runningmeans_2_NDJFM_twice.ipynb

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    "# runningmeans\n",
    "\n",
    "This is the second step in reproducing the cluster analysis from Sara and David following Amini et al 2019\n",
    "https://doi.org/10.1007/s00382-018-4409-7\n",
    "\n",
    "This program:\n",
    "1. Reads data:\n",
    "* Input File: `/glade/work/mkorendy/metisregimes/era5.z500_pna_NDJFM_twicedaily.1980-2019.nc`\n",
    "* Input File: `/glade/work/mkorendy/metisregimes/era5.u250_pna_NDJFM_twicedaily.1980-2019.nc`\n",
    "2. Sorts data and time to be in chronological order\n",
    "3. Makes 5-day running means\n",
    "4. Extracts data for 19801201 to 20190301\n",
    "5. Writes data to single netcdf file containing both variables\n",
    "* Output File: `/glade/work/mkorendy/metisregimes/era5.z500_u250_pna_5dyrm_NDJFM_twicedaily.1980-2019.nc`"
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   "source": [
    "### Function to calculate the running running mean over the season from November 1 to March 31 1980-2019"
   ]
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  {
   "cell_type": "code",
   "execution_count": 2,
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   "source": [
    "def rm_season(da,window,yrs_list,varname):\n",
    "\n",
    "    nt,ny,nx=da.shape\n",
    "    ndays=149\n",
    "    nyr=int(nt/ndays)\n",
    "    \n",
    "    # Create empty list to store each years 5-day running mean\n",
    "    ds_rm_tmp=[]\n",
    "    \n",
    "    # Loop over all years\n",
    "    for yr in yrs_list:\n",
    "         \n",
    "        # Define the start date as November 1st and the end date to get\n",
    "        # a total of 149 days\n",
    "        start_date=pd.to_datetime(str(yr)+'1101')\n",
    "        end_date=start_date+pd.DateOffset(days=ndays) + pd.DateOffset(hours=12)\n",
    "        \n",
    "        # Select just the 149 days\n",
    "        ds_this_year=da.sel(time=slice(start_date,end_date))\n",
    "        #print(ds_this_year)\n",
    "        #print(ds_this_year.rolling(time=window,center=True))\n",
    "        #print(ds_this_year.rolling(time=window,center=True).mean().dropna(dim='time'))\n",
    "        \n",
    "        # Calculate the running mean & append to list\n",
    "        ds_rm_tmp.append(ds_this_year.rolling(time=window,center=True).mean().dropna(dim='time'))\n",
    "\n",
    "    # Combine each year's 5-day running mean together in the time index and convert to xarray.Dataset\n",
    "    ds_rm = xr.combine_nested(ds_rm_tmp, concat_dim='time').to_dataset(name=varname)\n",
    "    \n",
    "    # Return the xarray.Dataset\n",
    "    return ds_rm"
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  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
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   "cell_type": "code",
   "execution_count": 4,
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   "source": [
    "yrs_list=np.arange(1980,2020)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define input and output files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Input\n",
    "path='/glade/work/mkorendy/metisregimes/'\n",
    "f_z='era5.z500_pna_NDJFM_twicedaily.1980-2019.nc'\n",
    "f_u='era5.u250_pna_NDJFM_twicedaily.1980-2019.nc'\n",
    "\n",
    "# Output\n",
    "ofname='era5.z500_u250_pna_5dyrm_NDJFM_twicedaily.1980-2019.nc'\n",
    "outfile=path+ofname"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Read the data"
   ]
  },
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   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_z=xr.open_dataset(path+f_z,decode_times=True)\n",
    "#ds_z"
   ]
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   "execution_count": 7,
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   "source": [
    "ds_u=xr.open_dataset(path+f_u,decode_times=True)\n",
    "#ds_u"
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       "</style><div class='xr-wrap'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-5dfe517c-f72b-45c0-abc0-2637f72eb04c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5dfe517c-f72b-45c0-abc0-2637f72eb04c' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 22</li><li><span class='xr-has-index'>lon</span>: 53</li><li><span class='xr-has-index'>time</span>: 14580</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9330f62f-2741-45bb-ad6c-69d412ce8b55' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9330f62f-2741-45bb-ad6c-69d412ce8b55' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>151.9 154.7 157.5 ... 295.3 298.1</div><input id='attrs-dc9da162-0f23-4fa8-a05a-19fc870468b7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dc9da162-0f23-4fa8-a05a-19fc870468b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-73660144-802d-4db6-85c3-33fb953b5c74' class='xr-var-data-in' type='checkbox'><label for='data-73660144-802d-4db6-85c3-33fb953b5c74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>array([151.875 , 154.6875, 157.5   , 160.3125, 163.125 , 165.9375, 168.75  ,\n",
