{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "# 06. Global atmospheric temperature trends\n", "\n", "## Analysing large data sets in MATLAB/octave\n", "\n", "
By Edward Sternin, 2023-10
\n", "\n", "This simple demo of octave-based data plotting is based on the publicly-available data from UAH (University of Alabama, Huntsville), as reported by the group of John Christy . The raw satellite data (NOAA series of satellites; AQUA, starting in mid-2002) from the National Space Science and Technology Centre (http://vortex.nsstc.uah.edu/) is extensively verified and corrected for calibration errors, as those are detected. For example, camera drift as NOAA-18 and NOAA-19 satellites aged was discovered and corrected in 2017, as described here.\n", " This is the best large-scale atmospheric temperature data that we (the humans) have, free of any bias that may (or may not) exist in the surface-measured temperatures." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "### this sets the Jupyter working directory\n", "%cd ~/5P10" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "### this sets the Octave working directory and search path\n", "cd ~/5P10\n", "addpath(\"~/5P10\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The following only needs to be done once, using either method below. Rather than read the external data files directly, we first make local copies using the operating system command wget or urlwrite(external_URL,local_file_name):" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "### retrieval of files across the network could be deferred to the operating system\n", "### the advantage is that the files will only be downloaded if they changed at the source\n", "system('wget -Nq https://www.nsstc.uah.edu/data/msu/v6.0/tls/uahncdc_ls_6.0.txt');\n", "system('wget -Nq https://www.nsstc.uah.edu/data/msu/v6.0/tmt/uahncdc_mt_6.0.txt');\n", "system('wget -Nq https://www.nsstc.uah.edu/data/msu/v6.0/tlt/uahncdc_lt_6.0.txt');\n", "system('wget -Nq http://www.sidc.be/silso/DATA/SN_m_tot_V2.0.txt');\n", "system('wget -Nq https://solarscience.msfc.nasa.gov/greenwch/sunspot_area.txt');" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "### this is a pure octave call, and will download every time, even if there was no change\n", "urlwrite('https://www.nsstc.uah.edu/data/msu/v6.0/tls/uahncdc_ls_6.0.txt','uahncdc_ls_6.0.txt');\n", "urlwrite('https://www.nsstc.uah.edu/data/msu/v6.0/tmt/uahncdc_mt_6.0.txt','uahncdc_mt_6.0.txt');\n", "urlwrite('https://www.nsstc.uah.edu/data/msu/v6.0/tlt/uahncdc_lt_6.0.txt','uahncdc_lt_6.0.txt');\n", "\n", "# Sunspot count data from WDC-SILSO, Royal Observatory of Belgium, Brussels\n", "# column format: year, month, decimal year, SNvalue , SNerror, Nb observations\n", "# monthly averages. The file has no header.\n", "urlwrite('http://www.sidc.be/silso/DATA/SN_m_tot_V2.0.txt','SN_m_tot_V2.0.txt');\n", "\n", "# Monthly averages of the daily sunspot areas, x1e-6 of hemisphere. From dave.hathaway@comcast.net\n", "# - first line is the header with column titles \n", "# - whitespace as separators (default is comma ',') \n", "urlwrite('https://solarscience.msfc.nasa.gov/greenwch/sunspot_area.txt','sunspot_area.txt');" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "### only need to do this once\n", "### this signal-processing package contains Savitsky-Golay filter implementation\n", "pkg load signal;\n", "### this is a useful way of keeping all data in one place\n", "pkg load dataframe;\n", "### needed for regression analysis\n", "pkg load statistics;" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Reading the data in" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "### read in the