ACCESS-OM2_OceanHeat_Make_Scaling.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Very simple testing script for \"temporal\" based perturbations on the experiment calendar.\n",
    "\n",
    "The perturbations are done using the libaccessom2 perturbations code, see the tutorial here https://github.com/COSIMA/access-om2/wiki/Tutorials#Scaling-the-forcing-fields"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import cosima_cookbook as cc\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import netCDF4 as nc\n",
    "import xarray as xr\n",
    "import cmocean as cm\n",
    "from collections import OrderedDict\n",
    "import cftime\n",
    "import glob\n",
    "import copy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define inputs and output folders:\n",
    "JRAin = '/g/data/ik11/inputs/JRA-55/RYF/v1-4/' # Location of RYF JRA55-do input forcing files\n",
    "SRin = JRAin + 'RYF.rsds.1990_1991.nc' # shortwave radiation forcing file\n",
    "\n",
    "JRAout = '/scratch/e14/rmh561/access-om2/input/JRA55-do/perts/' # Output location for storing scaling files created by this script\n",
    "SRout = JRAout + 'RYF.rsds.1990_1991_1yrstep.nc' # Longwave radiation scaling file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define start and end times (based on \"experiment\" calendar, see https://github.com/COSIMA/access-om2/wiki/Tutorials#Scaling-the-forcing-fields)\n",
    "tstart = 1900 # start year of window in which scaling will be applied (1900 = initial time of control simulation)\n",
    "tend = 1910 # end year of window in which scaling will be applied\n",
    "\n",
    "seconds_in_year = (cftime.DatetimeNoLeap(1901,1,1,0,0,0,0) - cftime.DatetimeNoLeap(1900,1,1,0,0,0,0)).total_seconds()\n",
    "\n",
    "# Define sinusoid properties:\n",
    "SRamp = 20   # Wm-2\n",
    "period = 2 # years\n",
    "zeroYR = 0  # years\n",
    "\n",
    "# Extract time series and structure from original files:\n",
    "SRds_in = xr.open_dataset(SRin)\n",
    "\n",
    "timeRYF = SRds_in.time.values\n",
    "timeFULL = np.concatenate(np.array([np.array([cftime.DatetimeNoLeap(year,x.month,x.day,x.hour,0,0,0) for x in timeRYF]) for year in np.arange(tstart,tend+1)])).ravel()\n",
    "timeYR = np.array([(x-cftime.DatetimeNoLeap(1900,1,1,0,0,0,0)).total_seconds()/seconds_in_year for x in timeFULL])\n",
    "\n",
    "# Make a square wave:\n",
    "rsds_ts = SRamp*np.sign(np.sin(2*np.pi*(timeYR-zeroYR)/period))\n",
    "\n",
    "# Create new Dataset:\n",
    "rsds = xr.DataArray(rsds_ts, dims=['time'], coords={'time': timeFULL}, attrs=SRds_in.rsds.attrs)\n",
    "SRds_out = SRds_in.drop_vars('rsds').assign_coords({'time':timeFULL})\n",
    "SRds_out['rsds'] = rsds\n",
    "SRds_out.attrs.update({'title': 'Scaling for ' + SRds_out.attrs['title']})\n",
    "\n",
    "# Plot as check:\n",
    "SRds_out.rsds.plot()\n",
    "\n",
    "# Convert time back to days since 1900-1-1 (this is clunky... I'm sure there's a better way):\n",
    "SRds_out = SRds_out.assign_coords({'time':timeYR*seconds_in_year/86400})\n",
    "attrsdic = {\n",
    "    '_FillValue':      -9.99e+34,\n",
    "    'units':          \"days since 1900-01-01\",\n",
    "    'cartesian_axis': \"T\",\n",
    "    'modulo': \" \",\n",
    "    'calendar':       \"noleap\"}\n",
    "SRds_out.time.attrs = attrsdic\n",
    "\n",
    "# Save back to netcdf:\n",
    "SRds_out.to_netcdf(SRout)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Forcing file perturbation transitions\n",
      "[cftime.DatetimeNoLeap(1900, 1, 1, 3, 0, 0, 0)\n",
      " cftime.DatetimeNoLeap(1901, 1, 1, 3, 0, 0, 0)\n",
      " cftime.DatetimeNoLeap(1902, 1, 1, 3, 0, 0, 0)\n",
      " cftime.DatetimeNoLeap(1903, 1, 1, 3, 0, 0, 0)\n",
      " cftime.DatetimeNoLeap(1904, 1, 1, 3, 0, 0, 0)\n",
      " cftime.DatetimeNoLeap(1905, 1, 1, 3, 0, 0, 0)\n",
      " cftime.DatetimeNoLeap(1906, 1, 1, 3, 0, 0, 0)\n",
      " cftime.DatetimeNoLeap(1907, 1, 1, 3, 0, 0, 0)\n",
      " cftime.DatetimeNoLeap(1908, 1, 1, 3, 0, 0, 0)\n",
      " cftime.DatetimeNoLeap(1909, 1, 1, 3, 0, 0, 0)\n",
      " cftime.DatetimeNoLeap(1910, 1, 1, 3, 0, 0, 0)]\n",
