Reading Veros Output.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "aa0d6a91-4284-4325-8c94-73439f8bfb97",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "import numpy as np\n",
    "import cmocean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2c7fc209-993e-4e91-b645-2521e0bc0646",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "OUTPUT_FILES = {\n",
    "    \"snapshot\": \"4deg.snapshot.nc\",\n",
    "    \"averages\": \"4deg.averages.nc\",\n",
    "    \"overturning\": \"4deg.overturning.nc\",\n",
    "    \"energy\": \"4deg.energy.nc\",\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5f3109f4-d937-4001-8739-184e6ba44644",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body[data-theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\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",
       ".xr-index-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",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\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.Dataset&gt;\n",
       "Dimensions:       (Time: 10, isle: 6, nmonths: 12, yu: 40, xu: 90, zt: 15,\n",
       "                   yt: 40, xt: 90, tensor1: 2, tensor2: 2, zw: 15)\n",
       "Coordinates:\n",
       "  * Time          (Time) timedelta64[ns] 32760 days 33120 days ... 36000 days\n",
       "  * isle          (isle) float64 0.0 1.0 2.0 3.0 4.0 5.0\n",
       "  * nmonths       (nmonths) float64 0.0 1.0 2.0 3.0 4.0 ... 8.0 9.0 10.0 11.0\n",
       "  * tensor1       (tensor1) float64 0.0 1.0\n",
       "  * tensor2       (tensor2) float64 0.0 1.0\n",
       "  * xt            (xt) float64 2.0 6.0 10.0 14.0 ... 346.0 350.0 354.0 358.0\n",
       "  * xu            (xu) float64 4.0 8.0 12.0 16.0 ... 348.0 352.0 356.0 360.0\n",
       "  * yt            (yt) float64 -78.0 -74.0 -70.0 -66.0 ... 66.0 70.0 74.0 78.0\n",
       "  * yu            (yu) float64 -76.0 -72.0 -68.0 -64.0 ... 68.0 72.0 76.0 80.0\n",
       "  * zt            (zt) float64 -4.855e+03 -4.165e+03 -3.575e+03 ... -65.0 -35.0\n",
       "  * zw            (zw) float64 -4.51e+03 -3.87e+03 -3.28e+03 ... -50.0 0.0\n",
       "Data variables:\n",
       "    psi           (Time, yu, xu) float64 ...\n",
       "    salt          (Time, zt, yt, xt) float64 ...\n",
       "    surface_taux  (Time, yt, xu) float64 ...\n",
       "    surface_tauy  (Time, yu, xt) float64 ...\n",
       "    temp          (Time, zt, yt, xt) float64 ...\n",
       "    u             (Time, zt, yt, xu) float64 ...\n",
       "    v             (Time, zt, yu, xt) float64 ...\n",
       "    w             (Time, zw, yt, xt) float64 ...\n",
       "Attributes:\n",
       "    date_created:      2021-10-26T12:02:31.193084\n",
       "    veros_version:     1.4.2\n",
       "    setup_identifier:  4deg\n",
       "    history:           Thu Oct 28 16:05:51 2021: ncks -d Time,90,99 4deg.aver...\n",
       "    NCO:               netCDF Operators version 4.8.0 (Homepage = http://nco....</pre><div class='xr-wrap' style='display:none'><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-6366a36b-158b-4738-8dc5-d0034b77a631' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6366a36b-158b-4738-8dc5-d0034b77a631' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>Time</span>: 10</li><li><span class='xr-has-index'>isle</span>: 6</li><li><span class='xr-has-index'>nmonths</span>: 12</li><li><span class='xr-has-index'>yu</span>: 40</li><li><span class='xr-has-index'>xu</span>: 90</li><li><span class='xr-has-index'>zt</span>: 15</li><li><span class='xr-has-index'>yt</span>: 40</li><li><span class='xr-has-index'>xt</span>: 90</li><li><span class='xr-has-index'>tensor1</span>: 2</li><li><span class='xr-has-index'>tensor2</span>: 2</li><li><span class='xr-has-index'>zw</span>: 15</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-144d9df4-45f3-42e5-844b-59011a17d1db' class='xr-section-summary-in' type='checkbox'  checked><label for='section-144d9df4-45f3-42e5-844b-59011a17d1db' class='xr-section-summary' >Coordinates: <span>(11)</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'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>32760 days ... 36000 days</div><input id='attrs-293aca19-5333-4526-bac1-ecc248eee6ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-293aca19-5333-4526-bac1-ecc248eee6ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3a0fd8d-eeab-4ce9-ba06-fe96dabc0def' class='xr-var-data-in' type='checkbox'><label for='data-c3a0fd8d-eeab-4ce9-ba06-fe96dabc0def' 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>Time</dd><dt><span>time_origin :</span></dt><dd>01-JAN-1900 00:00:00</dd></dl></div><div class='xr-var-data'><pre>array([2830464000000000000, 2861568000000000000, 2892672000000000000,\n",