local file, skipping the first line as a header, to the end, only the first three columns\n", "d = dlmread('uahncdc_ls_6.0.txt','',[1 0 inf 2]);\n", "### make a decimal date out of year + (month-0.5)/12, i.e. place time at mid-month\n", "### v 6.0 data has a nine-line footer in the file, skip that\n", "year = d(1:end-9,1)+(d(1:end-9,2)-0.5)/12;\n", "t_ls = d(1:end-9,3);\n", "### only need the third columns from the other two data files, year and month are the same\n", "d = dlmread('uahncdc_mt_6.0.txt','',[1 0 inf 2]);\n", "t_mt = d(1:end-9,3);\n", "d = dlmread('uahncdc_lt_6.0.txt','',[1 0 inf 2]);\n", "t_lt = d(1:end-9,3);\n", "\n", "### sunspot count data goes back many more years, no header, no footer\n", "# column format: year, month, decimal year, SNvalue , SNerror, Nb observations\n", "d = dlmread('SN_m_tot_V2.0.txt','',[0 0 inf 4]);\n", "sc_year = d(:,1)+(d(:,2)-0.5)/12;\n", "sc = sgolayfilt(d(:,4),2,13);\n", "\n", "### sunspot area data goes back many more years, one-line header, no footer\n", "d = dlmread('sunspot_area.txt','',[1 0 inf 2]);\n", "sa_year = d(:,1)+(d(:,2)-0.5)/12;\n", "sa = sgolayfilt(d(:,3),2,13);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Notes:\n", "\n", "\n", "## Visualizing the data and identifying influencers\n", "\n", "The most obvious influencer is the solar input, and a visual inspection confirms that there is a likely correlation between the solar activity and the atmospheric temperatires:\n" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "%plot inline -w 900 -h 600" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "scrolled": false }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "subplot(2,1,1);\n", "plot(year,t_ls,'c-;lower stratosphere;',\n", " year,t_mt,'g-;mid-troposphere;',\n", " year,t_lt,'r-;lower troposphere;');\n", "xlim([1977,2024]);\n", "ylabel('\\Delta T, ^{\\circ}C');\n", "xlabel('Year');\n", "box on;\n", "grid on;\n", "title('Changes in global average atmospheric temperatures, data from John Christy ');\n", "\n", "subplot(2,1,2);\n", "[ax,h1,h2] = plotyy(sa_year,sa,sc_year,sc);\n", "xlim(ax(1),[1977,2024]);\n", "xlim(ax(2),[1977,2024]);\n", "ylabel (ax(1), 'Average daily sunspot area, \\times 10^{-6} of hemisphere');\n", "ylabel (ax(2), 'Sunspot count, from WDC-SILSO');\n", "xlabel('Year');\n", "#legend([h1 h2],'sunspot area','sunspot count');\n", "box on;\n", "grid on;\n", "title('Record of the Sun activity, from and WDC-SILSO');" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "### other useful settings that may come in handy for tweaking the graphs\n", "#set(gcf, 'Position', 0.75*get(0, 'ScreenSize'));\n", "#set(gca, 'FontSize', 15);\n", "#set(legend(),'FontSize', 13);\n", "#set(gcf,'Visible','on');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Clearly, some of the oscillations observed in the temperature data have the same periodicity and are similar in phase to the Sun activity as reported by either of the sun spots data. The next step is to perform some form of regression analysis, to try to remove the effects of this strong influencer.\n", "

\n", "However, it is also obvious, especially from the lower stratospheric data, that something else has a dramatic short-term effect on temperature. The two peaks at 1982-93 and 1992-93 stand out. These seem to correspond to the time of two major recent volcaninc eruptions, El Chichon (Mexico, 1982) and Mt. Pinatubo (Phillipines, June 1991). Therefore, full analysis will have to include multiple regressions against both the solar activity and the atmospheric transmission rate which was greatly affected by the volcanic ash emissions.\n", "