      "Output file perturbation transitions\n",
      "[[cftime.DatetimeNoLeap(1901, 1, 2, 0, 0, 0, 0)]\n",
      " [cftime.DatetimeNoLeap(1902, 1, 2, 0, 0, 0, 0)]\n",
      " [cftime.DatetimeNoLeap(1903, 1, 2, 0, 0, 0, 0)]\n",
      " [cftime.DatetimeNoLeap(1904, 1, 2, 0, 0, 0, 0)]\n",
      " [cftime.DatetimeNoLeap(1905, 1, 1, 0, 0, 0, 0)]\n",
      " [cftime.DatetimeNoLeap(1906, 1, 1, 0, 0, 0, 0)]\n",
      " [cftime.DatetimeNoLeap(1907, 1, 1, 0, 0, 0, 0)]\n",
      " [cftime.DatetimeNoLeap(1908, 1, 1, 0, 0, 0, 0)]\n",
      " [cftime.DatetimeNoLeap(1908, 12, 31, 0, 0, 0, 0)]\n",
      " [cftime.DatetimeNoLeap(1909, 12, 31, 0, 0, 0, 0)]]\n",
      "Losing a day in 1904 and 1908 - the leap years.\n"
     ]
    },
    {
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      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Testing of correspondence between forcing transition times (from +20 to -20) and otput transition times\n",
    "\n",
    "plt.figure(figsize=(20,10))\n",
    "# Extract transitions from forcing file:\n",
    "forc = xr.open_dataset(SRout)\n",
    "rsds_forc = forc.rsds.diff('time')\n",
    "rsds_forc.plot()\n",
    "rsds_forc_trans = rsds_forc.time.where(abs(rsds_forc)>5.).dropna('time')\n",
    "\n",
    "# Extract transitions from output file:\n",
    "out = xr.open_mfdataset('/scratch/e14/rmh561/access-om2/archive/1deg_jra55_ryf_wcwc_step_test1/output0**/ocean/ocean-scalar*.nc')\n",
    "rsds_out = out.total_ocean_swflx.diff('time')\n",
    "rsds_out.plot()\n",
    "rsds_out_trans = rsds_out.time.where(abs(rsds_out)>5.).dropna('time')\n",
    "\n",
    "print('Forcing file perturbation transitions')\n",
    "print(rsds_forc_trans.values)\n",
    "print('Output file perturbation transitions')\n",
    "print(rsds_out_trans.values)\n",
    "print('Losing a day in 1904 and 1908 - the leap years.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x14e40b7138b0>]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ERKQEEx8iIiKyGUx8iEhnvGUFEVkqJj5EpDPesoKILBUTH7JObJAgIiIlmPgQERGRzWDiQ9aJPTFERKQEEx8iIiKyGUx8iIiIyGYw8SHrxOJmIiJSgokPERER2QwmPmSdWNxMRERKMPEhIiIim8HEh4iIiGwGEx+yTixuJiIiJZj4EBERkc1g4kNEREQ2g4kPWSeO6iIiIiWY+BAREZHNYOJDRERENoOJD1knjuoiIiIlmPgQERGRzWDiQ0RERDaDiQ9ZJ47qIiIiJZj4EJHOBCaWRGShmPiQdWJxMxERKcHEh4h0JmJiSUQWiokPERER2QwmPmSdWINCRERKMPEhIiIim8HEh6wTa1DKFUd1EZGlYuJDRERENoOJDxHpjKO6iMhSMfEhIiIim8HEh6wTa1CIiEgJJj5EpDMWNxORpWLiQ9aJNShERKQEEx8iIiKyGUx8iEhnHNVFRJaKiQ8RERHZDCY+RKQzFjcTkaVi4kNEREQ2g4kPERER2QyrSnyio6MhEonkfgIDA00dFpHVYXEzEVkqB1MHYGivvPIK9u/fL/3d3t7ehNEQERGRObG6xMfBwYGtPERERKSUVXV1AcDNmzcRFBSEqlWrYsiQIbhz547a5XNzc5GZmSn3Q0TqcVQXEVkqq0p8IiMj8eOPP2LPnj1YvXo1UlJSEBUVhdTUVJXrLFy4EF5eXtKf4OBgI0ZMRERExmRViU+PHj3w2muvoUGDBujcuTN27twJANiwYYPKdaZNm4aMjAzpT2JiorHCJSIiIiOzuhofWW5ubmjQoAFu3rypchmxWAyxWGzEqIgsH0d1EZGlsqoWH0W5ubm4evUqKlWqZOpQiIiIyAxYVeIzefJkHD58GHfv3kVMTAwGDhyIzMxMvPXWW6YOjciqsLiZiCyVVXV1JSUlYejQoXjy5An8/f3RokULnDp1CqGhoaYOjYiIiMyAVSU+mzZtMnUIREREZMasqquLiIiISB0mPkSkM47qIiJLxcSHiHTG4mYislRMfIiIiMhmMPEhIiIim8HEh4iIiGwGEx8iIiKyGUx8iEhnHNVFRJaKiQ8R6YyjuozjRb4E7248i81nEk0dCpHVMHjiI/CISERkEBtP3sOeyw8xZcu/pg6FyGrolfgMHz4c2dnZpR6Pj49H27ZtyxwUEREB6c/zTB0CkdXRK/G5cuUKGjRogOPHj0sf27BhAxo1aoSAgACDBUdEZMtEYDEVkaHpdZPSmJgYzJgxAx07dsSkSZNw8+ZN7N69GytWrMDbb79t6BiJiIiIDEKvxMfBwQGff/45xGIx5s2bBwcHBxw+fBgtW7Y0dHxEREREBqNXV1d+fj4mTZqEL774AtOmTUPLli3Rv39/7Nq1y9DxERHZLE4bQGR4erX4RERE4NmzZzh06BBatGgBQRCwaNEiDBgwAG+//Ta+/fZbQ8dJREREVGZ6tfhEREQgLi4OLVq0AACIRCJ8+umnOHXqFI4cOWLQAImIiIgMRa8Wn7Vr1yp9PDw8HOfOnStTQERERETlRevEJzMzU+uNisVivYIhIqISLPEhMjytEx9vb2+INFTaCYIAkUgEiURS5sCIyoInDCIiUkbrxOfgwYPlGQeRQfHGKWQVOKyLyOC0TnxWrFiB9evXw9PTEz/++CMGDx7MLi0iIiKyKFqP6tqxYwdycnIAAKNGjUJGRka5BUVERERUHrRu8alTpw6mTZuGDh06QBAEbN68GZ6enkqXHTFihMECJCIiIjIUrROfVatWYeLEidi5cydEIhFmzJihtNhZJBIx8SEiMgBW+BAZntaJT1RUFE6dOgUAsLOzw/Xr13kndiIiIrIoes3cfPfuXVSsWNHQsRARkQwO6iIyPL1mbh42bBjatWuH9u3bo1WrVnBzczN0XEREREQGp1eLT69evRAbG4uBAweiQoUKaNmyJaZOnYrdu3cjOzvb0DESEdkkEat8iAxOr8Rn2rRp2L17N54+fYojR46gb9++iIuLQ58+feDr62voGInIzAicIZKILJReXV3Fbt68iQsXLuDChQv4999/4enpiTZt2hgqNiK98TqZiIiU0SvxGTx4MI4cOYLCwkK0bdsWbdu2xbRp09CwYUNDx0ekFzZIlC8W3RKRpdIr8fntt9/g5+eHkSNHokOHDmjTpg3c3d0NHRsRERGRQelV45OWloY1a9agoKAAM2bMgJ+fHyIjI/Hpp5/i77//NnSMREQ2iS1rRIanV+Lj7e2NPn36YOnSpTh37hwuX76MevXqYenSpejVq5ehYyQiIiIyCL26utLS0nD48GEcOnQIhw4dwuXLl+Hj44O+ffuiQ4cOho6RSGe8UCZrwP2YyPD0Snz8/f3h5+eHNm3aYOzYsWjfvj3q169v6NiIiIiIDEqvxOfChQtMdMiscVQXWQPW+BAZnl41PtWrV8ezZ8+kv9+7dw/Lly/Hnj17DBYYERERkaHplfj07dsXP/74IwAgPT0dzZs3x5IlS9CvXz989913Bg2QiIiIyFD0SnxiY2OlMzT//vvvCAwMxL179/Djjz/iq6++MmiARGR+eMsKIrJUeiU+z549g4eHBwBg7969GDBgAOzs7NCiRQvcu3fPoAES6YOlEWQNRCzyITI4vRKfGjVqYNu2bUhMTMSePXvQtWtXAMCjR4/g6elp0ACJ9MEGifLF8zERWSq9Ep9Zs2Zh8uTJCAsLQ2RkJFq2bAmgqPWncePGBg2QiIiIyFD0Gs4+cOBAtG7dGsnJyWjUqJH08U6dOqF///7S35OSkhAUFAQ7O73yKyIiIiKD0ivxAYDAwEAEBgbKPda8eXO53+vVq4e4uDhUq1ZN35chNQRBQL5EgJND+SSWgiCwxoCUYnEzEVmqcm2KEXh0LFeTfruA2jP/xv305zqvezU5E09z8lQ+v+dyCiI+248Tt56UJcRSTtx+go82nUdqdq7O66ZkvED6M9UxX03OlP7fkOnansspaD5/P07dSdV53VuPsnDpfobK55/lFWD+zis4d+9pWUIsJTHtGd77KRYXEtN1XjfmTio2nrqn9vt7Uo/PQpPEtGdou+ggNpyI13ndC4npWLH/JvIKClUus+VcEg5ef1SGCEvLlxRiyu8XsD3uvs7rJmc8x8ZT9/A8T6JymSsPMlU+py9JoYBB35/EJ79d0Hndh5kvsGTvdSRnqD7mZL7Ix73UnLKEqNT4n87hjTWndD6vZL3Ix9cHbuLO42yVy7zIl+C2muf1NfevK+ix4ihe5Kv+GytTICnEmqN3cPmB6mNHanYu/rzwALkFum1bk1WHb6Pd4oN4mPlC53X/vpis9nh353E2Jm2+UC6ftS7YB2XB/oi9D0EAflQ4UQiCgMsPMlR+2S7dz0CPFUcRMX+/ym2/u/EcUnPyMGxNjCFDxrDVMdge9wBzd1wp9dy91ByVJ4H0Z3losfAAwufuU7ntdzeeM1icitt9lJWL4WtLfxYHrz1Se3DqvPQIen19TGXC9tWBW1h99C5e++6EweIFgPd/OY+dF5PR95vjpZ5Lf5anNoEc/MMpzNx2CcdvKU9u9EkAtfHZzitISHuG2X9eLvXc9ZQsHL35WOW6fb85jmX7b2Dd8btKn49/koNJv13AqHVnDBYvUJRMbT6bhI82xZV6TlIoqP2c+648jpnbLmHh31dVLrPzYrIhwpQTm/AUp++m4bdzSaWeyysoxM2HWSqTi7fXn8HX/9xS+zlGzNuPdosP4e4TwyU/hYUCdl1MwfFbqbijsN0CSSEu3c9AYaHymOfvvIol+26gy7IjKrff75vj6LTkMI7dNOyF3n+P38XV5Ez8eeGB3OOCIOBqciYKJMoT9Z9iEvDZzqvo+dUxldt+/fuT+PCX81i674ZBY/7872u4l/oMy/ffLBXz9ZQsleeV8wlP8X8/xaLX16pjfnNNDLbEJmHY6lMGjVlXTHys0B+x99Hzq2MY8d/TSp8/9rIVR6LkQHHzYRae5RWUa3xA0dW9rLjEdLRbfAidlx5WGtetR6qvEIoP0rInmfJoa8yXyG/15sMsjFp/RuXBSfbk8ShLvoXrfvpzpGS8wM2HWYYPFMBdFVdU+ZJChM/dh/C5+zT+ne+lKT9xxSYYtnWqmOLnK6vb8iMYvvY0bj1S/3ldV/g8X+RL8CD9eanP31BS1bSavrkmBuFz9+G8is+rOKZD15UndKpO5GWlbrujN5xBl2VHsD3ugdLnL79sgbqWIv85C4Ig/U7nvTyZGzJBlo1YMSebse0Sen19DEv2XVe67pn4NADKj3dJT59BEATp+/njfOlk0BAUP/M1R++ix4qjmLhZeaubuouph5kvUFgo4M7jou/n7ksphgtUhmJStvfKQ3RbfgQDVym/SLv5UPUxOuN5PiSFAh5kFLUiPcwsn++jtpj4WKH/xRTNpXT6bhoW7FJ9NanoxO0n6LLsCLovP1peoam06+WV7f305+i67LDWB/0X+RJ0WXYE0/741+hD2G8/LkkMBq06iXyFA4Wqt/A8T4JWn/+DFgsPoKCcTm6qarMyn+dL/19v1p5SCag6U36/gP7fHkd+gem6sDsvPaJTS0LXZUcQ9fk/uJZi+C4jQP2w/uLuwP7fnsDms4lab/O3s4novvwIEp9q/7cxlKMvWzwm/Bon/U5qI/rPy2iz6KBci5udAfub1XVvbTpT9Nl+c/C20hY/VWuuO34Xrb84iHk7So6Rdkaqafzm0C0AwJ8XHuCL3de0Xu/g9UeIXHAA43+KlT5mrCrM384WJYWX7mdi4q9xWq9390kOGs3Zi6EmbuWRVa6JDwtjTe+HI3cAFDVDaqoF+utlc2yCDifD8nD7cQ5Sc/Jw6k4qzt0rulpTdfD6+1Iybj3Kxi+nE01acHs6Pg0Hrz3CpfsZ0i4ZVQfrxzKtD4rJkrGtOx6Pmw+zsD3ufql4RQqH1M1nk3A+IR0xd8unq0tb0/74F0+yc3Hg6kOlV/Gyivfl8roq1taU3/9FxvN8/H0xWWO9xye//4trKVlKu/yMafxPscgtkODA1YfIyVXfOrjhZNHF1qLdJa0uhjz+a/vVnvPXFRQWCjhx+wkyX+SrXbb4ovC/5ZSsaeu7Q7cBAP8mpSPtZQuiqmPZqpfL7r5csj8bK1mT9cf5opq2yw8ykKQhQd/yskv19N20co9LWyxuNgM5uQU4eTtV40FcFU1r3XiYhf7fnkCrz/8pWl7FCsoeV/WdSn+Wh/+duqe2hqEsMp7nY8gPp/DadydV9oMDQIFM94js/qYs7Izn+Vi697rabrOykBQK6PX1MQxfexqJac/kWnxk4xEgG7Pmbf56JkFtYWZZdVl2BB9tilPZ5aJIU8yCIOD7w7dx+IZ229PV8/xCdF9+BKM3nMXPpxPknlNM1kpi0rzdg9ce4cRtw9Z4yBqz4Qz+76fYUq2wqr5jz9QUPRc7cPUhfj2ToHE5fc3feRWjN5zFez/Hal4Y8u9F1en4bHwa1h67q9P5QX5R9ev9ciYBw1bHYMC3J9QurvR4pyLqaymZ+PbQLZ2LlLV1+m4a+qw8Lj1Gq6L0raj4oBPTnuHrAzf1PkZr+uskPX2Gnl8dQ+svDr5cXvkaqh43pXJNfK5cuYLQ0NDyfAmr8NZ/T2Po6lNYffSOQban+D2IS0jXaj3lBwLlxv8UixnbLml9QNTVUy3rdQQV/1dmzp+X8dU/t9Bl2eGyhCal7kIr6elzFKo4sMs+rGqZYpvPJuLTLRfRcYmhYlYdtLq6AvltqH/+6M0nWPj3NbylosZM5XZ1WPZJdtH+sf/KQ62W13TwTc3Oxaj1ZzBsdUy5XbCdiS+q9dkaq+UIMC3CGL3hLD7dcrHcRslsPFXUkqNtUiz7N1S1rw1cdRLzdlzBnsva/e0A3U6exZ+vpgscZVtUtW93X34Ui3Zfl7bO6ErxtRRf5p9rRaMNn2tKrJQErarFp/+3x7Fk3w1M++OidkHq6GqydvWJ5dSbXyZ6JT45OTmYOXMmoqKiUKNGDVSrVk3up1hwcDDs7e0NFqy1OvtyKPPmM6XrAB5n5eJiknYnJFU0nVyLKTu4yH6p8goKpbU3J24XdXeoGvlT1sJM2dYvteHrkEQUF+UqW0xSKODWI9WjWbQhe/yxV9NmLhunspcTBEE6LFvTMPeydpXJxmynJmbZz0VT07q6LlVBKPqcyxK37Kur+5y1URyHXKKt5G+irtVRV+o+Z1m6nOxTs0tf1SdnPEeWku4eXbqgdP06yG5b06soq9VKzc5VOs2GLnFoe7xTtpymj0bZUO2sF/l6Df2WpXjcUfUOlO0TqkIuvjhQNvXEi3yJTvV9ymh9XrGWxGfMmDFYu3Yt2rRpg/fffx8fffSR3A+pl5NbgNdXncCqw5qvHprN34/eK4+pnRuh2It8idITt6TUl0r5nqgsVyk+yb3IlyDis33o/23p4dGKVuy/ifC5e9UWoWr6LsgmTgIEuS+P7HuU/fK9yC+UWafIez/FYvhazVfxkzbHofPSI1ivxxwyytjbyccme0CV/ZxPx5fu9x61/gzC5+5FxvN8tQeN3ZdSUHP63/hdybBkZTR9BooJjaqYjymZ22n1kTvovPSwXP2SMlvP30fnpUcwZsNZzQFrQdv6hqSnpZOxVYdvo+b0v3H6bpr8/qWw3P3056gfvQczt13S6rU0f87yv6t6B8rm8Dl1JxXdlh2RjlRSJSXjBVou/AdN5qme/qE8yCa0xRP233qUhZ5fHcWey+rrrHILJGj62X40nrevTImm4uBAlUmE0q79or/G46xc9P76GP53SvNNtxtE70XkggMa9311tC1zULZY8VfgRb4Er686odXw9h4rjqLNooNanVdUxqJlzOZY8qJX4vP333/jt99+wxdffIEJEyYw8dFBanYufo5JwJn4p/j879LV/Dm5BXiUVfrqQd3QUEEQ8DgrFw3n7MU7SuaySX+mvsivmNIM/uWXKjbhKTJfFOCCFq1Py/bfQOaLAnyh5P3JKpAUou/KY3jv59hSB//MFyXFlIphqTtJFcsrKERaTh52XkzG0ZtPcC+19NWN7MFm28vhu98c1JyMTvn9AsZsOFsqriyZmHPzC9U08ao/EBy6/hjP8iTYp6EbZ9z/iv7Wk5VMRKeYD/xn60W0//JQqSJV2atrdQdfdc/dfJiF+buu4tajbHx14Gap53MLJNKD5NpjRYWk2tT/rD9+F92WHSn1fciWeQ+aCitLliud+BR//6Zvle8KUDxQrz5yBy/yC6XdPrJKF4Anotn8/fg3KV1lLNqe5HIUanye5uRhyA+ncP1hFl5fdVLtds++HBSgbooAoOi9nrydivaLD+K4hslKtYk7V2YCSRFESMvJw4e/xOHyg0yl82wVSAqln/fTnJLjVE6u/HtX/K7dfJiFzksPl5ofB5CfKkPXyf1EKDpGL9t/AxfvZ2CGkmRXNmZZF++nq932k+xc9FhxVPodkCXbVakuZmWvaycSITnjObbH3ceZ+KdKv4OFhYLc36/4olTTPFG5BRK89t0JfP73tVLHlHiZY6q62ifzS3v0vGVFhQoV4OPjY+hYrN6Wc0mYpHCSki2mzJMU4pXZewAA/9e+Oj7tXkf6nKbm6e1x95FXUIh9Vx6iSYi33HOL95SMtJjz12X4e4iVb0TJHppXUIiuyw6jTqCn9DHFL+aU3y9g89kkzO9fH29EltR0aboYv5KciQtJGbiQlIF32srf1qT4pA4UFVj2bhQk/b1QEGD38oSj7mIi6vMD0v8rzuPy8a9x2Hr+Prq9EoDvh0doHbMgCNj8clhnwypecs998vu/0v8PWxODi9FdVWxD+bbfXBODEF9X6e8Zz+UT1u1x9/HRpji0qemHjaMj1Qeq4OeYogLYLbHyrUPFozOAov1kdOuqStdXd9KTnRju4v0M1Asq2Vc2nozHzO1Fo5Nuze+hU7N39F9Fk1zKjhQC5Gs3rqVk4YbM3D3aNAAt2XsdMXdKWkwU940LSRnSCSWvzO2m0xXrlJf7gLrat8wXBbieovv8TY3VtN5cT8nEoO+LkqETUztq/TkLAjB8bQwKCgW8oWGyUm1aqGXN+esynqq56HqclYsa0/8GAGx7rxUCPGWOSwp/R8UBAdO3XsKtR9n48JfzpbabJpPMT92iW33LTzEJ+ClGdbF4bkGhNOYfhjdF11dKbtukqjC62A9H7uBqcibm7biCCq6Ocs8dlKmhGrXuDIK8XZRuQ9nX8FpKFloulC+Klt1nBQGoPfNv5EuE0sdoNfEKAnDg6iOcu/cU5+49RZd6AXLPyw7D7/nVUYxto/zWVFbT4jNv3jzMmjULz56ZdtizpYn+q/Tw1NsyB3HZq1LFIjp1O+jqo3fxIL3kqjhWTTHzuuPx+FPF5GSqds8bD7PlrqzWHJW/YilOBKZv1a4rAADOJ6TLXTEUD7tXZuOpe3InO9k41fUzy3Z9ffK7fMK59eUJX5cCSwByV2uampTlr7ZL/oKqIj5264k0QQGAeTuuyJ3Ii2cHPqrj7LI7/y25qlOcjVWRbNO37D6n2F2qSpzCLTKKkx5AczGk7HuVnSdEU1fewWu63Ybi639uyXUxZjzPl3tt2Vm0t2hbiAzghyMl39nENPVTR8hejBhi2Lfs5/zlnutqr7JlX27Mj2e1nktKWUuFOsqSHtkuLNlh5O/9FCuXrCl+JLLPjVp/ptTszapsPa/7rUQUybYgyXbzlmpdV/NnnPbHRblaTXUJYXH9pDLaphBHZI4RGc/zpccixWO0ul1vS2wSTsrEoq4FWnZOM0VmmPfo1+KzZMkS3L59GwEBAQgLC4Ojo3z2GhtbPiN9LJ26PmVNNC32XxVT9SujOOtqMW0z8xtazjasKWZlV2uq/EemO0Kbri5F91KfIVSmNUUVTX+Nz3ZqPyGkqvoKbYsCAXVTD2i/DV1G3g1U0oUCaN89A6iOWSTS/u/1hw4nrIUaulS1oSpmiaRQ65gX7NI+jv1XdUu4dZFfKGi9f/yjQ9KYpmaWam2pSqALBfWl3LLPKeu2VKest84wxPsGdLu/ncpkX8u/q7YzwmtqpVLWvavKVBWjx8ww79Ev8enXr5+Bw7AN2UomATPF5FOqaLuDahuzpi+VvuQSBwNfTpT3n0MQBIOEbOwhovrOMSVLJCr/Zm+5+ZIM8Foikcgsr1gB1e9P0y5syiOOyqQYpbtn5Ncz3R/BTazdyGRjfK7afgpuYu1O7ZZyvDM0vRKf2bNnGzoOq5egpLgWUL/jya4ju1iBpBAO9oabgulpTh4GrjqhtrlSlrqY5ebOKMcvVWGhgA83ncfZl3OjlEVKhvKhqIb8nItP+oN/OCV3F3l9aRrmboiPvvjvvO74XbXN79qKf/IMyUo+6wJJYZmHpSv6cs91g3RznLqTWqrIWJYhThzFm9h1MRlrdJjLS9UJZf/Vh4gIq1DqcUmhgIJCw84UfvD6I0TrMMO0qtbOBxkvkPlcdkCDIP03t0D7VjdtnE94KnfLB81U/5Fl6/BkW+9f5Evg7Gi4qVwS055h2JpTGrtQpbGoeS41W/noM0PHnPEsHz1WHJHen8uc6JX4kO7+uaa8aVvd8b7t4oPS/xd/qf577C6+3Htd5+JWVRJSn+GXMwlaJz2A+hafzktLJtorXurQ9UeYuuUiFg1sqG+Ycm49ykZaTh52/KvbnatVRd1iYUkRdPEIuLPxaXhzbQymyhSYl8XDzBfwdHY02LTtxYWssh5lvsCwNTEY0izYIK9xP73oZohzXhYZa0vV7qGsyy3jWT46LzuMltV8YYh0LeN5PgoLBaw8eKvM2wKAv5Xc6qKwUMDoDWfg6eKIupU8laylm4zn+cgtkOh4MlZ99f8sT4JZ20snI72/PoZHWbn4aki47kEqkVsg0flu9+qu/l/9quQegcUNjO9sPIejNx9j14dt9AmxlBf5Eryz8ZyOQ89VB91ozl7p/4v33ug/L2P9iXj8/ZFhYs54no/5O69qnfQA6hPypp/tL1nu5b8/HLmNBbuuYcPbzfWMUl5ObgF+OZOgNunJfJEPT2dHlc+XJ70SH4lEgmXLlmHz5s1ISEhAXp58H2hamvnck8NcqCog1GZ4OFB0pXQ9JQtzdxSdhGQLMMui7eKDqB3godM6ezXMxyHrUdYLjHx5cFR1t3hd9fr6GFrV8NV5vXgVrW6ycgsKkVsgkda6ROt40ldl2OoYjGgZqnlBBdreCT39WR5aLzqIvIJCneqQ1PnqwE29bpWhbd1IXkEh3v3fWTzOylU6LFkfe688xFvrdN/PNM0xUyzrRT5+O5skHYWj6i7mukjNyUOHxYd0Xu8vHT6z+Cc5uPKypXGYhtFb2oqYt1/zQgr+iNV+zqmnOXnSglpDzVz+yuw9OnebaVvgLhIVlTMUzwXWY4VhbvbcaM5eVPN302kdrb9PIhFyCyTS+jRdZ1tX5ZXZe9CxTkW1y+TmFwLOBnk5nYkEPTpPZ82ahTVr1mDixImYOXMmpk+fjvj4eGzbtg2zZs3Chx9+WB6xGkVmZia8vLyQkZEBT8+yX80VK86oiaiIs6Od3Mg7S+DiaK/5tgJmplfDSjq3jppav/Ag6dxalqJdLf9yuz9deanq51bm4m99nf5PJ1T0NGzmo+35W68Chp9++gmrV6/G5MmT4eDggKFDh2LNmjWYNWsWTp0yn1vPmxMT34SbyOxYWtIDaHEvJTNkaUkPAItLegDtJuU0N6ZKegDVvSDGoFfik5KSggYNGgAA3N3dkZFR1F3Tq1cv7Ny503DRWRGJgYsKiYiILFWBhlnFy5NeiU+VKlWQnFx0FVGjRg3s3VtU4HXmzBmIxSpmBTaib7/9FlWrVoWzszOaNm2Ko0cN09daFupGhhAREdmSPBN2g+iV+PTv3x8HDhSNhPnoo48wc+ZM1KxZEyNGjMDbb79t0AB19euvv2LChAmYPn06zp8/jzZt2qBHjx5ISFA9DbkxqLvXFhERkS0x9NQKutCruFnRqVOncOLECdSoUQN9+vQxRFx6i4yMRJMmTfDdd99JH6tbty769euHhQsXaly/vIqb3914VufbIxAREVmjv95vjQYK9zssK23P3waZx6dFixZo0aKFITZVJnl5eTh37hymTp0q93jXrl1x4oRhhn/ry9GAEw4SERFZMovr6gKAjRs3olWrVggKCsK9e0X381i+fDm2b99usOB09eTJE0gkEgQEyN9FNiAgACkpyufpyM3NRWZmptxPeTDHabuJiIhMocDSEp/vvvsOEydOxKuvvor09HRIJEWFu97e3li+fLkh49OL4o0/BUFQeTPQhQsXwsvLS/oTHGyYWW8V6XJjSiIiImuWb2mjur7++musXr0a06dPh719yb09IiIicPGi8ju0GoOfnx/s7e1Lte48evSoVCtQsWnTpiEjI0P6k5iYWC6xGeImj0RERNYg34TFzXolPnfv3kXjxo1LPS4Wi5GTY7oJkZycnNC0aVPs27dP7vF9+/YhKipK6TpisRienp5yP+WBLT5ERERFKnqYbuobvYqbq1atiri4OISGyt976O+//0a9evUMEpi+Jk6ciOHDhyMiIgItW7bEDz/8gISEBIwbN86kcZlylkoiIiJz8kqQYUd06UKvxOeTTz7Be++9hxcvXkAQBJw+fRq//PILFi5ciDVr1hg6Rp0MHjwYqampmDt3LpKTk1G/fn3s2rWrVJJmbOzqIiIiMj29Ep9Ro0ahoKAAU6ZMwbNnzzBs2DBUrlwZK1aswJAhQwwdo87Gjx+P8ePHmzoMOaacnpuIiIiK6D2cfezYsbh37x4ePXqElJQUJCYmYvTo0YaMzaoYa5ZKb1dHXJjd1SivZUi/jWtp6hB0dmhye9QKcDd1GDr5fnhTtK3lb+owdPLzmEh8+XojU4ehk8UDG+L74U1NHYZONo5ujqtzu5s6DJ1E966Ha/MsK+ZhkSEW9zlX83fDv9GWd15RRe/i5ps3bwIoGklVsWJFAMDNmzcRHx9vsOCsibGG7s3v1wBeLo54rUkVo7yeIYxqFYZmYT4Y1666qUPRWsMqXgjzc8OMnqatadNVt1cCMa5tNVOHoZOoGn7oWKeiqcPQyesRwWhb07ISzDY1/eHiZA+xg+VMttqvcWU4O9rjlaDyGZRSHt6IDIGLkz36NAoydShaGxUVBk9nR3zQsYapQzEIvfbwkSNHKp0JOSYmBiNHjixrTFbJWDU+9nZF8xUtHtgQ+z5ui0BPZ6O8blnYv5xjaUq32vjz/Vao7O1i4og0K/6c29byx6U53TC0efnM/1Qeomr4Yc+EtvikW21Th6I1HzcnXJ7TDb+MNf0M8dpycbLHyWkdsW5kM7nHTTmaRRv/RnfFiakdTR2GVhxezoi//b1WODejM+yUT9dmVhzsimJeMSQc52Z0Rqivq4kj0sz+ZcyTutbGuRmd0cjAt5owNr0Sn/Pnz6NVq1alHm/RogXi4uLKGpNVKs9RXZ7OJaVaxSdkOzsRagZ44PCU9tLnfN2cyi0GXUVW9ZH+396+JOaGVbyxf2I7uWXN5Qq0RsWSbi17mQkx3cUOWNC/gdyyEaEVjBaXOg4qzgS1Az3wXocaaC7zd/iwU01jhaUXN7EDWlb3xeSutaSPbRzd3IQRaVbJywUd6lSUS352T2hrwog0EzvYI8jbBTH/6SR97M/3Sx/vTUX22FG8fzvY28HXXYxLc7pJn5vZy3xaY4dFhkj/X3yMFolE8HUXY+/HJfvDqw0CjR6bKv0bV5b+X/Y44usuxmaZ0gR/M0/kldHrjCISiZCVlVXq8YyMDOksziSvPKfnPjuji/T/iic6sUPJBJPmtINueLvkhKUYs4uTvdzvdipm3Ta2n8dGSv9vrxCzSCSSa11TfA+mInuSVZYDye4T5nK1/Nu4lnBV8/m5i0sSfRHMI+j3O9RAm5p+Kp/3cy/5nB3szSPmav5u+LhzLZXPV3A1nwslWR/JJOiK90B0dZLdN8zHJ11LWlfVHaPNiWxdneLxTjZmc/qctaVX4tOmTRssXLhQLsmRSCRYuHAhWrdubbDgrIlii8+OD1rjvQ761bR88VpJ60LPhpXgJNMiYleOZ6+o6r7oUV+/K5Kvh5ZMeNmhtj+cHUu+OMXNqKpUriDf9eXt6qj16w5sWgWfdq+j9fKyNr1T0q3i5mSPih4liY2mk5fiAVnXpuG3W1XVafli+z5uK7c/yLZSOSj7nGV2Sw9n+c91TGvdYtC3APmv91sj2Kfkb9wszEdtC6nsM4q7e99w3eomRkaF6bR8sRVDwtGqhq/099Gtq6rtzhZkolY88cm2YGjjm2FNdFq+2JjWVdG5bskM9osHNoJEzaAL2esNxQTTScdW2EUDG+q0fLHwYG+51pKFAxrI7RuKJ2RDmtGzrt5dOh/K1MKMjAqTu3grz5jfbVsN3V5RfpcCTeb1fUX6/8iqPnJxqotZ2XWph7NB7n9ebvRKfBYtWoR//vkHtWvXxqhRozBq1CjUrl0bR44cweLFiw0do1VQHNVVv7IXPulWckKOqu6ruIpKg5uF4NKcblg5rDEWvSZ/QFHVtQEUtUp8PbQxPJ0dMLt3PXwzrAkaBXtLn9/+nvrm7P+NjsS3b5QcdHWpH+rdKAh3FryK7e+1wiqF0S72Glp0vh/eFG1q+mHVm02wflQzDGhcUrh9dEoHtet++Xoj/F97/RLMFtV8cWfBq1g3shkOftJe7jlNrVAze9VDRQ8xpnSvjT/GR8kVbmsahbLtvVaY1Vu/ZvqaAR648VkPbH+vlVxXBQBoyC/xRmQI2tbyR3TvergwqyvelYlZcVuKPutXHwObVkG4zP6krQBPMY5O6Yi/P2qDQ5PbA9C+Jq5pWAVU9nZBqxq+ODWtE5YNCpc+t+pN9QlC70ZBiO7zCt6QObE62Wt3SBQ72OOnMS0Q859OODS5PSq4OWkds9jBHj0bVEKbmn44N6MzfpapWxrbRn2yGezjgp4NK2H54HDpY61rqG5pkiUSAWveisDRKR3w85hINA2tAImaGeUV9/G+4UEI9HTGgUntEDuzpJW5SYi3xoRzUEQw/plU0oWt7UWfSAQs6N8AMf/phFVvNsXgiGCd6iVHtAyFvZ0IW8dH4bxMzIB8y5EyY9pUwzaZY6IuCcXErrURO7MLVgwJx9QedeSaRdQmERBJW+FWvdkUJ6Z2lCtl+ErmAlKZaa/WxffDI6S/16yo/ajT4S3DcDG6KxYPbIgfZLahKWagJLGd3bsednzQGs3DSpL5HR+YX2OIXolPvXr18O+//2LQoEF49OgRsrKyMGLECFy7dg3169c3dIxWQaJiVNf49tUREVoB60Y1U/q8Ku5iB/RqGAQ3sXxmremE3LtREOJmdcWoVlXRs2EluecaqTlpVfd3g52dCCKRCIsGNkRUdV/s0bFWwc5OhEbB3qWadjW1nlT3d8fG0ZHoXr8S2teuKHeVH+yjXWHgD8ObIjzYW3pi1SXmDnUqyrX2AOoTTACo6ueGmP90wvj2NdAkpILcTXKdHe0xXk0y1rBy0VXm1vFRaBZWAdvfa4UKOrRyAUV/ywBPxZjVf92dHe3x49vNMbJVVXgpvJ6jvR3m91f93e5Ut2jU1dJBjRAe7I01IyLQpZ6WJ4qXH03dSp4I83MDoH3iI3awx+FP2uN/oyMR6OUs1+IpEolwdkZnletGv0wuP+lWG61q