       "       171.5625, 174.375 , 177.1875, 180.    , 182.8125, 185.625 , 188.4375,\n",
       "       191.25  , 194.0625, 196.875 , 199.6875, 202.5   , 205.3125, 208.125 ,\n",
       "       210.9375, 213.75  , 216.5625, 219.375 , 222.1875, 225.    , 227.8125,\n",
       "       230.625 , 233.4375, 236.25  , 239.0625, 241.875 , 244.6875, 247.5   ,\n",
       "       250.3125, 253.125 , 255.9375, 258.75  , 261.5625, 264.375 , 267.1875,\n",
       "       270.    , 272.8125, 275.625 , 278.4375, 281.25  , 284.0625, 286.875 ,\n",
       "       289.6875, 292.5   , 295.3125, 298.125 ])</pre></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>79.53 76.74 73.95 ... 23.72 20.93</div><input id='attrs-a1e79764-5f4f-47f2-bae8-772f397c40e0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a1e79764-5f4f-47f2-bae8-772f397c40e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c21c078b-d6eb-4b73-a5c5-717fcddf2659' class='xr-var-data-in' type='checkbox'><label for='data-c21c078b-d6eb-4b73-a5c5-717fcddf2659' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>array([79.53, 76.74, 73.95, 71.16, 68.37, 65.58, 62.79, 60.  , 57.21, 54.42,\n",
       "       51.63, 48.84, 46.04, 43.25, 40.46, 37.67, 34.88, 32.09, 29.3 , 26.51,\n",
       "       23.72, 20.93])</pre></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1980-01-01 ... 2019-12-31T12:00:00</div><input id='attrs-282d61aa-34d9-46d3-8e08-1ce2871869c6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-282d61aa-34d9-46d3-8e08-1ce2871869c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa616372-368e-4363-aac6-8ef9f7261285' class='xr-var-data-in' type='checkbox'><label for='data-aa616372-368e-4363-aac6-8ef9f7261285' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>array([&#x27;1980-01-01T00:00:00.000000000&#x27;, &#x27;1980-01-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1980-01-02T00:00:00.000000000&#x27;, ..., &#x27;2019-12-30T12:00:00.000000000&#x27;,\n",
       "       &#x27;2019-12-31T00:00:00.000000000&#x27;, &#x27;2019-12-31T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></li></ul></div></li><li class='xr-section-item'><input id='section-cc62f312-3855-4baa-aacf-3e194cfba09e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-cc62f312-3855-4baa-aacf-3e194cfba09e' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>z500</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-808b0967-f74e-42b9-aeb0-c1ff506c2501' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-808b0967-f74e-42b9-aeb0-c1ff506c2501' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3a3cdfd-8e68-472f-9ea1-97668cd3dce8' class='xr-var-data-in' type='checkbox'><label for='data-e3a3cdfd-8e68-472f-9ea1-97668cd3dce8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>129</dd><dt><span>GRIB_shortName :</span></dt><dd>z</dd><dt><span>GRIB_units :</span></dt><dd>m**2 s**-2</dd><dt><span>GRIB_name :</span></dt><dd>Geopotential</dd><dt><span>GRIB_cfName :</span></dt><dd>geopotential</dd><dt><span>GRIB_cfVarName :</span></dt><dd>z</dd><dt><span>GRIB_dataType :</span></dt><dd>an</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>359.75</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>long_name :</span></dt><dd>Geopotential</dd><dt><span>units :</span></dt><dd>m**2 s**-2</dd><dt><span>standard_name :</span></dt><dd>geopotential</dd></dl></div><pre class='xr-var-data'>[17000280 values with dtype=float64]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>u250</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1578b3e7-2ee9-4cd5-ae20-095f8fba55df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1578b3e7-2ee9-4cd5-ae20-095f8fba55df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a814fcae-3593-4ed1-87a9-e9abf17b2319' class='xr-var-data-in' type='checkbox'><label for='data-a814fcae-3593-4ed1-87a9-e9abf17b2319' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>131</dd><dt><span>GRIB_shortName :</span></dt><dd>u</dd><dt><span>GRIB_units :</span></dt><dd>m s**-1</dd><dt><span>GRIB_name :</span></dt><dd>U component of wind</dd><dt><span>GRIB_cfName :</span></dt><dd>eastward_wind</dd><dt><span>GRIB_cfVarName :</span></dt><dd>u</dd><dt><span>GRIB_dataType :</span></dt><dd>an</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>359.75</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>long_name :</span></dt><dd>U component of wind</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>standard_name :</span></dt><dd>eastward_wind</dd></dl></div><pre class='xr-var-data'>[17000280 values with dtype=float64]</pre></li></ul></div></li><li class='xr-section-item'><input id='section-6aceaf46-f2b3-4cba-a3b2-521fc5e4b9aa' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6aceaf46-f2b3-4cba-a3b2-521fc5e4b9aa' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (lat: 22, lon: 53, time: 14580)\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 151.9 154.7 157.5 160.3 ... 289.7 292.5 295.3 298.1\n",