       "       2923776000000000000, 2954880000000000000, 2985984000000000000,\n",
       "       3017088000000000000, 3048192000000000000, 3079296000000000000,\n",
       "       3110400000000000000], dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>isle</span></div><div class='xr-var-dims'>(isle)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.0 2.0 3.0 4.0 5.0</div><input id='attrs-e66b34d5-f4ee-4d24-8998-7d0da195296d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e66b34d5-f4ee-4d24-8998-7d0da195296d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-091eb833-1546-4d29-b8fd-d0b3aa82696d' class='xr-var-data-in' type='checkbox'><label for='data-091eb833-1546-4d29-b8fd-d0b3aa82696d' 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>Island number</dd><dt><span>units :</span></dt><dd></dd></dl></div><div class='xr-var-data'><pre>array([0., 1., 2., 3., 4., 5.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nmonths</span></div><div class='xr-var-dims'>(nmonths)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.0 2.0 3.0 ... 9.0 10.0 11.0</div><input id='attrs-75a4798d-4bb9-48bf-90ca-b60fef07dfa5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-75a4798d-4bb9-48bf-90ca-b60fef07dfa5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6796bec-e82c-44f1-962b-a972a27c7987' class='xr-var-data-in' type='checkbox'><label for='data-a6796bec-e82c-44f1-962b-a972a27c7987' 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>nmonths</dd><dt><span>units :</span></dt><dd></dd></dl></div><div class='xr-var-data'><pre>array([ 0.,  1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>tensor1</span></div><div class='xr-var-dims'>(tensor1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.0</div><input id='attrs-4614fdbf-42c2-4493-9b4f-eb663f9f52bb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4614fdbf-42c2-4493-9b4f-eb663f9f52bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-565daba3-2283-4880-a88d-eabcdae1d932' class='xr-var-data-in' type='checkbox'><label for='data-565daba3-2283-4880-a88d-eabcdae1d932' 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>tensor1</dd><dt><span>units :</span></dt><dd></dd></dl></div><div class='xr-var-data'><pre>array([0., 1.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>tensor2</span></div><div class='xr-var-dims'>(tensor2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.0</div><input id='attrs-54c836af-733f-4218-b763-f56cc92cedb7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-54c836af-733f-4218-b763-f56cc92cedb7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-304aed07-49d6-4997-a485-3de678cb6bc4' class='xr-var-data-in' type='checkbox'><label for='data-304aed07-49d6-4997-a485-3de678cb6bc4' 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>tensor2</dd><dt><span>units :</span></dt><dd></dd></dl></div><div class='xr-var-data'><pre>array([0., 1.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xt</span></div><div class='xr-var-dims'>(xt)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0 6.0 10.0 ... 350.0 354.0 358.0</div><input id='attrs-768e9034-1715-47bf-9775-10ec41440f9f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-768e9034-1715-47bf-9775-10ec41440f9f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c2dfb30-1aec-476d-90c2-3b0cf9d045f5' class='xr-var-data-in' type='checkbox'><label for='data-7c2dfb30-1aec-476d-90c2-3b0cf9d045f5' 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>Zonal coordinate (T)</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([  2.,   6.,  10.,  14.,  18.,  22.,  26.,  30.,  34.,  38.,  42.,  46.,\n",
       "        50.,  54.,  58.,  62.,  66.,  70.,  74.,  78.,  82.,  86.,  90.,  94.,\n",
       "        98., 102., 106., 110., 114., 118., 122., 126., 130., 134., 138., 142.,\n",
       "       146., 150., 154., 158., 162., 166., 170., 174., 178., 182., 186., 190.,\n",
       "       194., 198., 202., 206., 210., 214., 218., 222., 226., 230., 234., 238.,\n",
