{ "metadata": { "name": "Scientific American graph" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "Warming of the oceans\n", "=====================\n", "\n", "Roberto De Almeida [rob@marinexplore.com](mailto:rob@marinexplore.com)\n", "\n", "This notebook was used to generate the graph for the article [Warming Ocean Threatens Sea Life](http://www.scientificamerican.com/article.cfm?id=warming-ocean-threatens-sea-life), using data from the [ICOADS](http://icoads.noaa.gov/) program. Data used for the plots was downloaded from the [Earth System Research Laboratory](http://www.esrl.noaa.gov/psd/cgi-bin/db_search/DBSearch.pl?Dataset=ICOADS+2-degree+Standard&Dataset=ICOADS+2-degree+Enhanced&Variable=Sea+Surface+Temperature) at NOAA using the `wget` Linux utility:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "%%bash\n", "\n", "if [ ! -f sst.mean.nc ]; then\n", " wget ftp://ftp.cdc.noaa.gov/Datasets/coads/2degree/enh/sst.mean.nc 2>/dev/null\n", "fi\n", "\n", "if [ ! -f sst.stddev.nc ]; then\n", " wget ftp://ftp.cdc.noaa.gov/Datasets/coads/2degree/enh/sst.stddev.nc 2>/dev/null\n", "fi" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 1 }, { "cell_type": "markdown", "metadata": {}, "source": [ "We now use the [Ferret](http://ferret.pmel.noaa.gov/Ferret/) application to:\n", " \n", "1. calculate the (monthly) seasonal cycle\n", "2. remove it from the original time series\n", "3. average over the whole globe\n", "4. smooth with a 13-point box moving average\n", "\n", "One important detail about the Ferret averaging is that it is automatically based by area. This is important because the grid cells in the Tropics are larger than the grid cells close to the poles. Simply averaging by number would result in values that are below the true average.\n", "\n", "Here we perform steps 1-2, calculating the anomalies from the seasonal cycle:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "%%bash\n", "\n", "ferret << EOF\n", "\n", "USE \"sst.mean.nc\"\n", "\n", "! here we limit the period to 1900-01-01 to 2012-12-31, same as the one \n", "! used for the Scientific American article\n", "LET sst_interest = sst[d=1,t=1-jan-1900:31-dec-2012]\n", "\n", "! create seasonal cycle\n", "USE climatological_axes\n", "CANCEL DATA climatological_axes\n", "LET sstc = sst_interest[Gt=month_reg@mod]\n", "\n", "! calculate anomalies from the climatology\n", "LET ssta = sst[d=1] - sstc[gt=sst[d=1]@asn]\n", "\n", "set memory/size=1000\n", "save/file=ssta.mean.nc/clobber ssta\n", "\n", "quit\n", "EOF" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "yes? \n", "yes? USE \"sst.mean.nc\"\n", "yes? \n", "yes? ! here we limit the period to 1900-01-01 to 2012-12-31, same as the one \n", "yes? ! used for the Scientific American article\n", "yes? LET sst_interest = sst[d=1,t=1-jan-1900:31-dec-2012]\n", "yes? \n", "yes? ! create seasonal cycle\n", "yes? USE climatological_axes\n", "yes? CANCEL DATA climatological_axes\n", "yes? LET sstc = sst_interest[Gt=month_reg@mod]\n", "yes? \n", "yes? ! calculate anomalies from the climatology\n", "yes? LET ssta = sst[d=1] - sstc[gt=sst[d=1]@asn]\n", "yes? \n", "yes? set memory/size=1000\n", "yes? save/file=ssta.mean.nc/clobber ssta\n", "yes? \n", "yes? quit\n", " \tNOAA/PMEL TMAP\n", " \tFERRET v6.82 \n", " \tLinux 2.6.32-279.1.1.el6.x86_64 64-bit - 08/03/12\n", " \t24-Mar-13 20:57 \n", "\n" ] }, { "output_type": "stream", "stream": "stderr", "text": [ " *** NOTE: regarding /usr/local/ferret/go/climatological_axes.cdf ...