       "  * lat      (lat) float64 79.53 76.74 73.95 71.16 ... 29.3 26.51 23.72 20.93\n",
       "  * time     (time) datetime64[ns] 1980-01-01 ... 2019-12-31T12:00:00\n",
       "Data variables:\n",
       "    z500     (time, lat, lon) float64 ...\n",
       "    u250     (time, lat, lon) float64 ..."
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = xr.merge([ds_z,ds_u])\n",
    "#ds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Put data in consecutive order"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "#ds=ds.reindex(time=sorted(ds['time'].values))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Quick look plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<xarray.Dataset>\n",
      "Dimensions:  (lat: 22, lon: 53, time: 2)\n",
      "Coordinates:\n",
      "  * lon      (lon) float64 151.9 154.7 157.5 160.3 ... 289.7 292.5 295.3 298.1\n",
      "  * lat      (lat) float64 79.53 76.74 73.95 71.16 ... 29.3 26.51 23.72 20.93\n",
      "  * time     (time) datetime64[ns] 1980-12-03 1980-12-03T12:00:00\n",
      "Data variables:\n",
      "    z500     (time, lat, lon) float64 ...\n",
      "    u250     (time, lat, lon) float64 ...\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x2ba543abc6d8>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAD4CAYAAADiry33AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAeeElEQVR4nO2df8xd9X3fX28MTgiQYEIgYEzwkGWVoOJolpOWTSNJQcZjZa26FW+jpKvkpgtSomVaSCctW6RKkaZky0YW6gZEsqWkkRIS1LoJFmtEojQJDoMGMB4OocWxhUXjGDNYkPFnfzznhsv1vc9z7/n5/Z7zfkmPnnvPPfec7/n+eJ3P/ZxfigiMMcb0l1O6LoAxxphmseiNMabnWPTGGNNzLHpjjOk5Fr0xxvScU7suwDRWn3J6nH7q67suhpnCidNP67oIJ/Hya9V1EYzpnBcPH3g2It407bMkRX/6qa/nl8/7za6LYcZ48fK1XRfhJI5sXN11EYxJhr/6r//6r2d9lqToTVqkJHnL3ZjFsejNsqQi+SEL/tilJyp9/6wf+lDc0LHozVQs+PapKvR5lmvpDxOL3pxECpLvu+Cbkvq867Xwh4VFb15F15Lvo+C7kvpyWPjDwqI3gAVfFylKfTmOXXrCsh8AK7awpHWS/kLSXkmPSnp/Mf0cSbslPVH8XzPj+1sl7ZO0X9ItdW+AqU6Xkj+ycXW2kj926YmT/nIk13Kb+ZlnV34c+GBE/ALwDuB9ki4DbgHui4gNwH3F+1chaRXwKeBa4DJge/FdkwhdST5HwfdB6rPo2/aYV7Ni6iYiDgGHitfHJO0F1gLXA1cVs30W+AbwoYmvbwH2R8STAJK+UHzvsRrKbirSpeRzwQI0fWChHL2kS4C3Ad8Fzi92AkTEIUnnTfnKWuDpsfcHgLfPWPYOYAfAa1edtUixTCbkInjL3fSNuUUv6UzgS8AHIuI5aa77i0ybaeojrSJiJ7AT4A2rz/djr3pGDpIfsuB9QLbfzCV6SaexJPnPR8SXi8nPSLqgiOYvAA5P+eoBYN3Y+4uAg1UKbOqhzbRNypIfstzBgh8K85x1I+B2YG9EfGLso3uAm4rXNwFfnfL1B4ANktZLWg3cUHzPDIRUJd/HA6qLYskPh3la+krgRuBdkh4q/rYBHwOulvQEcHXxHkkXStoFEBHHgZuBrwN7gS9GxKMNbIdZgLai+RQlb8EvYckPi3nOuvkW03PtAO+eMv9BYNvY+13ArrIFNHmSkuQtdjN0fGXswGgjmk9F8hb8dBzNDw+L3tRKCpK34GdjyQ+TJEV/4vTTfh55nv7IjzsuTX9oOprvWvIW/PJY8sMlSdGPMykniz9NupS8Bb8ylvywSV70k0yLSi3/lWkymu9K8hb8fFjyJjvRT8NRf3dY8mljyRvoiegnsfhfTdf3mq8TC35+LHkzopein2RcdEOXfp20Hc1b8vNjyZtxBiH6cYYm/aai+TYlb8HPjwVvpjE40Y8zNOnXhSWfJpa8mcWgRT9OH6Wfc27egl8MS94sh0U/BR/MnU0b0bwlvxiWvFkJi34OchR/E9F805K34BfHkjfzYNGXYDmJprATyDFlY8kb0xwWfc3MkmxbO4Acz7Kx5MvhaN7Mi0XfEm2kfxzJDwdL3izCiqKXdAdwHXA4Ii4vpv0JsLGY5WzgpxGxacp3nwKOAS8DxyNic03lzp66786Z271sLPhyWPCmDPNE9HcCtwKfG02IiN8cvZb0ceDoMt9/Z0Q8W7aAfacO4Vvyw8CSN2VZsedExP3AT6Z9Vjw4/J8Cd9VcrsFRVta5pWss+XJY8vWyZt9LrNn3UtfFaI2qOfq/DzwTEU/M+DyAeyUF8IcRsbPi+nrNotF9bg8SseTLYcnPpqqsy3y/6wfslKGq6LezfDR/ZUQclHQesFvS48UvhJOQtAPYAfCa155dsVh58+Lla1eUvSU/DCz5V0glAp9WjtTlX1r0kk4Ffh34u7PmiYiDxf/Dku4GtgBTRV9E+zsBXnf+ujiycXUyDdsFy0X3OaVrLPjyWPLpyH0lxsuZovSrRPS/AjweEQemfSjpDOCUiDhWvL4G+OgiK5issFwavU4mhd+G5OvqqJZ8eYYs+dzH+WT5UxD/PKdX3gVcBZwr6QDwkYi4HbiBibSNpAuBz0TENuB84O6l47WcCvxxRHytSmGHLP62onhLvnss+X4x2qYuhb+i6CNi+4zp75ky7SCwrXj9JHBFxfIty3jF9bGD5IolbxZlCOO3S+H35spYS786KfzEHDpDi+aHOFa7EH4ve9WRjat//mfmwymb7rHkh0Wb29/7nmXht4clXx5Lfpi0VQ+D6V0W/mzqqBdLvjyW/LBpoz56k6Ofl5HU3NmWsOS7ZUiS95jrjuH0sgkc4RvTHpb88jRdP4MV/Yghy97RfLcMJZq35OejyXoaRk9bgSHK3pLvlr5LfnR3SEt+MZqqr373tgUYouyrYMmbaVju1Wmi/iz6MYYi+6rbaclXo4/RvAWfNv3rcRXpu+z7vn2p0yfJOz3THHXXaX96nVkR5+VNXVjueWHRT8FR73Qs+Wr0IZp3BN8eddZz/j3PzIXz8t3SF8mbPMm/9zVEn6J6S95UwVF8/gzuFghDo087rFmcuf7o1OnP/+gNLZdkOjlH8xZ8P7DolyH359b2+eDrLLnPmqcr6ecq+Zz7vTmZFXuhpDskHZb0yNi0/yDpx5IeKv62zfjuVkn7JO2XdEudBTfNk5rkz1x/9Od/phmcpkmLutpinnDjTmDrlOn/OSI2FX+7Jj+UtAr4FHAtcBmwXdJlVQrbBbmmPvqWl68q9y52DjlF8xZ8v5nnmbH3S7qkxLK3APuLZ8ci6QvA9cBjJZZlFqBPkq9T0GeuP5pM3j4VLPdhUCXkuFnSXxWpnTVTPl8LPD32/kAxbSqSdkjaI2nP8Rf/b4ViDZtcf4FMknuKJodo3pIfDmV746eBS4FNwCHg41Pm0ZRpMWuBEbEzIjZHxOZTTz+jZLGaIRd59uXga86Ch/Ql7zTN8Ch11k1EPDN6LemPgD+dMtsBYN3Y+4uAg2XWZ9rBku83lnt+1BVklhK9pAsi4lDx9teAR6bM9gCwQdJ64MfADcA/K1XKBEj9VMvc8/J9EXyK0XzK/da0w4qil3QXcBVwrqQDwEeAqyRtYikV8xTwu8W8FwKfiYhtEXFc0s3A14FVwB0R8eg8hXr5NUviSXHQpEguqaVZWPLNYMHnTZ3jep6zbrZPmXz7jHkPAtvG3u8CTjr1cl4mo8yuB1KKUX3ueXlLvn5S66Ome7K6MnZcSCkNrK6w5M04FryZRba2PHbpiU4klUqaxJJPhxSCDku+X9Ttmawi+mmMZJXCYGuLVHY2ZelK8k1cLNV1v7Pg+0cT4zt70Y9oU/hd5urr6gRdRPN9iuK7xoI3i9C7MLjr0wSbxJJPi66ieUu+vzT1a713ood28ve5p0/axJKvD0u+nxzZuLpRp/RS