining this dataset with the Global $\\text{CO}_2$ data, the correlation of these datasets can be examined. Both of the datasets' moving averages are plotted below for a visual comparison. Further, the Pearson correlation co-efficient $(r)$ can be calculated for the datasets. $r$ is given by,\n", "```{math}\n", "r(x,y) = \\frac{\\sum (x_i-\\bar{x})(y_i-\\bar{y})}{\\sqrt{\\sum (x_i-\\bar{x})^2 \\sum (y_i-\\bar{y})^2 }}.\n", "```\n", "Where $\\bar{q}$ indicates the mean of $q$. The $r$ value can be calculated for the global $\\text{CO}_2$ concentration and the temperature by taking both variables evaluated simultaneously in time. \n", "\n", "```{note}\n", "The error bars on the $\\text{CO_2}$ concentration are two times the standard error on the mean. However, the error bars on the temperature is the mean of the uncertainty over the window. This is because the uncertainty corresponds to 95\\% of recorded percentages. \n", "```" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "pycharm": { "name": "#%%\n" }, "tags": [ "hide-input" ] }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "trend_co2_data = co2_data[co2_data[\"decimal\"] > 1960]\n", "trend_co2_ave = moving_ave_frame(co2_data, WINDOW)\n", "trend_co2_std = moving_std_frame(co2_data, WINDOW)\n", "co2_lb, co2_ub = lb_ub(\n", " trend_co2_ave[\"average\"], trend_co2_std[\"average\"], factor=2\n", ")\n", "trend_co2_ave.to_csv(\n", " f\"../output_files/co2_{int(WINDOW/12)}\" \"_moving_average.csv\"\n", ")\n", "trend_co2_std.to_csv(\n", " f\"../output_files/co2_{int(WINDOW/12)}\" \"_moving_std.csv\"\n", ")\n", "fig, ax = plt.subplots(1, 1, figsize=(10, 6))\n", "# Temp\n", "ax1 = ax.twinx()\n", "ax.plot(\n", " trend_ave[\"dt\"],\n", " trend_ave[\"monthly_anomaly\"],\n", " c=colours.durham.ink,\n", " label=\"Moving Average\",\n", ")\n", "ax.fill_between(\n", " trend_ave[\"dt\"], lb, ub, alpha=0.2, color=colours.durham.red\n", ")\n", "\n", "ax.set_ylabel(\n", " f\"{int(WINDOW / 12)} Year Moving Average of \\n\"\n", " r\"Land Average Temperature Anomaly $(^{\\circ}\\textrm{{C}})$\"\n", ")\n", "ax.set_yticks(\n", " np.arange(-0.2, 1.4, 0.2),\n", " np.round(np.arange(-0.2, 1.4, 0.2), 2),\n", " color=colours.durham.red,\n", ")\n", "ax.set_xlabel(\"Window Midpoint (Year)\")\n", "# CO2\n", "ax1.plot(\n", " trend_co2_ave[\"decimal\"],\n", " trend_co2_ave[\"average\"],\n", " color=colours.durham.ink,\n", ")\n", "ax1.fill_between(\n", " trend_co2_ave[\"decimal\"],\n", " co2_lb,\n", " co2_ub,\n", " alpha=0.2,\n", " color=colours.durham.ink,\n", ")\n", "ax1.set_ylabel(\n", " rf\"{int(WINDOW / 12)} Year Moving Average of\"\n", " r\" $\\textrm{{CO}}_2$ (ppm)\"\n", ")\n", "\n", "plt.xlim(1985, 2017);" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pearson Correlation Coefficient:0.99\n" ] } ], "source": [ "\"\"\"\n", "To calculate the correlation coefficient, the arrays must \n", "have the same size along the time axis. So they are clipped\n", "for this calculation. \n", "\"\"\"\n", "\n", "co2_slice = np.where(\n", " (1985 < trend_co2_ave[\"decimal\"]) & (trend_co2_ave[\"decimal\"] < 2016)\n", ")\n", "temp_slice = np.where((1985 < trend_ave[\"dt\"]) & (trend_ave[\"dt\"] < 2016))\n", "bound_co2 = trend_co2_ave[\"average\"].iloc[co2_slice]\n", "bound_temp = trend_ave[\"monthly_anomaly\"].iloc[temp_slice]\n", "r_coef = stats.pearsonr(bound_co2, np.array(bound_temp)[1:])\n", "print(f\"Pearson Correlation Coefficient:{r_coef[0]:.2}\")" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "As expected the two quantities are very strongly correlated. The Pearson correlation coefficient in this scenario is not particularly useful. The information it provides is redundant with the above graph. However, with high dimensional data, a correlation matrix can glean insight into the relationship of variables. A short medium article on correlation matrix plots can be found [here](https://towardsdatascience.com/better-heatmaps-and-correlation-matrix-plots-in-python-41445d0f2bec)" ] } ], "metadata": { "celltoolbar": "Tags", "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.4" }, "vscode": { "interpreter": { "hash": "59741db575107ab5410b00365ec93382e14756ed49d68fa4219f7bcb47931d56" } } }, "nbformat": 4, "nbformat_minor": 2 }