CouplingIndex_DevelopIndependentFunction.ipynb

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    "import numpy as np \n",
    "import xarray as xr \n",
    "import pandas as pd\n",
    "import datetime\n",
    "import comet as cm\n",
    "\n",
    "# Plotting utils \n",
    "import matplotlib.pyplot as plt \n",
    "import matplotlib.colors as colors\n",
    "import cartopy\n",
    "import cartopy.feature as cfeature\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.util\n",
    "\n",
    "\n"
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   "source": [
    "### Read in data"
   ]
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     "text": [
      "Finished reading in CAM file\n",
      "Finished reading in CLM file\n"
     ]
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      "<ipython-input-2-85d09a089033>:7: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  camDS_CLM45['time'] = camDS_CLM45.indexes['time'].to_datetimeindex()\n",
      "<ipython-input-2-85d09a089033>:11: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  clmDS_CLM45['time'] = clmDS_CLM45.indexes['time'].to_datetimeindex()\n"
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    "dataDir = '/Users/mdfowler/Documents/Analysis/Coupling_initial/data/day/CLM5_revertVars/'\n",
    "\n",
    "fileCLM = dataDir+'f.e21.FHIST.f09_f09_mg17.CESM2-CLM45physics.002.clm2.h1.1979-83_SoilWater10cm.nc'\n",
    "fileCAM = dataDir+'f.e21.FHIST.f09_f09_mg17.CESM2-CLM45physics.002.cam.h1.1979-83_CIvars.nc'\n",
    "\n",
    "camDS_CLM45         = xr.open_dataset(fileCAM, decode_times=True)\n",
    "camDS_CLM45['time'] = camDS_CLM45.indexes['time'].to_datetimeindex()\n",
    "print('Finished reading in CAM file')\n",
    "\n",
    "clmDS_CLM45         = xr.open_dataset(fileCLM, decode_times=True)\n",
    "clmDS_CLM45['time'] = clmDS_CLM45.indexes['time'].to_datetimeindex()\n",
    "print('Finished reading in CLM file')\n",
    "\n"
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   "source": [
    "## Base off of Ahmed's python script here: "
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    "# Make one big xr.Dataset containing all the information we need  \n",
    "ds = camDS_CLM45\n",
    "ds['SOILWATER_10CM'] = (('time','lat','lon'), clmDS_CLM45.SOILWATER_10CM.values)\n"
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    "# # fields = ['SOILWATER_10CM','EFLX_LH_TOT']\n",
    "# fields = ['SOILWATER_10CM','FSH_TO_COUPLER']  # Soil moisture & SHFLX (as sent to coupler)\n",
    "# ds = get_ds(fields)\n",
    "# ds"
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      "/Users/mdfowler/opt/anaconda3/envs/newBase/lib/python3.8/site-packages/xarray/core/nanops.py:142: RuntimeWarning: Mean of empty slice\n",
      "  return np.nanmean(a, axis=axis, dtype=dtype)\n",
      "/Users/mdfowler/opt/anaconda3/envs/newBase/lib/python3.8/site-packages/numpy/lib/nanfunctions.py:1664: RuntimeWarning: Degrees of freedom <= 0 for slice.\n",
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    "xname = 'SOILWATER_10CM'\n",
    "yname = 'SHFLX'\n",
    "\n",
    "# xday = ds[xname].resample({'time':'1D'}).mean().groupby('time.season')\n",
    "# yday = ds[yname].resample({'time':'1D'}).mean().groupby('time.season')\n",
    "\n",
    "xday = ds[xname].groupby('time.season')\n",
    "yday = ds[yname].groupby('time.season')\n",
    "\n",
    "covarTerm = ((xday - xday.mean()) * (yday - yday.mean())).groupby('time.season').sum() / xday.count()\n",
    "\n",
    "couplingIndex = covarTerm/xday.std()\n"
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       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lat      (lat) float64 -90.0 -89.06 -88.12 -87.17 ... 87.17 88.12 89.06 90.0\n",
       "  * lon      (lon) float64 0.0 1.25 2.5 3.75 5.0 ... 355.0 356.2 357.5 358.8\n",
       "  * time     (time) datetime64[ns] 1979-01-01 1979-01-02 ... 1984-01-01\n",
       "    season   (time) &lt;U3 &#x27;DJF&#x27; &#x27;DJF&#x27; &#x27;DJF&#x27; &#x27;DJF&#x27; ... &#x27;DJF&#x27; &#x27;DJF&#x27; &#x27;DJF&#x27; &#x27;DJF&#x27;</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1826</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-8f720277-68f3-4f43-8f57-60036ef3cd43' class='xr-array-in' type='checkbox' checked><label for='section-8f720277-68f3-4f43-8f57-60036ef3cd43' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>nan nan nan nan nan nan nan nan ... nan nan nan nan nan nan nan nan</span></div><div class='xr-array-data'><pre>array([[[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-4bc65df7-cd77-4029-a91b-4510ce785f57' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4bc65df7-cd77-4029-a91b-4510ce785f57' class='xr-section-summary' >Coordinates: <span>(4)</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'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-afcc5cbb-eb26-4b08-bdf7-ded69f01846a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-afcc5cbb-eb26-4b08-bdf7-ded69f01846a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-57e1a96e-bc97-4f74-82fa-1334c612451e' class='xr-var-data-in' type='checkbox'><label for='data-57e1a96e-bc97-4f74-82fa-1334c612451e' 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>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,\n",
       "       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,\n",
       "       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,\n",
       "       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,\n",
       "       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,\n",
       "       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,\n",
       "       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,\n",
       "       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,\n",
       "       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,\n",
       "       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,\n",
       "       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,\n",
       "       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,\n",
       "       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,\n",
       "       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,\n",
       "       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,\n",
       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
       "        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,\n",
       "        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,\n",
       "        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,\n",
       "        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,\n",
       "        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,\n",
       "        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,\n",
       "        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,\n",
       "        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,\n",
       "        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,\n",
       "        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,\n",
       "        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,\n",
       "        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,\n",
       "        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,\n",
       "        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><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'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-267ba0f0-6daa-4252-86de-51a2720f731b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-267ba0f0-6daa-4252-86de-51a2720f731b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39679b10-bfce-47df-a7d5-7f20aa233807' class='xr-var-data-in' type='checkbox'><label for='data-39679b10-bfce-47df-a7d5-7f20aa233807' 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>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></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'>1979-01-01 ... 1984-01-01</div><input id='attrs-fbd6147a-efbc-4aea-9cda-5de1be46e09e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fbd6147a-efbc-4aea-9cda-5de1be46e09e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d426e800-d9e0-4e79-967e-c9e8bf06652a' class='xr-var-data-in' type='checkbox'><label for='data-d426e800-d9e0-4e79-967e-c9e8bf06652a' 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><div class='xr-var-data'><pre>array([&#x27;1979-01-01T00:00:00.000000000&#x27;, &#x27;1979-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;1979-01-03T00:00:00.000000000&#x27;, ..., &#x27;1983-12-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-12-31T00:00:00.000000000&#x27;, &#x27;1984-01-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>season</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;DJF&#x27; &#x27;DJF&#x27; &#x27;DJF&#x27; ... &#x27;DJF&#x27; &#x27;DJF&#x27;</div><input id='attrs-f365c656-fa18-4928-b4a1-998c2be26ef8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f365c656-fa18-4928-b4a1-998c2be26ef8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb1f2979-8236-4905-8bd4-7c05d30d7bee' class='xr-var-data-in' type='checkbox'><label for='data-bb1f2979-8236-4905-8bd4-7c05d30d7bee' 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><div class='xr-var-data'><pre>array([&#x27;DJF&#x27;, &#x27;DJF&#x27;, &#x27;DJF&#x27;, ..., &#x27;DJF&#x27;, &#x27;DJF&#x27;, &#x27;DJF&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-823a9e54-265f-4637-b023-4e4801abe22f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-823a9e54-265f-4637-b023-4e4801abe22f' 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.DataArray (time: 1826, lat: 192, lon: 288)>\n",