9CP6JPuco/m+YcmbOmnDI70WPfRD9jn/ekglms/9rpWWfD9pa2z3XvTmFdqO5lORfJ10Ec1b8v2kzQBuEKLPOarPNZq35OvBku8nbY/rQYge8pR9nctsM5rvo+S7wJI3dTEY0bdBqtH30CVfR36+7Wjeku8vXXiiNxdMzUMbd8QcNWLVgZrqTsM0g8U+DLoa14MSPbR3++MqV886ZZMWTfSXLsU+rX95R9NvBif6NknxtsZNkarkUzqtss2+sGiwsNz8Q+nDTdPlr/RBir7Nh5rMm8ppohO0Fc2nKvk6qKOftCHKLs788g5gfrpOxQ5S9ND+E6wmG3rNvpc6b3zTPLlLfpH1WvzTSWGcz/MowTuA64DDEXF5Me0/Af8IeAn4IfDbEfHTKd99CjgGvAwcj4jN9RU9b5pufEfz1akaCPRZ8tNw7v/VpNQ28/TkO4GtE9N2A5dHxC8C/wf48DLff2dEbEpR8r7vS7/pMj8/NMnPYnSzrqZv2pUaqW3riqKPiPuBn0xMuzcijhdvvwNc1EDZTEkczVenSjRvyc9mCNJPcdvqyNH/S+BPZnwWwL2SAvjDiNg5ayGSdgA7AFatWVNDseaj7Vx9X+iz5MvSVpoiRZGUoY85/lTbppLoJf074Djw+RmzXBkRByWdB+yW9HjxC+Ekip3AToDXXLwuqpRryDgdtUSVtE2ZHb8lX53xbctN+qm3S+lQVtJNLB2k/ecRMVXMEXGw+H8YuBvYUnZ9TWI5Loaj+W5IXSZ1klOKJ4cyloroJW0FPgT8g4h4YcY8ZwCnRMSx4vU1wEdLl9SsiHdY3ZBb9JkbqaZ4chD8iBUjekl3AX8JbJR0QNLvALcCZ7GUjnlI0m3FvBdK2lV89XzgW5IeBr4H/FlEfK2RragBS3I++h7NL5q2SUU6QyKFaD8nycMcEX1EbJ8y+fYZ8x4EthWvnwSuqFQ6MzfeUb1CW6dVpnxLg6HQdrTfdTuUHeeDvTJ2Gj4DZ3n6Hs2b/Klb/F2LHeoJ4iz6HuBovh4W2ck7ZZMHK4k65VuR1DmuHb5OkJs0cytvH7Dk+0OKkj926Ynax7VFP4Vc5Ol7zZ9MSrclrosUZWSaoakx7dSNMQvgaN40QdNBmyP6GaQe1adevtzwQXjTFW2M5Swi+sm0QVs/z1M9C6dtyeeStukjTtv0lzbHcZKiX/Wal5eVy5nrj/YyFzsPjuS7w2kbUxdtj+P0wtU5OXP90VYiTYs1H4a68zd50YVTshX9iCHJvotyDCFtM096roto3mmbftHEaZPzkr3oYRiy73r9xpjydD1+eyF66Lfsu+4kpn0czfeHFMZvkgdjU6btM3FS6CSmXVKRfNW+l+IZa22TyvjtlejbOhunLdmn0klywAdiq1N3f5u2vCHJP6Xx2yvRt8moEZvquCl1EtNf2u5nk+vrq/hTG7+9E33b59jXHd2n1kFMu7SRtkmpj61Ulhx3BCnV74jeib4L6ojuU+wcuZxaWXXHnuoV0HWTYh9biVllTrW9Uq3jeR4leIekw5IeGZt2jqTdkp4o/q+Z8d2tkvZJ2i/pljoLvhxdCWrR82RH86faOUw/6GMfGx87qWxbKuWYxjy7xTuBrRPTbgHui4gNwH3F+1chaRXwKeBa4DJgu6TLKpV2AbqMRic74GSnTKlzmnSoO20zpH7W9bhKvZ7neWbs/ZIumZh8PXBV8fqzwDeAD03MswXYXzw7FklfKL73WOnSZkjqHSB3fLbNyQy9z7V9wLfr+p4nqC2boz8/Ig4BRMQhSedNmWct8PTY+wPA22ctUNIOYAfAaW/y4DVpcWTj6kZvg1BXNN+1dFKkyWMwudyWpMldnaZMi1kzR8TOiNgcEZtPfcPrailALgcTTTnajuabOiOmjuUOKU1Thj7UTZUbOZYV/TOSLgAo/h+eMs8BYN3Y+4uAgyXXZ0yjdCWCuiRv2ienR3mWFf09wE3F65uAr06Z5wFgg6T1klYDNxTfM6YyXeXmj2xcncwtCsCSX4Qc66qu27HPc3rlXcBfAhslHZD0O8DHgKslPQFcXbxH0oWSdgFExHHgZuDrwF7gixHxaOUSG9MQi4igquzr2GHkKK6+0HTd1/28jXnOutk+46N3T5n3ILBt7P0uYFfp0tXAkJ9G1VdSac+RqBc9SJvSL4KhkcPFcU0cW0x7i41pmTKR2rzirjPt42i+PFXrrsm6b+oEEt8CwWRFKtH8JJMCH4/ym7gQyvSLps8QtOhNNqQq+Wk0lZ6x5OuhbAqnifpv4zTwQYjeeXqzCKnmcbuU/Lwy6vM4y1XyMBDRm8VJ7WKztgWSmuzbkHwdbT5tGanKv+s2bnOMWfRmKs//6A3JyL4rUXQtglEZmqKt9h1fT6rSb5u2x5ZFb0yCNCX4rnfeln43bWDRm6TpWgZ9eRh814KfxqhMXbfxvJz1w1OyPRhu0ZtkSUUAbch+SIKfpCvhd5GW66o90jnaZEzCNBnJDVny49R92X9qdLltjuhNkqQSzY+Ty4Pgc5dlbimdeei6TSx6kxwpD/BxOadywc2IrmVSN77+pT4semNKMq/0czkHPkX6IPsU2saiN0mR66DO4arVXMlZ9qm0jQ/Gmpm0PbhyHcxdkopImiaV7ez6Arqy5FlqY0wy8muLFM7KWeSXW9dlHWcwok+p0o2pypD7c13bnuvFT2UoLXpJGyU9NPb3nKQPTMxzlaSjY/P8++pFNn3EaZv5GbLkR3RRB7lG81DhYGxE7AM2AUhaBfwYuHvKrN+MiOvKrscY8wqpCSR3mrjqOcU2qmsL3w38MCL+uqblGWMmSFEgXdJmCmfeaD7VNqpL9DcAd8347JckPSzpzyW9ddYCJO2QtEfSnuNHX6ipWMbkzegAZKoC6Zo2ZN+HXH7l8+glrQZ+FfjwlI8fBN4SEc9L2gZ8BdgwbTkRsRPYCfC6DRdG1XIZkzMW+/ykcp592212zcX7XvX+B8vMW8cFU9cCD0bEM5MfRMRzY693Sfrvks6NiGdrWK/pCSkM0lRIWfCTYinDvX+zsYaSnEwdsp+Wr08tmi/bBnWIfjsz0jaS3gw8ExEhaQtLqaK/rWGdpUhlz2/MJCkKvg6xL7fMuqVft+xTOsumaltUEr2k1wFXA787Nu29ABFxG/AbwO9JOg68CNwQEU7LGFOQguCbEPoi620qyi9LCo+QHKeO9qkk+oh4AXjjxLTbxl7fCtxaZR3G9JUuJd+V3KdRp/Dr+tWeQjRfZxuls9sa4/Wr/19SHXGodPHw6CHQ5Vk011y8L9mxVVfZ2qzfHCQPid+9ssl8njFd0KXgc6GuCL/pY3K5SB4SF/04qebzTD30/UC5Bb8411y8L3nZ10mTbZVk6mY5cu64OdGFmPqawrHky1NHOqeJVE7dy2u6rbKJ6Ouiqz38rI6RS7RhFscHW+ujrugeqo+53CQPmYq+jkZvg3k6RB8fhFyFnH5qz8KCb4Y6c/ew+JjLUfAjskvdjEi9Qy/aKVK6n0nX5eh6/VWw5Junru2cd8w1MTbbbqssI/oRuUT2i+AIP0+63jkNRfIj6j73fpzR2GuiTbtqp6xFnyp1dJA+pDCqkNP2O4rvjibOxuuT4Edkm7oZ0XUFTlJnJ/GZL2njC5/SIeW6SKFsvYjoF03hNBUtNjHo24xsU5N8qmksR/Bpktq1Nim1VfYR/YiuK7XJwd+GWFKT/Dgplc2ST5+u6ynFX1u9iOjLUGek3KaIc/klUjdd5uy7rp/UpJEDXUT3KbdTr0TfRQqnbQnULbyuJbYIbcu+67pJWRy50Ibwc2inXom+bboSQapX+LVBG3n7FOolB3nkRBPCz6mNeif6tqL6FGSQyhV+XdCE8FOpl5wEkhtVhZ9r2/RO9GVYVPapCGHEvNJLrdx1UFX4KdVJrhLJkXmF35c2qfoowaeAY8DLwPGI2DzxuYBPAtuAF4D3RMSDVdY5D01eMZuSGCZJuWxNM77tOe7w+iKU3BhKvdcR0b8zIp6d8dm1wIbi7+3Ap4v/jdNECidFQZiTya2dhiIb0x1Nn0d/PfC5WOI7wNmSLmh4naVZThC5ycPkgSVv2qCq6AO4V9L3Je2Y8vla4Omx9weKaSchaYekPZL2vHDkZxWLtUSZQTQS+ujy9pTuKmn6hSVv2qJq6ubKiDgo6Txgt6THI+L+sc815TsxbUERsRPYCfDmt54zdZ62sNhNk1jwpm0qRfQRcbD4fxi4G9gyMcsBYN3Y+4uAg1XWuSgeVCYl3B9NF5QWvaQzJJ01eg1cAzwyMds9wG9piXcARyPiUOnSlsSDy6SA+6HpiioR/fnAtyQ9DHwP+LOI+Jqk90p6bzHPLuBJYD/wR8C/qlTaCniQmS5x/zNdUjpHHxFPAldMmX7b2OsA3ld2HXXTxydSpcxychtSO1jypmt8ZaypjUWENm3ePsrfkjcpMDjRO6qvlzpFNr6s3NvIgjcpMTjRg2VfB02LLFfpW/AmRQYperDsy9KFyHKRviVvUmWwogfLfhFSkViK0k+lboyZxaBFD5b9cqQusK4fBp16/aTMjWu+veI8/+PIL7dQkmEweNGbk8lNYJPlHfpj41JnHsnPms/yL4dFj6N66JfAZm3Lom3cpzpJgXkFP88yLPzFsOgLhij7oYlsaNubEnVIftryLPz5aPp+9FkxFBFcc/G+wWyr6Z66Jd/WsvuEI/oJ+hrZW+ymC9oQsaP7lbHop9AX2VvupkvajrYt/NlY9DPo+tS9MljsJhW6TKlY+Cdj0a9AihfojGO5m9RIJW9u4b+CRb8AdZ22V/f6jUmFVCQ/zniZ2pL+ovXQdLks+hqwgI3Jg6ai/Ko7uDp2kB9f5jOL3hhTCylG87OYLGsZ8ee0vaVFL2kd8DngzcAJYGdEfHJinquArwI/KiZ9