       "       242., 246., 250., 254., 258., 262., 266., 270., 274., 278., 282., 286.,\n",
       "       290., 294., 298., 302., 306., 310., 314., 318., 322., 326., 330., 334.,\n",
       "       338., 342., 346., 350., 354., 358.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xu</span></div><div class='xr-var-dims'>(xu)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.0 8.0 12.0 ... 352.0 356.0 360.0</div><input id='attrs-4e99d279-f231-4825-984d-feddda415777' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e99d279-f231-4825-984d-feddda415777' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69fa7c20-b4b3-47f1-a82b-34fa71cf205f' class='xr-var-data-in' type='checkbox'><label for='data-69fa7c20-b4b3-47f1-a82b-34fa71cf205f' 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>Zonal coordinate (U)</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([  4.,   8.,  12.,  16.,  20.,  24.,  28.,  32.,  36.,  40.,  44.,  48.,\n",
       "        52.,  56.,  60.,  64.,  68.,  72.,  76.,  80.,  84.,  88.,  92.,  96.,\n",
       "       100., 104., 108., 112., 116., 120., 124., 128., 132., 136., 140., 144.,\n",
       "       148., 152., 156., 160., 164., 168., 172., 176., 180., 184., 188., 192.,\n",
       "       196., 200., 204., 208., 212., 216., 220., 224., 228., 232., 236., 240.,\n",
       "       244., 248., 252., 256., 260., 264., 268., 272., 276., 280., 284., 288.,\n",
       "       292., 296., 300., 304., 308., 312., 316., 320., 324., 328., 332., 336.,\n",
       "       340., 344., 348., 352., 356., 360.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yt</span></div><div class='xr-var-dims'>(yt)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-78.0 -74.0 -70.0 ... 74.0 78.0</div><input id='attrs-dfa62961-caca-42c0-8714-c4195d328884' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dfa62961-caca-42c0-8714-c4195d328884' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-73da47ad-1124-47e0-bc43-1d3ed785ad2b' class='xr-var-data-in' type='checkbox'><label for='data-73da47ad-1124-47e0-bc43-1d3ed785ad2b' 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>Meridional coordinate (T)</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-78., -74., -70., -66., -62., -58., -54., -50., -46., -42., -38., -34.,\n",
       "       -30., -26., -22., -18., -14., -10.,  -6.,  -2.,   2.,   6.,  10.,  14.,\n",
       "        18.,  22.,  26.,  30.,  34.,  38.,  42.,  46.,  50.,  54.,  58.,  62.,\n",
       "        66.,  70.,  74.,  78.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yu</span></div><div class='xr-var-dims'>(yu)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-76.0 -72.0 -68.0 ... 76.0 80.0</div><input id='attrs-1ee20cde-e596-4604-9327-06d8d5a85998' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ee20cde-e596-4604-9327-06d8d5a85998' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3cb0040-759f-49a3-8a61-cf1e9d52879c' class='xr-var-data-in' type='checkbox'><label for='data-f3cb0040-759f-49a3-8a61-cf1e9d52879c' 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>Meridional coordinate (U)</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-76., -72., -68., -64., -60., -56., -52., -48., -44., -40., -36., -32.,\n",
       "       -28., -24., -20., -16., -12.,  -8.,  -4.,   0.,   4.,   8.,  12.,  16.,\n",
       "        20.,  24.,  28.,  32.,  36.,  40.,  44.,  48.,  52.,  56.,  60.,  64.,\n",
       "        68.,  72.,  76.,  80.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zt</span></div><div class='xr-var-dims'>(zt)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-4.855e+03 -4.165e+03 ... -35.0</div><input id='attrs-77e61711-1495-49d0-9e4c-b10c7fadd0f4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-77e61711-1495-49d0-9e4c-b10c7fadd0f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54b0715d-4f46-4377-b592-aded6a29264f' class='xr-var-data-in' type='checkbox'><label for='data-54b0715d-4f46-4377-b592-aded6a29264f' 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>Vertical coordinate (T)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array([-4855., -4165., -3575., -2985., -2495., -2005., -1615., -1225.,  -935.,\n",