       "array([[[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lat      (lat) float64 -90.0 -89.06 -88.12 -87.17 ... 87.17 88.12 89.06 90.0\n",
       "  * lon      (lon) float64 0.0 1.25 2.5 3.75 5.0 ... 355.0 356.2 357.5 358.8\n",
       "  * time     (time) datetime64[ns] 1979-01-01 1979-01-02 ... 1984-01-01\n",
       "    season   (time) <U3 'DJF' 'DJF' 'DJF' 'DJF' ... 'DJF' 'DJF' 'DJF' 'DJF'"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "((xday - xday.mean()) * (yday - yday.mean()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5466c386",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "78048bc9",
   "metadata": {},
   "source": [
    "### What's happening with resample?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0986c2e3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-26T16:42:20.282891Z",
     "start_time": "2021-05-26T16:42:20.262861Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-3-c38eba469f69>:6: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  flxDS_mon['time'] = flxDS_mon.indexes['time'].to_datetimeindex()\n",
      "<ipython-input-3-c38eba469f69>:9: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  smDS_mon['time'] = smDS_mon.indexes['time'].to_datetimeindex()\n"
     ]
    }
   ],
   "source": [
    "dataDir = '/Users/mdfowler/Documents/Analysis/Coupling_initial/data/Monthly/CLM45/'\n",
    "monthlyFile_flx = dataDir+'f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.cam.h0.2000-2005_sfcFluxes.nc'\n",
    "monthlyFile_SM  = dataDir+'f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2000-2005_SOILWATER10.nc'\n",
    "\n",
    "flxDS_mon = xr.open_dataset(monthlyFile_flx, decode_times=True)\n",
    "flxDS_mon['time'] = flxDS_mon.indexes['time'].to_datetimeindex()\n",
    "\n",
    "smDS_mon = xr.open_dataset(monthlyFile_SM, decode_times=True)\n",
    "smDS_mon['time'] = smDS_mon.indexes['time'].to_datetimeindex()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "338b265c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-26T16:43:32.285578Z",
     "start_time": "2021-05-26T16:43:32.084048Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x7fc97e3379d0>"
      ]
     },
     "execution_count": 10,
     "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(smDS_mon.lon.values,smDS_mon.lat.values,smDS_mon[xname].values[10,:,:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "1e2a08c8",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-26T16:43:50.114132Z",
     "start_time": "2021-05-26T16:43:49.949243Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x7fc97e662640>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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YtLZ2nrCMwfoNVcjLMJfNsLjmmaoRWr7yXh0hzc4Y9Z3/x5A3gxL6c+vWNPpdst0g1BfmOjsApRmywybmcb951Fl+1aUFVlYwY7LC+iL2fFQ2Y7TObk55jEHkITChT5Ptja9KsLR1D26CXyfRhywMecIee+FsQjoP5Fl8YymUsdI0T+alpcvSG9ln5q1rn/esOs8ZC8EKfZoy322R72wMLhgYn8g3EeOytW6MYcj66/vMk0VluckOVmUuojG1DL3NjBWR1SLyDRH5H/PvrxWR+0Tkm/P/5Tt/O5AXuWXN+zShri9jFHNqx1rvYm6Vgz98zZCuK5pFz22atnV/F5vIg98lEG4Gnkp93wc8oKrbgQfm351wjfi0v9Y18mMU+xjDnEcoIhtKOIx2JIaAD4MgzzOQR4wiD56EXkQ2A38D+HTq8B7gzvnnO4Gfdr1fnYWs8mbWxZoYWbpyN3WxjlBZoevCMofl6+HUxcQ+brpOP1fvQSz48tH/a+BXgIXUsUtV9RkAVX1GRC7J+6GI7AX2Alx40WvOH3fZDDfd+RJzIuTRpcinP/toLSTpkBbd09tmWWvhyKpGvtMmv6nLGPON4Y8x5Y3WQi8iPwU8p6oPi8i76v5eVfcD+wEWNmzW9LmqiB5brdsFWTEfatG0LEml0GZ/2LZ7y4KJfYzkGRbQLj+MPQ/4sOh/DHifiOwGLgJeLSL/FXhWRC6fW/OXA895eJbhgMsMx7LfNrXyF46synWlFI2QKmLshc5oTpHIt2EK+a210KvqrcCtAHOL/hZV/VkR+ThwPXDH/P/dbZ81JfI2Rsger6Ivy315QVnrVAh9WOOG0ZQpiHuaLsfR3wEcEJEbgGPA+zt81qjJrpedPZ6cK6KOld7GZ39s9wXAksjXFfOyGY2GkZBnSNTJa1MTefAs9Kr6IPDg/PP/Ba72eX9jOXUs9qKNFtK0EfmZMBeLfLrJXbSpSFfibjNo46fMZeMq8lMU+IQoZsZmsQ60GU3dOH3OaCxy4wwpvpZ34uLUjmJ3YJnIWzovEaXQTzUB24iyy/LFbZilyVKBdCmYPsW9qLN3qnllLDQReUvzlUQp9EYzQplh63OMfHbjcGM8FOWRIfcTjhUTesMbWau+iCYib4V5uph7pj0m9EbQWEE28rB8UQ8TeiNYrDCPnyaLh1m+qI/NWumYrhb0ipE6w+CsMIdFF3m4zgYhCVPKFz4nPJrQpzBB7g4XkTeBD5MhyoXlBb+DJ0blunHZT7SM9GgQX5ls7Jk1HV9FQ+GqRH7scRQ7faZP3paCvsvkFAnWoq+7qYCvjQe6nqU5BvLSxXUoXBYrvNPFdZ9Ys+5XUleforHoizYLT2824nNsdl4FY5mtHjYszqjC8sFyuprUGJzQt1nKtm2msaUV3ClagMzVF2+MAysz/qgr8nXiPljXzdDNNR/PHtOIm/S7lK0y2WSzGMMw3GlSuQYn9GmBd127JOsrbiOuVUO+mtx/LGIPy7dvzHuvsmFxJvLjw9LUD01cNnXiPjihL6PqxVw6B432NNn/1Rg3Vt76o0l5ai30IrJFRH5fRJ4SkSdE5Ob58deKyH0i8s35/4117+26YFVeR2ybztmq37lGdOwC17QFkyb2ODCMMeDDon8Z+Ceq+heAdwA3ishOYB/wgKpuBx6Yf6+NS5O/zSy6MiHzIVJTdllM9b2niKV1c7pcPjzBx56xzwDPzD+fFpGngE3AHuBd88vuZLbz1Eeq7pcdRulCG+u96LdTG01QNHzVlSnFlWH4pmux9+qjF5E3AD8CfBW4dF4JJJXBJQW/2SsiB0Xk4EtnXzh/vK5wdCU0UxCwtv7VKcSRYcSMN6EXkfXA54EPqeoPXH+nqvtV9UpVvXLN2lflujpcfcVNBMdF5Opsexdjh3CbJSNM5A2jHX1sCORlwpSIrGEm8p9T1S/MDz8rIper6jMicjnwnI9nVZE3xrupGFW5b4qEPMa1OVzdNTG9k2EYM3yMuhHgM8BTqvqJ1Kl7gOvnn68H7m77rJCIxVqvQ9UoJxN5w+iPOvNUqhBVbRUYEflx4H8BjwPJ0oUfZeanPwBcARwD3q+q3y2718WXbtHt133Ym6BUWdZ1l1toszxDrMTYOjGMmGmiS4996sMPq+qVRdf6GHXzZUAKTl/d5J5pl0nThcWqIqsrizwWQXQdVRTL+xjGGKijS3WuDW5RswSf/m8fSxiPaWuz9DIGsYXdMIz6BCv0VfS9frzrujsxEXv4DcNwI6q1borITvbpethf7MMKYw67YYyZrspmtBZ9QtbS9jH5ZwobE4/pXQxjTHThpRiFRe+L9G5VLtTd7tAwDMMVn8ZY9BZ9HmUbY5Rd6/ob12sMw+ifMW0B6muL1FEJfZ0E9b3UcMyZyTCMcROU0K/+4WzyVhMru2wH+bqUPd8E3TDiIvZhxD6s+qCEHuoL9hAuFHPbGEa4+HJ3hERb/QtO6OvSV02dXQemybr5hmH0Q1/za2IheqEfChN3w4iDMZdV13czoTcMY9Tk+ejHNDLHBRtHbxiGMXLMos/g4nuPvRffMKZC2Qi609vOpY6Ou0ybRW8YxuRYLvLjp3OhF5H3iMiiiBwWkX1dP88XY1qW2DCMasY8QqdToReR1cC/A94L7AT+rojs7PKZvshu8j3mTGAYxrjp2qK/Cjisqt9S1bPAXcCejp/pjazAm9gbxrgZaxnvWug3AU+nvh+fHzuPiOwVkYMicvClsy90HJxymi6zYBhGPVxbyUO0psco9l0Lfd5esst2I1fV/ap6papeuWbtqzoOjhsm6IYxbhaOrMr9nDC25ce7FvrjwJbU983AyTY37CPix7htoGGExJC7tCXPXTiyKlfks4xB8LseR/81YLuIbAVOANcBf6/NDfMWLOo6w5jIG4ZxbPeSXC4cWRWVLnRq0avqy8AvAfcCTwEHVPUJ38/xUdtOYftAw4iJvqxol9ZFdtz96W3nlgl/6HQeUlX9IvBFn/fcuHj2fCS7NL2qiL1ZZhhjIz171UcZz5In7E2WNz62+4IorPvoZ8YmNW0XYh164hnGWKlahKyv57pwetu54I3FaIW+i1o+jYm8YUyTpmIfMtEKvS8hLqqJxza8yjBiY+Pi2c4NurJn1yVkrYhW6H1hlrthhMuQ5TP97KIKZ/3W7/cVnFZMXuhDroUNwwiHqtZFyEZjPOODDMOYJCEJ6MKRVcv88c8f3XD+eMhELfTpSPftU5vSpgSGETpJWR26HOZ1usYwvDJqoZ9NdPB/39B70A3D6J+YdSFqoW9Ty5tv3jDiISnjQ23jmRX5tKsmdGseIhf6pmRFPj37Lq/WPr3tXGHLwWWPWWMlLgvHhdJcN8IgyQ8h7dkcSjiqCLsHoScSX3/dptmpHWsb/W7q2OqgRlv6nikbemdrFdFa9Nmdn1yFIi+D+BBqE6p8fC44Z3E8bbJr0Qxl2SeiH1N+jFbo0+K8cGRVpRi0EZyijQnSYQipORkCS/Ezi6Mqi8jiz2hCH0ZAUsHEbNXHG/ICmixbUCcBT+1Yy7HdF5i7poIm8WMd5EYVXRhyU2B0Qt+UIrF3GSMbwzjaPsmu0123IrU1howyhhD77DNjK++thF5EPi4ifywij4nI74jIa1LnbhWRwyKyKCLvbh3SmjRJ9KwgmYDXY92hEyuOxdzcNcIlXS7TAyKyRoJPwyHZoCRGTWhbCu8DdqnqW4A/AW4FEJGdzLYNfDPwHuDfi8jqls+qTVOxXziyiiu++HJhglZtLDw11h06wbpDJziza9MyX2Z6NFP2zzDaki2f2T6zLFNuJbZSKVX90ny7QICvMNv8G2APcJeqvqiqR4HDwFVtnpUlLbBVwlE3gctq7LobC0+BM7s2nRf5hOyaIFlM7A0flJVVE/slfCrVLwC/O/+8CXg6de74/NgKRGSviBwUkYMvnX3B+WFthlO2YaoZpYx009hVwJtUkhb3hgt5+7tO3bCoHF4pIvcDl+Wcuk1V755fcxvwMvC55Gc512ve/VV1P7AfYGHD5txriqiyGuvgsjelCc0Sy4U9Pw3K0ic7PLbuc2P0kxrdkyfyhoPQq+o1ZedF5Hrgp4CrVTUR6uPAltRlm4GTTQNZxKywL81ObeNKafPbqYlOHeu9bGkJwzD6oe2om/cAHwHep6r/L3XqHuA6EblQRLYC24GH2jzLBROT/nCJa9fOV0s3o0+m2DJvOzP23wIXAveJCMBXVPUfqeoTInIAeJKZS+dGVX2l5bOCIREm64wdhqm1oIz6ZFv4Uy+rrYReVf98ybnbgdvb3N8ImyIffF0LPa8QZtc1SWN+esMFaykuEe1aNwlpP72/+xWfy4rPlMUmsZq6KlBFyxbnHZtyOhhGFdELfRaXTtk26553tauVsRyXdf5DWMnQCIP1W78PLN/DtcgAKctPY81Do3Rc1bUwY53WPBZ8T3gzjDSx7QbVBaOz6I1+6csPamJv5DHLF8XzONJUifyYKwETemMUjLmQGsWc3nbuvNsmezzBFiccietm4+LZFbW3LaDVHXnx3eez8wqtWfxGGVPPH6Ox6H2PvjH6JTuCp6gimXqBNYpJOmKNlYxG6MtouzyC0Q9WSRtNMIGvZhJCn2bqvrquyQ5zS5PnXvOFpauRhxl4M0Yl9BsXz3J626heKVrWb/3+sjHNkCfGa1d0mlnry2hKegE9y0PLGZ0qdjlT06jm+aMbVoh8kbWd9KukaVJAzZo30pT170w1r4xO6LPYZIl+WTiyCo5sZAH3mcbWwWo0YbZtZbkLMJu/prpkxuiEPmslTi1B+yLPGm8a1+nf+dz20ZgGZa3AxIqfujExOqEHK/x90UU8W6E0fJN22Uw1b1mPhREcrhWIVejTpY5gWz7xZNGLyC3Ax4HXq+p35sduBW4AXgE+qKr3+nhWQl5CW4IavrDlqMeBpduM1kIvIluAvw4cSx3bCVwHvBn4s8D9IvKmrneZyvaqT7mXPXaKljmw9DSy1Nnxbar5x4fr5l8BvwJo6tge4C5VfVFVjwKHgas8PKuSUzvWnv9LvhvjYKhCOlVxGANF5X/doRM9h2RY2m4O/j7ghKo+mjm1CXg69f34/FjePfaKyEEROfjS2RfaBMcwjAnjOn9maiIPDq4bEbkfuCzn1G3AR4Fr836Wc0xzjqGq+4H9AAsbNudeYxhDYJa8MRYqhV5Vr8k7LiJ/EdgKPCoiAJuBr4vIVcws+C2pyzcDJ1uH1hEbomc0IT2ZxkQ+Poo2mTdadMaq6uPAJcl3Efk2cKWqfkdE7gF+Q0Q+wawzdjvwUMuw1sIS2DDGi4sxV6YBZ3blepJHSycTplT1CRE5ADwJvAzc6HvETVFCm8AbTbG8Mw2mJvLgUehV9Q2Z77cDt/u6fx5DFcyqzpwpZiTD6JvE2CsbVpmU1amXSZsZWxOXHvt1h05MsmffaIbll3bkbRu6cfHssjidevyOcq2bWMjLfFO3PPombxLWukMnekuHPDGyPNCOrMgn9JmuoWEWfU3qZJQyK6LoXGLdTd0C6Ys8kU/+95EOefnJ0r4dp3asLSynU41bs+h7pk5Gy7NAzOrrjrLKt8v4trRsR93NamKy7NN5sk2YTeg7pq0FYe6dMIhJHIxqYknPM7s2LWtlJsfqYq6bgDiza9P5vzKm2vw0DBdcR+NNyUVqFn0OTRI/XfO2ea7rfcyF45903OelQyxW4JQp6ogtw1eruW6ZbFqGm+RDUQ1neZmFDZv17T9609DBANzFPoTOtK7Ep+g9piR2vnykRjekJ02WifyZXZuWLXHRRxl1yS9l+assjNlr/+DefQ+r6pVF10/Com9Sc7pEetH9kuOxNwuLWhdTak1M4R2NbnAxEtLH2w7UKCMooV915iWn6+q+pI/C2kS8y54bSyXgwyU1VaZUIQ5FdimUsvw65BIXLnmhblmrc21QQg/hC2CSGGMovCELUTYfhBjGIvJ8+wkxvUdsJJPfqvpX8vJWX7pTlq+7DENQPvoNay/Vd17yd5yvj73Q+ErYNh1HLvfqc4hnHb9kiLTp2zH8ErrR6JPfO/FvxumjH0NBGbIjt8z/ng1XKHEdekuqjY/VOr6NLglW6KeaweuKf5t4CtH/XtUXEqq7qUk81hlGmxDaexv+KTMACtO/IisFJfTn1q2xjJyDxclKQhX8rgm9VWM0Jy9dfaV165mxInKTiCyKyBMi8rHU8VtF5PD83LvbPsfoj/SCXkPNHqwz6WToVknfzx/6fWMgxjjqMsytLHoR+WvAHuAtqvqiiFwyP74TuA54M7OtBO8XkTf53mUqIfYOvCEJebmFOkNah/JxDxU/ZtkXE6PIJ3TVUm3ruvlF4A5VfRFAVZ+bH98D3DU/flREDgNXAX/U8nnniTkxYyIEMQmxLyEETOyXM6Y84ttwaSv0bwL+iojcDvwQuEVVvwZsAr6Suu74/FhrxpSYhjt1J6yNXQCz8TH29y1jSprQtHO+UuhF5H7gspxTt81/vxF4B/CXgQMi8kZAcq7PHbAvInuBvQAXrV5ovPZDliln/DFTNCJhqPTuY7kLn7Mpx8aU3x3c379S6FX1mqJzIvKLwBd0NuvqIRE5B7yOmQW/JXXpZuBkwf33A/thNmEqfc7lJcyymS4hpXXdFQuLfm/52OiCtq6b/w78JPCgiLwJWAt8B7gH+A0R+QSzztjtwENNH+KS6a1gGDFQlU+bLFk7Vab87nVpK/SfBT4rIoeAs8D1c+v+CRE5ADwJvAzc6DLiJhlHH0KT3JgGfVvQvp+XlBfrmF1JG9dviJS6LSteLai1bkJaj34KTGnWZd1C7jMu+uhbMpdPNbEJfZ20tPXojUKyrafs7kpd75TTJ3WtuzrvVFRhjmUDmtiJTeAhvHH0RsS4iJ1rhotNZHyGt6jCbELTSjOvIostTbogJpHvMr1M6FsQYmGq6t+oM8u0iTXrQp/LHveFTyve17LTMbS0xohr67HPdDGhb0iSeHXG/ZclbHbvyyZhKTveZLx12WYNLmGo88yxiFKTDsC27zzVwQtVeSaUNZpCSBMT+o4os7AS0hmg6TZndYW0q/v7+m3Vb0IoNHUoa1X5HHkzRvJazKFWaiGFJQ8T+gLyrOF0YraZkVin8Fdl9qkRakGvQ6zh7hoX4wjc46/rWcMxpWNQwyuzWwk29RG3naVYhsuuQH2ExcS/OTEV0DHTJs/WSUNfZSPkfBP18Moh3A2+7t11RkwsfRP4YoriJx13dSrikAv61BhLn44PXDQgaKGPla5Gq3RxjymSpE8dkTBB8Y9Lq7TpyLGmYQiZNu9tQj8AJtD9UEc4YirwY6bJWj9jnesB/rTChL5HTODDwpr/YeCSDm2X6wg9jbNx4FsrTOg7wAQ9PNIFKO26cUmr9ByHhKbDYUPGx9pHTe4x5dVps/HVlXaY0BuToKn1nifyyfHYxb7JJLgmzxhSpEM0uoYIkwm9MWnyRKhI3NPELvLgb6mFur9ps0Jn0+HKQ1c4aVw7mH2OqjOhN4wUIYr8lJaTrsLXTO3Q4jBvfo5Py9+E3pgseVbexsWzwfjky9YwCk2o6tA0/HUnK1aFoez+Y6OV0IvIW4H/CFzEbCepf6yqD83P3QrcALwCfFBV720XVMNoj0vn17pDy7+HKAB9jyXv83lDVWQ+RmG5hD1GH/3HgF9T1d8Vkd3z7+8SkZ3AdcCbme0Ze7+IvMllO0HDCI22BTP05Sr6Cs8Qyxb4ok54Qgs7tBd6BV49/7wBODn/vAe4S1VfBI6KyGHgKuCPWj7PMKIjxILfNW2sYlvawz9thf5DwL0i8i+AVcA758c3AV9JXXd8fmwFIrIX2Atw0eqFlsExDGNIfC69PJTYj7GSqRR6EbkfuCzn1G3A1cAvq+rnReQDwGeAawDJuT53mUxV3Q/sh9nqlY7hNgwjIELsxzCWqBR6Vb2m6JyI/Bfg5vnX3wI+Pf98HNiSunQzS24dwzBGhIl8+Kxq+fuTwF+df/5J4Jvzz/cA14nIhSKyFdgOPNTyWYZhTAirQPzR1kf/D4FPisgFwA+Z+9pV9QkROQA8yWzY5Y024sYwjDqM0Vc+FK2EXlW/DLy94NztwO1t7m8YRth0ZXWbyPvFZsYahlELE/f4MKE3DMMZnyJvwt4fJvSGYTjjujCYiXhYmNAbhtEIE/N4aDu80jAMwwgcE3rDMIyRI6rhrDogIqeBxaHD0ZDXAd8ZOhANiTXssYYbLOxDEGu4oTrsf05VX190MjQf/aKqXjl0IJogIgct7P0Sa7jBwj4EsYYb2ofdXDeGYRgjx4TeMAxj5IQm9PuHDkALLOz9E2u4wcI+BLGGG1qGPajOWMMwDMM/oVn0hmEYhmdM6A3DMEZOMEIvIu8RkUUROSwi+4YOTxki8m0ReVxEHhGRg/NjrxWR+0Tkm/P/G4cOJ4CIfFZEnhORQ6ljhWEVkVvnabAoIu8eJtTnw5IX9l8VkRPzuH9ERHanzgURdhHZIiK/LyJPicgTInLz/Hjw8V4S9qDjXUQuEpGHROTRebh/bX48hjgvCru/OFfVwf+A1cAR4I3AWuBRYOfQ4SoJ77eB12WOfQzYN/+8D/jnQ4dzHpafAN4GHKoKK7BzHvcXAlvnabI6sLD/KnBLzrXBhB24HHjb/PMC8Cfz8AUf7yVhDzreme1TvX7+eQ3wVeAdkcR5Udi9xXkoFv1VwGFV/ZaqngXuAvYMHKa67AHunH++E/jp4YKyhKr+T+C7mcNFYd0D3KWqL6rqUeAws7QZhIKwFxFM2FX1GVX9+vzzaeApYBMRxHtJ2IsIIuw64/n51zXzPyWOOC8KexG1wx6K0G8Cnk59P0555hoaBb4kIg+LyN75sUtV9RmYFRbgksFCV01RWGNJh18Skcfmrp2kKR5k2EXkDcCPMLPSoor3TNgh8HgXkdUi8gjwHHCfqkYT5wVhB09xHorQS86xkMd9/piqvg14L3CjiPzE0AHyRAzp8B+AbcBbgWeAfzk/HlzYRWQ98HngQ6r6g7JLc46FFvbg411VX1HVtwKbgatEZFfJ5cGEGwrD7i3OQxH648CW1PfNwMmBwlKJqp6c/38O+B1mzaZnReRygPn/54YLYSVFYQ0+HVT12XmhOAf8J5aarEGFXUTWMBPKz6nqF+aHo4j3vLDHEu8Aqvo94EHgPUQS5wnpsPuM81CE/mvAdhHZKiJrgeuAewYOUy4i8ioRWUg+A9cCh5iF9/r5ZdcDdw8TQieKwnoPcJ2IXCgiW4HtwEMDhK+QpNDO+ZvM4h4CCruICPAZ4ClV/UTqVPDxXhT20ONdRF4vIq+Zf14HXAP8MXHEeW7Yvcb5EL3MBT3Pu5n18B8Bbhs6PCXhfCOzHu9HgSeSsAJ/BngA+Ob8/2uHDus8XP+NWbPvJWaWwA1lYQVum6fBIvDeAMP+68DjwGPzDH95aGEHfpxZU/ox4JH53+4Y4r0k7EHHO/AW4Bvz8B0C/un8eAxxXhR2b3FuSyAYhmGMnFBcN4ZhGEZHmNAbhmGMHBN6wzCMkWNCbxiGMXJM6A3DMEaOCb1hGMbIMaE3DMMYOf8fLP+ZcGXW3qwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.contourf(flxDS_mon.lon.values,flxDS_mon.lat.values,flxDS_mon[yname].values[10,:,:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "e809abb2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-26T16:47:35.931453Z",
     "start_time": "2021-05-26T16:47:35.928488Z"
    }
   },
   "outputs": [],
   "source": [
    "# Make one big xr.Dataset containing all the information we need  \n",
    "ds = flxDS_mon\n",
    "ds['SOILWATER_10CM'] = (('time','lat','lon'), smDS_mon.SOILWATER_10CM.values)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "79410b7f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-26T16:48:12.497918Z",
     "start_time": "2021-05-26T16:48:07.013790Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/mdfowler/opt/anaconda3/envs/newBase/lib/python3.8/site-packages/xarray/core/common.py:1123: FutureWarning: 'base' in .resample() and in Grouper() is deprecated.\n",
      "The new arguments that you should use are 'offset' or 'origin'.\n",
      "\n",
      ">>> df.resample(freq=\"3s\", base=2)\n",
      "\n",
      "becomes:\n",
      "\n",
      ">>> df.resample(freq=\"3s\", offset=\"2s\")\n",
      "\n",
      "  grouper = pd.Grouper(\n",
      "/Users/mdfowler/opt/anaconda3/envs/newBase/lib/python3.8/site-packages/xarray/core/nanops.py:142: RuntimeWarning: Mean of empty slice\n",
      "  return np.nanmean(a, axis=axis, dtype=dtype)\n",
      "/Users/mdfowler/opt/anaconda3/envs/newBase/lib/python3.8/site-packages/numpy/lib/nanfunctions.py:1664: RuntimeWarning: Degrees of freedom <= 0 for slice.\n",
      "  var = nanvar(a, axis=axis, dtype=dtype, out=out, ddof=ddof,\n"
     ]
    }
   ],
   "source": [
    "xname = 'SOILWATER_10CM'\n",
    "yname = 'SHFLX'\n",
    "\n",
    "xday = ds[xname].resample({'time':'1D'}).mean().groupby('time.season')\n",
    "yday = ds[yname].resample({'time':'1D'}).mean().groupby('time.season')\n",
    "\n",
    "# xday = ds[xname].groupby('time.season')\n",
    "# yday = ds[yname].groupby('time.season')\n",
    "\n",
    "covarTerm = ((xday - xday.mean()) * (yday - yday.mean())).groupby('time.season').sum() / xday.count()\n",
    "\n",
    "couplingIndex = covarTerm/xday.std()\n",
    "\n"
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  {
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   "id": "cd596669",
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    "np.nanmean(couplingIndex[1,:,:])"
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  {
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     "start_time": "2021-05-26T16:18:30.799819Z"
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   "source": [
    "testResample2 = smDS_mon[xname].resample({'time':'1D'}).mean()"
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:         (hist_interval: 2, lat: 192, lon: 288, time: 72)\n",
       "Coordinates:\n",
       "  * time            (time) datetime64[ns] 2000-02-01 2000-03-01 ... 2006-01-01\n",
       "  * lon             (lon) float32 0.0 1.25 2.5 3.75 ... 356.25 357.5 358.75\n",
       "  * lat             (lat) float32 -90.0 -89.057594 -88.11518 ... 89.057594 90.0\n",
       "Dimensions without coordinates: hist_interval\n",
       "Data variables:\n",
       "    time_bounds     (time, hist_interval) object 2000-01-01 00:00:00 ... 2006...\n",
       "    SOILWATER_10CM  (time, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    title:                                     CLM History file information\n",
       "    comment:                                   NOTE: None of the variables ar...\n",
       "    Conventions:                               CF-1.0\n",
       "    history:                                   Tue Sep 29 09:27:34 2020: ncrc...\n",
       "    source:                                    Community Land Model CLM4.0\n",
       "    hostname:                                  cheyenne\n",
       "    username:                                  hannay\n",
       "    version:                                   cesm2.1.1-exp17\n",
       "    revision_id:                               $Id: histFileMod.F90 42903 201...\n",
       "    case_title:                                UNSET\n",
       "    case_id:                                   f.e20.FHIST.f09_f09.cesm2_1_cl...\n",
       "    Surface_dataset:                           surfdata_0.9x1.25_hist_16pfts_...\n",
       "    Initial_conditions_dataset:                arbitrary initialization\n",
       "    PFT_physiological_constants_dataset:       clm_params.c170913.nc\n",
       "    ltype_vegetated_or_bare_soil:              1\n",
       "    ltype_crop:                                2\n",
       "    ltype_UNUSED:                              3\n",
       "    ltype_landice_multiple_elevation_classes:  4\n",
       "    ltype_deep_lake:                           5\n",
       "    ltype_wetland:                             6\n",
       "    ltype_urban_tbd:                           7\n",
       "    ltype_urban_hd:                            8\n",
       "    ltype_urban_md:                            9\n",
       "    ctype_vegetated_or_bare_soil:              1\n",
       "    ctype_crop:                                2\n",
       "    ctype_crop_noncompete:                     2*100+m, m=cft_lb,cft_ub\n",
       "    ctype_landice:                             3\n",
       "    ctype_landice_multiple_elevation_classes:  4*100+m, m=1,glcnec\n",
       "    ctype_deep_lake:                           5\n",
       "    ctype_wetland:                             6\n",
       "    ctype_urban_roof:                          71\n",
       "    ctype_urban_sunwall:                       72\n",
       "    ctype_urban_shadewall:                     73\n",
       "    ctype_urban_impervious_road:               74\n",
       "    ctype_urban_pervious_road:                 75\n",
       "    cft_c3_crop:                               1\n",
       "    cft_c3_irrigated:                          2\n",
       "    time_period_freq:                          month_1\n",
       "    Time_constant_3Dvars_filename:             ./f.e20.FHIST.f09_f09.cesm2_1_...\n",
       "    Time_constant_3Dvars:                      ZSOI:DZSOI:WATSAT:SUCSAT:BSW:H...\n",
