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  1. {
  2.  "cells": [
  3.   {
  4.    "cell_type": "code",
  5.    "execution_count": 1,
  6.    "metadata": {
  7.     "collapsed": true
  8.    },
  9.    "outputs": [],
  10.    "source": [
  11.     "import xarray as xr\n",
  12.     "import numpy as np\n",
  13.     "import matplotlib.pyplot as plt"
  14.    ]
  15.   },
  16.   {
  17.    "cell_type": "code",
  18.    "execution_count": 2,
  19.    "metadata": {
  20.     "collapsed": true
  21.    },
  22.    "outputs": [],
  23.    "source": [
  24.     "# Load model output of sea surface temperature (SST) from netCDF files\n",
  25.     "datapath = '/mnt/disk2/data/CM4_historical/'\n",
  26.     "data  = xr.open_dataset(datapath + 'ocean_monthly_1x1deg.201001-201412.tos.nc')\n",
  27.     "grid = xr.open_dataset(datapath + 'ocean_monthly_1x1deg.static.nc')\n",
  28.     "tos = data.tos.load()"
  29.    ]
  30.   },
  31.   {
  32.    "cell_type": "code",
  33.    "execution_count": 4,
  34.    "metadata": {
  35.     "collapsed": true
  36.    },
  37.    "outputs": [],
  38.    "source": [
  39.     "# Calculate monthly averages\n",
  40.     "monthly_average = np.zeros((12,nlat,nlon))\n",
  41.     "nyears = ntime/12.\n",
  42.     "for jtime in range(0,ntime):\n",
  43.     "    current_month = np.mod(jtime,12) # Keep track of which month we're in\n",
  44.     "    monthly_average[current_month,:,:] = tos[jtime,:,:] + monthly_average[current_month,:,:]\n",
  45.     "monthly_average[:,:,:] = monthly_average[:,:,:]/nyears"
  46.    ]
  47.   },
  48.   {
  49.    "cell_type": "code",
  50.    "execution_count": 5,
  51.    "metadata": {
  52.     "collapsed": true
  53.    },
  54.    "outputs": [],
  55.    "source": [
  56.     "# Calculate monthly anomalies by subtracting the monthly climatology\n",
  57.     "tos_anomaly = np.zeros((ntime,nlat,nlon))\n",
  58.     "for jtime in range(0,ntime):\n",
  59.     "    current_month = np.mod(jtime,12) # Keep track of which month we're in\n",
  60.     "    tos_anomaly[jtime,:,:] = tos[jtime,:,:] - monthly_average[current_month,:,:]"
  61.    ]
  62.   },
  63.   {
  64.    "cell_type": "code",
  65.    "execution_count": 28,
  66.    "metadata": {},
  67.    "outputs": [
  68.     {
  69.      "name": "stdout",
  70.      "output_type": "stream",
  71.      "text": [
  72.       "0\n",
  73.       "10\n",
  74.       "20\n",
  75.       "30\n",
  76.       "40\n",
  77.       "50\n",
  78.       "60\n",
  79.       "70\n",
  80.       "80\n",
  81.       "90\n",
  82.       "100\n",
  83.       "110\n",
  84.       "120\n",
  85.       "130\n",
  86.       "140\n",
  87.       "150\n",
  88.       "160\n",
  89.       "170\n"
  90.      ]
  91.     }
  92.    ],
  93.    "source": [
  94.     "# Calculate the El-Nino Southern Oscillation (ENSO) Index from the Nino 3.4 region\n",
  95.     "nino_minlat = -5  ; nino_maxlat = 5\n",
  96.     "nino_minlon = -170 ; nino_maxlon = -120\n",
  97.     "nino_index = np.zeros((ntime,1))\n",
  98.     "pt_counter = 0\n",
  99.     "for jlat in range(0,nlat):\n",
  100.     "    if (np.mod(jlat,10)==0):\n",
  101.     "        print(jlat)\n",
  102.     "    for jlon in range(0,nlon):\n",
  103.     "        inregion = ( (grid.geolat[jlat,jlon] >= nino_minlat and grid.geolat[jlat,jlon] <= nino_maxlat) and \n",
  104.     "                     (grid.geolon[jlat,jlon] >= nino_minlon and grid.geolon[jlat,jlon] <= nino_maxlon) )\n",
  105.     "        if (inregion):  \n",
  106.     "            pt_counter = pt_counter + 1\n",
  107.     "            for jtime in range(0,ntime):\n",
  108.     "                nino_index[jtime] = nino_index[jtime] + tos_anomaly[jtime,jlat,jlon]\n",
  109.     "nino_index[:] = nino_index[:] / pt_counter"
  110.    ]
  111.   },
  112.   {
  113.    "cell_type": "code",
  114.    "execution_count": 24,
  115.    "metadata": {},
  116.    "outputs": [],
  117.    "source": [
  118.     "# Calculate the covariance between the ENSO index and sea surface temperatures\n",
  119.     "nino_sst_covariance = np.zeros((nlat,nlon))\n",
  120.     "for jtime in range(0,ntime):\n",
  121.     "    for jlat in range(0,nlat):\n",
  122.     "        for jlon in range(0,nlon):\n",
  123.     "            nino_sst_covariance[jlat,jlon] = (nino_sst_covariance[jlat,jlon] + \n",
  124.     "                                              tos_anomaly[jtime,jlat,jlon]*nino_index[jtime])\n",
  125.     "nino_sst_covariance = nino_sst_covariance/(ntime - 1)\n",
  126.     "            "
  127.    ]
  128.   },
  129.   {
  130.    "cell_type": "code",
  131.    "execution_count": 38,
  132.    "metadata": {},
  133.    "outputs": [
  134.     {
  135.      "data": {
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0XYU8pza//qkVbn/PGgwhTQMsRepaGNcl/+LLX8PHP/8VLI+mJBUe21xhfTyk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phOmh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\nZqS22p+nRURQhqVhg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2Z8mRKWf5s36emrqr+ln5PItwDf+GaGG9655/2DwPcC5/77s8A9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\noKrbQMJ8AAAAAElFTkSuQmCC\n",
  137.       "text/plain": [
  138.        "<matplotlib.figure.Figure at 0x7f8f1d65fcf8>"
  139.       ]
  140.      },
  141.      "metadata": {},
  142.      "output_type": "display_data"
  143.     }
  144.    ],
  145.    "source": [
  146.     "plt.pcolormesh(nino_sst_covariance); plt.colorbar(); plt.show()"
  147.    ]
  148.   },
  149.   {
  150.    "cell_type": "code",
  151.    "execution_count": null,
  152.    "metadata": {
  153.     "collapsed": true
  154.    },
  155.    "outputs": [],
  156.    "source": []
  157.   }
  158.  ],
  159.  "metadata": {
  160.   "kernelspec": {
  161.    "display_name": "Python 3",
  162.    "language": "python",
  163.    "name": "python3"
  164.   },
  165.   "language_info": {
  166.    "codemirror_mode": {
  167.     "name": "ipython",
  168.     "version": 3
  169.    },
  170.    "file_extension": ".py",
  171.    "mimetype": "text/x-python",
  172.    "name": "python",
  173.    "nbconvert_exporter": "python",
  174.    "pygments_lexer": "ipython3",
  175.    "version": "3.6.0"
  176.   }
  177.  },
  178.  "nbformat": 4,
  179.  "nbformat_minor": 2
  180. }
RAW Paste Data
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