       "        -645.,  -455.,  -265.,  -175.,   -65.,   -35.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zw</span></div><div class='xr-var-dims'>(zw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-4.51e+03 -3.87e+03 ... -50.0 0.0</div><input id='attrs-fd5f1377-e72e-4585-8154-11d22026d9c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd5f1377-e72e-4585-8154-11d22026d9c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-960e04f6-b155-490d-a9e0-7c5e88fd0d90' class='xr-var-data-in' type='checkbox'><label for='data-960e04f6-b155-490d-a9e0-7c5e88fd0d90' 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>Vertical coordinate (W)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array([-4510., -3870., -3280., -2740., -2250., -1810., -1420., -1080.,  -790.,\n",
       "        -550.,  -360.,  -220.,  -120.,   -50.,     0.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ab726ffa-29f2-451c-a7fe-f56965f77d39' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ab726ffa-29f2-451c-a7fe-f56965f77d39' class='xr-section-summary' >Data variables: <span>(8)</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>psi</span></div><div class='xr-var-dims'>(Time, yu, xu)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-25075566-9835-43e2-9e67-a1b1d5d04d31' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25075566-9835-43e2-9e67-a1b1d5d04d31' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2458a553-101c-4950-8457-dc242bbcaf93' class='xr-var-data-in' type='checkbox'><label for='data-2458a553-101c-4950-8457-dc242bbcaf93' 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>Streamfunction</dd><dt><span>units :</span></dt><dd>m^3/s</dd></dl></div><div class='xr-var-data'><pre>[36000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>salt</span></div><div class='xr-var-dims'>(Time, zt, yt, xt)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0306f0eb-9649-4008-b89c-a8733dbd7a84' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0306f0eb-9649-4008-b89c-a8733dbd7a84' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5a4b2b8-281d-44d7-85cc-340c37ca5319' class='xr-var-data-in' type='checkbox'><label for='data-a5a4b2b8-281d-44d7-85cc-340c37ca5319' 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>Salinity</dd><dt><span>units :</span></dt><dd>g/kg</dd></dl></div><div class='xr-var-data'><pre>[540000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>surface_taux</span></div><div class='xr-var-dims'>(Time, yt, xu)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-64f5081f-17e6-451d-9b81-2ff95dbe4ecd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64f5081f-17e6-451d-9b81-2ff95dbe4ecd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23db8418-534e-46e9-9641-ecc79d0a5b5d' class='xr-var-data-in' type='checkbox'><label for='data-23db8418-534e-46e9-9641-ecc79d0a5b5d' 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>Surface wind stress</dd><dt><span>units :</span></dt><dd>N/m^2</dd></dl></div><div class='xr-var-data'><pre>[36000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>surface_tauy</span></div><div class='xr-var-dims'>(Time, yu, xt)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7c7e7361-5cc1-4d25-99ac-7b3362a8c9c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7c7e7361-5cc1-4d25-99ac-7b3362a8c9c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a70f07d9-89f6-45e1-86e1-e8b9406a8965' class='xr-var-data-in' type='checkbox'><label for='data-a70f07d9-89f6-45e1-86e1-e8b9406a8965' 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>Surface wind stress</dd><dt><span>units :</span></dt><dd>N/m^2</dd></dl></div><div class='xr-var-data'><pre>[36000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(Time, zt, yt, xt)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-115aa8ee-26a0-492e-9241-bb5058386ec8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-115aa8ee-26a0-492e-9241-bb5058386ec8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c668a06b-9fbf-4a3f-9313-c0e82af6a22b' class='xr-var-data-in' type='checkbox'><label for='data-c668a06b-9fbf-4a3f-9313-c0e82af6a22b' 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>Temperature</dd><dt><span>units :</span></dt><dd>deg C</dd></dl></div><div class='xr-var-data'><pre>[540000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(Time, zt, yt, xu)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-207adaa1-3a9f-499a-bfd5-e9981caa102b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-207adaa1-3a9f-499a-bfd5-e9981caa102b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6d4c08c-c586-45ef-9c17-99878e980a5f' class='xr-var-data-in' type='checkbox'><label