       "    NCO:                                       netCDF Operators version 4.7.9...</pre><div class='xr-wrap' hidden><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-2ac927d0-b453-4192-be06-aa008df3d943' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2ac927d0-b453-4192-be06-aa008df3d943' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>hist_interval</span>: 2</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span class='xr-has-index'>time</span>: 72</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ccca9dac-822b-4528-ba6f-e4b1e89c593f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ccca9dac-822b-4528-ba6f-e4b1e89c593f' 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'>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'>2000-02-01 ... 2006-01-01</div><input id='attrs-bc48e323-32f3-4966-9846-89c4928fcb4d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bc48e323-32f3-4966-9846-89c4928fcb4d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca0e82d2-74b2-415b-bb7a-804a18d84517' class='xr-var-data-in' type='checkbox'><label for='data-ca0e82d2-74b2-415b-bb7a-804a18d84517' 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><div class='xr-var-data'><pre>array([&#x27;2000-02-01T00:00:00.000000000&#x27;, &#x27;2000-03-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-04-01T00:00:00.000000000&#x27;, &#x27;2000-05-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-06-01T00:00:00.000000000&#x27;, &#x27;2000-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-08-01T00:00:00.000000000&#x27;, &#x27;2000-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-10-01T00:00:00.000000000&#x27;, &#x27;2000-11-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-12-01T00:00:00.000000000&#x27;, &#x27;2001-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-02-01T00:00:00.000000000&#x27;, &#x27;2001-03-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-04-01T00:00:00.000000000&#x27;, &#x27;2001-05-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-06-01T00:00:00.000000000&#x27;, &#x27;2001-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-08-01T00:00:00.000000000&#x27;, &#x27;2001-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-10-01T00:00:00.000000000&#x27;, &#x27;2001-11-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-12-01T00:00:00.000000000&#x27;, &#x27;2002-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-02-01T00:00:00.000000000&#x27;, &#x27;2002-03-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-04-01T00:00:00.000000000&#x27;, &#x27;2002-05-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-06-01T00:00:00.000000000&#x27;, &#x27;2002-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-08-01T00:00:00.000000000&#x27;, &#x27;2002-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-10-01T00:00:00.000000000&#x27;, &#x27;2002-11-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-12-01T00:00:00.000000000&#x27;, &#x27;2003-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-02-01T00:00:00.000000000&#x27;, &#x27;2003-03-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-04-01T00:00:00.000000000&#x27;, &#x27;2003-05-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-06-01T00:00:00.000000000&#x27;, &#x27;2003-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-08-01T00:00:00.000000000&#x27;, &#x27;2003-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-10-01T00:00:00.000000000&#x27;, &#x27;2003-11-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-12-01T00:00:00.000000000&#x27;, &#x27;2004-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-02-01T00:00:00.000000000&#x27;, &#x27;2004-03-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-04-01T00:00:00.000000000&#x27;, &#x27;2004-05-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-06-01T00:00:00.000000000&#x27;, &#x27;2004-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-08-01T00:00:00.000000000&#x27;, &#x27;2004-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-10-01T00:00:00.000000000&#x27;, &#x27;2004-11-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-12-01T00:00:00.000000000&#x27;, &#x27;2005-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-02-01T00:00:00.000000000&#x27;, &#x27;2005-03-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-04-01T00:00:00.000000000&#x27;, &#x27;2005-05-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-06-01T00:00:00.000000000&#x27;, &#x27;2005-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-08-01T00:00:00.000000000&#x27;, &#x27;2005-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-10-01T00:00:00.000000000&#x27;, &#x27;2005-11-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-12-01T00:00:00.000000000&#x27;, &#x27;2006-01-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><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'>float32</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 357.5 358.75</div><input id='attrs-064cd6b5-fe99-4c65-8e92-e074a38f9e68' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-064cd6b5-fe99-4c65-8e92-e074a38f9e68' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eeaa4899-e55d-4f74-883a-9199e2b102bd' class='xr-var-data-in' type='checkbox'><label for='data-eeaa4899-e55d-4f74-883a-9199e2b102bd' 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>long_name :</span></dt><dd>coordinate longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75], dtype=float32)</pre></div></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'>float32</div><div class='xr-var-preview xr-preview'>-90.0 -89.057594 ... 89.057594 90.0</div><input id='attrs-21fda0ce-4162-42af-82f2-0ae945acbbdf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-21fda0ce-4162-42af-82f2-0ae945acbbdf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d735c0bd-cd7a-4fb6-b349-f80061bd1e73' class='xr-var-data-in' type='checkbox'><label for='data-d735c0bd-cd7a-4fb6-b349-f80061bd1e73' 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>long_name :</span></dt><dd>coordinate latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057594, -88.11518 , -87.172775, -86.23037 , -85.28796 ,\n",
       "       -84.34555 , -83.403145, -82.46073 , -81.518326, -80.57591 , -79.63351 ,\n",
       "       -78.6911  , -77.74869 , -76.80628 , -75.86388 , -74.92146 , -73.97906 ,\n",
       "       -73.03665 , -72.09424 , -71.15183 , -70.20943 , -69.26701 , -68.32461 ,\n",
       "       -67.3822  , -66.43979 , -65.49738 , -64.55498 , -63.612564, -62.67016 ,\n",
       "       -61.72775 , -60.78534 , -59.842934, -58.900524, -57.958115, -57.015705,\n",
       "       -56.0733  , -55.13089 , -54.18848 , -53.246075, -52.303665, -51.361256,\n",
       "       -50.41885 , -49.47644 , -48.53403 , -47.59162 , -46.649216, -45.706806,\n",
       "       -44.764397, -43.82199 , -42.87958 , -41.937172, -40.994766, -40.052357,\n",
       "       -39.109947, -38.167538, -37.225132, -36.282722, -35.340313, -34.397907,\n",
       "       -33.455498, -32.51309 , -31.57068 , -30.628273, -29.685863, -28.743456,\n",
       "       -27.801046, -26.858639, -25.916231, -24.973822, -24.031414, -23.089005,\n",
       "       -22.146597, -21.20419 , -20.26178 , -19.319372, -18.376963, -17.434555,\n",
       "       -16.492147, -15.549738, -14.607329, -13.664922, -12.722513, -11.780105,\n",
       "       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,\n",
       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
       "        11.780105,  12.722513,  13.664922,  14.607329,  15.549738,  16.492147,\n",
       "        17.434555,  18.376963,  19.319372,  20.26178 ,  21.20419 ,  22.146597,\n",
       "        23.089005,  24.031414,  24.973822,  25.916231,  26.858639,  27.801046,\n",
       "        28.743456,  29.685863,  30.628273,  31.57068 ,  32.51309 ,  33.455498,\n",
       "        34.397907,  35.340313,  36.282722,  37.225132,  38.167538,  39.109947,\n",
       "        40.052357,  40.994766,  41.937172,  42.87958 ,  43.82199 ,  44.764397,\n",
       "        45.706806,  46.649216,  47.59162 ,  48.53403 ,  49.47644 ,  50.41885 ,\n",
       "        51.361256,  52.303665,  53.246075,  54.18848 ,  55.13089 ,  56.0733  ,\n",
       "        57.015705,  57.958115,  58.900524,  59.842934,  60.78534 ,  61.72775 ,\n",
       "        62.67016 ,  63.612564,  64.55498 ,  65.49738 ,  66.43979 ,  67.3822  ,\n",
       "        68.32461 ,  69.26701 ,  70.20943 ,  71.15183 ,  72.09424 ,  73.03665 ,\n",
       "        73.97906 ,  74.92146 ,  75.86388 ,  76.80628 ,  77.74869 ,  78.6911  ,\n",
       "        79.63351 ,  80.57591 ,  81.518326,  82.46073 ,  83.403145,  84.34555 ,\n",
       "        85.28796 ,  86.23037 ,  87.172775,  88.11518 ,  89.057594,  90.      ],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-400f7dc8-783f-44ea-a7ef-30bfc583273e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-400f7dc8-783f-44ea-a7ef-30bfc583273e' 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>time_bounds</span></div><div class='xr-var-dims'>(time, hist_interval)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b089f14a-d4a9-48ae-ae3c-6c8f14b297ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b089f14a-d4a9-48ae-ae3c-6c8f14b297ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0638082-4732-443e-9bc9-f8ebb9ab52f3' class='xr-var-data-in' type='checkbox'><label for='data-b0638082-4732-443e-9bc9-f8ebb9ab52f3' 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>long_name :</span></dt><dd>history time interval endpoints</dd></dl></div><div class='xr-var-data'><pre>array([[cftime.DatetimeNoLeap(2000, 1, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2000, 2, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2000, 2, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2000, 3, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2000, 3, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2000, 4, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2000, 4, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2000, 5, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2000, 5, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2000, 6, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2000, 6, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2000, 7, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2000, 7, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2000, 8, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2000, 8, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2000, 9, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2000, 9, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2000, 10, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2000, 10, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2000, 11, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2000, 11, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2000, 12, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2000, 12, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2001, 1, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2001, 1, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2001, 2, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2001, 2, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2001, 3, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2001, 3, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2001, 4, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2001, 4, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2001, 5, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2001, 5, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2001, 6, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2001, 6, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2001, 7, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2001, 7, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2001, 8, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2001, 8, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2001, 9, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2001, 9, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2001, 10, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2001, 10, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2001, 11, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2001, 11, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2001, 12, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2001, 12, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2002, 1, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2002, 1, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2002, 2, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2002, 2, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2002, 3, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2002, 3, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2002, 4, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2002, 4, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2002, 5, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2002, 5, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2002, 6, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2002, 6, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2002, 7, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2002, 7, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2002, 8, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2002, 8, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2002, 9, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2002, 9, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2002, 10, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2002, 10, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2002, 11, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2002, 11, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2002, 12, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2002, 12, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2003, 1, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2003, 1, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2003, 2, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2003, 2, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2003, 3, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2003, 3, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2003, 4, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2003, 4, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2003, 5, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2003, 5, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2003, 6, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2003, 6, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2003, 7, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2003, 7, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2003, 8, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2003, 8, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2003, 9, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2003, 9, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2003, 10, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2003, 10, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2003, 11, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2003, 11, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2003, 12, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2003, 12, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2004, 1, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2004, 1, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2004, 2, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2004, 2, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2004, 3, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2004, 3, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2004, 4, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2004, 4, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2004, 5, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2004, 5, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2004, 6, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2004, 6, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2004, 7, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2004, 7, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2004, 8, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2004, 8, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2004, 9, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2004, 9, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2004, 10, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2004, 10, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2004, 11, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2004, 11, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2004, 12, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2004, 12, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2005, 1, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2005, 1, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2005, 2, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2005, 2, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2005, 3, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2005, 3, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2005, 4, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2005, 4, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2005, 5, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2005, 5, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2005, 6, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2005, 6, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2005, 7, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2005, 7, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2005, 8, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2005, 8, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2005, 9, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2005, 9, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2005, 10, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2005, 10, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2005, 11, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2005, 11, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2005, 12, 1, 0, 0, 0, 0)],\n",
       "       [cftime.DatetimeNoLeap(2005, 12, 1, 0, 0, 0, 0),\n",
       "        cftime.DatetimeNoLeap(2006, 1, 1, 0, 0, 0, 0)]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SOILWATER_10CM</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d60bf01c-a780-42d2-9a46-d12cf6097573' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d60bf01c-a780-42d2-9a46-d12cf6097573' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d02dd4f8-7939-462e-8ec0-a44369e89a9a' class='xr-var-data-in' type='checkbox'><label for='data-d02dd4f8-7939-462e-8ec0-a44369e89a9a' 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>long_name :</span></dt><dd>soil liquid water + ice in top 10cm of soil (veg landunits only)</dd><dt><span>units :</span></dt><dd>kg/m2</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd></dl></div><div class='xr-var-data'><pre>[3981312 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6937d07b-cee7-4dfc-9df6-afceaaddefcf' class='xr-section-summary-in' type='checkbox'  ><label for='section-6937d07b-cee7-4dfc-9df6-afceaaddefcf' class='xr-section-summary' >Attributes: <span>(41)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>title :</span></dt><dd>CLM History file information</dd><dt><span>comment :</span></dt><dd>NOTE: None of the variables are weighted by land fraction!</dd><dt><span>Conventions :</span></dt><dd>CF-1.0</dd><dt><span>history :</span></dt><dd>Tue Sep 29 09:27:34 2020: ncrcat -v SOILWATER_10CM f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2000-01.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2000-02.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2000-03.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2000-04.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2000-05.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2000-06.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2000-07.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2000-08.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2000-09.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2000-10.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2000-11.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2000-12.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2001-01.