+GLJ640wsavqrh9lAjydpTFre1saEYBv3miCjaMj4esuljupiESiUjVusj7sWHSyfrVBJbSr5Y8p3Wvj4y7a1WYV74PBPq6IepksqWtZU9zDVwxpjONTO6K6v7tcdyMALJVJOBUV12RV9XND3/AgvNUyFJO66FZYH+DpjO71A2FnJ9Ip8Znbtz6uzu2OxiEVUEGhxnFCZ9Wf24AmRfUtIpEIY9tURY/6gVj1pm7TE/i4OaFveNGos8JC1S1+ij7qXBPX5nVH9/qBCFIY6KFuJFiYTJH09FfronUNP/ylY9Lh4eyI1yOCS33/NcU8KCIY1+Z1x6hWVVG/snwrmeLv5kDvqtGgoCAsWLAAO3fuxO+//45Zs2bBx0e3JltbMq9fyUlD9kp0Svc6+P3/olT28zo52CFEy5M7oF39gNzJQeE5VaOTfn23pJhtUEQwfh7botSXo9iAJpV1amXRtelXMbdT1fQve3XU9ZVAbHuvlfQkpeiVIE+8o8Mwb2UxC5A/IMsmO4oxFycKiraOj5L+fRqHVMBv46LQKNhbblvFhjYPwY9va1/cW9bPuVcD5QfdjzvXQiWvogN0NX93bHuvFTrXC1Da91+3kmfRFbAMXWu4FPMLB3s7pZ8PIF9bI2vFkHD4vnzO29UJP41pgdeaVlEa86sNAku1rCp7OW0HMKh7u4IgyHVPyqpZ0R2vRxR9P50c7LDh7eYY31758GIPZwe5lixVVF2QKcZZ/H/l+33pxyt5FSXdkVV98P7LZE0kEmHFkMaY07e+ys9AMVlWtpiun7OqbjmRSIR2Sua0CvZxwZcDS7ptp/esh+/ebKpyH4uq7qux9VvX7jnZUgDF1x3VKqzU8iIRsPfjkoR5bNtq+N+YSLntyGpe1UenXgZNrVSlY5ZfRrHcQN/uWkPRO/FJT0/HkiVLMGbMGIwdOxbLli1DRkaGIWOzKp3qBmDzuy3x5/ut0L1+JaXLKM5F4WAnwuU53fDru9oP4Q3VIUlSRtm8ND5uTipPIMpqJJYOCsfELpqvnItrdTrULtscLbIjIZqEeGPHB63x5euN0Luh8s95lpLRHjs/bIMpWgzvblmt6GDxZouy3QKlaajyi4TGIcpHg81/mTjLHn8WDmiAtrX85ZqVlen0cg4cZXVDismaOoqJ7rV53fHPpHb4sJPyk2/xKDHZK9E/32+Fce2qY3BESYKt7JA6/dW6AIB32+k/51BxghTgWXrf7RteudRjANDnZZeNbPLxafc6GNQsWONQ+qHNihKNZmGl/4ayyZqqE6jscrLzpdxd+Cr+mdQOuz5qo3SdWgEeAOSvymf3fgXz+zeQO8Eoe9XiRKq5kjojdXEqIzty7eS0Trg2r7tcnZzitp0d5U8/Q5uHYPWICI2fc3GsxcmVKtpE/53MRej+iW1x47MeOPJJB5W1ktX95S+calZ0x89jW+BHDaMLZesSvVzUtN5qEfR/Xn43gKJ6z5vze+DGZz1UJnjKiu43v9sSy4eEa3yt4u9OhIZjjCayXbgDm1Yp1dtgbHpVIJ09exbdunWDi4sLmjdvDkEQsHTpUsyfPx979+5FkyamzebMlbKDi6xt77VCanYeWiw8AKDoSsrR3k56Na3OgUntkP2iABV1nLendoAH4hLTpb8rdp0B6vuJo/u8gklda6HFggPIySspdne0t0OjYG9ckNm2omOfdsTjrFxUVdEKo0o1f/l45FtWRKhf2Utt8+rbraticLNgjPvfORy9+UT6uIO9HUa3roq1x+6qXPfH0c2RkvFC6y62YordTkDRVZS2zfY9GlTCxeiuWHc8Hkv33ZB7blSrMJyOT1O57jdvNMGl+xkqkypVZK/gig+qvm5OSM3Jkz6v+LeQVb+yF67O7Y7YhKd4Y00MgJLWncndauPXs4kAlJ9gx7athh4NAss0p1Px/Cj9GlfG94fvaLVOJS8XXJ7TDXkFhWg8bx+AkmSkpYYr5NcjqqBuJU/ULMNs3g1fdjd7y4yoEolEaj9nD2dHxM3qAicHO9SbtedlzEVB92xYCe/9rPr1agd6IHZmF/UnYxVcHO3xPF8irTFS/E6oam0oFjerKwoKBdSfveflI0Uxa/qcfdyccGF2V7ho2L4yYb6uiE99hhbVio7FzjIt7e5iR41F27sntEVObgHC5+6Tibgk+VTF0d4Ol+d0g0hUMveQtpqEeOPg9cfS9ys7cCLA07nUQApF60c1R2pOLprPPyD3eEUPZ3g6OyDzRYHKdY9M6YAXeYUqW/cB5S2Yob7yx3TZ9xykIWE1Br0Sn48//hh9+vTB6tWr4eBQtImCggKMGTMGEyZMwJEjRwwapK1wtLdDoMxOIWhZMwAU1cGo0rluAPZffai0cPI/PevCxcke/WTmbPiwYw1sjbuPxLTnWr22h7OjzleHQFGdkmKtQLHpr9bF/F1X8Vm/0nUlgyKC8TgrFy2qlRwgG4d443xCulxLgjpuYge9Yna0t1OZ9IxrVx1z/rqCng1KX82EB3tjRs+6ct2Wf77fCt8euo2d/yZr9doezo56DR11drRXecX2btvq2HUxBb2V1A64ix2wbHAjFBaWDCH/YUQE/u9/57SeI8XFyV4uZl1626pUUP45F99yQ9XIka3jo/Ag/QXqVipqQf2wY00UFgrYcOIe8rSYVsJN7ACJkC/9Xdm3UNnbEIlEaKBiFFDtQA84OdipnLxw/8S2iEvMkLZSDm0ejN2XktGxjnZ1Ut4KQ891mTXMR838XhU9xHicnau0+23fxLY4cuOJtB6mRkV3zO37CvxVtA4rUkyMlB3uVH1H1SVqjap44UJSBropGYH609gW+O1sorTF1s5OhBVDwpGTK5E79qriaG8n91nrcoxWdlFZrF94ELbFPcC7Srrbv3y9EX44cgeDmpUc2/47MgJXHmQq7apTZG8nKlWjqC2xg73KMowPOtbA1//cQnSfV0o993GXWnieL0HvhiXHlXWjmmH3xRSM03OwiSHp3eIjm/QAgIODA6ZMmYKIiAg1a5IprHqzCRKfPlfasuLl4lhqx53YtTYmdq2NsKk7tX4NQw/QHNu2GgYpKbIDir7IipPt/TymBW48zEJDHYafGjrmkVFhaFndFzVUJKFj2sgf1F4J8sI3w5rg4LXdeJan3fxXhp7SqFGwN/6N7goPFQfl/o3lb33SNLQCYv7TSbekUa5WpOgX2S42Xd9SjYruOPJJB/i4Kz9hNw6pgMYy5S1uYgdM71kP/yZlIOau6pYxWbIjDXU5uani7GiPf2d3VVkkWqOiB2pULGk1cHVywG/jovR/QW2zNQ2OT+2IAomgtPWmSgVXuaHmADCiZZjuL/KSAT5mAMAf41vhWV5BqekZAKCytwsmKMxdpKrbUxuGmpZ22eBwzOtXX2nMvu5iTJPp3gKAjnUCtE6K1SlL/JO61sY7baspjVnZpK4dalcsc1mDoehV4+Pp6YmEhIRSjycmJsLDQ32TH2nPUF8qB3s7nbuTdKbsoFrGI5m65lVFLk72KouAVVG2aFlCFolEqBPoqXNTtq6voais+4mnji12uraUlcckgyG+ripbCw1BtphTaQ6hRwbq7GhfrvuGLF1qt9RxtLcz2mScymLWZ8+xtxMpPRmXCwMdpEUiI8ZsQJYYM6Bn4jN48GCMHj0av/76KxITE5GUlIRNmzZhzJgxGDp0qKFjtFmGugIyBkucvdMSY7ZEmnIEM5mYW46dXIuPCQPRk9JuIzPf4y3yc1bymDnuzyRPr0umL7/8EiKRCCNGjEBBQVFhlKOjI/7v//4Pn3/+uUEDtGX6FO+ZSnm0RJQ35TGbd9SGbqUyBqXnARPErMtLyg/fNfMPWAnLi9gyY7Z4Nvqh69Xi4+TkhBUrVuDp06eIi4vD+fPnkZaWhmXLlkEsLilsS0pKQqGaKdFJuXUjmyHU19Xsb8Aoa+mgonkvpiv0RZuz6T3rwtPZAZO0GHpvLgZFBMPZ0U5pMbK5ahJaAbUDPNBZxdxF5tgSYScqqiXy9xCXGqECmG9r4aCIKqjs7aJ0/zDXlogPO9WEj5uT0gkFzTXmBf0bwMvFEctkZtAuZqYhY82ICHg4O+CH4bpNxGiNytRJ7urqigYNGqh8vl69eoiLi0O1avrPxWGLOtSpiA515E8SmoYdmlqnugG4