OSI+utKy37jqeW5c823n1ozJhJykN43cy78SVSL648AHI+LB4iHh35e0OyIem5jvmxFxXZkVdJFbM8aYvlH6ytiIOBQRDxavjwF7gbV1FWySG9d8u/d7XWNyxOMyfWq5BYKkS4C3Ad+d8vEvSXpY0p9Leusyy9ghaY+kPUd+cmLmutypjEkHj8c8qCx6SWcCXwI+EBHPTXz8IPCWiLgC+G/AV2YtJyJ2RsTmiNi85pzli+Xo3pju8RjMh0qil3QaS5L/fER8efLziHguIp4vXu8CTpN0bpV1juOOZkw3eOzlRWnRSxJwO7A3Ij4xY543F/MhaUuxvr8tu85puMMZY8zyVDnr5krgRuAHkh4qpv0+cDFARNwG/Abwe5KOAy8CN0REVFjnVHypszHt4eAqP0qLPiK+BWiFeW4Fbi27jkXxuffGNIslnye9e/CIO6Ix9eMTIPKmd6IHy96YurDg+0EvRQ+WvTFV8RjqD70VPbijGlMGR/H9o/d3r/QZOcasjMXeb3ov+hEWvjEnY8EPg8GIfoRPwTRDwzI3gxM9OLo3+WN5m0UYpOhHWPgmFyx2U4VBi36EhV8PVWTkup+NJW+qYtGPYeGvTFPSqeMZnn3Dgjd1YdFPwcJfokvRDP0xkpa8qROLfhmGJvxU5TKkdki1DUzeWPRz0FfR5CaVvkb5ubWDyQ+LfgFyzyP3SSh9kH6f2sOkjUVfgWkDNQXpDE0gOe2Ah9Y2Jg0s+pqZZyAvIiKLYXFS2wG7DU3XVBK9pK3AJ4FVwGci4mMTn6v4fBvwAvCeiHiwyjr7gAd++9RV5/PsMNy+JjVKi17SKuBTwNXAAeABSfdExGNjs10LbCj+3g58uvhvTJZY4iZHqtyPfguwPyKejIiXgC8A10/Mcz3wuVjiO8DZki6osE5jjDELUiV1sxZ4euz9AU6O1qfNsxY4NLkwSTuAHcXbn216y4FHKpQtd84Fnu26EB0y9O0H14G3f/Htf8usD6qIXlOmRYl5liZG7AR2AkjaExGbK5Qta7z9w95+cB14++vd/iqpmwPAurH3FwEHS8xjjDGmQaqI/gFgg6T1klYDNwD3TMxzD/BbWuIdwNGIOCltY4wxpjlKp24i4rikm4Gvs3R65R0R8aik9xaf3wbsYunUyv0snV7523MufmfZcvUEb78Zeh14+2tEEVNT5sYYY3pCldSNMcaYDLDojTGm5yQleklbJe2TtF/SLV2Xpw0k3SHpsKRHxqadI2m3pCeK/2u6LGOTSFon6S8k7ZX0qKT3F9MHUQeSXivpe5IeLrb/PxbTB7H9IyStkvS/Jf1p8X5o2/+UpB9IekjSnmJabXWQjOjHbqlwLXAZsF3SZd2WqhXuBLZOTLsFuC8iNgD3Fe/7ynHggxHxC8A7gPcV7T6UOvgZ8K6IuALYBGwtzlAbyvaPeD+wd+z90LYf4J0RsWns/Pna6iAZ0TPfLRV6R0TcD/xkYvL1wGeL158F/nGrhWqRiDg0utFdRBxjabCvZSB1UNwe5Pni7WnFXzCQ7QeQdBHwD4HPjE0ezPYvQ211kJLoZ90uYYicP7reoPh/XsflaQVJlwBvA77LgOqgSFs8BBwGdkfEoLYf+C/AvwVOjE0b0vbD0s79XknfL24HAzXWQUr3o5/7dgmmf0g6E/gS8IGIeG7pDtfDICJeBjZJOhu4W9LlXZepLSRdBxyOiO9Luqrr8nTIlRFxUNJ5wG5Jj9e58JQiet8u4RWeGd3ls/h/uOPyNIqk01iS/Ocj4svF5EHVAUBE/BT4BkvHbIay/VcCvyrpKZbSte+S9D8ZzvYDEBEHi/+HgbtZSmXXVgcpiX6eWyoMhXuAm4rXNwFf7bAsjVI8nOZ2YG9EfGLso0HUgaQ3FZE8kk4HfgV4nIFsf0R8OCIuiohLWBrz/ysi/gUD2X4ASWdIOmv0GrgGeIQa6yCpK2MlbWMpXze6pcIfdFykxpF0F3AVS7clfQb4CPAV4IvAxcDfAP8kIiYP2PYCSX8P+CbwA17J0f4+S3n63teBpF9k6UDbKpYCry9GxEclvZEBbP84Rerm30TEdUPafkl/h6UoHpbS6X8cEX9QZx0kJXpjjDH1k1LqxhhjTANY9MYY03MsemOM6TkWvTHG9ByL3hhjeo5Fb4wxPceiN8aYnvP/AQEyPqw5ZFnIAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tmp=ds.sel(time='19801203')\n",
    "print(tmp)\n",
    "plt.contourf(tmp['z500'][0,::-1,:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2ba543b3db70>]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(ds['z500'][0:92,12,25])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculate the 5-day running means for Z500 and U250 and combine them together in the same `xarray.Dataset`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "z500_rm=rm_season(ds['z500'],5,yrs_list,'z500')\n",
    "u250_rm=rm_season(ds['u250'],5,yrs_list,'u250')\n",
    "ds_5dayrm=xr.merge([z500_rm,u250_rm])\n",
    "#print(z500_rm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
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       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt, dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><div class='xr-wrap'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-41092282-aa50-4053-9a9a-21fda186fbfa' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-41092282-aa50-4053-9a9a-21fda186fbfa' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 22</li><li><span class='xr-has-index'>lon</span>: 53</li><li><span class='xr-has-index'>time</span>: 13984</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ec43dd1e-0ce4-4f8d-a464-8630f29324e8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ec43dd1e-0ce4-4f8d-a464-8630f29324e8' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>151.9 154.7 157.5 ... 295.3 298.1</div><input id='attrs-5ce67375-eee2-4c9e-96dc-8641bfcb8eb7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5ce67375-eee2-4c9e-96dc-8641bfcb8eb7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9718e148-d428-401f-9e5b-e7d22d04322f' class='xr-var-data-in' type='checkbox'><label for='data-9718e148-d428-401f-9e5b-e7d22d04322f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>array([151.875 , 154.6875, 157.5   , 160.3125, 163.125 , 165.9375, 168.75  ,\n",
       "       171.5625, 174.375 , 177.1875, 180.    , 182.8125, 185.625 , 188.4375,\n",
       "       191.25  , 194.0625, 196.875 , 199.6875, 202.5   , 205.3125, 208.125 ,\n",
       "       210.9375, 213.75  , 216.5625, 219.375 , 222.1875, 225.    , 227.8125,\n",
       "       230.625 , 233.4375, 236.25  , 239.0625, 241.875 , 244.6875, 247.5   ,\n",
       "       250.3125, 253.125 , 255.9375, 258.75  , 261.5625, 264.375 , 267.1875,\n",
       "       270.    , 272.8125, 275.625 , 278.4375, 281.25  , 284.0625, 286.875 ,\n",