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2001-02.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2001-03.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2001-04.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2001-05.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2001-06.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2001-07.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2001-08.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2001-09.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2001-10.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2001-11.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2001-12.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2002-01.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2002-02.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2002-03.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2002-04.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2002-05.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2002-06.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2002-07.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2002-08.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2002-09.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2002-10.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2002-11.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2002-12.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2003-01.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2003-02.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2003-03.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2003-04.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2003-05.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2003-06.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2003-07.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2003-08.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2003-09.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2003-10.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2003-11.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2003-12.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2004-01.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2004-02.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2004-03.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2004-04.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2004-05.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2004-06.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2004-07.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2004-08.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2004-09.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2004-10.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2004-11.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2004-12.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2005-01.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2005-02.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2005-03.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2005-04.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2005-05.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2005-06.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2005-07.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2005-08.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2005-09.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2005-10.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2005-11.nc f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2005-12.nc /glade/work/mdfowler/data/temp_staging/f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.2000-2005_SOILWATER10.nc\n",
       "created on 09/12/20 13:28:35</dd><dt><span>source :</span></dt><dd>Community Land Model CLM4.0</dd><dt><span>hostname :</span></dt><dd>cheyenne</dd><dt><span>username :</span></dt><dd>hannay</dd><dt><span>version :</span></dt><dd>cesm2.1.1-exp17</dd><dt><span>revision_id :</span></dt><dd>$Id: histFileMod.F90 42903 2012-12-21 15:32:10Z muszala $</dd><dt><span>case_title :</span></dt><dd>UNSET</dd><dt><span>case_id :</span></dt><dd>f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001</dd><dt><span>Surface_dataset :</span></dt><dd>surfdata_0.9x1.25_hist_16pfts_Irrig_CMIP6_simyr1850_c190214.nc</dd><dt><span>Initial_conditions_dataset :</span></dt><dd>arbitrary initialization</dd><dt><span>PFT_physiological_constants_dataset :</span></dt><dd>clm_params.c170913.nc</dd><dt><span>ltype_vegetated_or_bare_soil :</span></dt><dd>1</dd><dt><span>ltype_crop :</span></dt><dd>2</dd><dt><span>ltype_UNUSED :</span></dt><dd>3</dd><dt><span>ltype_landice_multiple_elevation_classes :</span></dt><dd>4</dd><dt><span>ltype_deep_lake :</span></dt><dd>5</dd><dt><span>ltype_wetland :</span></dt><dd>6</dd><dt><span>ltype_urban_tbd :</span></dt><dd>7</dd><dt><span>ltype_urban_hd :</span></dt><dd>8</dd><dt><span>ltype_urban_md :</span></dt><dd>9</dd><dt><span>ctype_vegetated_or_bare_soil :</span></dt><dd>1</dd><dt><span>ctype_crop :</span></dt><dd>2</dd><dt><span>ctype_crop_noncompete :</span></dt><dd>2*100+m, m=cft_lb,cft_ub</dd><dt><span>ctype_landice :</span></dt><dd>3</dd><dt><span>ctype_landice_multiple_elevation_classes :</span></dt><dd>4*100+m, m=1,glcnec</dd><dt><span>ctype_deep_lake :</span></dt><dd>5</dd><dt><span>ctype_wetland :</span></dt><dd>6</dd><dt><span>ctype_urban_roof :</span></dt><dd>71</dd><dt><span>ctype_urban_sunwall :</span></dt><dd>72</dd><dt><span>ctype_urban_shadewall :</span></dt><dd>73</dd><dt><span>ctype_urban_impervious_road :</span></dt><dd>74</dd><dt><span>ctype_urban_pervious_road :</span></dt><dd>75</dd><dt><span>cft_c3_crop :</span></dt><dd>1</dd><dt><span>cft_c3_irrigated :</span></dt><dd>2</dd><dt><span>time_period_freq :</span></dt><dd>month_1</dd><dt><span>Time_constant_3Dvars_filename :</span></dt><dd>./f.e20.FHIST.f09_f09.cesm2_1_clm4.5.001.clm2.h0.1996-01.nc</dd><dt><span>Time_constant_3Dvars :</span></dt><dd>ZSOI:DZSOI:WATSAT:SUCSAT:BSW:HKSAT:ZLAKE:DZLAKE</dd><dt><span>NCO :</span></dt><dd>netCDF Operators version 4.7.9 (Homepage = http://nco.sf.net, Code = http://github.com/nco/nco)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:         (hist_interval: 2, lat: 192, lon: 288, time: 72)\n",
       "Coordinates:\n",
       "  * time            (time) datetime64[ns] 2000-02-01 2000-03-01 ... 2006-01-01\n",
       "  * lon             (lon) float32 0.0 1.25 2.5 3.75 ... 356.25 357.5 358.75\n",
       "  * lat             (lat) float32 -90.0 -89.057594 -88.11518 ... 89.057594 90.0\n",
       "Dimensions without coordinates: hist_interval\n",
       "Data variables:\n",
       "    time_bounds     (time, hist_interval) object ...\n",
       "    SOILWATER_10CM  (time, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    title:                                     CLM History file information\n",
       "    comment:                                   NOTE: None of the variables ar...\n",
       "    Conventions:                               CF-1.0\n",
       "    history:                                   Tue Sep 29 09:27:34 2020: ncrc...\n",
       "    source:                                    Community Land Model CLM4.0\n",
       "    hostname:                                  cheyenne\n",
       "    username:                                  hannay\n",
       "    version:                                   cesm2.1.1-exp17\n",
       "    revision_id:                               $Id: histFileMod.F90 42903 201...\n",
       "    case_title:                                UNSET\n",
       "    case_id:                                   f.e20.FHIST.f09_f09.cesm2_1_cl...\n",
       "    Surface_dataset:                           surfdata_0.9x1.25_hist_16pfts_...\n",
       "    Initial_conditions_dataset:                arbitrary initialization\n",
       "    PFT_physiological_constants_dataset:       clm_params.c170913.nc\n",
       "    ltype_vegetated_or_bare_soil:              1\n",
       "    ltype_crop:                                2\n",
       "    ltype_UNUSED:                              3\n",
       "    ltype_landice_multiple_elevation_classes:  4\n",
       "    ltype_deep_lake:                           5\n",
       "    ltype_wetland:                             6\n",
       "    ltype_urban_tbd:                           7\n",
       "    ltype_urban_hd:                            8\n",
       "    ltype_urban_md:                            9\n",
       "    ctype_vegetated_or_bare_soil:              1\n",
       "    ctype_crop:                                2\n",
       "    ctype_crop_noncompete:                     2*100+m, m=cft_lb,cft_ub\n",
       "    ctype_landice:                             3\n",
       "    ctype_landice_multiple_elevation_classes:  4*100+m, m=1,glcnec\n",
       "    ctype_deep_lake:                           5\n",
       "    ctype_wetland:                             6\n",
       "    ctype_urban_roof:                          71\n",
       "    ctype_urban_sunwall:                       72\n",
       "    ctype_urban_shadewall:                     73\n",
       "    ctype_urban_impervious_road:               74\n",
       "    ctype_urban_pervious_road:                 75\n",
       "    cft_c3_crop:                               1\n",
       "    cft_c3_irrigated:                          2\n",
       "    time_period_freq:                          month_1\n",
       "    Time_constant_3Dvars_filename:             ./f.e20.FHIST.f09_f09.cesm2_1_...\n",
       "    Time_constant_3Dvars:                      ZSOI:DZSOI:WATSAT:SUCSAT:BSW:H...\n",
       "    NCO:                                       netCDF Operators version 4.7.9..."