for='data-e6d4c08c-c586-45ef-9c17-99878e980a5f' 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>Zonal velocity</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>[540000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(Time, zt, yu, xt)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7c673197-f261-4819-845b-4e956f210cdd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7c673197-f261-4819-845b-4e956f210cdd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ab2e7aa-7b7f-4b84-b852-1a1bbe55ba4c' class='xr-var-data-in' type='checkbox'><label for='data-8ab2e7aa-7b7f-4b84-b852-1a1bbe55ba4c' 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>Meridional velocity</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>[540000 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>w</span></div><div class='xr-var-dims'>(Time, zw, yt, xt)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7ca68f13-122e-4535-bbe0-6d84d4ee5adf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ca68f13-122e-4535-bbe0-6d84d4ee5adf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27f811e7-7a07-42c3-9919-333deb4421cf' class='xr-var-data-in' type='checkbox'><label for='data-27f811e7-7a07-42c3-9919-333deb4421cf' 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>Vertical velocity</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>[540000 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-67b6021a-4fca-4384-be86-a3f4ca265179' class='xr-section-summary-in' type='checkbox'  ><label for='section-67b6021a-4fca-4384-be86-a3f4ca265179' class='xr-section-summary' >Indexes: <span>(11)</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-index-name'><div>Time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-85547423-e7e3-43d5-8658-f3f1cc4b7b05' class='xr-index-data-in' type='checkbox'/><label for='index-85547423-e7e3-43d5-8658-f3f1cc4b7b05' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(TimedeltaIndex([&#x27;32760 days&#x27;, &#x27;33120 days&#x27;, &#x27;33480 days&#x27;, &#x27;33840 days&#x27;,\n",
       "                &#x27;34200 days&#x27;, &#x27;34560 days&#x27;, &#x27;34920 days&#x27;, &#x27;35280 days&#x27;,\n",
       "                &#x27;35640 days&#x27;, &#x27;36000 days&#x27;],\n",
       "               dtype=&#x27;timedelta64[ns]&#x27;, name=&#x27;Time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>isle</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3e93881f-d558-4390-afcd-cfb9ab78b5f8' class='xr-index-data-in' type='checkbox'/><label for='index-3e93881f-d558-4390-afcd-cfb9ab78b5f8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0.0, 1.0, 2.0, 3.0, 4.0, 5.0], dtype=&#x27;float64&#x27;, name=&#x27;isle&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>nmonths</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-5a0fea7b-31ce-4e37-acf7-5116c3f685be' class='xr-index-data-in' type='checkbox'/><label for='index-5a0fea7b-31ce-4e37-acf7-5116c3f685be' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0], dtype=&#x27;float64&#x27;, name=&#x27;nmonths&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>tensor1</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f30beb04-fbdf-4b0c-bbf2-79082c8c9a9f' class='xr-index-data-in' type='checkbox'/><label for='index-f30beb04-fbdf-4b0c-bbf2-79082c8c9a9f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0.0, 1.0], dtype=&#x27;float64&#x27;, name=&#x27;tensor1&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>tensor2</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c32c7da1-a575-4e38-b8a8-88b6ff7a336e' class='xr-index-data-in' type='checkbox'/><label for='index-c32c7da1-a575-4e38-b8a8-88b6ff7a336e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0.0, 1.0], dtype=&#x27;float64&#x27;, name=&#x27;tensor2&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>xt</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-767da8cc-e9e2-4a6a-8246-7fd72e448241' class='xr-index-data-in' type='checkbox'/><label for='index-767da8cc-e9e2-4a6a-8246-7fd72e448241' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  2.0,   6.0,  10.0,  14.0,  18.0,  22.0,  26.0,  30.0,  34.0,  38.0,\n",
       "        42.0,  46.0,  50.0,  54.0,  58.0,  62.0,  66.0,  70.0,  74.0,  78.0,\n",
       "        82.0,  86.0,  90.0,  94.0,  98.0, 102.0, 106.0, 110.0, 114.0, 118.0,\n",