       "       289.6875, 292.5   , 295.3125, 298.125 ])</pre></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>79.53 76.74 73.95 ... 23.72 20.93</div><input id='attrs-c8e8da91-fe09-4448-a3b2-de4e878bde4c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c8e8da91-fe09-4448-a3b2-de4e878bde4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6f2df9fa-c2b4-4016-b709-e36cb7574dc1' class='xr-var-data-in' type='checkbox'><label for='data-6f2df9fa-c2b4-4016-b709-e36cb7574dc1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>array([79.53, 76.74, 73.95, 71.16, 68.37, 65.58, 62.79, 60.  , 57.21, 54.42,\n",
       "       51.63, 48.84, 46.04, 43.25, 40.46, 37.67, 34.88, 32.09, 29.3 , 26.51,\n",
       "       23.72, 20.93])</pre></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1980-11-02 ... 2019-12-30T12:00:00</div><input id='attrs-021cd80f-d705-4925-b6da-adb614d8beed' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-021cd80f-d705-4925-b6da-adb614d8beed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ebb9b7a-ff72-4c6e-bb4c-26fa3908a158' class='xr-var-data-in' type='checkbox'><label for='data-1ebb9b7a-ff72-4c6e-bb4c-26fa3908a158' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>array([&#x27;1980-11-02T00:00:00.000000000&#x27;, &#x27;1980-11-02T12:00:00.000000000&#x27;,\n",
       "       &#x27;1980-11-03T00:00:00.000000000&#x27;, ..., &#x27;2019-12-29T12:00:00.000000000&#x27;,\n",
       "       &#x27;2019-12-30T00:00:00.000000000&#x27;, &#x27;2019-12-30T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></li></ul></div></li><li class='xr-section-item'><input id='section-735bf324-e291-41fa-bbc5-1810c680e809' class='xr-section-summary-in' type='checkbox'  checked><label for='section-735bf324-e291-41fa-bbc5-1810c680e809' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>z500</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.076e+04 5.083e+04 ... 5.763e+04</div><input id='attrs-7e4c344f-9387-4604-ad5f-38c109d32340' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7e4c344f-9387-4604-ad5f-38c109d32340' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c3cd549-a5c0-48c5-b667-e8ebc6396e35' class='xr-var-data-in' type='checkbox'><label for='data-1c3cd549-a5c0-48c5-b667-e8ebc6396e35' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>array([[[50756.40084375, 50832.58184375, 50911.36184375, ...,\n",
       "         49199.61584375, 49294.00334375, 49401.24984375],\n",
       "        [50659.30284375, 50731.13084375, 50792.09384375, ...,\n",
       "         48819.84984375, 48902.57534375, 49018.10084375],\n",
       "        [50584.84984375, 50616.92734375, 50632.37984375, ...,\n",
       "         48623.08984375, 48745.15234375, 48881.22484375],\n",
       "        ...,\n",
       "        [57898.46784375, 57969.22184375, 58055.66184375, ...,\n",
       "         57542.32584375, 57573.29734375, 57642.98284375],\n",
       "        [58059.68884375, 58133.42384375, 58212.90784375, ...,\n",
       "         57674.28384375, 57710.27784375, 57740.92584375],\n",
       "        [58099.39984375, 58162.32584375, 58200.01784375, ...,\n",
       "         57721.86784375, 57739.55484375, 57733.49584375]],\n",
       "\n",
       "       [[50705.5628125 , 50788.8068125 , 50872.7898125 , ...,\n",
       "         49610.1978125 , 49716.5708125 , 49833.2518125 ],\n",
       "        [50578.9068125 , 50640.9303125 , 50695.2418125 , ...,\n",
       "         49320.9078125 , 49424.9673125 , 49558.5208125 ],\n",
       "        [50459.0878125 , 50477.0003125 , 50482.3178125 , ...,\n",
       "         49123.9578125 , 49258.2903125 , 49399.2078125 ],\n",
       "        ...,\n",
       "        [57832.5228125 , 57915.2868125 , 58000.6278125 , ...,\n",
       "         57535.9398125 , 57561.3583125 , 57617.4098125 ],\n",
       "        [58017.9478125 , 58100.5278125 , 58188.7018125 , ...,\n",
       "         57671.9538125 , 57700.5868125 , 57726.3448125 ],\n",
       "        [58074.5778125 , 58151.2613125 , 58198.8558125 , ...,\n",
       "         57731.8958125 , 57735.6688125 , 57726.0838125 ]],\n",
       "\n",
       "       [[50704.727875  , 50790.796875  , 50876.879875  , ...,\n",
       "         50119.365875  , 50210.366375  , 50305.533875  ],\n",
       "        [50520.303875  , 50584.352375  , 50630.307875  , ...,\n",
       "         49846.193875  , 49929.781375  , 50042.008875  ],\n",
       "        [50345.866875  , 50350.644375  , 50340.291875  , ...,\n",
       "         49641.491875  , 49765.606875  , 49894.781875  ],\n",
       "        ...,\n",
       "        [57735.799875  , 57807.587375  , 57903.463875  , ...,\n",
       "         57575.685875  , 57592.692875  , 57638.672875  ],\n",
       "        [57963.982875  , 58047.020875  , 58135.231875  , ...,\n",
       "         57696.549875  , 57711.971875  , 57737.289875  ],\n",
       "        [58047.311875  , 58115.905875  , 58165.333875  , ...,\n",
       "         57736.801875  , 57734.857875  , 57721.876875  ]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[48451.2873125 , 48453.8723125 , 48469.3753125 , ...,\n",