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "smDS_mon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "3acc15dd",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-26T16:26:14.917989Z",
     "start_time": "2021-05-26T16:26:14.913411Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 7.3506985,  8.017492 ,  8.274174 ,  7.4084   ,  7.2128267,\n",
       "        7.1359296,  8.487063 ,  7.946712 , 10.644889 , 10.939372 ,\n",
       "        8.588856 ,  7.8139424,  7.6468215,  7.336437 ,  8.257264 ,\n",
       "        7.5397954,  7.291109 ,  7.219929 ,  7.1428204,  8.887676 ,\n",
       "       10.742615 ,  7.5528975,  7.2602654,  7.1930714,  8.723995 ,\n",
       "        8.480621 ,  7.7608476,  7.66485  ,  7.37055  ,  7.2233095,\n",
       "        7.63525  ,  7.321258 ,  9.004702 ,  7.7478995,  7.7397017,\n",
       "        7.9680905, 14.9434185, 12.815184 , 11.866061 ,  8.218248 ,\n",
       "        7.4860177,  7.4199286,  7.713141 ,  7.2906528,  7.621982 ,\n",
       "        7.313528 ,  7.2167716,  7.6301284,  7.5861554,  7.5928636,\n",
       "        7.5506606,  7.8195453,  7.2629504,  7.194107 ,  7.3777804,\n",
       "        7.9473777, 13.478857 ,  7.6085544,  7.585482 , 13.161855 ,\n",
       "       16.773415 ,  9.839684 ,  8.831545 ,  7.704231 ,  7.4554014,\n",
       "        7.4028587,  7.37782  ,  8.28383  , 13.247179 ,  8.066718 ,\n",
       "        7.3426404,  7.2546577], dtype=float32)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "smDS_mon.SOILWATER_10CM.values[:,120,200]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "536554a5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-26T16:26:40.231758Z",
     "start_time": "2021-05-26T16:26:40.218618Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;SOILWATER_10CM&#x27; (time: 31)&gt;\n",
       "array([7.3506985,       nan,       nan,       nan,       nan,       nan,\n",
       "             nan,       nan,       nan,       nan,       nan,       nan,\n",
       "             nan,       nan,       nan,       nan,       nan,       nan,\n",
       "             nan,       nan,       nan,       nan,       nan,       nan,\n",
       "             nan,       nan,       nan,       nan,       nan, 8.017492 ,\n",
       "             nan], dtype=float32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 2000-02-01 2000-02-02 ... 2000-03-02\n",
       "    lon      float32 250.0\n",
       "    lat      float32 23.089005</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'SOILWATER_10CM'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 31</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-7f89ba2b-68ea-4b38-a571-e1b2aeaa91b4' class='xr-array-in' type='checkbox' checked><label for='section-7f89ba2b-68ea-4b38-a571-e1b2aeaa91b4' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>7.3506985 nan nan nan nan nan nan ... nan nan nan nan nan 8.017492 nan</span></div><div class='xr-array-data'><pre>array([7.3506985,       nan,       nan,       nan,       nan,       nan,\n",
       "             nan,       nan,       nan,       nan,       nan,       nan,\n",
       "             nan,       nan,       nan,       nan,       nan,       nan,\n",
       "             nan,       nan,       nan,       nan,       nan,       nan,\n",
       "             nan,       nan,       nan,       nan,       nan, 8.017492 ,\n",
       "             nan], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-1577cd4e-8e9e-4d51-be71-3eb358d1a22a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1577cd4e-8e9e-4d51-be71-3eb358d1a22a' 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'>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'>2000-02-01 ... 2000-03-02</div><input id='attrs-0959ba88-9c95-49c4-9aba-44a7836a2718' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0959ba88-9c95-49c4-9aba-44a7836a2718' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d71d2e51-81c7-4ec8-9430-7a9eb9070607' class='xr-var-data-in' type='checkbox'><label for='data-d71d2e51-81c7-4ec8-9430-7a9eb9070607' 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><div class='xr-var-data'><pre>array([&#x27;2000-02-01T00:00:00.000000000&#x27;, &#x27;2000-02-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-02-03T00:00:00.000000000&#x27;, &#x27;2000-02-04T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-02-05T00:00:00.000000000&#x27;, &#x27;2000-02-06T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-02-07T00:00:00.000000000&#x27;, &#x27;2000-02-08T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-02-09T00:00:00.000000000&#x27;, &#x27;2000-02-10T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-02-11T00:00:00.000000000&#x27;, &#x27;2000-02-12T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-02-13T00:00:00.000000000&#x27;, &#x27;2000-02-14T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-02-15T00:00:00.000000000&#x27;, &#x27;2000-02-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-02-17T00:00:00.000000000&#x27;, &#x27;2000-02-18T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-02-19T00:00:00.000000000&#x27;, &#x27;2000-02-20T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-02-21T00:00:00.000000000&#x27;, &#x27;2000-02-22T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-02-23T00:00:00.000000000&#x27;, &#x27;2000-02-24T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-02-25T00:00:00.000000000&#x27;, &#x27;2000-02-26T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-02-27T00:00:00.000000000&#x27;, &#x27;2000-02-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-02-29T00:00:00.000000000&#x27;, &#x27;2000-03-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-03-02T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>250.0</div><input id='attrs-8472411f-ecae-42b3-b2bc-7a13dc2a9223' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8472411f-ecae-42b3-b2bc-7a13dc2a9223' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-87a32864-19af-4162-9913-b1f7730f78a6' class='xr-var-data-in' type='checkbox'><label for='data-87a32864-19af-4162-9913-b1f7730f78a6' 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>long_name :</span></dt><dd>coordinate longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array(250., dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>23.089005</div><input id='attrs-db39fe10-26a2-4ada-b669-1b3579fdf4d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-db39fe10-26a2-4ada-b669-1b3579fdf4d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fbc3b858-a973-4036-a930-929fed2edbbf' class='xr-var-data-in' type='checkbox'><label for='data-fbc3b858-a973-4036-a930-929fed2edbbf' 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>long_name :</span></dt><dd>coordinate latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array(23.089005, dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-11b2bfe6-cacb-424c-8e74-3e796fbf477a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-11b2bfe6-cacb-424c-8e74-3e796fbf477a' 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>"
      ],
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       "array([7.3506985,       nan,       nan,       nan,       nan,       nan,\n",
       "             nan,       nan,       nan,       nan,       nan,       nan,\n",
       "             nan,       nan,       nan,       nan,       nan,       nan,\n",
       "             nan,       nan,       nan,       nan,       nan,       nan,\n",
       "             nan,       nan,       nan,       nan,       nan, 8.017492 ,\n",
       "             nan], dtype=float32)\n",
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       "    lon      float32 250.0\n",
       "    lat      float32 23.089005"
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      "/Users/mdfowler/opt/anaconda3/envs/newBase/lib/python3.8/site-packages/xarray/core/nanops.py:142: RuntimeWarning: Mean of empty slice\n",
      "  return np.nanmean(a, axis=axis, dtype=dtype)\n"
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;SOILWATER_10CM&#x27; (time: 1827, lat: 192, lon: 288)&gt;\n",
       "array([[[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1979-01-01 1979-01-02 ... 1984-01-01\n",
       "  * lat      (lat) float64 -90.0 -89.06 -88.12 -87.17 ... 87.17 88.12 89.06 90.0\n",
       "  * lon      (lon) float64 0.0 1.25 2.5 3.75 5.0 ... 355.0 356.2 357.5 358.8</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'SOILWATER_10CM'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1827</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-5e26b1ee-8e4e-43a7-b807-d081c5d8eb7b' class='xr-array-in' type='checkbox' checked><label for='section-5e26b1ee-8e4e-43a7-b807-d081c5d8eb7b' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>nan nan nan nan nan nan nan nan ... nan nan nan nan nan nan nan nan</span></div><div class='xr-array-data'><pre>array([[[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-3db628dd-bf22-4047-83a1-2ff7ee8794db' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3db628dd-bf22-4047-83a1-2ff7ee8794db' 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'>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'>1979-01-01 ... 1984-01-01</div><input id='attrs-e221c8ff-1cec-4601-9081-e5fc8484199f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e221c8ff-1cec-4601-9081-e5fc8484199f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b9fe6aa-121b-4aa3-b14b-b4fd90119a39' class='xr-var-data-in' type='checkbox'><label for='data-6b9fe6aa-121b-4aa3-b14b-b4fd90119a39' 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><div class='xr-var-data'><pre>array([&#x27;1979-01-01T00:00:00.000000000&#x27;, &#x27;1979-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;1979-01-03T00:00:00.000000000&#x27;, ..., &#x27;1983-12-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-12-31T00:00:00.000000000&#x27;, &#x27;1984-01-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></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'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-18e0f3ad-4768-49cc-99da-12d36dd1703e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18e0f3ad-4768-49cc-99da-12d36dd1703e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-957b18ea-e3ca-4466-a270-2267715da31c' class='xr-var-data-in' type='checkbox'><label for='data-957b18ea-e3ca-4466-a270-2267715da31c' 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>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,\n",
       "       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,\n",
       "       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,\n",
       "       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,\n",
       "       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,\n",
       "       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,\n",