\n", " *** NOTE: Climatological axes SEASONAL_REG, MONTH_REG, MONTH_IRREG, MONTH_GREGORIAN, MONTH_NOLEAP, MONTH_360_DAY, MONTH_ALL_LEAP defined\n", " Cached data cleared from memory\n", " LISTing to file ssta.mean.nc\n" ] } ], "prompt_number": 2 }, { "cell_type": "markdown", "metadata": {}, "source": [ "And now steps 3-4, averaging over the globe and smoothing the resulting time series with the 13-point box:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "%%bash\n", "\n", "ferret << EOF\n", "\n", "use \"ssta.mean.nc\"\n", "use \"sst.stddev.nc\"\n", "\n", "! average over x/y, and apply 13-point box moving average\n", "LET mean = ssta[d=1,x=@ave,y=@ave,t=1-jan-1900:31-dec-2012@sbx:13]\n", "LET std_dev = sst[d=2,x=@ave,y=@ave,t=1-jan-1900:31-dec-2012@sbx:13]\n", "\n", "save/file=global.nc/clobber mean, std_dev\n", "\n", "quit\n", "EOF" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "yes? \n", "yes? use \"ssta.mean.nc\"\n", "yes? use \"sst.stddev.nc\"\n", "yes? \n", "yes? ! average over x/y, and apply 13-point box moving average\n", "yes? LET mean = ssta[d=1,x=@ave,y=@ave,t=1-jan-1900:31-dec-2012@sbx:13]\n", "yes? LET std_dev = sst[d=2,x=@ave,y=@ave,t=1-jan-1900:31-dec-2012@sbx:13]\n", "yes? \n", "yes? save/file=global.nc/clobber mean, std_dev\n", "yes? \n", "yes? quit\n", " \tNOAA/PMEL TMAP\n", " \tFERRET v6.82 \n", " \tLinux 2.6.32-279.1.1.el6.x86_64 64-bit - 08/03/12\n", " \t24-Mar-13 20:57 \n", "\n" ] }, { "output_type": "stream", "stream": "stderr", "text": [ " LISTing to file global.nc\n" ] } ], "prompt_number": 3 }, { "cell_type": "markdown", "metadata": {}, "source": [ "We now repeat the process for the Atlantic and Pacific basins separately. The Ferret mailing list has [an example](http://www.pmel.noaa.gov/maillists/tmap/ferret_users/fu_2004/msg00323.html) of how to do that. We need a file which identifies the ocean basins." ] }, { "cell_type": "code", "collapsed": false, "input": [ "%%bash\n", "\n", "ferret << EOF\n", "\n", "use \"ssta.mean.nc\"\n", "use \"sst.stddev.nc\"\n", "\n", "! file contaning the different ocean basins; we need to regrid it to\n", "! the same grid as the SST\n", "USE \"http://dods.ipsl.jussieu.fr/cgi-bin/nph-dods/ocmip/grids/LEV_grid.nc\"\n", "USE \"http://dods.ipsl.jussieu.fr/cgi-bin/nph-dods/ocmip/specials/LEV_Basins.nc\"\n", "LET lev_basin = reshape(basin[d=LEV_Basins.nc],area[d=LEV_grid.nc])\n", "LET sst_basin = lev_basin[Gxy=ssta[d=1]]\n", "\n", "LET atl_ssta = if sst_basin eq 0 then ssta[d=1]\n", "LET atl_mean = atl_ssta[x=@ave,y=@ave,t=1-jan-1900:31-dec-2012@sbx:13]\n", "LET atl_sd = if sst_basin eq 0 then sst[d=2]\n", "LET atl_std_dev = atl_sd[x=@ave,y=@ave,t=1-jan-1900:31-dec-2012@sbx:13]\n", "\n", "LET pac_ssta = if sst_basin eq 1 then ssta[d=1]\n", "LET pac_mean = pac_ssta[x=@ave,y=@ave,t=1-jan-1900:31-dec-2012@sbx:13]\n", "LET pac_sd = if sst_basin eq 1 then sst[d=2]\n", "LET pac_std_dev = pac_sd[x=@ave,y=@ave,t=1-jan-1900:31-dec-2012@sbx:13]\n", "\n", "save/file=atlantic.nc/clobber atl_mean, atl_std_dev\n", "save/file=pacific.nc/clobber pac_mean, pac_std_dev\n", "\n", "quit\n", "EOF" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "yes? \n", "yes? use \"ssta.mean.nc\"\n", "yes? use \"sst.stddev.nc\"\n", "yes? \n", "yes? ! file contaning the different ocean basins; we need to regrid it to\n", "yes? ! the same grid as the SST\n", "yes? USE \"http://dods.ipsl.jussieu.fr/cgi-bin/nph-dods/ocmip/grids/LEV_grid.nc\"\n", "yes? USE \"http://dods.ipsl.jussieu.fr/cgi-bin/nph-dods/ocmip/specials/LEV_Basins.nc\"\n", "yes? LET lev_basin = reshape(basin[d=LEV_Basins.nc],area[d=LEV_grid.nc])\n", "yes? LET sst_basin = lev_basin[Gxy=ssta[d=1]]\n", "yes? \n", "yes? LET atl_ssta = if sst_basin eq 0 then ssta[d=1]\n", "yes? LET atl_mean = atl_ssta[x=@ave,y=@ave,t=1-jan-1900:31-dec-2012@sbx:13]\n", "yes? LET atl_sd = if sst_basin eq 0 then sst[d=2]\n", "yes? LET atl_std_dev = atl_sd[x=@ave,y=@ave,t=1-jan-1900:31-dec-2012@sbx:13]\n", "yes? \n", "yes? LET pac_ssta = if sst_basin eq 1 then ssta[d=1]\n", "yes? LET pac_mean = pac_ssta[x=@ave,y=@ave,t=1-jan-1900:31-dec-2012@sbx:13]\n", "yes? LET pac_sd = if sst_basin eq 1 then sst[d=2]\n", "yes? LET pac_std_dev = pac_sd[x=@ave,y=@ave,t=1-jan-1900:31-dec-2012@sbx:13]\n", "yes? \n", "yes? save/file=atlantic.nc/clobber atl_mean, atl_std_dev\n", "yes? save/file=pacific.nc/clobber pac_mean, pac_std_dev\n", "yes? \n", "yes? quit\n", " \tNOAA/PMEL TMAP\n", " \tFERRET v6.82 \n", " \tLinux 2.6.32-279.1.1.el6.x86_64 64-bit - 08/03/12\n", " \t24-Mar-13 20:57 \n", "\n" ] }, { "output_type": "stream", "stream": "stderr", "text": [ " *** NOTE: unsupported ordering of axes in variable BOUNDS_LON\n", " *** NOTE: The default ordering will be used\n", " *** NOTE: unsupported ordering of axes in variable BOUNDS_LAT\n", " *** NOTE: The default ordering will be used\n", " LISTing to file atlantic.nc\n", " LISTing to file pacific.nc\n" ] } ], "prompt_number": 4 }, { "cell_type": "markdown", "metadata": {}, "source": [ "For making the graph, Python was used. In addition to the standard library, the script depends on [Numpy](http://www.numpy.org/) (a numerical library for Python), [pupynere](https://pypi.python.org/pypi/pupynere) (a library for reading/writing NetCDF files in Python), and [coards](http://pypi.python.org/pypi/coards) (for parsing dates from the NetCDF file)." ] }, { "cell_type": "code", "collapsed": false, "input": [ "from pupynere import netcdf_file\n", "import coards\n", "import numpy as np" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 5 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Using pupynere we load the data from the NetCDF files created using Ferret:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "f1 = netcdf_file(\"global.nc\", maskandscale=True)\n", "f2 = netcdf_file(\"atlantic.nc\", maskandscale=True)\n", "f3 = netcdf_file(\"pacific.nc\", maskandscale=True)\n", "\n", "# convert time to pylab internal units\n", "time = date2num([coards.parse(v, f1.variables['TIME'].units) for v in f1.variables['TIME']])\n", "\n", "mean = f1.variables['MEAN'][:]\n", "std = f1.variables['STD_DEV'][:]\n", "atl_mean = f2.variables['ATL_MEAN'][:]\n", "atl_std = f2.variables['ATL_STD_DEV'][:]\n", "pac_mean = f3.variables['PAC_MEAN'][:]\n", "pac_std = f3.variables['PAC_STD_DEV'][:]" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 6 }, { "cell_type": "markdown", "metadata": {}, "source": [ "This is a list of El Ni\u00f1o and La Ni\u00f1a events, as well as the date where human population reached 2 to 7 billion:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "elnino = [2009, 2006, 2004, 2002, 1997, 1994, 1993, 1992, 1991, 1987, 1982, 1977, 1972, 1969, 1965, 1963, 1957, 1953, 1951, 1946, 1941, 1940, 1932, 1925, 1923, 1919, 1918, 1914, 1913, 1911, 1905, 1902, 1896][:-1]\n", "lanina = [2008, 2007, 2000, 1998, 1996, 1988, 1975, 1974, 1973, 1971, 1970, 1964, 1956, 1955, 1950, 1947, 1938, 1924, 1921, 1917, 1916, 1910, 1909, 1908, 1906, 1893, 1892][:-2]\n", "population = {2: 1927, 3: 1960, 4: 1974, 5: 1987, 6: 1999, 7:2011} " ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 7 }, { "cell_type": "markdown", "metadata": {}, "source": [ "And this is the plot of the data:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "fig = figure(figsize=(15, 5))\n", "\n", "ax = fig.gca()\n", "title('Global, Atlantic and Pacific sea surface temperature from 1900 to present')\n", "\n", "ax.fill_between(time, mean-std, mean+std, color='k', alpha=0.05)\n", "ax.plot_date(time, atl_mean, 'b-', linewidth=1)\n", "ax.plot_date(time, pac_mean, 'r-', linewidth=1)\n", "ax.plot_date(time, mean, 'w-', linewidth=4)\n", "ax.plot_date(time, mean, 'k-', linewidth=2)\n", "ax.plot_date(time, mean+std, 'w-', linewidth=1)\n", "ax.plot_date(time, mean-std, 'w-', linewidth=1)\n", "ax.set_ylabel(u'\u00b0C')\n", "\n", "handles = [\n", " Rectangle((0, 0), 1, 1, fc=\"k\", ec='k', linewidth=2),\n", " Rectangle((0, 0), 1, 1, fc=\"b\", ec='b', linewidth=1),\n", " Rectangle((0, 0), 1, 1, fc=\"r\", ec='r', linewidth=1)]\n", "labels = [\"Global\", \"Atlantic\", \"Pacific\"]\n", "legend1 = legend(handles, labels, loc=2, prop={'size':9})\n", "\n", "# WW1\n", "x = date2num([datetime.datetime(1914, 7, 28), datetime.datetime(1918, 11, 11)])\n", "y = [-1.5, 1.5]\n", "ax.fill([x[0], x[1], x[1], x[0]], [y[0], y[0], y[1], y[1]], color='k', alpha=0.1, linewidth=0)\n", "ax.text(0.5*(x[0]+x[1]), 1.3, 'WWI', horizontalalignment='center', verticalalignment='center')\n", "\n", "# WW2\n", "x = date2num([datetime.datetime(1939, 9, 1), datetime.datetime(1945, 5, 8)])\n", "y = [-1.5, 1.5]\n", "ax.fill([x[0], x[1], x[1], x[0]], [y[0], y[0], y[1], y[1]], color='k', alpha=0.1, linewidth=0)\n", "ax.text(0.5*(x[0]+x[1]), 1.3, 'WWII', horizontalalignment='center', verticalalignment='center')\n", "\n", "handles = []\n", "labels = []\n", "\n", "# El Ninos\n", "for year in elnino:\n", " x = date2num(datetime.datetime(year, 12, 31))\n", " ax.fill([x, x], y, color='r', alpha=0.1, linewidth=2)\n", "handles.append(Rectangle((0, 0), 1, 1, fc=\"r\", alpha=0.1, linewidth=0))\n", "labels.append('El Nino event')\n", "\n", "# La Ninas\n", "for year in lanina:\n", " x = date2num(datetime.datetime(year, 12, 31))\n", " ax.fill([x, x], y, color='b', alpha=0.1, linewidth=2)\n", "handles.append(Rectangle((0, 0), 1, 1, fc=\"b\", alpha=0.1, linewidth=0))\n", "labels.append('La Nina event')\n", "\n", "# population\n", "for billions, year in population.items():\n", " x = date2num(datetime.datetime(year, 6, 1))\n", " ax.fill([x, x], y, color='#00aa00', alpha=0.1, linewidth=2)\n", " ax.text(x, 1.3, '%dB' % billions, horizontalalignment='center', verticalalignment='center', color='#00aa00', alpha=0.9)\n", "handles.append(Rectangle((0, 0), 1, 1, fc=\"#00aa00\", alpha=0.1, linewidth=0))\n", "labels.append('Population')\n", "\n", "# Pinatubo 15-06-91\n", "x = date2num(datetime.datetime(1991, 6, 15))\n", "ax.fill([x, x], y, color='k', alpha=0.5, linewidth=2)\n", "handles.append(Rectangle((0, 0), 1, 1, fc=\"k\", alpha=0.5, linewidth=0))\n", "labels.append('Volcanic eruption')\n", "\n", "# Katmai-Novarupta 07-06-1912\n", "x = date2num(datetime.datetime(1912, 6, 7))\n", "ax.fill([x, x], y, color='k', alpha=0.5, linewidth=2)\n", "\n", "legend(handles, labels, loc=4, prop={'size':9})\n", "ax.add_artist(legend1)\n", "\n", "axis((693598.0, 734596.0, -1.5, 1.5))\n", "\n", "fig.savefig('fig1a.png')\n", "fig.savefig('fig1a.pdf')" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "display_data", "png": "iVBORw0KGgoAAAANSUhEUgAAA3oAAAFACAYAAADqLQ6aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRK5CYII=\n", "text": [ "" ] } ], "prompt_number": 8 }, { "cell_type": "code", "collapsed": false, "input": [], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 8 } ], "metadata": {} } ] }