       "       122.0, 126.0, 130.0, 134.0, 138.0, 142.0, 146.0, 150.0, 154.0, 158.0,\n",
       "       162.0, 166.0, 170.0, 174.0, 178.0, 182.0, 186.0, 190.0, 194.0, 198.0,\n",
       "       202.0, 206.0, 210.0, 214.0, 218.0, 222.0, 226.0, 230.0, 234.0, 238.0,\n",
       "       242.0, 246.0, 250.0, 254.0, 258.0, 262.0, 266.0, 270.0, 274.0, 278.0,\n",
       "       282.0, 286.0, 290.0, 294.0, 298.0, 302.0, 306.0, 310.0, 314.0, 318.0,\n",
       "       322.0, 326.0, 330.0, 334.0, 338.0, 342.0, 346.0, 350.0, 354.0, 358.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;xt&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>xu</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-08170ceb-7138-4149-ba89-ddc178a9d1cc' class='xr-index-data-in' type='checkbox'/><label for='index-08170ceb-7138-4149-ba89-ddc178a9d1cc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  4.0,   8.0,  12.0,  16.0,  20.0,  24.0,  28.0,  32.0,  36.0,  40.0,\n",
       "        44.0,  48.0,  52.0,  56.0,  60.0,  64.0,  68.0,  72.0,  76.0,  80.0,\n",
       "        84.0,  88.0,  92.0,  96.0, 100.0, 104.0, 108.0, 112.0, 116.0, 120.0,\n",
       "       124.0, 128.0, 132.0, 136.0, 140.0, 144.0, 148.0, 152.0, 156.0, 160.0,\n",
       "       164.0, 168.0, 172.0, 176.0, 180.0, 184.0, 188.0, 192.0, 196.0, 200.0,\n",
       "       204.0, 208.0, 212.0, 216.0, 220.0, 224.0, 228.0, 232.0, 236.0, 240.0,\n",
       "       244.0, 248.0, 252.0, 256.0, 260.0, 264.0, 268.0, 272.0, 276.0, 280.0,\n",
       "       284.0, 288.0, 292.0, 296.0, 300.0, 304.0, 308.0, 312.0, 316.0, 320.0,\n",
       "       324.0, 328.0, 332.0, 336.0, 340.0, 344.0, 348.0, 352.0, 356.0, 360.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;xu&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>yt</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-13314f56-c2e6-4d1c-a1c6-2b926fc4237f' class='xr-index-data-in' type='checkbox'/><label for='index-13314f56-c2e6-4d1c-a1c6-2b926fc4237f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-78.0, -74.0, -70.0, -66.0, -62.0, -58.0, -54.0, -50.0, -46.0, -42.0,\n",
       "       -38.0, -34.0, -30.0, -26.0, -22.0, -18.0, -14.0, -10.0,  -6.0,  -2.0,\n",
       "         2.0,   6.0,  10.0,  14.0,  18.0,  22.0,  26.0,  30.0,  34.0,  38.0,\n",
       "        42.0,  46.0,  50.0,  54.0,  58.0,  62.0,  66.0,  70.0,  74.0,  78.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;yt&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>yu</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7a6129b6-e8d6-4a71-94a6-4ac44fb18dd4' class='xr-index-data-in' type='checkbox'/><label for='index-7a6129b6-e8d6-4a71-94a6-4ac44fb18dd4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-76.0, -72.0, -68.0, -64.0, -60.0, -56.0, -52.0, -48.0, -44.0, -40.0,\n",
       "       -36.0, -32.0, -28.0, -24.0, -20.0, -16.0, -12.0,  -8.0,  -4.0,   0.0,\n",
       "         4.0,   8.0,  12.0,  16.0,  20.0,  24.0,  28.0,  32.0,  36.0,  40.0,\n",
       "        44.0,  48.0,  52.0,  56.0,  60.0,  64.0,  68.0,  72.0,  76.0,  80.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;yu&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>zt</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ced793a7-7a89-4c00-a703-924515f3e94b' class='xr-index-data-in' type='checkbox'/><label for='index-ced793a7-7a89-4c00-a703-924515f3e94b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-4855.0, -4165.0, -3575.0, -2985.0, -2495.0, -2005.0, -1615.0, -1225.0,\n",
       "        -935.0,  -645.0,  -455.0,  -265.0,  -175.0,   -65.0,   -35.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;zt&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>zw</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ac90c8da-dbda-41ab-946b-77afe5f3d252' class='xr-index-data-in' type='checkbox'/><label for='index-ac90c8da-dbda-41ab-946b-77afe5f3d252' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-4510.0, -3870.0, -3280.0, -2740.0, -2250.0, -1810.0, -1420.0, -1080.0,\n",