       "         48947.7373125 , 49090.6878125 , 49210.8043125 ],\n",
       "        [48915.3423125 , 48908.9368125 , 48924.7693125 , ...,\n",
       "         49365.5473125 , 49469.8778125 , 49555.4393125 ],\n",
       "        [49543.0303125 , 49600.8078125 , 49643.7353125 , ...,\n",
       "         49857.3953125 , 49903.4278125 , 49910.2903125 ],\n",
       "        ...,\n",
       "        [57187.5613125 , 57018.1253125 , 56841.2013125 , ...,\n",
       "         57575.1953125 , 57452.3993125 , 57322.9583125 ],\n",
       "        [57715.7013125 , 57631.9283125 , 57532.1693125 , ...,\n",
       "         57693.8173125 , 57608.8588125 , 57499.0793125 ],\n",
       "        [57989.7503125 , 57933.5733125 , 57872.9233125 , ...,\n",
       "         57748.1133125 , 57680.0553125 , 57607.2203125 ]],\n",
       "\n",
       "       [[48394.31359375, 48371.96109375, 48355.02259375, ...,\n",
       "         48063.22859375, 48270.92659375, 48457.97659375],\n",
       "        [48849.37659375, 48801.40909375, 48749.74259375, ...,\n",
       "         48595.97859375, 48770.64259375, 48925.58259375],\n",
       "        [49436.55859375, 49411.01109375, 49372.48859375, ...,\n",
       "         49262.56859375, 49382.18109375, 49477.48359375],\n",
       "        ...,\n",
       "        [57300.67459375, 57132.88009375, 56947.76259375, ...,\n",
       "         57603.99259375, 57478.02059375, 57334.41159375],\n",
       "        [57762.52359375, 57676.21059375, 57570.35459375, ...,\n",
       "         57708.68459375, 57625.81509375, 57513.39559375],\n",
       "        [58011.17659375, 57955.45459375, 57882.66459375, ...,\n",
       "         57747.87459375, 57679.67409375, 57601.46359375]],\n",
       "\n",
       "       [[48501.4143125 , 48490.8508125 , 48483.1443125 , ...,\n",
       "         47160.4643125 , 47380.0853125 , 47592.2283125 ],\n",
       "        [48956.2603125 , 48913.5053125 , 48860.2083125 , ...,\n",
       "         47742.0623125 , 47939.2518125 , 48134.4883125 ],\n",
       "        [49541.9653125 , 49504.4228125 , 49443.7703125 , ...,\n",
       "         48605.6903125 , 48759.9178125 , 48908.8503125 ],\n",
       "        ...,\n",
       "        [57392.3283125 , 57252.4068125 , 57093.6063125 , ...,\n",
       "         57619.7763125 , 57509.7678125 , 57378.2193125 ],\n",
       "        [57791.2473125 , 57720.2998125 , 57626.0403125 , ...,\n",
       "         57727.4683125 , 57655.8193125 , 57554.7473125 ],\n",
       "        [58021.0733125 , 57965.5388125 , 57901.6703125 , ...,\n",
       "         57754.7303125 , 57702.8493125 , 57630.1193125 ]]])</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>u250</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.101 -3.222 -3.08 ... 9.595 9.217</div><input id='attrs-32eb223d-ca37-47ed-8ba8-93e8fb2cafb9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-32eb223d-ca37-47ed-8ba8-93e8fb2cafb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8766bca0-926b-4afe-b33b-759e8a558ff3' class='xr-var-data-in' type='checkbox'><label for='data-8766bca0-926b-4afe-b33b-759e8a558ff3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>array([[[ -3.10109619,  -3.22177588,  -3.07995557, ..., -14.66123682,\n",
       "         -14.18590088, -13.65325244],\n",
       "        [ -0.33587744,  -0.52748682,  -0.64486182, ...,  -8.29542432,\n",
       "          -8.08784619,  -8.05973682],\n",
       "        [ -0.90359619,  -1.13718994,  -1.83554932, ...,  -3.69351807,\n",
       "          -3.12746338,  -2.27906494],\n",
       "        ...,\n",
       "        [ 13.90152881,  12.06050537,  10.25057568, ...,  16.05854443,\n",
       "          13.26509912,  10.06531006],\n",
       "        [  0.84754443,  -0.85989307,  -1.88767432, ...,   5.60416943,\n",
       "           7.36609131,   6.73107568],\n",
       "        [ -7.46081494, -10.97553369, -13.05123682, ...,   9.71960693,\n",
       "           8.2477085 ,   7.04491943]],\n",
       "\n",
       "       [[ -2.514474  ,  -2.64095056,  -2.53625525, ..., -12.97600525,\n",
       "         -12.22165369, -11.54661462],\n",
       "        [ -0.81188025,  -1.21819275,  -1.68519275, ...,  -7.61619275,\n",
       "          -7.20017712,  -7.14708337],\n",
       "        [ -1.44983337,  -2.098974  ,  -2.94100525, ...,  -5.14256775,\n",
       "          -4.29823181,  -3.66827087],\n",
       "        ...,\n",
       "        [ 15.15986975,  12.71592444,  11.277651  , ...,  19.700776  ,\n",
       "          16.57314319,  15.01135413],\n",
       "        [  2.55713538,  -0.13629431,  -0.71969275, ...,  10.198776  ,\n",
       "           8.28409631,   7.47079163],\n",
       "        [ -4.70348962,  -8.0177865 , -11.165224  , ...,   9.104526  ,\n",
       "           7.37179163,   5.67882288]],\n",
       "\n",
       "       [[ -3.29043555,  -3.53829492,  -3.67474805, ..., -10.7394043 ,\n",
       "         -10.0694668 ,  -9.36249805],\n",