       "       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,\n",
       "       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,\n",
       "       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,\n",
       "       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,\n",
       "       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,\n",
       "       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,\n",
       "       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,\n",
       "       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,\n",
       "       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,\n",
       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
       "        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,\n",
       "        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,\n",
       "        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,\n",
       "        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,\n",
       "        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,\n",
       "        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,\n",
       "        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,\n",
       "        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,\n",
       "        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,\n",
       "        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,\n",
       "        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,\n",
       "        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,\n",
       "        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,\n",
       "        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><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'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-cbe6aa62-b4e7-44ce-8a44-4075a55817b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cbe6aa62-b4e7-44ce-8a44-4075a55817b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4d71c28-04bc-4129-977e-ce59b84a909b' class='xr-var-data-in' type='checkbox'><label for='data-e4d71c28-04bc-4129-977e-ce59b84a909b' 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>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6cee46f7-aa59-4d97-a50e-f459fe0b55b1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6cee46f7-aa59-4d97-a50e-f459fe0b55b1' 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>"
      ],
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       "array([[[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
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       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1979-01-01 1979-01-02 ... 1984-01-01\n",
       "  * lat      (lat) float64 -90.0 -89.06 -88.12 -87.17 ... 87.17 88.12 89.06 90.0\n",
       "  * lon      (lon) float64 0.0 1.25 2.5 3.75 5.0 ... 355.0 356.2 357.5 358.8"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testResample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "1930219b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-26T16:07:08.062832Z",
     "start_time": "2021-05-26T16:07:08.051869Z"
    },
    "scrolled": true
   },
   "outputs": [
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       ".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",
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       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
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       "\n",
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       "\n",
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       "\n",
       ".xr-attrs dt, dd {\n",
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       "\n",
       ".xr-attrs dt {\n",
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       "  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",
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       "\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><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;time&#x27; (time: 1826)&gt;\n",
       "array([&#x27;1979-01-01T00:00:00.000000000&#x27;, &#x27;1979-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;1979-01-03T00:00:00.000000000&#x27;, ..., &#x27;1983-12-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-12-31T00:00:00.000000000&#x27;, &#x27;1984-01-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1979-01-01 1979-01-02 ... 1984-01-01</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'time'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1826</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-be950b7c-6346-4153-bd43-63b8a270e744' class='xr-array-in' type='checkbox' checked><label for='section-be950b7c-6346-4153-bd43-63b8a270e744' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1979-01-01 1979-01-02 1979-01-03 ... 1983-12-30 1983-12-31 1984-01-01</span></div><div class='xr-array-data'><pre>array([&#x27;1979-01-01T00:00:00.000000000&#x27;, &#x27;1979-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;1979-01-03T00:00:00.000000000&#x27;, ..., &#x27;1983-12-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-12-31T00:00:00.000000000&#x27;, &#x27;1984-01-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></div></li><li class='xr-section-item'><input id='section-83f04c70-547d-4f29-81c0-35c684bcb39d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-83f04c70-547d-4f29-81c0-35c684bcb39d' class='xr-section-summary' >Coordinates: <span>(1)</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'>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'>1979-01-01 ... 1984-01-01</div><input id='attrs-0c329e5b-5030-4cb1-a8d1-84a17b738275' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0c329e5b-5030-4cb1-a8d1-84a17b738275' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c50ae5e5-3ca9-449d-8d92-de06b274f9f1' class='xr-var-data-in' type='checkbox'><label for='data-c50ae5e5-3ca9-449d-8d92-de06b274f9f1' 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><div class='xr-var-data'><pre>array([&#x27;1979-01-01T00:00:00.000000000&#x27;, &#x27;1979-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;1979-01-03T00:00:00.000000000&#x27;, ..., &#x27;1983-12-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-12-31T00:00:00.000000000&#x27;, &#x27;1984-01-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-06be4df9-53f7-4f69-bd63-0656e6ad34d4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-06be4df9-53f7-4f69-bd63-0656e6ad34d4' 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.DataArray 'time' (time: 1826)>\n",
       "array(['1979-01-01T00:00:00.000000000', '1979-01-02T00:00:00.000000000',\n",
       "       '1979-01-03T00:00:00.000000000', ..., '1983-12-30T00:00:00.000000000',\n",
       "       '1983-12-31T00:00:00.000000000', '1984-01-01T00:00:00.000000000'],\n",
       "      dtype='datetime64[ns]')\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1979-01-01 1979-01-02 ... 1984-01-01"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "ds[xname].time"
   ]
  },
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   "metadata": {},
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   "id": "bc521814",
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   "outputs": [],
   "source": []
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  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "3d3f7b54",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-19T17:34:42.070945Z",
     "start_time": "2021-05-19T17:34:42.066246Z"
    },
    "scrolled": true
   },
   "outputs": [
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     "data": {
      "text/plain": [
       "-7.975338563186384"
      ]
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     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.nanmean(couplingIndex[7,:,:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "430c58c1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-19T17:49:50.800765Z",
     "start_time": "2021-05-19T17:49:50.796466Z"
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "-8.181537856698116"
      ]
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     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.nanmean(couplingIndex[1,:,:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d5f791e1",
   "metadata": {},
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   "cell_type": "code",
   "execution_count": null,
   "id": "3cafaf96",
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   "source": []
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  {
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   "execution_count": 6,
   "id": "ee4a8d0c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-19T15:30:59.048720Z",
     "start_time": "2021-05-19T15:30:51.329666Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/mdfowler/opt/anaconda3/envs/newBase/lib/python3.8/site-packages/xarray/core/common.py:1123: FutureWarning: 'base' in .resample() and in Grouper() is deprecated.\n",
      "The new arguments that you should use are 'offset' or 'origin'.\n",
      "\n",
      ">>> df.resample(freq=\"3s\", base=2)\n",
      "\n",
      "becomes:\n",
      "\n",
      ">>> df.resample(freq=\"3s\", offset=\"2s\")\n",
      "\n",
      "  grouper = pd.Grouper(\n",
      "/Users/mdfowler/opt/anaconda3/envs/newBase/lib/python3.8/site-packages/xarray/core/nanops.py:142: RuntimeWarning: Mean of empty slice\n",
      "  return np.nanmean(a, axis=axis, dtype=dtype)\n",
      "/Users/mdfowler/opt/anaconda3/envs/newBase/lib/python3.8/site-packages/numpy/lib/nanfunctions.py:1664: RuntimeWarning: Degrees of freedom <= 0 for slice.\n",
      "  var = nanvar(a, axis=axis, dtype=dtype, out=out, ddof=ddof,\n"
     ]
    }
   ],
   "source": [
    "# Compute coupling index \n",
    "terraLeg_coupling_CLM45 = cm.metrics.CouplingIndex()\n",
    "terraLeg_coupling_CLM45 = terraLeg_coupling_CLM45.compute(ds, xname='SOILWATER_10CM',yname='SHFLX',averaging='season')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1eba2704",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-19T15:31:30.004919Z",
     "start_time": "2021-05-19T15:31:30.002380Z"
    }
   },
   "outputs": [],
   "source": [
    "cometCI = terraLeg_coupling_CLM45.SOILWATER_10CM_SHFLX_CI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7425e0ad",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-19T15:31:49.658066Z",
     "start_time": "2021-05-19T15:31:49.651941Z"
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "np.nanmin(couplingIndex - cometCI)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "72ab6475",
   "metadata": {},
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