       "        -790.0,  -550.0,  -360.0,  -220.0,  -120.0,   -50.0,     0.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;zw&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bafa1379-5f18-460c-864e-1c73d80779c9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bafa1379-5f18-460c-864e-1c73d80779c9' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>date_created :</span></dt><dd>2021-10-26T12:02:31.193084</dd><dt><span>veros_version :</span></dt><dd>1.4.2</dd><dt><span>setup_identifier :</span></dt><dd>4deg</dd><dt><span>history :</span></dt><dd>Thu Oct 28 16:05:51 2021: ncks -d Time,90,99 4deg.averages.nc ../4deg.averages.nc</dd><dt><span>NCO :</span></dt><dd>netCDF Operators version 4.8.0 (Homepage = http://nco.sf.net, Code = http://github.com/nco/nco)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:       (Time: 10, isle: 6, nmonths: 12, yu: 40, xu: 90, zt: 15,\n",
       "                   yt: 40, xt: 90, tensor1: 2, tensor2: 2, zw: 15)\n",
       "Coordinates:\n",
       "  * Time          (Time) timedelta64[ns] 32760 days 33120 days ... 36000 days\n",
       "  * isle          (isle) float64 0.0 1.0 2.0 3.0 4.0 5.0\n",
       "  * nmonths       (nmonths) float64 0.0 1.0 2.0 3.0 4.0 ... 8.0 9.0 10.0 11.0\n",
       "  * tensor1       (tensor1) float64 0.0 1.0\n",
       "  * tensor2       (tensor2) float64 0.0 1.0\n",
       "  * xt            (xt) float64 2.0 6.0 10.0 14.0 ... 346.0 350.0 354.0 358.0\n",
       "  * xu            (xu) float64 4.0 8.0 12.0 16.0 ... 348.0 352.0 356.0 360.0\n",
       "  * yt            (yt) float64 -78.0 -74.0 -70.0 -66.0 ... 66.0 70.0 74.0 78.0\n",
       "  * yu            (yu) float64 -76.0 -72.0 -68.0 -64.0 ... 68.0 72.0 76.0 80.0\n",
       "  * zt            (zt) float64 -4.855e+03 -4.165e+03 -3.575e+03 ... -65.0 -35.0\n",
       "  * zw            (zw) float64 -4.51e+03 -3.87e+03 -3.28e+03 ... -50.0 0.0\n",
       "Data variables:\n",
       "    psi           (Time, yu, xu) float64 ...\n",
       "    salt          (Time, zt, yt, xt) float64 ...\n",
       "    surface_taux  (Time, yt, xu) float64 ...\n",
       "    surface_tauy  (Time, yu, xt) float64 ...\n",
       "    temp          (Time, zt, yt, xt) float64 ...\n",
       "    u             (Time, zt, yt, xu) float64 ...\n",
       "    v             (Time, zt, yu, xt) float64 ...\n",
       "    w             (Time, zw, yt, xt) float64 ...\n",
       "Attributes:\n",
       "    date_created:      2021-10-26T12:02:31.193084\n",
       "    veros_version:     1.4.2\n",
       "    setup_identifier:  4deg\n",
       "    history:           Thu Oct 28 16:05:51 2021: ncks -d Time,90,99 4deg.aver...\n",
       "    NCO:               netCDF Operators version 4.8.0 (Homepage = http://nco...."
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_avg = xr.open_dataset(\"4deg/\" + OUTPUT_FILES[\"averages\"])\n",
    "ds_avg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "dffbec79-5b4d-41e2-97e6-75a5a05db4d8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert units of the barotropic stream function\n",
    "ds_avg[\"psi\"] = ds_avg.psi / 1e6\n",
    "ds_avg[\"psi\"].attrs[\"units\"] = \"Sv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "77fec076-835b-467d-b187-bb2deb9e52a7",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x7f39e5a363e0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot last time snapshot of psi\n",
    "ds_avg[\"psi\"].isel(Time=-1).plot.contourf(levels=50, cmap=\"cmo.balance\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4b0bbc21-ab3b-4709-bcb4-c28d56dcf32f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x7f39ddd58d90>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compute the decadal mean (of the last 10yrs) of zonal-mean ocean salinity\n",
    "ds_avg[\"salt\"].isel(Time=slice(-10,None)).mean(dim=(\"Time\", \"xt\")).plot.contourf(levels=50, cmap=\"cmo.haline\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "6f1aa8ae-1a9c-42f2-93a9-ed62b49ed908",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "ds_snap = xr.open_dataset(\"4deg/\" + OUTPUT_FILES[\"snapshot\"])\n",
    "# Use cell area as weights, replace missing values (land) with 0\n",
    "weights = ds_snap[\"area_t\"].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "9d3dbfd6-6983-47b0-b257-2be34fbb95a3",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculate and plot the meridional mean temperature\n",
    "temp_weighted = (\n",
    "    ds_avg[\"temp\"]\n",
    "    .isel(Time=-1)\n",
    "    .weighted(weights)\n",
    "    .mean(dim=\"yt\")\n",
    "    .plot.contourf(vmin=-2, vmax=22, levels=25, cmap=\"cmo.thermal\")\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "40a5a12f-5eca-4647-b174-278076f06c86",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}