Nq+7/CRWJoxHG9X93RE3q6vcnB2aZig1NT93MS5Gd5OL01xPDsUc7e2we4LyOWgA82xlE4lE2DOhLQoFQeNwYXOyaGAjFBYK5XrPPkOb2KUWJnSqaVExD4sMwZBmwRYVc+d6AbigcLwz+4N0OSnXb7QhRkNQkZ/GtEDjEG9slplB2dwojvz4/LWGqODqKL01gDlSPHC92646Qnxc1U5nb2qOCjMVd6xTEdX83aTDis2RSCSSi9nfQ4zmYT5oWc1Xrzlk9IpBx+Xt7USlkp42Nf3g5+6EVlreH8sUFPfpNyJD4OZkr/cNWY1BMeZPu9eBi6O90qHS5kIx5q+GNoa72AEbdJhN3dgUY177VjN4uzpi2WD9bjBsqURCOWYnHh4euHDhgkW1+GRmZsLLywsZGRnw9PTUvIIVKx7OHlnVR+6WFboQBEGvETC2pO7M3XieXzScPf7znnptwxI/5+JDj7HiHvz9Selw9rJ8zpJCwWijswylQFJocTFLCoVyvZN5ebC01jbAMo8dqmh7/jbve8eTxbOWL5S5s8TP2dgxG+IKTyQSaXU/PHNjaUkPoPu95cyBpSU9gGUeO8rK8r4NRFbGBo87REQmU66Jjy1mkkRERGS+WNxMRDaBl2FEBJRzjc+VK1cQFGQ5840QmQKvD4iIjEfrxGfAgAFab/SPP/4AAAQHa3enbCIiIiJj0Drx8fLS/q7XRKQ9lsIZBxvWiAjQIfFZt25decZBREREVO44nJ3IxFjjYxxsWCMioAzFzb///js2b96MhIQE5OXlyT0XGxtb5sDIfLArhoiIrIVeLT5fffUVRo0ahYoVK+L8+fNo3rw5fH19cefOHfTo0cPQMZKJsUWCiIishV6Jz7fffosffvgBK1euhJOTE6ZMmYJ9+/bhww8/REZGhqFjJLJqbFEzDubvRATomfgkJCQgKioKAODi4oKsrCwAwPDhw/HLL78YLjoiIiIiA9Ir8QkMDERqaioAIDQ0FKdOnQIA3L17l7M1E+mIXxnjYMMaEQF6Jj4dO3bEX3/9BQAYPXo0Pv74Y3Tp0gWDBw9G//79DRogmR67YoiIyFroNarrhx9+QGFhIQBg3Lhx8PHxwbFjx9C7d2+MGzfOoAGS6bFFgoiIrIVeiU9SUpLc7SgGDRqEQYMGQRAEJCYmIiQkxGABElk7tqgRERmPXl1dVatWxePHj0s9npaWhqpVq5Y5KCJbwhY14+DHTESAnomPIAgQKblMzc7OhrOzc5mDIvPCFgkiIrIWOnV1TZw4EQAgEokwc+ZMuLq6Sp+TSCSIiYlBeHi4QQMkIjIE5u9EBOiY+Jw/fx5AUYvPxYsX4eTkJH3OyckJjRo1wuTJkw0bIZkcu2KIiMha6JT4HDx4EAAwatQorFixAp6enuUSFJEtYVciEZHx6DWqa926ddL/JyUlQSQSoXLlygYLisiWsEXNOPgxExGgZ3FzYWEh5s6dCy8vL4SGhiIkJATe3t6YN2+edH4fsh5skSAiImuhV4vP9OnTsXbtWnz++edo1aoVBEHA8ePHER0djRcvXmD+/PmGjpOIqEyYvxMRoGfis2HDBqxZswZ9+vSRPtaoUSNUrlwZ48ePZ+JjZdgVQ0RE1kKvrq60tDTUqVOn1ON16tRBWlpamYMiIiIiKg96JT6NGjXCypUrSz2+cuVKNGrUqMxBkXlhjQ8REVkLvbq6Fi1ahJ49e2L//v1o2bIlRCIRTpw4gcTEROzatcvQMRIREREZhN736rpx4wb69++P9PR0pKWlYcCAAbh+/TpCQ0MNHSMRERGRQejV4lO1alUkJyeXKmJOTU1FcHAwJBKJQYIj88DiZiIishZ636RUGd6klIiIiMyZ3jcpnTVrFm9SaiNY3ExERNaCNyklIiIim8GblBIREZHNKPNNSomIiIgshV7FzURERESWiIkPERER2QwmPkRERGQzmPgQERGRzWDiQ0RERDaDiQ8RERHZDCY+REREZDOY+BAREZHNYOJDRERENoOJDxEREdkMJj5ERERkM6wq8QkLC4NIJJL7mTp1qqnDIiIiIjOh101KzdncuXMxduxY6e/u7u4mjIaIiIjMidUlPh4eHggMDDR1GERaEyCYOgQiIpthVV1dAPDFF1/A19cX4eHhmD9/PvLy8tQun5ubi8zMTLkfIiIisk5W1eLz0UcfoUmTJqhQoQJOnz6NadOm4e7du1izZo3KdRYuXIg5c+YYMUoieSKITB0CEZHNMPsWn+jo6FIFy4o/Z8+eBQB8/PHHaNeuHRo2bIgxY8Zg1apVWLt2LVJTU1Vuf9q0acjIyJD+JCYmGuutERERkZGZfYvP+++/jyFDhqhdJiwsTOnjLVq0AADcunULvr6+SpcRi8UQi8VlipGIiIgsg9knPn5+fvDz89Nr3fPnzwMAKlWqZMiQiAyKxc1ERMZj9omPtk6ePIlTp06hQ4cO8PLywpkzZ/Dxxx+jT58+CAkJMXV4REREZAasJvERi8X49ddfMWfOHOTm5iI0NBRjx47FlClTTB0aERERmQmrSXyaNGmCU6dOmToMIp1xVBcRkfGY/aguImvHGh8iIuNh4kMasUWCiIisBRMf0ogtEkREZC2Y+BAREZHNYOJDZGLsSiQiMh4mPkQmxq5EIiLjYeJDGrFFgoiIrAUTH9KILRJERGQtmPgQkU0QseGSiMDEh4hshMCGSyICEx/SAmt8iIjIWjDxISIiIpvBxIc0YnEzERFZCyY+REREZDOY+BCRTeCoLiICmPiQFljcTNaAo7qICGDiQ0RERDaEiQ8RERHZDCY+REREZDOY+BCRTWBxMxEBTHyIyEawuJmIACY+REREZEOY+BAREZHNYOJDRERENoOJDxHZBBY3ExHAxIeIiIhsCBMfIrIJHNVFRAATHyIiIrIhTHyIiIjIZjDxISIiIpvBxIeIbAJHdRERwMSHiGwEi5uJCGDiQ2RyPCETERkPEx8iIiKyGUx8iEyMtSdERMbDxIeIbAITTCICmPgQERGRDWHiQ2RiLG42Dn7ORAQw8SEiIiIbwsSHyMRYe0JEZDxMfIjIJjDBJCKAiQ+RybH2hIjIeJj4kEa8UiZrwASTiAAmPqQFnjCIiMhaMPEhMjG2qBERGQ8THyKyCUwwiQhg4kNkcuxKJCIyHiY+pBGvlImIyFow8SGN2CJB1oD7MREBTHyITI4takRExsPEh8jE2BJBRGQ8THxII7ZIkDXgfkxEABMfIiIisiFMfEgjdsUQEZG1YOJDZGLsgjEOJvBEBDDxITI5npCJiIyHiQ9pxBYJsgbcj4kIYOJDRERENoSJD2nErhgiIrIWTHyIyCYwgScigIkPaYG1EUREZC2Y+BCRTWACT0QAEx8iIiKyIUx8SCPWRhARkbVg4kNEREQ2g4kPacTaCLIGbLkkIoCJDxEREdkQi0l85s+fj6ioKLi6usLb21vpMgkJCejduzfc3Nzg5+eHDz/8EHl5ecYNlIjMElsuiQgAHEwdgLby8vLw+uuvo2XLlli7dm2p5yUSCXr27Al/f38cO3YMqampeOuttyAIAr7++msTRExERETmxmISnzlz5gAA1q9fr/T5vXv34sqVK0hMTERQUBAAYMmSJRg5ciTmz58PT09PY4VKREREZspiuro0OXnyJOrXry9NegCgW7duyM3Nxblz51Sul5ubi8zMTLkfIrI+LG4mIsCKEp+UlBQEBATIPVahQgU4OTkhJSVF5XoLFy6El5eX9Cc4OLi8QyUiIiITMWniEx0dDZFIpPbn7NmzWm9PpKR6URAEpY8XmzZtGjIyMqQ/iYmJer0XIjJvLG4mIsDENT7vv/8+hgwZonaZsLAwrbYVGBiImJgYuceePn2K/Pz8Ui1BssRiMcRisVavYWuc7O2QJylEqxp+pg7FqtWv7IVz957CycFqGmCJiMyWSRMfPz8/+PkZ5qTasmVLzJ8/H8nJyahUqRKAooJnsViMpk2bGuQ1bM3BT9rj+K0n6Bde2dShWLVvhjXBNwdvYUTLUFOHQkRk9SxmVFdCQgLS0tKQkJAAiUSCuLg4AECNGjXg7u6Orl27ol69ehg+fDgWL16MtLQ0TJ48GWPHjuWILj1V9nbBoAjWPJW3QC9nzOtX39RhEBHZBItJfGbNmoUNGzZIf2/cuDEA4ODBg2jfvj3s7e2xc+dOjB8/Hq1atYKLiwuGDRuGL7/80lQhExERkZmxmMRn/fr1KufwKRYSEoIdO3YYJyAiIiKyOKymJCIiIpvBxIeIiIhsBhMfIiIishlMfIjIJogd7E0dAhGZASY+RGQT5vZ9BVX93PD5gAamDoWITMhiRnUREZVFqK8bDk5ub+owiMjE2OJDRERENoOJDxEREdkMJj5ERERkM5j4EBERkc1g4kNEREQ2g4kPERER2QwmPkRERGQzmPgQERGRzWDiQ0RERDaDiQ8RERHZDCY+REREZDOY+BAREZHNYOJDRERENoOJDxEREdkMB1MHYG4EQQAAZGZmmjgSIiIi0lbxebv4PK4KEx8FWVlZAIDg4GATR0JERES6ysrKgpeXl8rnRYKm1MjGFBYW4sGDB/Dw8IBIJDLYdjMzMxEcHIzExER4enoabLtk+bhvkDrcP0gV7hvyBEFAVlYWgoKCYGenupKHLT4K7OzsUKVKlXLbvqenJ3dQUor7BqnD/YNU4b5RQl1LTzEWNxMREZHNYOJDRERENoOJj5GIxWLMnj0bYrHY1KGQmeG+Qepw/yBVuG/oh8XNREREZDPY4kNEREQ2g4kPERER2QwmPkRERGQzmPgQERGRzWDio4MjR46gd+/eCAoKgkgkwrZt2+Sef/jwIUaOHImgoCC4urqie/fuuHnzptwyubm5+OCDD+Dn5wc3Nzf06dMHSUlJcss8ffoUw4cPh5eXF7y8vDB8+HCkp6eX87ujsjDWvtGnTx+EhITA2dkZlSpVwvDhw/HgwYPyfntURsbaPwBg586diIyMhIuLC/z8/DBgwIDyfGtURsbaN2JjY9GlSxd4e3vD19cX77zzDrKzs8v77ZklJj46yMnJQaNGjbBy5cpSzwmCgH79+uHOnTvYvn07zp8/j9DQUHTu3Bk5OTnS5SZMmICtW7di06ZNOHbsGLKzs9GrVy9IJBLpMsOGDUNcXBx2796N3bt3Iy4uDsOHDzfKeyT9GGvf6NChAzZv3ozr169jy5YtuH37NgYOHGiU90j6M9b+sWXLFgwfPhyjRo3ChQsXcPz4cQwbNswo75H0Y4x948GDB+jcuTNq1KiBmJgY7N69G5cvX8bIkSON9TbNi0B6ASBs3bpV+vv169cFAMKlS5ekjxUUFAg+Pj7C6tWrBUEQhPT0dMHR0VHYtGmTdJn79+8LdnZ2wu7duwVBEIQrV64IAIRTp05Jlzl58qQAQLh27Vo5vysyhPLaN5TZvn27IBKJhLy8PMO/ESoX5bV/5OfnC5UrVxbWrFljnDdCBlde+8b3338vVKxYUZBIJNJlzp8/LwAQbt68Wc7vyvywxcdAcnNzAQDOzs7Sx+zt7eHk5IRjx44BAM6dO4f8/Hx07dpVukxQUBDq16+PEydOAABOnjwJLy8vREZGSpdp0aIFvLy8pMuQZTHUvqEoLS0NP/30E6KiouDo6FiO74DKk6H2j9jYWNy/fx92dnZo3LgxKlWqhB49euDy5ctGfDdkSIbaN3Jzc+Hk5CR3404XFxcAkG7HljDxMZA6deogNDQU06ZNw9OnT5GXl4fPP/8cKSkpSE5OBgCkpKTAyckJFSpUkFs3ICAAKSkp0mUqVqxYavsVK1aULkOWxVD7RrFPP/0Ubm5u8PX1RUJCArZv326090KGZ6j9486dOwCA6OhozJgxAzt27ECFChXQrl07pKWlGfdNkUEYat/o2LEjUlJSsHjxYuTl5eHp06f4z3/+AwDS7dgSJj4G4ujoiC1btuDGjRvw8fGBq6srDh06hB49esDe3l7tuoIgQCQSSX+X/b+qZchyGHLfAIBPPvkE58+fx969e2Fvb48RI0ZA4ATsFstQ+0dhYSEAYPr06XjttdfQtGlTrFu3DiKRCL/99lu5vw8yPEPtG6+88go2bNiAJUuWwNXVFYGBgahWrRoCAgI0bscaMfExoKZNmyIuLg7p6elITk7G7t27kZqaiqpVqwIAAgMDpdm2rEePHiEgIEC6zMOHD0tt+/Hjx9JlyPIYYt8o5ufnh1q1aqFLly7YtGkTdu3ahVOnThntvZDhGWL/qFSpEgCgXr160ufFYjGqVauGhIQEI70TMjRDHTuGDRuGlJQU3L9/H6mpqYiOjsbjx4+l27ElTHzKgZeXF/z9/XHz5k2cPXsWffv2BVC0Azs6OmLfvn3SZZOTk3Hp0iVERUUBAFq2bImMjAycPn1aukxMTAwyMjKky5DlKsu+oUxxS09xLQBZtrLsH02bNoVYLMb169ely+Tn5yM+Ph6hoaHGfSNkcIY6dgQEBMDd3R2//vornJ2d0aVLF6O9B3PhYOoALEl2djZu3bol/f3u3buIi4uDj48PQkJC8Ntvv8Hf3x8hISG4ePEiPvroI/Tr109adObl5YXRo0dj0qRJ8PX1hY+PDyZPnowGDRqgc+fOAIC6deuie/fuGDt2LL7//nsAwDvvvINevXqhdu3axn/TpBVj7BunT5/G6dOn0bp1a1SoUAF37tzBrFmzUL16dbRs2dIk75u0Y4z9w9PTE+PGjcPs2bMRHByM0NBQLF68GADw+uuvG/9Nk1aMsW8AwMqVKxEVFQV3d3fs27cPn3zyCT7//HN4e3sb+y2bnglHlFmcgwcPCgBK/bz11luCIAjCihUrhCpVqgiOjo5CSEiIMGPGDCE3N1duG8+fPxfef/99wcfHR3BxcRF69eolJCQkyC2TmpoqvPHGG4KHh4fg4eEhvPHGG8LTp0+N9C5JH8bYN/7991+hQ4cOgo+PjyAWi4WwsDBh3LhxQlJSkjHfKunBWMeOvLw8YdKkSULFihUFDw8PoXPnznJDocn8GGvfGD58uODj4yM4OTkJDRs2FH788UdjvUWzIxIEVkUSERGRbWCNDxEREdkMJj5ERERkM5j4EBERkc1g4kNEREQ2g4kPERER2QwmPkRERGQzmPgQERGRzWDiQ0QW79ChQxCJREhPTzd1KERk5jiBIRFZnPbt2yM8PBzLly8HAOTl5SEtLQ0BAQGl7mZPRCSL9+oiIovn5OSEwMBAU4dBRBaAXV1EZFFGjhyJw4cPY8WKFRCJRBCJRFi/fr1cV9f69evh7e2NHTt2oHbt2nB1dcXAgQORk5ODDRs2ICwsDBUqVMAHH3wAiUQi3XZeXh6mTJmCypUrw83NDZGRkTh06JBp3igRlQu2+BCRRVmxYgVu3LiB+vXrY+7cuQCAy5cvl1ru2bNn+Oqrr7Bp0yZkZWVhwIABGDBgALy9vbFr1y7cuXMHr732Glq3bo3BgwcDAEaNGoX4+Hhs2rQJQUFB2Lp1K7p3746LFy+iZs2aRn2fRFQ+mPgQkUXx8vKCk5MTXF1dpd1b165dK7Vcfn4+vvvuO1SvXh0AMHDgQGzcuBEPHz6Eu7s76tWrhw4dOuDgwYMYPHgwbt++jV9++QVJSUkICgoCAEyePBm7d+/GunXrsGDBAuO9SSIqN0x8iMgqubq6SpMeAAgICEBYWBjc3d3lHnv06BEAIDY2FoIgoFatWnLbyc3Nha+vr3GCJqJyx8SHiKySo6Oj3O8ikUjpY4WFhQCAwsJC2Nvb49y5c7C3t5dbTjZZIiLLxsSHiCyOk5OTXFGyITRu3BgSiQSPHj1CmzZtDLptIjIfHNVFRBYnLCwMMTExiI+Px5MnT6StNmVRq1YtvPHGGxgxYgT++OMP3L17F2fOnMEXX3yBXbt2GSBqIjIHTHyIyOJMnjwZ9vb2qFevHvz9/ZGQkGCQ7a5btw4jRozApEmTULt2bfTp0wcxMTEIDg42yPaJyPQ4czMRERHZDLb4EBERkc1g4kNEREQ2g4kPERER2QwmPkRERGQzmPgQERGRzWDiQ0RERDaDiQ8RERHZDCY+REREZDOY+BAREZHNYOJDRERENoOJDxEREdkMJj5ERERkM/4fejZRfMh7xsQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rsds_out.plot()"
   ]
  },
  {
   "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": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}