\n", "Unfortunately, the data for atmospheric transparency is not as extensive, and some missing dates may need to be excluded from consideration. The atmospheric transmission data is derived from the measurements of direct solar radiation at Mauna Loa, Hawaii. The reason why the data measured at a location in Hawaii are very valuable for the global records is because of its remote location from any anthropogenic activities and pollution sources, other land-related events, cross-Atlantic dust storm signatures or continent weather conditions. It is not a perfect global marker; for example, the April 2010 volcanic eruption in Iceland (Eyjafjallajökull) does not seem to affect the Mauna Loa data very strongly, with only a small feature around 2010. Still, it is a good starting point.\n", "

\n", "First we download the transparency data and add another graph to the previous plot(s). The transparency decreases due to volcanic eruptions appear to be highly correlated with prominent temperature peaks in the lower statosphere." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "system('wget -Nq https://www.esrl.noaa.gov/gmd/webdata/grad/mloapt/mlo_transmission.dat');\n", "### or this:\n", "#urlwrite('https://www.esrl.noaa.gov/gmd/webdata/grad/mloapt/mlo_transmission.dat','mlo_transmission.dat');" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "### transparency data has a two-line header, no footer\n", "### columns are MMM-YYYY, decimal_year, transparency\n", "# MLO Apparent Transmission Values\n", "# (Morning, monthly means)\n", "# JAN-1958 1958.0416 0.9364\n", "# ...\n", "d = dlmread('mlo_transmission.dat','',[2 0 inf 3]);\n", "tr_year = d(:,2);\n", "tr = d(:,3);" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "%plot inline -w 900 -h 900" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "subplot(3,1,1);\n", "plot(year,t_ls,'c-;lower stratosphere;',\n", " year,t_mt,'g-;mid-troposphere;',\n", " year,t_lt,'r-;lower troposphere;');\n", "xlim([1977,2024]);\n", "ylabel('\\Delta T, ^{\\circ}C');\n", "xlabel('Year');\n", "box on;\n", "grid on;\n", "title('Changes in global average atmospheric temperatures, data from John Christy ');\n", "\n", "subplot(3,1,2);\n", "[ax,h1,h2] = plotyy(sa_year,sa,sc_year,sc);\n", "xlim(ax(1),[1977,2024]);\n", "xlim(ax(2),[1977,2024]);\n", "ylabel (ax(1), 'Average daily sunspot area, \\times 10^{-6} of hemisphere');\n", "ylabel (ax(2), 'Sunspot count, from WDC-SILSO');\n", "xlabel('Year');\n", "#legend([h1;h2],'sunspot area','sunspot count');\n", "box on;\n", "grid on;\n", "title('Record of the Sun activity, from and WDC-SILSO');\n", "\n", "subplot(3,1,3);\n", "plot(tr_year,tr,'b-;MLO monthly means;');\n", "xlim([1977,2024]);\n", "ylabel('Apparent transmission');\n", "xlabel('Year');\n", "box on;\n", "grid on;\n", "title('Mauna Loa (Hawaii) atmospheric transparency');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Dataframes are useful\n", "\n", "Dataframes are objects that offer database or spreadsheet-like properties. After you have all your data gathered into a single dataframe, with descriptive headers, column types (strings, numerical values, etc.) established, and erratic or missing values identified, certain global operations become particularly simple.\n", "