       "        [ -2.45231055,  -2.9231543 ,  -3.58087305, ...,  -6.36631055,\n",
       "          -5.86080273,  -5.6794043 ],\n",
       "        [ -2.55706055,  -3.31006836,  -4.3231543 , ...,  -5.50456055,\n",
       "          -4.37202148,  -3.36010742],\n",
       "        ...,\n",
       "        [ 16.09289258,  15.01833789,  13.53918945, ...,  19.3084707 ,\n",
       "          17.0828457 ,  16.13243945],\n",
       "        [  5.35201758,   2.40057227,   1.46468945, ...,  12.2670957 ,\n",
       "          10.79120508,   8.53826758],\n",
       "        [ -0.8745293 ,  -4.32860742,  -7.30049805, ...,   9.78481445,\n",
       "           6.80310352,   5.8879082 ]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[  2.1010509 ,   2.33480481,   2.85947278, ...,   7.78464465,\n",
       "           7.34862512,   6.7150509 ],\n",
       "        [  9.82641809,  10.51704309,  10.9296759 , ...,  12.10856653,\n",
       "          10.29783997,   8.68685559],\n",
       "        [ 13.77776184,  14.000047  ,  15.00787903, ...,  12.7346759 ,\n",
       "          11.70201965,  10.94350403],\n",
       "        ...,\n",
       "        [ 44.6343634 ,  46.55278918,  49.07666028, ...,  16.63644153,\n",
       "          17.09005481,  19.0096759 ],\n",
       "        [ 30.40647278,  32.58852747,  34.56114465, ...,  12.41414465,\n",
       "          14.20616809,  14.94033997],\n",
       "        [ 19.89725403,  20.61930481,  22.05866028, ...,  13.91528528,\n",
       "          15.27203528,  15.03355872]],\n",
       "\n",
       "       [[  2.50429602,   2.19137024,   2.48424133, ...,   7.41125696,\n",
       "           7.61741711,   7.32735852],\n",
       "        [  9.48325696,   9.83289368,   9.98152258, ...,  14.65308508,\n",
       "          12.80350305,  11.3287179 ],\n",
       "        [ 12.78064758,  12.80549133,  13.27650696, ...,  16.54252258,\n",
       "          15.52344055,  14.95654602],\n",
       "        ...,\n",
       "        [ 43.37928821,  45.80736243,  48.70952258, ...,  14.79599133,\n",
       "          15.87785071,  17.44302258],\n",
       "        [ 29.36425696,  31.65165149,  34.08272571, ...,  10.75714758,\n",
       "          11.81586633,  12.64517102],\n",
       "        [ 20.71789758,  20.59229211,  21.94153821, ...,  11.17391321,\n",
       "          12.09225305,  11.84820227]],\n",
       "\n",
       "       [[  2.6939635 ,   2.37403381,   2.667026  , ...,   7.0219635 ,\n",
       "           7.33408069,   7.530026  ],\n",
       "        [  9.63413538,   9.72443225,   9.22605725, ...,  16.66811975,\n",
       "          15.30612756,  14.26076038],\n",
       "        [ 11.94001038,  11.94231506,  12.07336975, ...,  19.56493225,\n",
       "          18.79688538,  18.26016663],\n",
       "        ...,\n",
       "        [ 41.90468225,  43.72948694,  46.3587135 , ...,  15.0149635 ,\n",
       "          15.67170569,  16.49943225],\n",
       "        [ 29.1273385 ,  30.45036975,  32.7300885 , ...,   9.395276  ,\n",
       "          10.318401  ,  10.75401038],\n",
       "        [ 21.4038385 ,  21.18034631,  21.167151  , ...,   8.53405725,\n",
       "           9.59455725,   9.21699475]]])</pre></li></ul></div></li><li class='xr-section-item'><input id='section-f31753bd-bf28-4b09-895f-cdf87a895c45' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f31753bd-bf28-4b09-895f-cdf87a895c45' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (lat: 22, lon: 53, time: 13984)\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 151.9 154.7 157.5 160.3 ... 289.7 292.5 295.3 298.1\n",
       "  * lat      (lat) float64 79.53 76.74 73.95 71.16 ... 29.3 26.51 23.72 20.93\n",
       "  * time     (time) datetime64[ns] 1980-11-02 ... 2019-12-30T12:00:00\n",
       "Data variables:\n",
       "    z500     (time, lat, lon) float64 5.076e+04 5.083e+04 ... 5.77e+04 5.763e+04\n",
       "    u250     (time, lat, lon) float64 -3.101 -3.222 -3.08 ... 8.534 9.595 9.217"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#ds_5dayrm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Quick look plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x2ba543bfd5f8>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.contourf(ds_5dayrm['z500'][0,::-1,:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2ba54b8e4dd8>]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(ds_5dayrm['z500'][:,12,25])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2ba5535ca048>]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(ds['z500'][0:88,12,25])\n",
    "plt.plot(ds_5dayrm['z500'][0:88,12,25])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Write to netcdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_5dayrm.to_netcdf(outfile)"
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   "outputs": [],
   "source": []
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