\n", "In order to analyze the atmospheric temperature data further and to perform some statistical or other forms of analysis, we blend into a dataframe the data on solar activity from two different sources. Since the data in this case is a time series of measurements we establish a common timebase index for all data." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "ans = dataframe with 11 rows and 7 columns \r\n", " _1 Year T_lowstrato T_midtropo T_lowtropo SunSpotArea SunSpotCount MLOtransparency\r\n", " Nr double double double double double double double\r\n", " 1 1979.0 1.14000 -0.300000 -0.48000 1895.3 179.18 0.93380\r\n", " 2 1979.0 1.14000 -0.300000 -0.48000 2068.2 187.28 0.93270\r\n", " 3 1979.1 0.92000 -0.280000 -0.44000 2123.4 192.48 0.93150\r\n", " 4 1979.2 0.98000 -0.220000 -0.39000 2024.8 184.01 0.92580\r\n", " 5 1979.3 1.09000 -0.230000 -0.41000 2029.6 190.89 0.92200\r\n", "533 2023.3 -0.28000 0.070000 0.18000 NaN 129.74 NaN\r\n", "534 2023.4 -0.24000 0.300000 0.37000 NaN 132.70 NaN\r\n", "535 2023.5 -0.22000 0.320000 0.38000 NaN 134.87 NaN\r\n", "536 2023.5 -0.24000 0.540000 0.64000 NaN 136.27 NaN\r\n", "537 2023.6 -0.20000 0.620000 0.70000 NaN 136.88 NaN\r\n", "538 2023.7 -0.16000 0.770000 0.90000 NaN 136.71 NaN\r\n" ] } ], "source": [ "### give columns meaningfuls names\n", "Columns = [\"Year\";\"T_lowstrato\";\"T_midtropo\";\"T_lowtropo\";\"SunSpotArea\";\"SunSpotCount\";\"MLOtransparency\"];\n", "\n", "### create a dataframe, and append two NaN-filled columns for sunspot data \n", "zc = NaN(length(year),1);\n", "df = dataframe([year,t_ls,t_mt,t_lt,zc,zc,zc]);\n", "df.colnames = Columns;\n", "\n", "### for each temperature data point, find and fill the sunspot values \n", "for i = 1:length(year)\n", " df.SunSpotArea(i)=sa( abs(sa_year - year(i)) < 0.01 );\n", " df.SunSpotCount(i)=sc( abs(sc_year - year(i)) < 0.01 );\n", " df.MLOtransparency(i)=tr( abs(tr_year - year(i)) < 0.01 );\n", "endfor\n", "\n", "### print out a few lines at the top and bottom of the dataframe\n", "df([1:5,end-5:end],Columns)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Multi-factor regression analysis\n", "\n", "A full regression analysis can calculate the statistical influence of the two major factors, and remove them from the data. Other effects and long-term trends in the data that may be obscured by these major influencers, may then become apparent. However, it is clear that there could be a time lag between a rise in ash emissions and the associated reduction in the amount of radiation reaching the surface, and any temperature changes in the various layers of the atmosphere. In fact, each of the identified layers may well have its own time delay, different from the others." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "%plot inline -w 900 -h 600" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "ans =\n", "\n", " 0.55275\n", " -0.17207\n", " -0.26870\n", "\n", "ans =\n", "\n", " -0.65813\n", " 0.15691\n", " 0.35029\n", "\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "### SunSpot count data is available for all dates\n", "corr([df.T_lowstrato, df.T_midtropo, df.T_lowtropo], df.SunSpotCount)\n", "[R_ls,lag_ls] = xcov(df.SunSpotCount,df.T_lowstrato,'coeff');\n", "[R_mt,lag_mt] = xcov(df.SunSpotCount,df.T_midtropo,'coeff');\n", "[R_lt,lag_lt] = xcov(df.SunSpotCount,df.T_lowtropo,'coeff');\n", "\n", "subplot(2,1,1);\n", "plot(lag_ls,R_ls,'c-;lower stratosphere;',\n", " lag_mt,R_mt,'g-;mid-troposphere;',\n", " lag_lt,R_lt,'r-;lower troposphere;');\n", "ylabel('Correlation coefficient');\n", "xlabel('Months');\n", "xlim([-500,500]);\n", "box on;\n", "grid on;\n", "title('Time lag in correlation between temperature and sunspot counts');\n", "\n", "### transparency is missing some dates, use only the ones that have all data\n", "df1 = df([~isnan(df.MLOtransparency)],Columns);\n", "corr ([df1.T_lowstrato, df1.T_midtropo, df1.T_lowtropo], df1.MLOtransparency)\n", "[RR_ls,llag_ls] = xcov(df1.MLOtransparency,df1.T_lowstrato,'coeff');\n", "[RR_mt,llag_mt] = xcov(df1.MLOtransparency,df1.T_midtropo,'coeff');\n", "[RR_lt,llag_lt] = xcov(df1.MLOtransparency,df1.T_lowtropo,'coeff');\n", "\n", "subplot(2,1,2);\n", "plot(llag_ls,RR_ls,'c-;lower stratosphere;',\n", " llag_mt,RR_mt,'g-;mid-troposphere;',\n", " llag_lt,RR_lt,'r-;lower troposphere;');\n", "ylabel('Correlation coefficient');\n", "xlabel('Months');\n", "xlim([-500,500]);\n", "legend(\"location\",'southeast');\n", "box on;\n", "grid on;\n", "title('Time lag in correlation between temperature and atmospheric transparency');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Homework\n", "\n", "Complete the multi-factor regression analysis of the data, and plot the temperature data adjusted by subtracting the effects of the two major influencers, level of solar activity and the atmospheric transparency. Be sure to consider and allow for appropriate time lag in the response of the temperature to changes in the influencers. " ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "%plot inline -w 900 -h 300" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "shifts =\r\n", "\r\n", " 12 54 35 1 18 2\r\n", "\r\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "### optimal values of time shifts\n", "[Rmax, i0] = max(abs([R_ls R_mt R_lt]));\n", "[RRmax, i1] = max(abs([RR_ls RR_mt RR_lt]));\n", "shifts = - [ [lag_ls lag_mt lag_lt](i0) [llag_ls llag_mt llag_lt](i1) ]\n", "\n", "hold on;\n", "\n", "ind = ~isnan(df.MLOtransparency);\n", "\n", "x1 = fracshift(df.SunSpotCount,shifts(1));\n", "x2 = fracshift(df.MLOtransparency,shifts(4));\n", "X = [ones(size(df1.Year)) x1(ind) x2(ind) ];\n", "b = regress(df1.T_lowstrato,X);\n", "YY = df1.T_lowstrato - X*b;\n", "plot(df1.Year,YY,'c-;lower stratosphere;');\n", "\n", "x1 = fracshift(df.SunSpotCount,shifts(2));\n", "x2 = fracshift(df.MLOtransparency,shifts(5));\n", "X = [ones(size(df1.Year)) x1(ind) x2(ind) ];\n", "b = regress(df1.T_midtropo(ind),X);\n", "YY = df1.T_midtropo - X*b;\n", "plot(df1.Year,YY,'g-;mid-troposphere;');\n", "\n", "x1 = fracshift(df.SunSpotCount,shifts(3));\n", "x2 = fracshift(df.MLOtransparency,shifts(6));\n", "X = [ones(size(df1.Year)) x1(ind) x2(ind) ];\n", "b = regress(df1.T_lowtropo,X);\n", "YY = df1.T_lowtropo - X*b;\n", "plot(df1.Year,YY,'r-;lower troposphere;');\n", "xlim([1977,2024]);\n", "box on;\n", "grid on;\n", "\n", "hold off;" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Follow-up questions\n", "\n", "Evaluate the long-term trends (slope, in $^\\circ$C/decade) in the three observed atmospheric zones. Use appropriate statistical methods to evaluate the 95% significance interval ($p<0.05$ for the null hypothesis) for the result. Does this interval include zero? What does this mean?\n", "

\n", "Note the sign of the slope in the linear regression of the atmospheric transparency. What does this imply in terms of the planetary radiative energy balance for Earth?\n", "

\n", "Note the size of the regression estimates for the three atmosphetic zones, and compare the strengths of our influencers on the temperature in the three zones. Discuss." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "hide_input": false, "kernelspec": { "display_name": "Octave", "language": "octave", "name": "octave" }, "language_info": { "file_extension": ".m", "help_links": [ { "text": "GNU Octave", "url": "https://www.gnu.org/software/octave/support.html" }, { "text": "Octave Kernel", "url": "https://github.com/Calysto/octave_kernel" }, { "text": "MetaKernel Magics", "url": "https://metakernel.readthedocs.io/en/latest/source/README.html" } ], "mimetype": "text/x-octave", "name": "octave", "version": "4.2.2" }, "toc": { "nav_menu": {}, "number_sections": false, "sideBar": true, "skip_h1_title": false, "toc_cell": false, "toc_position": {}, "toc_section_display": "none", "toc_window_display": false } }, "nbformat": 4, "nbformat_minor": 2 }